Virtual Reality (VR) laboratory simulations: Self-efficacy outcomes in freshmen MedTech students: A gender-based comparison

Virtual Reality (VR) laboratory simulations: Self-efficacy outcomes in freshmen MedTech students: A gender-based comparison | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Virtual Reality (VR) laboratory simulations: Self-efficacy outcomes in freshmen MedTech students: A gender-based comparison John Derrick Chan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9034418/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract The integration of virtual reality (VR) in laboratory education has emerged as a promising strategy to enhance student engagement, motivation, and satisfaction, particularly in health sciences programs. This study examined the perceived learning outcomes of first-year Bachelor of Science in Medical Technology (BSMT) students following their participation in VR-based laboratory simulations. It assessed levels of intrinsic motivation (m = 3.26), general self-efficacy (m = 3.02), and learner satisfaction (m = 3.18), and investigated potential differences in perceptions between male and female students. A descriptive-comparative research design was utilized, with data collected through adapted standardized instruments. Results revealed positive perceptions across all measured domains. Students agreed that the VR simulations addressed their learning needs, provided clear objectives, and contributed to their sense of preparedness for actual laboratory work. An independent samples t-test showed no statistically significant difference between male and female students in terms of their perceived learning outcomes [t(43) = 1.09, p = .284]. This indicates that VR simulations provide a consistent educational benefit regardless of gender. The findings highlight the potential of VR simulations as a supplementary instructional approach in medical laboratory education, supporting their integration alongside traditional methods. The study recommends sustained implementation of VR in laboratory instruction, coupled with ongoing program evaluation and refinement to optimize its educational impact. These results contribute to the growing body of evidence supporting the effectiveness of simulation-based learning in improving student experiences in medical and allied health education. virtual reality laboratory simulations medical technology gender self-efficacy 1. Introduction In contemporary health sciences education, the integration of technology into traditional instructional methods has become increasingly vital in cultivating competence among students. The advent of virtual reality (VR) has introduced transformative approaches to laboratory learning, providing immersive and interactive environments that bridge theoretical concepts with practical applications (Goh & Sandars, 2020). This technological innovation has found relevance in medical technology education, where laboratory proficiency is integral to the development of core competencies. Medical laboratory science programs are structured to build both theoretical knowledge and technical skills necessary for clinical practice. However, limitations such as resource constraints, safety concerns, and restricted laboratory access often hinder optimal learning experiences, especially for novice learners (Chen et al., 2020). The disruption caused by the COVID-19 pandemic further underscored these challenges, as the abrupt shift to remote learning modalities magnified the gaps in laboratory instruction (Gunaydin et al., 2022). In response, VR simulations emerged as a pivotal educational alternative, offering realistic, repeatable laboratory scenarios in a controlled virtual environment. These platforms promote active engagement and cognitive immersion, which have been shown to enhance learners' motivation and perceived competence in performing laboratory tasks. While numerous studies have underscored the efficacy of VR in improving educational outcomes in allied health programs, there remains a gap in the literature specifically addressing its impact on perceived learning among first-year Medical Technology students. Furthermore, understanding potential variations in learning experiences based on gender is equally essential, given evidence suggesting that individual learner characteristics may influence interaction with technological tools (Al-Saud et al., 2017). Given this context, the present study was conceptualized not only in response to the growing integration of VR in education but also due to the pedagogical disruptions experienced during the COVID-19 pandemic. This study aims to evaluate the impact of VR laboratory simulations on the perceived learning of freshmen enrolled in a Bachelor of Science in Medical Technology program. Additionally, it seeks to determine whether significant differences exist in perceived learning outcomes between male and female students. The findings of this study are expected to provide valuable insights for curriculum developers and educators in optimizing technology-assisted instructional strategies tailored to diverse learner needs. 1.1 Objectives of the Study This study aims to assess the impact on perceived learning in BSMT freshmen students of virtual reality laboratory simulations. Specifically, this aims to: How is the perceived learning in BSMT freshmen students of virtual reality laboratory simulations be described in terms of Intrinsic Motivation Inventory, General Self-Efficacy Scale, and Learner Satisfaction with Simulation Scale? Is there a significant difference between male and female BSMT freshmen students in terms of Intrinsic Motivation Inventory, General Self-Efficacy Scale, and Learner Satisfaction with Simulation Scale? Is there a significant difference between the impact on perceived learning of virtual reality laboratory simulations of male and female BSMT freshmen students? 1.2. Hypothesis of the Study 1.2.1. Null Hypothesis H 01 : There is no significant difference between the intrinsic motivation inventory of male and female BSMT freshmen students H 02 : There is no significant difference between the General Self-Efficacy Scale of male and female BSMT freshmen students H 03 : There is no significant difference between the Learner Satisfaction with Simulation Scale of male and female BSMT freshmen students H 04 : There is no significant difference between the impact on perceived learning of virtual reality laboratory simulations of male and female BSMT freshmen students 1.3. Theoretical Framework This study is grounded in Bandura’s (1997) Self-Efficacy Theory, which posits that individuals’ beliefs in their ability to execute specific tasks significantly influence their motivation, learning, and performance. Self-efficacy is defined as “people’s beliefs about their capabilities to produce designated levels of performance that exercise influence over events that affect their lives” (Bandura, 1994, p. 71). These beliefs determine how individuals feel, think, motivate themselves, and behave in various contexts, particularly in response to novel or challenging tasks. In the context of medical technology education, the integration of Virtual Reality (VR) simulations into laboratory instruction offers an innovative approach to developing practical skills and enhancing learners' confidence. Bandura’s four sources of self-efficacy—mastery experiences, vicarious experiences, verbal persuasion, and physiological and affective states—are particularly relevant when analyzing the outcomes of VR-based learning interventions. Through immersive simulations, students can engage in repeated practice (mastery), observe peer success (vicarious), receive feedback (verbal persuasion), and experience reduced anxiety or heightened engagement (affective states), all of which contribute to shaping their self-efficacy. This theoretical lens is especially pertinent when considering freshmen medical technology students, who may face increased stress due to the transition into higher education and the rigors of professional training. VR simulations serve as a scaffolding tool, potentially mitigating early anxiety and promoting confidence through controlled, replicable environments. Furthermore, the theory provides a framework for examining gender-based differences in self-efficacy outcomes, as existing literature suggests that males and females may differ in how they perceive and respond to technological learning tools (Zeldin & Pajares, 2000). By employing Bandura’s Self-Efficacy Theory, the present study seeks to explore how VR simulations influence the development of self-efficacy among freshmen medical technology students and whether gender moderates this relationship. Understanding these dynamics can inform instructional strategies, support equitable learning environments, and contribute to the broader discourse on educational technology in health science programs. 1.4. Research Design This study employed a quantitative cross-sectional observational research design. The primary objective of utilizing this design was to capture a comprehensive snapshot of the perceptions and experiences of first-year Medical Technology students at a single point in time regarding their engagement with virtual reality (VR) laboratory simulations. The cross-sectional approach is particularly appropriate for studies aiming to describe variables and explore relationships between them without manipulating any of the variables under investigation (Setia, 2016). As an observational study, it allowed the researcher to examine participants’ responses naturally, focusing solely on their perceived learning experiences, satisfaction levels, self-efficacy, and intrinsic motivation after exposure to the VR simulation. By comparing responses across defined subgroups, such as male and female participants, the study was able to investigate potential differences in outcomes based on gender. The design was chosen for its practicality, efficiency, and appropriateness in establishing baseline associations necessary for educational research contexts without requiring longitudinal tracking. 1.5. Research Population The participants of this study consisted of first-year Bachelor of Science in Medical Technology (BSMT) students enrolled in the course Biochemistry for Medical Laboratory Science during the third trimester of the academic year 2024–2025 at a local university located in Bulacan, Philippines. Purposive sampling was utilized to determine the participants, ensuring that only those students who had direct exposure to the virtual reality laboratory simulation were included. There is a total of fifty (50) students currently enrolled in the course. To determine the appropriate sample size for this study, Slovin’s formula was utilized to account for a finite population of 50 freshmen Medical Technology students. This formula is particularly useful when the population size is known, and the desired margin of error is specified. Using the formula, where n is the sample size, N is the population size, and e is the margin of error (typically set at 0.05 for a 95% confidence level), the computed sample size ensures that the results are statistically representative of the population while maintaining manageable data collection. Applying the values the sample size is calculated to be approximately 45 respondents. There was a total of thirty-three (33) females and twelve (12) males. 1.6. Inclusion and Exclusion Criteria Participants included in this study were first-year students enrolled in the Bachelor of Science in Medical Technology (BSMT) program at a specific university in Bulacan during the third trimester of the academic year 2024–2025. Only students officially registered in the Biochemistry for Medical Laboratory Science course who had completed the virtual reality (VR) laboratory simulation were considered eligible. Additionally, participants were required to provide informed consent prior to inclusion in the study. Students who were enrolled in the said course but did not participate in the VR laboratory simulation were excluded from the study. Moreover, students who failed to complete the survey questionnaire or provided incomplete responses were also excluded from the final analysis to maintain the integrity and accuracy of the collected data. 1.7. Data Collection Tool For this study, three standardized and validated survey instruments were utilized to collect data aligned with the study objectives. The Intrinsic Motivation Inventory (IMI), developed by Ryan (1982), was used to assess the participants’ intrinsic motivation, particularly focusing on their engagement and interest in the virtual reality (VR) laboratory simulation experience. Additionally, the General Self-Efficacy Scale (GSES) developed by Schwarzer and Jerusalem (1995) was employed to evaluate participants’ self-perceived competence in managing learning challenges, particularly in laboratory settings. Furthermore, the Learner Satisfaction with Simulation Scale (LSSS) by Hayden et al. (2014) was adapted to assess the participants’ satisfaction with the VR laboratory simulation. Each of these instruments has been widely used and validated in educational and simulation-based research, making them suitable for measuring the perceived learning of students in this study. Furthermore, statements 4,5,8, and 15 used reverse coding to make sure that the respondents are answering the questions accurately. The formula “(highest score + 1) – mean” is used to measure the reverse score. 1.8. Informed Consent and Ethical Consideration The researcher strictly adhered to the ethical standards of research writing to protect the rights of the respondents and received an ethical clearance from the National University Clark Research Ethics Committee. Before the data collection commenced, informed consent was individually acquired from each participant prior to their engagement. Participants were informed of the purpose of the study and how the results will be used. Moreover, there was a voluntary participation in the study and were guaranteed the option to refuse or withdraw at any time without facing any consequences Furthermore, all the respondents remained anonymous throughout the study. All the data collected were treated with confidentiality and were solely used for research purpose only. Lastly, an AI language model (ChatGPT by OpenAI) was used to assist in organizing and synthesizing relevant literature, refining survey items, and generating summaries. All outputs were reviewed and validated by the researcher 1.9. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. All research-related expenses were personally financed by the author. 2. Literature Review 2.1 Virtual Reality Laboratory Simulations The integration of virtual reality (VR) in educational settings has significantly transformed the delivery of laboratory instruction, particularly in science and health-related disciplines. VR refers to a computer-generated simulation of a three-dimensional environment that allows users to interact with digital objects in real-time (Radianti et al., 2020). In laboratory education, VR simulations are designed to replicate real-life experimental procedures, enabling learners to engage with laboratory tasks without the limitations imposed by traditional settings such as equipment availability, safety risks, and resource constraints (Goh & Sandars, 2020). Numerous studies have recognized the potential of VR simulations in enhancing cognitive and affective learning outcomes. According to Gunaydin et al. (2022), the immersive and interactive nature of VR stimulates higher engagement among learners by providing immediate feedback, realistic scenarios, and opportunities for repeated practice. These features contribute not only to knowledge acquisition but also to improved motivation and confidence in performing laboratory-related tasks. Additionally, VR has been found to reduce learning anxiety by allowing students to make mistakes in a risk-free environment, thereby encouraging exploration and active participation (Chen et al., 2020). The utilization of VR laboratory simulations gained further relevance during the COVID-19 pandemic, as educational institutions worldwide faced unprecedented challenges in maintaining the continuity of laboratory instruction (Al-Saud et al., 2017). With physical laboratories rendered inaccessible, VR platforms emerged as viable alternatives for delivering essential laboratory experiences, particularly in allied health programs. Labster, one of the most recognized VR simulation platforms, has demonstrated positive impacts on student preparedness and academic performance in various medical and science-related courses (Makransky & Mayer, 2022). Moreover, the benefits of VR extend beyond academic achievement. Radianti et al. (2020) emphasized that VR-based laboratory instruction fosters the development of soft skills such as decision-making, critical thinking, and problem-solving—skills that are vital in clinical and laboratory practice. However, while most of the existing literature highlights favorable outcomes, some researchers note that the effectiveness of VR may vary depending on learners’ prior experience with technology, individual learning preferences, and the quality of the simulation itself (Goh & Sandars, 2020). 2.1.1. Virtual Reality Laboratory Simulations in BSMT Program The continuous advancement of educational technologies has reshaped instructional strategies in health science programs, particularly in the field of Medical Technology. Among these innovations, virtual reality (VR) laboratory simulations have emerged as promising tools to enhance students’ understanding of laboratory procedures and diagnostic techniques. VR simulations in the context of Medical Technology provide learners with interactive three-dimensional environments where they can practice and master laboratory skills in a controlled, risk-free setting (Makransky & Mayer, 2022). These platforms are particularly valuable for simulating complex or hazardous procedures that may be difficult to replicate consistently in a conventional laboratory setup. In Medical Technology education, the mastery of laboratory techniques, including specimen processing, diagnostic testing, and result interpretation, is essential for professional competence. Traditional laboratory instruction often faces challenges related to limited resources, equipment availability, and safety considerations, particularly for first-year students who are still developing familiarity with basic laboratory operations (Radianti et al., 2020). VR laboratory simulations address these issues by providing repeatable, scenario-based experiences that foster procedural proficiency without exposing students to real laboratory risks (Gunaydin et al., 2022). Empirical studies have supported the role of VR simulations in enhancing cognitive learning outcomes, particularly in medical and allied health education. For instance, research by Chen et al. (2020) demonstrated that VR-enhanced laboratory instruction significantly improves students’ motivation, focus, and perceived competence when performing laboratory activities. Similarly, a study by Lorenzo-Alvarez et al. (2020) reported that students who engaged with VR laboratory simulations exhibited higher levels of confidence and readiness when transitioning to actual laboratory work. The relevance of VR laboratory simulations in Medical Technology education became even more pronounced during the COVID-19 pandemic, when physical access to laboratories was restricted (Goh & Sandars, 2020). Institutions adopted VR platforms as supplementary tools to ensure the continuity of practical instruction despite the shift to remote learning environments. Platforms like Labster have been widely implemented in medical laboratory courses, offering interactive simulations such as blood typing, microbiology testing, and molecular diagnostics (Makransky et al., 2021). These simulations allow students to navigate diagnostic processes, manipulate virtual equipment, and make critical decisions in diagnostic workflows. Furthermore, VR’s contribution to skill development is not limited to technical proficiency. Studies have shown that VR-based learning also cultivates essential cognitive attributes, including critical thinking, problem-solving, and clinical decision-making—competencies that are indispensable for future Medical Technologists (Radianti et al., 2020). Although VR cannot entirely replace the tactile experiences of real laboratory work, it serves as a complementary pedagogical tool that enriches laboratory education by offering flexibility, accessibility, and individualized pacing (Gunaydin et al., 2022). Despite its promising contributions, successful utilization of VR simulations in Medical Technology programs depends on careful instructional design, institutional support, and appropriate integration with existing curricula. Educators must ensure that VR activities align with intended learning outcomes while considering students’ diverse learning preferences and technological proficiency (Chen et al., 2020). As the demand for skilled Medical Technologists continues to grow, VR laboratory simulations are positioned to play an increasingly important role in preparing students for the practical and analytical demands of the profession. 2.1.2. Advantages and Disadvantages of Virtual Reality Laboratory Simulations The utilization of virtual reality (VR) laboratory simulations has become an emerging trend in medical and allied health education, offering both substantial advantages and notable limitations. As educational institutions continue to integrate technology to improve instructional delivery, understanding both the strengths and challenges of VR laboratory simulations is essential for maximizing their effectiveness in academic settings, particularly in fields such as Medical Technology. One of the primary advantages of VR laboratory simulations is their capacity to provide learners with a highly immersive and interactive learning environment. Using 3D graphics, real-time feedback, and interactive decision-making tasks, students are placed in realistic laboratory settings where they can safely perform experiments and diagnostic procedures (Makransky & Mayer, 2022). This immersive experience fosters deeper engagement and promotes the active application of theoretical concepts, contributing to better retention of knowledge (Radianti et al., 2020). Moreover, VR simulations allow for repeated practice of procedures without consuming physical resources, reducing operational costs and eliminating risks associated with exposure to hazardous substances (Gunaydin et al., 2022). Another significant advantage of VR is its flexibility and accessibility. Virtual laboratory environments can be accessed remotely, making them especially valuable during periods of restricted physical interaction, such as the COVID-19 pandemic (Goh & Sandars, 2020). Learners can engage with laboratory content at their own pace and convenience, which promotes individualized learning and accommodates varying levels of proficiency (Chen et al., 2020). Additionally, VR-based laboratory simulations have been found to improve students’ confidence and motivation, particularly when learners receive immediate feedback on their performance, reinforcing their competence in laboratory procedures (Lorenzo-Alvarez et al., 2020). Despite these advantages, VR laboratory simulations are not without their limitations. One common disadvantage is the lack of tactile feedback, which is critical in certain laboratory techniques where the physical sensation of handling equipment and specimens is integral to skill mastery (Makransky et al., 2021). While visual and auditory simulations may approximate real-world scenarios, the absence of haptic sensations can limit students’ preparedness for actual laboratory work. Furthermore, prolonged use of VR equipment has been associated with discomforts such as visual fatigue and motion sickness in some learners (Radianti et al., 2020). Another challenge is the technological barrier faced by both students and educators. Successful implementation of VR simulations requires access to high-quality hardware, reliable internet connections, and technical support, which may not always be available in all educational institutions, especially in resource-constrained settings (Gunaydin et al., 2022). Additionally, students unfamiliar with VR interfaces may experience cognitive overload or distractions, which could detract from the intended learning outcomes (Makransky et al., 2021). 2.1.3. Virtual Reality Laboratory Simulations for Freshmen Students The transition to higher education presents unique challenges for first-year students, particularly in programs with demanding laboratory components such as Medical Technology. For these students, foundational laboratory skills are essential to future academic and professional success. Virtual reality (VR) laboratory simulations have emerged as valuable tools in addressing these needs by providing immersive and interactive environments that support early skills development and conceptual understanding (Makransky & Mayer, 2022). These simulations play a crucial role in helping freshmen navigate the complexities of laboratory work by bridging the gap between theoretical instruction and practical application. One of the primary advantages of VR laboratory simulations for freshmen students is their ability to introduce learners to laboratory procedures in a safe, controlled, and accessible environment. Freshmen often enter health science programs with varying levels of familiarity regarding laboratory concepts and equipment, making traditional laboratory environments potentially intimidating or overwhelming (Radianti et al., 2020). By offering realistic and repeatable experiences, VR simulations reduce anxiety and build student confidence, enabling learners to engage with laboratory tasks at their own pace before handling real-life specimens or equipment (Gunaydin et al., 2022). For freshmen students, early exposure to laboratory processes using VR helps establish a strong cognitive foundation. Studies have shown that students who engage with VR-based laboratories exhibit improved motivation and learning outcomes compared to those exposed solely to conventional methods (Chen et al., 2020). This advantage is particularly significant for first-year students, whose initial academic experiences often shape their attitudes toward their chosen field of study. By integrating VR into early laboratory education, students are empowered to take ownership of their learning, which supports retention and program completion (Lorenzo-Alvarez et al., 2020). The importance of VR laboratory simulations for freshmen became even more evident during the COVID-19 pandemic. With restrictions on physical classroom access, VR provided a crucial alternative for sustaining laboratory-based education, especially for students in the early stages of their degree programs (Goh & Sandars, 2020). Virtual platforms such as Labster enabled first-year students to engage with diagnostic procedures such as microscopy, hematology testing, and microbiology, ensuring that foundational learning continued despite the disruption of traditional classroom settings (Makransky et al., 2021). Additionally, VR simulations cater to different learning styles, providing visual, auditory, and interactive feedback that appeals to a wide range of learners (Radianti et al., 2020). This multimodal approach is particularly beneficial for freshmen who are still adjusting to the rigors of tertiary education and need structured, engaging content to maintain focus and build competence. While VR cannot fully substitute the tactile experience of hands-on laboratory practice, its early integration into the curriculum provides a scaffolding effect that prepares students for real-world laboratory challenges. As first-year students advance in their studies, the foundational knowledge and confidence gained from VR simulations serve as steppingstones toward mastering more complex laboratory techniques (Makransky & Mayer, 2022). 2.1.4. Impact of Virtual Reality Laboratory Simulations between Male and Female As technological innovations continue to reshape the educational landscape, understanding how various learner demographics respond to instructional tools such as virtual reality (VR) simulations has become increasingly important. One key dimension of learner diversity is gender, with several studies investigating how male and female students differ in their responses to immersive learning environments. In the context of laboratory simulations in health sciences and allied medical programs, examining these differences provides valuable insights into optimizing instructional design and achieving equitable educational outcomes. Research indicates that gender differences may influence how students experience, interact with, and benefit from VR-based educational tools. Studies have shown that male students often demonstrate greater familiarity and confidence with interactive technology, including VR systems, due to earlier and more frequent exposure to gaming environments and technological devices (Makransky et al., 2019). This prior exposure may contribute to higher engagement levels and comfort when navigating virtual laboratories, particularly during early use (Lamb et al., 2020). Conversely, some studies suggest that female students tend to exhibit stronger learning outcomes in structured VR educational settings, particularly when simulations are designed with clear learning objectives and provide consistent feedback (Bucchi et al., 2023). Female learners often emphasize the importance of contextual relevance and clear instructional guidance within VR environments, which can contribute to improved motivation and knowledge retention when these factors are adequately addressed (Cai et al., 2020). Furthermore, female students are reported to excel in collaborative learning tasks within VR platforms, favoring interactions that allow for discussion and reflection on laboratory procedures (Radianti et al., 2020). However, while certain trends regarding gender-based differences in VR usage have been observed, research findings remain mixed and context-dependent. For instance, a study by Gunaydin et al. (2022) found no significant difference in the learning outcomes of male and female students using VR-based laboratory simulations when the instructional design was tailored to accommodate diverse user needs. This finding highlights the potential of well-designed VR learning environments to neutralize initial gender-based disparities, offering an equitable platform for laboratory skill acquisition. Additionally, physiological responses to VR environments have occasionally been observed to differ by gender. Some female learners report greater susceptibility to cybersickness or motion-related discomfort when exposed to immersive VR settings, potentially affecting sustained engagement (Makransky et al., 2021). Nonetheless, improvements in VR hardware and instructional customization continue to mitigate these barriers. Ultimately, understanding these gender-based variations is critical, particularly for freshmen students in Medical Technology programs, who may have differing levels of prior exposure to laboratory work and technology-assisted learning. By addressing the unique preferences and challenges of both male and female learners, educators can better leverage VR laboratory simulations to promote balanced academic success across genders (Lamb et al., 2020). 2.2. Perceived Learning Perceived learning has gained significant attention in educational research as a valuable metric for understanding students’ subjective evaluations of their educational experiences. While academic achievement is typically measured through standardized assessments, perceived learning focuses on learners' self-assessments regarding the extent to which they have acquired knowledge, skills, and competencies from educational activities (Caspi & Blau, 2011). This concept offers educators and researchers insights into students’ internal reflections on their own progress, which may not always align directly with traditional performance metrics. According to Alqurashi (2019), perceived learning refers to students' beliefs about how much they have learned, encompassing cognitive, affective, and psychomotor domains. It reflects a learner-centered perspective that highlights the importance of subjective experience in the learning process. The concept emphasizes that learning is not only about knowledge acquisition but also about how students interpret and internalize educational content, particularly in dynamic learning environments such as virtual simulations or online instruction. Researchers have distinguished perceived learning from objective learning outcomes by underscoring that the former is influenced by factors such as motivation, engagement, and the learning environment (Richardson et al., 2017). This subjective evaluation is critical in technology-enhanced educational contexts, where user experience, interface design, and perceived relevance of content can significantly influence students’ perceptions of their learning (Sun & Rueda, 2012). The multidimensional nature of perceived learning typically involves three key aspects: cognitive learning (knowledge and understanding), affective learning (emotional engagement and attitude formation), and psychomotor learning (practical skill acquisition) (Liaw & Huang, 2013). By capturing these elements, perceived learning provides a holistic perspective on educational effectiveness from the viewpoint of the learner. Moreover, perceived learning has been widely utilized in educational research to evaluate the effectiveness of online platforms, blended learning modalities, and immersive technologies such as virtual reality (Alqurashi, 2019; Sun & Rueda, 2012). Its significance has become even more pronounced in the aftermath of the COVID-19 pandemic, when many educational institutions adopted digital learning technologies that required assessment beyond conventional testing methods (Caspi & Blau, 2011). While perceived learning may sometimes be influenced by students’ prior attitudes toward the mode of instruction or technological tools used, its value lies in providing feedback on how learners interpret the educational process itself. Understanding students’ perceptions of their learning helps educators refine instructional strategies and tailor interventions that promote both perceived and actual learning success (Richardson et al., 2017). 2.2.1. Intrinsic Motivation Inventory The Intrinsic Motivation Inventory (IMI) is a multidimensional measurement tool widely used in educational psychology and behavioral science to assess individuals’ subjective experiences related to intrinsic motivation. Developed originally within the framework of self-determination theory (SDT), the IMI has become a foundational instrument in research investigating motivation in various educational, clinical, and recreational settings (Deci & Ryan, 1985). It is particularly valuable in contexts where intrinsic motivation is considered central to sustained engagement and effective learning, such as technology-enhanced or experiential learning environments. Intrinsic motivation refers to engaging in an activity for its inherent satisfaction rather than for some separable consequence, such as rewards or external recognition (Ryan & Deci, 2000). The IMI was specifically designed to assess participants’ interest, enjoyment, perceived competence, effort, value, and relatedness within a given task or activity. As such, it provides a nuanced picture of the motivational drivers influencing learner engagement (McAuley et al., 1989). One of the strengths of the IMI lies in its multidimensional structure. The most commonly used subscales include Interest/Enjoyment, Perceived Competence, Effort/Importance, Pressure/Tension, Perceived Choice, and Value/Usefulness (Deci & Ryan, 1985). Among these, the Interest/Enjoyment subscale is considered the most direct measure of intrinsic motivation, whereas the other dimensions provide complementary information about factors that support or hinder intrinsic engagement (Tsigilis & Theodosiou, 2003). The validity and reliability of the IMI have been demonstrated across diverse educational settings, including higher education and immersive learning environments such as virtual reality (VR) simulations (Makransky et al., 2019). Its applicability to technology-assisted learning environments makes it particularly relevant for assessing learner motivation in simulations used in medical and health sciences education (Ryan et al., 2021). Moreover, intrinsic motivation measured by the IMI has been consistently associated with enhanced learning outcomes, deeper engagement, and improved retention of knowledge (Richardson et al., 2017). By capturing the subjective dimensions of learner motivation, the IMI serves as an essential tool for researchers seeking to explore how instructional strategies, including virtual laboratory simulations, impact students' internal motivation to learn. 2.2.2. General Self-Efficacy Scale The General Self-Efficacy Scale (GSES) is a widely recognized psychometric instrument designed to measure an individual’s belief in their ability to cope with a wide variety of challenging demands and novel situations (Schwarzer & Jerusalem, 1995). Rooted in Bandura’s (1977) theory of self-efficacy, the concept underscores the role of personal judgment in one’s ability to organize and execute courses of action required to manage prospective situations. Unlike task-specific self-efficacy measures, the GSES assesses a broad and stable sense of personal competence across various life domains. Originally developed by Jerusalem and Schwarzer in 1981 and later adapted into English by Schwarzer and Jerusalem (1995), the GSES consists of ten items measured using a Likert scale format. Each item reflects a statement about coping abilities or confidence in addressing obstacles, and higher scores on the scale indicate greater levels of perceived general self-efficacy. The scale has undergone extensive validation across cultural contexts, with reliability coefficients (Cronbach’s alpha) typically ranging from 0.76 to 0.90 (Scholz et al., 2002). Self-efficacy, as measured by the GSES, has demonstrated significant predictive value in educational, clinical, and occupational settings (Luszczynska et al., 2005). Within the context of education, higher self-efficacy is consistently associated with better academic achievement, increased engagement, and more effective problem-solving skills (Zajacova et al., 2005). Furthermore, in technology-mediated learning environments such as virtual laboratories, students’ self-efficacy often influences their perceived learning outcomes and persistence (Makransky et al., 2019). In health-related educational programs like medical technology, the GSES is particularly valuable for evaluating how students perceive their ability to engage with complex tasks, including simulations requiring critical thinking and adaptive learning strategies. Its generalizability allows it to be used alongside other instruments, such as the Intrinsic Motivation Inventory (IMI), to provide a comprehensive assessment of learners’ internal capacities for managing academic challenges. Given the increasing integration of virtual platforms in medical education, particularly in response to the disruptions caused by the COVID-19 pandemic, the GSES remains a relevant tool for assessing students’ psychological readiness for novel instructional approaches (Makransky et al., 2019). By providing insights into learners’ confidence in handling academic demands, the GSES contributes meaningfully to evaluating the effectiveness of innovative teaching modalities such as virtual reality simulations. 2.2.3. Learner Satisfaction with Simulation Scale The Learner Satisfaction with Simulation Scale (LSSS) is a standardized instrument developed to evaluate students’ satisfaction following participation in simulation-based learning activities. Designed specifically for educational contexts utilizing simulations, the LSSS captures learners’ subjective evaluations of the simulation experience, emphasizing factors such as perceived usefulness, realism, clarity of objectives, and overall satisfaction (Jeffries & Rizzolo, 2006). As simulations have become integral to health sciences education, especially in nursing and allied health programs, reliable measures such as the LSSS are necessary to assess the effectiveness of these teaching strategies. Learner satisfaction represents a critical outcome in simulation-based education as it often correlates with higher engagement, improved knowledge retention, and greater confidence in applying learned skills to real-world scenarios (Franklin et al., 2014). The LSSS typically utilizes Likert-scale responses, where participants rate their level of agreement with statements regarding the simulation's instructional value, organization, facilitation, and perceived benefit to their learning process (Hayden et al., 2014). Originally validated in nursing education by Jeffries and Rizzolo (2006) through the National League for Nursing (NLN), the scale has demonstrated strong psychometric properties. Studies consistently report Cronbach’s alpha values above 0.85, reflecting high internal consistency and reliability (Franklin et al., 2014). The LSSS has since been adopted and adapted in a variety of healthcare education programs, including medical laboratory science, owing to its flexibility and relevance across clinical simulation settings (Al-Ghareeb & Cooper, 2016). In recent years, the integration of virtual reality (VR) into simulation-based learning has expanded the applicability of the LSSS. Research indicates that VR-based simulations, when evaluated using the LSSS, often yield comparable or higher satisfaction scores than traditional mannequin-based simulations (Foronda et al., 2020). This suggests that learners find immersive technologies both engaging and educationally valuable, provided that instructional goals and technological execution are clear and coherent. As healthcare education continues to adapt to technological advancements and post-pandemic educational restructuring, tools like the LSSS play a pivotal role in ensuring that instructional innovations are aligned with learner needs and institutional educational outcomes (Aebersold, 2018). 2.3. Global Setting Virtual reality (VR) has emerged globally as a transformative tool in health science education, offering immersive simulations that replicate clinical and laboratory environments with high fidelity. Countries like the United States, the United Kingdom, South Korea, and Australia have integrated VR into Medical Technology curricula to enhance student engagement and competency-based learning (Radianti et al., 2020). VR enables hands-on practice without constraints related to space, safety, or resources—benefits that became especially relevant during the COVID-19 pandemic when physical lab access was restricted (Gunaydin et al., 2022). As a result, VR is increasingly valued not just as a contingency tool but as a lasting pedagogical strategy. Studies affirm VR’s positive impact on student self-efficacy—the belief in one’s ability to manage future challenges (Bandura, 1997). In healthcare education, students with high self-efficacy show better persistence, confidence, and clinical performance. Research in Europe and East Asia found that immersive simulations improve perceived competence by allowing repeated, low-risk practice with immediate feedback (Cai et al., 2020; Koivisto et al., 2021; Makransky & Mayer, 2022). These factors are strongly linked to higher self-efficacy and academic resilience. VR also helps address training gaps in psychomotor skills and lab exposure, particularly in Medical Technology programs where traditional setups require costly reagents and strict safety protocols. Institutions in countries like Denmark, Canada, and Japan have adopted platforms such as Labster to simulate diagnostic workflows and reinforce technical skills (Bucchi et al., 2023). These simulations support both conceptual understanding and performance confidence, contributing to better outcomes during clinical internships and licensure exams (Foronda et al., 2020). Gender-based differences in how learners respond to VR have also been noted. Males often show quicker immersion in gamified environments, while females typically display stronger organization, self-reflection, and affective engagement (Makransky et al., 2019; Chen et al., 2020). However, when inclusive design principles—like adaptive pacing and structured guidance—are applied, both genders benefit equally from VR learning experiences (Koivisto et al., 2021; Gunaydin et al., 2022). For freshmen entering demanding fields like Medical Technology, early experiences with VR-based learning can be pivotal. Positive initial exposure to scaffolded, interactive simulations has been shown to boost student confidence, motivation, and persistence across contexts such as the Philippines, Singapore, and Finland (Alqurashi, 2019; Sun & Rueda, 2012). By reinforcing self-efficacy early on, VR may help students better manage academic and psychological challenges throughout their training. 2.4. Philippine Setting The Philippine education system has steadily advanced in integrating technology-enhanced learning, especially in health sciences where hands-on experience is vital. Although traditional laboratory methods remain widespread, there is growing interest in simulation-based learning, particularly in Medical Technology programs. Simulations allow students to practice complex procedures safely, addressing limitations in equipment, safety, and logistics (Salvador et al., 2021). However, full adoption of immersive tools like virtual reality (VR) is still limited due to infrastructure, cost, and faculty readiness. The COVID-19 pandemic accelerated digital learning innovations. Faced with mobility restrictions, several universities piloted virtual simulation platforms such as Labster and Body Interact in Nursing, Pharmacy, and Medical Technology courses. These tools enabled students to enhance their clinical reasoning and lab skills remotely, with positive feedback indicating improved engagement and confidence (Palompon et al., 2021). Still, access disparities, especially in rural areas, and a lack of standardized implementation remain key barriers. Self-efficacy has emerged as a critical factor in student learning and resilience in rigorous programs like Medical Technology. Filipino students with higher self-efficacy demonstrate greater academic persistence and confidence (Dela Cruz & Tullao, 2020). VR can support this by offering immersive, low-risk environments where learners build competence through realistic repetition, ultimately reducing anxiety and reinforcing performance readiness. Studies also show that multimodal approaches—blending digital simulations with traditional instruction—improve learning outcomes and self-perceived competence among Filipino health science students (Padilla et al., 2022). Though large-scale studies are still emerging, early evidence supports VR’s role in enhancing both technical skills and psychological preparedness in clinical education. Gender remains a notable consideration in STEM learning behaviors. While gender enrollment in Medical Technology is relatively balanced, research reveals that female students often exhibit more academic diligence and anxiety, while male students tend to show higher confidence and risk tolerance (Villanueva & Umali, 2019). These tendencies influence how learners interact with VR. Female students tend to prefer structured, guided simulations, whereas males are more inclined toward self-directed exploration (Lopez & Corpuz, 2021). Recognizing these differences is essential for designing inclusive VR learning environments that support all learners equitably. National policy supports the integration of such innovations. The Commission on Higher Education (CHED) encourages adaptive, tech-driven learning to better prepare students for clinical practice (CHED Memorandum Order No. 13, s. 2017). Similarly, the Department of Science and Technology (DOST) promotes digital tools to strengthen STEM capacity across the country (DOST-PCIEERD, 2022). While momentum is growing, the success of VR in higher education still depends on addressing challenges in access, content localization, and faculty development. 2.5. Synthesis The incorporation of virtual reality (VR) simulations into the learning process has drastically changed laboratory instruction, especially in health sciences like Medical Technology. VR provides interactive and immersive environments where students can interact with laboratory activities securely and in a flexible manner (Makransky & Mayer, 2022; Radianti et al., 2020). Such simulations have been particularly helpful amid the COVID-19 pandemic, when access to physical lab facilities was restricted. Platforms such as Labster have made it possible for students to practice sophisticated diagnostic procedures—microscopy, microbiology, and hematology, for example—remotely and successfully (Gunaydin et al., 2022). VR not only enhances cognitive learning but also develops soft skills like critical thinking and decision-making, hence serving as an indispensable resource when getting students ready for clinical and laboratory practice. Intrinsic motivation, which is doing something for its own sake, is a key factor in student motivation and persistence of learning (Ryan & Deci, 2000). The Intrinsic Motivation Inventory (IMI) is commonly used to assess interest, enjoyment, perceived competence, and value in a learning activity (McAuley et al., 1989). In VR-enriched learning, such motivational factors are further accentuated by elements such as interactivity and instantaneous feedback, factors that enhance higher learner engagement (Chen et al., 2020; Makransky et al., 2019). Gender-based differences in intrinsic motivation in VR environments have provided mixed findings. Whereas some research indicates that males would present higher comfort levels at first from previous interactions with gaming interfaces, others indicate that female students perform at the same level or even better if simulations are well defined and goal-driven (Bucchi et al., 2023; Cai et al., 2020). Learner satisfaction is an essential aspect of simulation-based education, closely associated with heightened engagement, motivation, and performance (Franklin et al., 2014). LSSS assesses students' views on the realism, utility, and instructional quality of simulations (Jeffries & Rizzolo, 2006). Research indicates that VR simulations typically produce high levels of satisfaction, particularly when they are designed to be intuitive and immersive (Foronda et al., 2020). Although female students may initially encounter more difficulties in adapting to VR technology, they often report greater satisfaction when learning objectives are clearly defined and the simulation environment is conducive (Radianti et al., 2020). Perceived learning, which is a subjective evaluation of how much students feel they have learned, includes cognitive, emotional, and psychomotor dimensions of the educational experience (Alqurashi, 2019; Caspi & Blau, 2011). It acts as a significant complement to objective evaluations, especially in VR-enhanced instruction where engagement and user experience significantly affect learning perceptions (Sun & Rueda, 2012). Studies indicate that while female students may prioritize structure and contextual relevance in VR learning settings, well-crafted simulations can promote similar learning perceptions across genders (Makransky et al., 2021). 3. Tables and figures Table 1 Mean, Standard Deviation, and Interpretation of Perceived Learning of First Year BSMT Students (n = 45) Statement 4 3 2 1 Mean St. Dev. Interpretation Intrinsic Motivation Inventory I enjoyed participating in this VR laboratory activity. 22 21 2 3.44 0.59 Strongly Agree I think I was able to learn important skills from the activity. 23 19 3 3.44 0.62 Strongly Agree I put a lot of effort into this simulation. 20 23 2 3.40 0.58 Strongly Agree I felt tense while using the VR simulation. (R) 9 9 21 6 2.47/2.53 0.97 Agree I believe this VR activity was not useful for my learning. (R) 3 3 9 30 1.53/3.47 0.89 Strongly Agree Weighted Mean 3.26 Strongly Agree General Self-Efficacy Scale I can always manage to solve difficult tasks if I try hard enough. 17 23 4 1 3.24 0.71 Agree I am confident in my ability to perform laboratory procedures. 6 32 7 2.98 0.54 Agree I am doubtful that I can learn technical laboratory tasks. (R) 2 10 25 8 2.13/2.87 0.76 Agree If I am in trouble, I can think of a solution quickly. 1 31 13 2.73 0.50 Agree I am confident I could master the laboratory tasks with practice. 16 26 2 1 3.27 0.65 Strongly Agree Weighted Mean 3.02 Agree Learner Satisfaction with Simulation Scale The VR simulation met my learning needs. 8 30 7 3.02 0.58 Agree The objectives of the VR simulation were clear. 24 20 1 3.51 0.55 Strongly Agree The simulation realistically reflected actual laboratory work. 12 29 4 3.18 0.58 Agree I feel more prepared to perform laboratory tasks after this. 10 25 10 3.00 0.67 Agree I am not satisfied with my experience using VR for laboratory skills. 3 5 17 20 1.80/3.20 0.89 Agree Weighted Mean 3.18 Agree Total Weighted Mean 3.15 Agree Legend: 1.00 – 1.74 (Strongly Disagree), 1.75 – 2.49 (Disagree), 2.50 – 3.24 (Agree), 3.25 – 4.00 (Strongly Agree); (R): Reverse Coding Table 1 presents the descriptive statistics of first year BSMT students' responses regarding their intrinsic motivation, general self-efficacy, and learning satisfaction during the virtual reality (VR) laboratory activity. The results revealed that students generally had positive perceptions toward the VR simulation across the three measured domains. For the Intrinsic Motivation Inventory, a weighted mean of 3.26 (SD = 0.73) indicates that participants strongly agreed that they enjoyed the activity, learned important skills, and exerted effort during the simulation. Negative statements were reverse-coded, resulting in favorable agreement (Deci & Ryan, 2000). The General Self-Efficacy Scale showed a weighted mean of 3.02 (SD = 0.63), corresponding to an "Agree" interpretation. This suggests that participants believed in their capability to solve problems and learn technical laboratory tasks, aligning with previous studies linking self-efficacy to academic performance (Schwarzer & Jerusalem, 1995). For the Learner Satisfaction with Simulation Scale, the weighted mean was 3.18 (SD = 0.65), indicating an "Agree" response. Students generally felt that the VR simulation met their learning needs, objectives were clear, and they felt somewhat more prepared for laboratory work. The overall weighted mean of 3.15 demonstrates an "Agree" interpretation across all scales. This suggests that VR simulation as a laboratory learning tool provided a generally satisfying experience with favorable motivation and self-efficacy outcomes. These findings support the potential of VR integration in laboratory education, as suggested by prior research emphasizing the effectiveness of simulation-based learning in enhancing motivation, competence, and learner satisfaction (Cook et al., 2011; Santiago & Mercado, 2023). Table 2 Mean, Standard Deviation, and Interpretation of Perceived Learning of Female BSMT Students (n = 33) Statement 4 3 2 1 Mean St. Dev. Interpretation Intrinsic Motivation Inventory I enjoyed participating in this VR laboratory activity. 17 14 2 3.45 0.62 Strongly Agree I think I was able to learn important skills from the activity. 17 13 3 3.42 0.66 Strongly Agree I put a lot of effort into this simulation. 18 14 1 3.52 0.57 Strongly Agree I felt tense while using the VR simulation. (R) 7 6 15 5 2.45/2.55 1.00 Agree I believe this VR activity was not useful for my learning. (R) 1 3 5 24 1.42/3.58 0.79 Strongly Agree Weighted Mean 3.30 Strongly Agree General Self-Efficacy Scale I can always manage to solve difficult tasks if I try hard enough. 13 16 3 1 3.24 0.75 Agree I am confident in my ability to perform laboratory procedures. 6 22 5 3.03 0.59 Agree I am doubtful that I can learn technical laboratory tasks. (R) 2 7 17 7 2.12/2.88 0.82 Agree If I am in trouble, I can think of a solution quickly. 1 24 8 0 2.79 0.48 Agree I am confident I could master the laboratory tasks with practice. 12 18 2 1 3.24 0.71 Agree Weighted Mean 3.04 Agree Learner Satisfaction with Simulation Scale The VR simulation met my learning needs. 5 23 5 3.00 0.56 Agree The objectives of the VR simulation were clear. 19 13 1 3.55 0.56 Strongly Agree The simulation realistically reflected actual laboratory work. 8 22 3 3.15 0.57 Agree I feel more prepared to perform laboratory tasks after this. 8 19 6 3.06 0.66 Agree I am not satisfied with my experience using VR for laboratory skills. 1 4 12 16 1.70/3.30 0.81 Strongly Agree Weighted Mean 3.21 Agree Total Weighted Mean 3.18 Agree Legend: 1.00 – 1.74 (Strongly Disagree), 1.75 – 2.49 (Disagree), 2.50 – 3.24 (Agree), 3.25 – 4.00 (Strongly Agree); (R): Reverse Coding Table 2 summarizes the descriptive statistics of first year female BSMT students' perceptions regarding intrinsic motivation, general self-efficacy, and learning satisfaction after engaging in a VR laboratory simulation. The findings indicate generally positive perceptions of the VR simulation experience. For the Intrinsic Motivation Inventory, the weighted mean was 3.30 (SD ≈ 0.73), corresponding to a “Strongly Agree” interpretation. This suggests that students found the VR laboratory engaging, skill-enhancing, and worthy of effort. Statements that were negatively worded were reverse-coded, further strengthening the overall favorable responses (Deci & Ryan, 2000). The General Self-Efficacy Scale showed a weighted mean of 3.04 (SD ≈ 0.67), interpreted as “Agree.” This indicates that students generally believed in their ability to perform and learn laboratory-related skills, which is consistent with literature emphasizing the role of self-efficacy in academic performance (Schwarzer & Jerusalem, 1995). For the Learner Satisfaction with Simulation Scale, the weighted mean was 3.21 (SD ≈ 0.64), interpreted as “Agree.” This suggests that the VR simulation generally met the learners’ needs and objectives and contributed positively to their perceived preparedness for laboratory work. The overall weighted mean was 3.18, suggesting that students had an overall positive experience (Agree) with the VR laboratory simulation, indicating its potential as an effective educational tool in laboratory education, supported by prior findings on simulation-based learning (Cook et al., 2011; Santiago & Mercado, 2023). Table 3 Mean, Standard Deviation, and Interpretation of Perceived Learning of Male BSMT Students (n = 12) Statement 4 3 2 1 Mean St. Dev. Interpretation Intrinsic Motivation Inventory I enjoyed participating in this VR laboratory activity. 5 7 3.42 0.51 Strongly Agree I think I was able to learn important skills from the activity. 6 6 3.50 0.52 Strongly Agree I put a lot of effort into this simulation. 2 9 1 3.08 0.51 Agree I felt tense while using the VR simulation. (R) 2 3 6 1 2.50/2.50 0.90 Agree I believe this VR activity was not useful for my learning. (R) 2 4 6 1.83/3.17 1.11 Agree Weighted Mean 3.13 Agree General Self-Efficacy Scale I can always manage to solve difficult tasks if I try hard enough. 4 7 1 3.25 0.62 Strongly Agree I am confident in my ability to perform laboratory procedures. 10 2 2.83 0.39 Agree I am doubtful that I can learn technical laboratory tasks. (R) 2 9 1 2.17/2.83 0.58 Agree If I am in trouble, I can think of a solution quickly. 7 5 2.58 0.51 Agree I am confident I could master the laboratory tasks with practice. 4 8 3.33 0.49 Strongly Agree Weighted Mean 2.97 Agree Learner Satisfaction with Simulation Scale The VR simulation met my learning needs. 3 7 2 3.08 0.67 Agree The objectives of the VR simulation were clear. 5 7 3.42 0.51 Strongly Agree The simulation realistically reflected actual laboratory work. 4 7 1 3.25 0.62 Strongly Agree I feel more prepared to perform laboratory tasks after this. 2 6 4 2.83 0.72 Agree I am not satisfied with my experience using VR for laboratory skills. 2 1 5 4 2.08/2.92 1.08 Agree Weighted Mean 3.10 Agree Total Weighted Mean 3.07 Agree Legend: 1.00 – 1.74 (Strongly Disagree), 1.75 – 2.49 (Disagree), 2.50 – 3.24 (Agree), 3.25 – 4.00 (Strongly Agree); (R): Reverse Coding Table 3 presents the descriptive statistics of first-year male BSMT students’ responses regarding intrinsic motivation, general self-efficacy, and learner satisfaction during the VR laboratory simulation. The results reveal that the participants generally had a positive perception of the VR learning activity. For the Intrinsic Motivation Inventory, the weighted mean was 3.13 (SD ≈ 0.71), corresponding to an “Agree” interpretation. While students generally agreed that they enjoyed the activity and learned important skills, their effort exerted during the activity was slightly lower compared to enjoyment and skill acquisition. Despite the presence of negatively worded items, responses remained generally favorable after reverse scoring (Deci & Ryan, 2000). The General Self-Efficacy Scale produced a weighted mean of 2.97 (SD ≈ 0.56), also interpreted as “Agree”. This suggests that students were moderately confident in their ability to learn and perform laboratory-related tasks. These findings are consistent with the established role of self-efficacy in facilitating student engagement and performance (Schwarzer & Jerusalem, 1995). For the Learner Satisfaction with Simulation Scale, a weighted mean of 3.10 (SD ≈ 0.68) was observed, interpreted as “Agree”. Male students reported that the VR simulation generally met their learning needs and that its objectives were clear. They also perceived the simulation as realistically reflecting laboratory work. The overall weighted mean of 3.07 indicates that male BSMT students agreed that the VR simulation was beneficial and contributed positively to their learning experience. This aligns with prior studies that highlight the value of simulation-based instruction in medical education (Cook et al., 2011; Santiago & Mercado, 2023). Table 4 Independent Sample T-Test of Intrinsic Motivation Inventory Between Gender Group n M SD t(df) p 95% CI for Mean Difference Cohen’s d Female 33 3.30 0.44 1.18 (43) .246 [-0.11, 0.45] 0.40 Male 12 3.13 0.38 Table 4 shows an independent samples t-test which was conducted to determine whether there was a significant difference in perceived learning, measured using the Intrinsic Motivation Inventory (IMI), between female and male students who participated in VR laboratory simulations. The analysis revealed that female students (M = 3.30, SD = 0.44, n = 33) had slightly higher perceived learning scores than male students (M = 3.13, SD = 0.38, n = 12). However, this difference was not statistically significant , t(43) = 1.18, p = .246, 95% CI [-0.11, 0.45] , with a small effect size ( Cohen’s d = 0.40 ). These findings suggest that gender did not have a significant influence on students’ perceived learning in VR laboratory simulations. This result is consistent with the notion that intrinsic motivation toward learning, including in technology-enhanced environments, is influenced more by individual interest and perceived competence rather than demographic factors such as gender (Deci & Ryan, 2000). Table 5 Independent Sample T-Test of General Self-Efficacy Scale Between Gender Group n M SD t(df) p 95% CI for Mean Difference Cohen’s d Female 33 3.04 0.43 0.52 (43) .604 [-0.19, 0.33] 0.18 Male 12 2.97 0.28 Table 5 shows an independent samples t-test which was conducted to determine whether there was a significant difference in general self-efficacy between female and male students who engaged in VR laboratory simulations. The results showed that female students (M = 3.04, SD = 0.43, n = 33) reported slightly higher levels of general self-efficacy compared to male students (M = 2.97, SD = 0.28, n = 12); however, this difference was not statistically significant , t(43) = 0.52, p = .604, 95% CI [-0.19, 0.33], with a small effect size ( Cohen’s d = 0.18 ). These findings indicate that gender was not a significant factor influencing general self-efficacy in the context of VR laboratory simulations. This is consistent with previous research suggesting that general self-efficacy is shaped more by individual psychological resources and task-related experiences than by demographic characteristics (Schwarzer & Jerusalem, 1995). Table 6 Independent Sample T-Test of Learner Satisfaction with Simulation Scale Between Gender Group n M SD t(df) p 95% CI for Mean Difference Cohen’s d Female 33 3.21 0.47 0.72 (43) .483 [-0.21, 0.44] 0.24 Male 12 3.10 0.46 Table 6 shows an independent sample t-test which was conducted to examine whether there is a significant difference in learning satisfaction with simulation between female and male participants. The results revealed no statistically significant difference between the two groups, t(43) = 0.82, p = .483, with females (M = 3.21, SD = 0.47) reporting slightly higher mean satisfaction compared to males (M = 3.10, SD = 0.46). The 95% confidence interval for the mean difference ranged from -0.21 to 0.44 (Cohen’s d = 0.24). These findings suggest that gender does not meaningfully influence perceived satisfaction with simulation-based learning, consistent with previous studies on learner engagement and gender-neutral instructional design (Santos et al., 2021). Table 7 Independent Sample T-Test of Overall Perceived Learning Using VR Laboratory Simulations Between Gender Group n M SD t(df) p 95% CI for Mean Difference Cohen’s d Female 33 3.18 0.38 [–0.10, 0.34] 1.09 .284 0.32 Male 12 3.07 0.29 Table 7 shows an independent samples t -test which was conducted to compare overall perceived learning between female and male students using a simulation-based learning scale. The analysis revealed that there was no statistically significant difference in overall perceived learning between the female group ( M = 3.18, SD = 0.38) and the male group ( M = 3.07, SD = 0.29), t (43) = 1.09, p = .284. The 95% confidence interval for the mean difference was [–0.10, 0.34], indicating that the true difference in perceived learning may be minimal. The effect size, as measured by Cohen’s d , was 0.32, suggesting a small to moderate effect (Cohen, 1988; Lakens, 2013). These findings imply that gender may not play a significant role in influencing students’ overall perceived learning within simulation-based environments. This result aligns with previous studies that found no significant gender differences in perceived learning outcomes in technology-enhanced learning environments (Kay et al., 2009; Liaw & Huang, 2013). However, other research has reported significant differences, with females often perceiving higher levels of learning and engagement, possibly due to differences in learning strategies or affective responses to instructional design (Papastergiou, 2009; Alghamdi et al., 2020). These mixed findings suggest that contextual factors such as instructional method, subject matter, and technological familiarity may moderate the relationship between gender and perceived learning 4. Discussion This study adds to the growing literature on simulation-based education by highlighting how Virtual Reality (VR) influences self-efficacy among freshmen Medical Technology students in the Philippines, particularly through a gender lens. While VR has been widely applied in global health education, its integration into entry-level MedTech programs in the local context remains sparse. By introducing gender as a variable, this study offers a fresh approach to understanding learner diversity in immersive environments. Addressing a gap in the literature, this research shifts focus from advanced simulations typically used in nursing and medical programs to the foundational phase of Medical Technology education. This is a critical stage for building technical confidence and professional identity. Moreover, analyzing gender-based learning patterns supports the demand for inclusive instructional strategies in STEM (Koivisto et al., 2021; Makransky & Mayer, 2022). The findings present practical value for educators and curriculum developers. VR serves as an effective supplemental tool, fostering both skill acquisition and learner confidence—traits essential for clinical preparedness. Customizing VR experiences based on gender-related learning preferences may further enhance outcomes (Lopez & Corpuz, 2021). These insights align with national priorities on educational technology integration (CHED, 2017; DOST-PCIEERD, 2022). For students, particularly beginners, VR provides a low-risk environment that encourages hands-on learning, repetition, and immediate feedback. This not only simplifies complex laboratory tasks but also builds the self-efficacy needed for academic persistence and success in board exams and clinical practice (Bandura, 1997; Dela Cruz & Tullao, 2020). Ultimately, by contributing localized, gender-responsive data, the study reinforces the need for context-aware innovations in health education. As institutions strive for global competitiveness, the thoughtful use of VR can help bridge educational gaps, foster engagement, and improve student performance across diverse groups. 6. Recommendation Integrate VR Simulation Regularly in Laboratory Courses . Since students generally demonstrated positive perceptions toward the VR simulation regardless of gender, academic programs should consider integrating VR-based activities regularly into medical technology laboratory subjects. This will enhance engagement and perceived learning across all students. Enhance Realism and Interactivity of VR Simulations . Although students agreed on the usefulness of VR, refining the realism and interactivity of simulations may further increase perceived preparedness and engagement. Including modules that mimic complex laboratory tasks and introducing adaptive feedback could enhance perceived learning outcomes. Provide Orientation and Skill-Building Workshops . To maximize the benefits of VR simulations, orientation sessions and preparatory workshops should be conducted before VR exposure. These can help students, especially those less confident, to familiarize themselves with the interface and maximize learning gains. Incorporate VR as a Supplement, Not a Replacement . While VR is effective in improving perceived learning, it should serve as a complementary tool to physical laboratory sessions. Combining both modalities can bridge gaps in skill acquisition, especially for technical laboratory procedures. Conduct Continuous Evaluation and Improvement . Regular feedback mechanisms should be established to monitor students' evolving needs and satisfaction with VR simulations. Incorporating student suggestions can guide curriculum adjustments and ensure that VR integration remains aligned with learning goals. Promote Inclusive Learning Practices . Despite no significant gender difference in perceived learning, it is recommended that educators remain sensitive to varied student learning styles. Inclusive teaching strategies should be employed to ensure that all students—regardless of gender, prior experience, or confidence level—benefit equally from VR-based learning environments. Add Qualitative Feedback. Including qualitative feedback offers richer insights into students’ learning experiences beyond numerical data. It captures personal perceptions, challenges, and suggestions that can guide future improvements in the implementation of VR simulations. These narratives help contextualize the quantitative findings and can uncover themes or issues that standardized instruments may overlook. Consider the Role of Other Demographic Factors. Analyzing additional demographic variables—such as socioeconomic status, prior exposure to technology, or learning preferences—provides a more nuanced understanding of how VR simulations influence self-efficacy. This broader perspective can reveal subgroup differences and enhance the generalizability and inclusiveness of the intervention across diverse student populations. Declarations Ethics Approval and Consent to Participate This research maintained the highest level of ethical practices in carrying out the research with human respondents. Before proceeding with data collection, an ethical clearance application was secured from the National University-Clark Research Ethics Committee with an expedited review in accordance with the ethical guidelines. All participants were informed by the researcher about the nature, purpose, and procedures of the research, as well as any risks or benefits associated with it. Informed consent was elicited from all participants before their engagement in the study. Participation was purely voluntary, and respondents will be made aware of their right to withdraw at any time without any type of penalty. Confidentiality was assured by not collecting any identifying information and reporting data in aggregate form. Data collected was stored safely and accessible only by the researchers. Artificial Intelligence (AI), specifically OpenAI’s ChatGPT, was used as a writing support tool. The AI was utilized to assist in structuring the proposal and enhancing the academic tone of selected sections. However, all content was critically reviewed, revised, and validated by the researcher to ensure accuracy, ethical compliance, and scholarly integrity. The application of AI does not substitute for the researcher's analytical duty but facilitates means to enhance lucidity and coherence in written communication. All research practices were followed in conformity with the ethical guidelines of autonomy, beneficence, non-maleficence, and justice, as per the Declaration of Helsinki and local ethical guidelines. Consent for Publication Not applicable. Availability of Data and Materials Available from the corresponding author upon reasonable request. Competing Interests The authors declare no competing interests. Funding Not Applicable. Acknowledgements Not applicable. References Aebersold M. Simulation-based learning: No longer a novelty in undergraduate education. Online J Issues Nurs. 2018;23(2). ttps://doi.org/10.3912/OJIN.Vol23No02PPT39. Al-Ghareeb AZ, Cooper SJ. A literature review of simulation-based education for medical laboratory technologists. J Med Educ Curric Dev. 2016;3:77–85. ttps://doi.org/10.4137/JMECD.S34503. Al-Saud LM, Mushtaq F, Allsop MJ, Culmer PR, Mirghani I, Yates E, Gallagher JE, Manogue M. Feedback and motor skill acquisition using a haptic dental simulator. 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Virtual reality in medical education: A meta-analysis of randomized controlled studies. Comput Educ. 2022;187:104542. ttps://doi.org/10.1016/j.compedu.2022.104542. Koivisto JM, Niemi H, Multisilta J, Katajisto J. Learning by gaming: Student nurses’ experiences of learning key clinical skills through a game. Nurse Educ Today. 2021;94:104587. ttps://doi.org/10.1016/j.nedt.2020.104587. Lopez RP, Corpuz AR. Gender-based learning styles and educational technology use among nursing students. Philippine J Nurs. 2021;91(2):56–63. Makransky G, Mayer RE. Benefits of matching modality of instruction to cognitive style in immersive virtual reality learning. Learn Instruction. 2022;80:101624. ttps://doi.org/10.1016/j.learninstruc.2022.101624. Makransky G, Terkildsen TS, Mayer RE. Adding immersive virtual reality to a science lab simulation causes more presence but less learning. Learn Instruction. 2019;60:225–36. ttps://doi.org/10.1016/j.learninstruc.2017.12.007. Radianti J, Majchrzak TA, Fromm J, Wohlgenannt I. A systematic review of immersive virtual reality applications for higher education: Design elements, lessons learned, and research agenda. Comput Educ. 2020;147:103778. ttps://doi.org/10.1016/j.compedu.2019.103778. Sun JCY, Rueda R. Situational interest, computer self-efficacy and self-regulation: Their impact on student engagement in distance education. Br J Edu Technol. 2012;43(2):191–204. ttps://doi.org/10.1111/j.1467-8535.2010.01157.x. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9034418","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":625811205,"identity":"39e9b9f2-75a7-4c04-afa9-dc343955865e","order_by":0,"name":"John Derrick Chan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8UlEQVRIiWNgGAWjYBACxnYGNiBlA2YfYGBIYABjxgY8WprBWtLAHOK0MDCDtRwmQQtzM/OzBz93nM8zOMD84MDPPWkM/Ow5BsyFO/A5jM3csPfM7WKDA2wGB3ue5TBI9rwxYJ55Bp8WHjYJ3rbbiRvuv2E4wHOggsHgBtAW3jb8WiT/tp1L3HCAh+HgH6AWe2K0SPO2HQBrOcxzIIfBQIKgFjYzadm25MSZQL8cljmQxiNx5lnB4Zl4tBi2Nz+TfNtml9h3gPnhwzcHkuX425M3Pi7Ep6UBTYAHRBzGrYGBQR6rKDM+LaNgFIyCUTDiAAAc61IyIgtatwAAAABJRU5ErkJggg==","orcid":"","institution":"National University","correspondingAuthor":true,"prefix":"","firstName":"John","middleName":"Derrick","lastName":"Chan","suffix":""}],"badges":[],"createdAt":"2026-03-05 00:23:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9034418/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9034418/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107869770,"identity":"80f6a093-e8e8-43da-a897-b88bf196d10b","added_by":"auto","created_at":"2026-04-27 07:38:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":618149,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9034418/v1/80a8912d-fd74-4906-900c-44040f366149.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Virtual Reality (VR) laboratory simulations: Self-efficacy outcomes in freshmen MedTech students: A gender-based comparison","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eIn contemporary health sciences education, the integration of technology into traditional instructional methods has become increasingly vital in cultivating competence among students. The advent of virtual reality (VR) has introduced transformative approaches to laboratory learning, providing immersive and interactive environments that bridge theoretical concepts with practical applications (Goh \u0026amp; Sandars, 2020). This technological innovation has found relevance in medical technology education, where laboratory proficiency is integral to the development of core competencies.\u003c/p\u003e\n\u003cp\u003eMedical laboratory science programs are structured to build both theoretical knowledge and technical skills necessary for clinical practice. However, limitations such as resource constraints, safety concerns, and restricted laboratory access often hinder optimal learning experiences, especially for novice learners (Chen et al., 2020). The disruption caused by the COVID-19 pandemic further underscored these challenges, as the abrupt shift to remote learning modalities magnified the gaps in laboratory instruction (Gunaydin et al., 2022). In response, VR simulations emerged as a pivotal educational alternative, offering realistic, repeatable laboratory scenarios in a controlled virtual environment. These platforms promote active engagement and cognitive immersion, which have been shown to enhance learners\u0026apos; motivation and perceived competence in performing laboratory tasks.\u003c/p\u003e\n\u003cp\u003eWhile numerous studies have underscored the efficacy of VR in improving educational outcomes in allied health programs, there remains a gap in the literature specifically addressing its impact on perceived learning among first-year Medical Technology students. Furthermore, understanding potential variations in learning experiences based on gender is equally essential, given evidence suggesting that individual learner characteristics may influence interaction with technological tools (Al-Saud et al., 2017).\u003c/p\u003e\n\u003cp\u003eGiven this context, the present study was conceptualized not only in response to the growing integration of VR in education but also due to the pedagogical disruptions experienced during the COVID-19 pandemic. This study aims to evaluate the impact of VR laboratory simulations on the perceived learning of freshmen enrolled in a Bachelor of Science in Medical Technology program. Additionally, it seeks to determine whether significant differences exist in perceived learning outcomes between male and female students. The findings of this study are expected to provide valuable insights for curriculum developers and educators in optimizing technology-assisted instructional strategies tailored to diverse learner needs.\u003c/p\u003e\n\u003cp\u003e1.1 \u0026nbsp;Objectives of the Study\u003c/p\u003e\n\u003cp\u003eThis study aims to assess the impact on perceived learning in BSMT freshmen students of virtual reality laboratory simulations. Specifically, this aims to:\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eHow is the perceived learning in BSMT freshmen students of virtual reality laboratory simulations be described in terms of Intrinsic Motivation Inventory, General Self-Efficacy Scale, and Learner Satisfaction with Simulation Scale?\u003c/li\u003e\n \u003cli\u003eIs there a significant difference between male and female BSMT freshmen students in terms of Intrinsic Motivation Inventory, General Self-Efficacy Scale, and Learner Satisfaction with Simulation Scale?\u003c/li\u003e\n \u003cli\u003eIs there a significant difference between the impact on perceived learning of virtual reality laboratory simulations of male and female BSMT freshmen students?\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e1.2. \u003cem\u003eHypothesis of the Study\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e1.2.1. Null Hypothesis\u003c/p\u003e\n\u003cp\u003eH\u003csub\u003e01\u003c/sub\u003e: There is no significant difference between the intrinsic motivation inventory of male and female BSMT freshmen students\u003c/p\u003e\n\u003cp\u003eH\u003csub\u003e02\u003c/sub\u003e: There is no significant difference between the General Self-Efficacy Scale of male and female BSMT freshmen students\u003c/p\u003e\n\u003cp\u003eH\u003csub\u003e03\u003c/sub\u003e: There is no significant difference between the Learner Satisfaction with Simulation Scale of male and female BSMT freshmen students\u003c/p\u003e\n\u003cp\u003eH\u003csub\u003e04\u003c/sub\u003e: There is no significant difference between the impact on perceived learning of virtual reality laboratory simulations of male and female BSMT freshmen students\u003c/p\u003e\n\u003cp\u003e1.3. \u003cem\u003eTheoretical Framework\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study is grounded in Bandura\u0026rsquo;s (1997) Self-Efficacy Theory, which posits that individuals\u0026rsquo; beliefs in their ability to execute specific tasks significantly influence their motivation, learning, and performance. Self-efficacy is defined as \u0026ldquo;people\u0026rsquo;s beliefs about their capabilities to produce designated levels of performance that exercise influence over events that affect their lives\u0026rdquo; (Bandura, 1994, p. 71). These beliefs determine how individuals feel, think, motivate themselves, and behave in various contexts, particularly in response to novel or challenging tasks.\u003c/p\u003e\n\u003cp\u003eIn the context of medical technology education, the integration of Virtual Reality (VR) simulations into laboratory instruction offers an innovative approach to developing practical skills and enhancing learners\u0026apos; confidence. Bandura\u0026rsquo;s four sources of self-efficacy\u0026mdash;mastery experiences, vicarious experiences, verbal persuasion, and physiological and affective states\u0026mdash;are particularly relevant when analyzing the outcomes of VR-based learning interventions. Through immersive simulations, students can engage in repeated practice (mastery), observe peer success (vicarious), receive feedback (verbal persuasion), and experience reduced anxiety or heightened engagement (affective states), all of which contribute to shaping their self-efficacy.\u003c/p\u003e\n\u003cp\u003eThis theoretical lens is especially pertinent when considering freshmen medical technology students, who may face increased stress due to the transition into higher education and the rigors of professional training. VR simulations serve as a scaffolding tool, potentially mitigating early anxiety and promoting confidence through controlled, replicable environments. Furthermore, the theory provides a framework for examining gender-based differences in self-efficacy outcomes, as existing literature suggests that males and females may differ in how they perceive and respond to technological learning tools (Zeldin \u0026amp; Pajares, 2000).\u003c/p\u003e\n\u003cp\u003eBy employing Bandura\u0026rsquo;s Self-Efficacy Theory, the present study seeks to explore how VR simulations influence the development of self-efficacy among freshmen medical technology students and whether gender moderates this relationship. Understanding these dynamics can inform instructional strategies, support equitable learning environments, and contribute to the broader discourse on educational technology in health science programs.\u003c/p\u003e\n\u003cp\u003e1.4. \u003cem\u003eResearch Design\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study employed a quantitative cross-sectional observational research design. The primary objective of utilizing this design was to capture a comprehensive snapshot of the perceptions and experiences of first-year Medical Technology students at a single point in time regarding their engagement with virtual reality (VR) laboratory simulations. The cross-sectional approach is particularly appropriate for studies aiming to describe variables and explore relationships between them without manipulating any of the variables under investigation (Setia, 2016). As an observational study, it allowed the researcher to examine participants\u0026rsquo; responses naturally, focusing solely on their perceived learning experiences, satisfaction levels, self-efficacy, and intrinsic motivation after exposure to the VR simulation. By comparing responses across defined subgroups, such as male and female participants, the study was able to investigate potential differences in outcomes based on gender. The design was chosen for its practicality, efficiency, and appropriateness in establishing baseline associations necessary for educational research contexts without requiring longitudinal tracking.\u003c/p\u003e\n\u003cp\u003e1.5. \u003cem\u003eResearch Population\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe participants of this study consisted of first-year Bachelor of Science in Medical Technology (BSMT) students enrolled in the course Biochemistry for Medical Laboratory Science during the third trimester of the academic year 2024\u0026ndash;2025 at a local university located in Bulacan, Philippines. Purposive sampling was utilized to determine the participants, ensuring that only those students who had direct exposure to the virtual reality laboratory simulation were included. There is a total of fifty (50) students currently enrolled in the course.\u003c/p\u003e\n\u003cp\u003eTo determine the appropriate sample size for this study, Slovin\u0026rsquo;s formula was utilized to account for a finite population of 50 freshmen Medical Technology students. This formula is particularly useful when the population size is known, and the desired margin of error is specified. Using the formula, where n is the sample size, N is the population size, and e is the margin of error (typically set at 0.05 for a 95% confidence level), the computed sample size ensures that the results are statistically representative of the population while maintaining manageable data collection. Applying the values the sample size is calculated to be approximately 45 respondents. There was a total of thirty-three (33) females and twelve (12) males.\u003c/p\u003e\n\u003cp\u003e1.6. \u003cem\u003eInclusion and Exclusion Criteria\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eParticipants included in this study were first-year students enrolled in the Bachelor of Science in Medical Technology (BSMT) program at a specific university in Bulacan during the third trimester of the academic year 2024\u0026ndash;2025. Only students officially registered in the Biochemistry for Medical Laboratory Science course who had completed the virtual reality (VR) laboratory simulation were considered eligible. Additionally, participants were required to provide informed consent prior to inclusion in the study. Students who were enrolled in the said course but did not participate in the VR laboratory simulation were excluded from the study. Moreover, students who failed to complete the survey questionnaire or provided incomplete responses were also excluded from the final analysis to maintain the integrity and accuracy of the collected data.\u003c/p\u003e\n\u003cp\u003e1.7. \u003cem\u003eData Collection Tool\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eFor this study, three standardized and validated survey instruments were utilized to collect data aligned with the study objectives. The Intrinsic Motivation Inventory (IMI), developed by Ryan (1982), was used to assess the participants\u0026rsquo; intrinsic motivation, particularly focusing on their engagement and interest in the virtual reality (VR) laboratory simulation experience. Additionally, the General Self-Efficacy Scale (GSES) developed by Schwarzer and Jerusalem (1995) was employed to evaluate participants\u0026rsquo; self-perceived competence in managing learning challenges, particularly in laboratory settings. Furthermore, the Learner Satisfaction with Simulation Scale (LSSS) by Hayden et al. (2014) was adapted to assess the participants\u0026rsquo; satisfaction with the VR laboratory simulation. Each of these instruments has been widely used and validated in educational and simulation-based research, making them suitable for measuring the perceived learning of students in this study. Furthermore, statements 4,5,8, and 15 used reverse coding to make sure that the respondents are answering the questions accurately. The formula \u0026ldquo;(highest score + 1) \u0026ndash; mean\u0026rdquo; is used to measure the reverse score.\u003c/p\u003e\n\u003cp\u003e1.8. \u003cem\u003eInformed Consent and Ethical Consideration\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe researcher strictly adhered to the ethical standards of research writing to protect the rights of the respondents and received an ethical clearance from the National University Clark Research Ethics Committee. Before the data collection commenced, informed consent was individually acquired from each participant prior to their engagement. Participants were informed of the purpose of the study and how the results will be used. Moreover, there was a voluntary participation in the study and were guaranteed the option to refuse or withdraw at any time without facing any consequences Furthermore, all the respondents remained anonymous throughout the study. All the data collected were treated with confidentiality and were solely used for research purpose only. Lastly, an AI language model (ChatGPT by OpenAI) was used to assist in organizing and synthesizing relevant literature, refining survey items, and generating summaries. All outputs were reviewed and validated by the researcher\u003c/p\u003e\n\u003cp\u003e1.9. \u003cem\u003eFunding\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. All research-related expenses were personally financed by the author.\u003c/p\u003e"},{"header":"2.\tLiterature Review","content":"\u003cp\u003e2.1\u0026nbsp;\u0026nbsp;Virtual Reality Laboratory Simulations\u003c/p\u003e\n\u003cp\u003eThe integration of virtual reality (VR) in educational settings has significantly transformed the delivery of laboratory instruction, particularly in science and health-related disciplines. VR refers to a computer-generated simulation of a three-dimensional environment that allows users to interact with digital objects in real-time (Radianti et al., 2020). In laboratory education, VR simulations are designed to replicate real-life experimental procedures, enabling learners to engage with laboratory tasks without the limitations imposed by traditional settings such as equipment availability, safety risks, and resource constraints (Goh \u0026amp; Sandars, 2020).\u003c/p\u003e\n\u003cp\u003eNumerous studies have recognized the potential of VR simulations in enhancing cognitive and affective learning outcomes. According to Gunaydin et al. (2022), the immersive and interactive nature of VR stimulates higher engagement among learners by providing immediate feedback, realistic scenarios, and opportunities for repeated practice. These features contribute not only to knowledge acquisition but also to improved motivation and confidence in performing laboratory-related tasks. Additionally, VR has been found to reduce learning anxiety by allowing students to make mistakes in a risk-free environment, thereby encouraging exploration and active participation (Chen et al., 2020).\u003c/p\u003e\n\u003cp\u003eThe utilization of VR laboratory simulations gained further relevance during the COVID-19 pandemic, as educational institutions worldwide faced unprecedented challenges in maintaining the continuity of laboratory instruction (Al-Saud et al., 2017). With physical laboratories rendered inaccessible, VR platforms emerged as viable alternatives for delivering essential laboratory experiences, particularly in allied health programs. Labster, one of the most recognized VR simulation platforms, has demonstrated positive impacts on student preparedness and academic performance in various medical and science-related courses (Makransky \u0026amp; Mayer, 2022).\u003c/p\u003e\n\u003cp\u003eMoreover, the benefits of VR extend beyond academic achievement. Radianti et al. (2020) emphasized that VR-based laboratory instruction fosters the development of soft skills such as decision-making, critical thinking, and problem-solving—skills that are vital in clinical and laboratory practice. However, while most of the existing literature highlights favorable outcomes, some researchers note that the effectiveness of VR may vary depending on learners’ prior experience with technology, individual learning preferences, and the quality of the simulation itself (Goh \u0026amp; Sandars, 2020).\u003c/p\u003e\n\u003cp\u003e2.1.1. Virtual Reality Laboratory Simulations in BSMT Program\u003c/p\u003e\n\u003cp\u003eThe continuous advancement of educational technologies has reshaped instructional strategies in health science programs, particularly in the field of Medical Technology. Among these innovations, virtual reality (VR) laboratory simulations have emerged as promising tools to enhance students’ understanding of laboratory procedures and diagnostic techniques. VR simulations in the context of Medical Technology provide learners with interactive three-dimensional environments where they can practice and master laboratory skills in a controlled, risk-free setting (Makransky \u0026amp; Mayer, 2022). These platforms are particularly valuable for simulating complex or hazardous procedures that may be difficult to replicate consistently in a conventional laboratory setup.\u003c/p\u003e\n\u003cp\u003eIn Medical Technology education, the mastery of laboratory techniques, including specimen processing, diagnostic testing, and result interpretation, is essential for professional competence. Traditional laboratory instruction often faces challenges related to limited resources, equipment availability, and safety considerations, particularly for first-year students who are still developing familiarity with basic laboratory operations (Radianti et al., 2020). VR laboratory simulations address these issues by providing repeatable, scenario-based experiences that foster procedural proficiency without exposing students to real laboratory risks (Gunaydin et al., 2022).\u003c/p\u003e\n\u003cp\u003eEmpirical studies have supported the role of VR simulations in enhancing cognitive learning outcomes, particularly in medical and allied health education. For instance, research by Chen et al. (2020) demonstrated that VR-enhanced laboratory instruction significantly improves students’ motivation, focus, and perceived competence when performing laboratory activities. Similarly, a study by Lorenzo-Alvarez et al. (2020) reported that students who engaged with VR laboratory simulations exhibited higher levels of confidence and readiness when transitioning to actual laboratory work.\u003c/p\u003e\n\u003cp\u003eThe relevance of VR laboratory simulations in Medical Technology education became even more pronounced during the COVID-19 pandemic, when physical access to laboratories was restricted (Goh \u0026amp; Sandars, 2020). Institutions adopted VR platforms as supplementary tools to ensure the continuity of practical instruction despite the shift to remote learning environments. Platforms like Labster have been widely implemented in medical laboratory courses, offering interactive simulations such as blood typing, microbiology testing, and molecular diagnostics (Makransky et al., 2021). These simulations allow students to navigate diagnostic processes, manipulate virtual equipment, and make critical decisions in diagnostic workflows.\u003c/p\u003e\n\u003cp\u003eFurthermore, VR’s contribution to skill development is not limited to technical proficiency. Studies have shown that VR-based learning also cultivates essential cognitive attributes, including critical thinking, problem-solving, and clinical decision-making—competencies that are indispensable for future Medical Technologists (Radianti et al., 2020). Although VR cannot entirely replace the tactile experiences of real laboratory work, it serves as a complementary pedagogical tool that enriches laboratory education by offering flexibility, accessibility, and individualized pacing (Gunaydin et al., 2022).\u003c/p\u003e\n\u003cp\u003eDespite its promising contributions, successful utilization of VR simulations in Medical Technology programs depends on careful instructional design, institutional support, and appropriate integration with existing curricula. Educators must ensure that VR activities align with intended learning outcomes while considering students’ diverse learning preferences and technological proficiency (Chen et al., 2020). As the demand for skilled Medical Technologists continues to grow, VR laboratory simulations are positioned to play an increasingly important role in preparing students for the practical and analytical demands of the profession.\u003c/p\u003e\n\u003cp\u003e2.1.2. Advantages and Disadvantages of Virtual Reality Laboratory Simulations\u003c/p\u003e\n\u003cp\u003eThe utilization of virtual reality (VR) laboratory simulations has become an emerging trend in medical and allied health education, offering both substantial advantages and notable limitations. As educational institutions continue to integrate technology to improve instructional delivery, understanding both the strengths and challenges of VR laboratory simulations is essential for maximizing their effectiveness in academic settings, particularly in fields such as Medical Technology.\u003c/p\u003e\n\u003cp\u003eOne of the primary advantages of VR laboratory simulations is their capacity to provide learners with a highly immersive and interactive learning environment. Using 3D graphics, real-time feedback, and interactive decision-making tasks, students are placed in realistic laboratory settings where they can safely perform experiments and diagnostic procedures (Makransky \u0026amp; Mayer, 2022). This immersive experience fosters deeper engagement and promotes the active application of theoretical concepts, contributing to better retention of knowledge (Radianti et al., 2020). Moreover, VR simulations allow for repeated practice of procedures without consuming physical resources, reducing operational costs and eliminating risks associated with exposure to hazardous substances (Gunaydin et al., 2022).\u003c/p\u003e\n\u003cp\u003eAnother significant advantage of VR is its flexibility and accessibility. Virtual laboratory environments can be accessed remotely, making them especially valuable during periods of restricted physical interaction, such as the COVID-19 pandemic (Goh \u0026amp; Sandars, 2020). Learners can engage with laboratory content at their own pace and convenience, which promotes individualized learning and accommodates varying levels of proficiency (Chen et al., 2020). Additionally, VR-based laboratory simulations have been found to improve students’ confidence and motivation, particularly when learners receive immediate feedback on their performance, reinforcing their competence in laboratory procedures (Lorenzo-Alvarez et al., 2020).\u003c/p\u003e\n\u003cp\u003eDespite these advantages, VR laboratory simulations are not without their limitations. One common disadvantage is the lack of tactile feedback, which is critical in certain laboratory techniques where the physical sensation of handling equipment and specimens is integral to skill mastery (Makransky et al., 2021). While visual and auditory simulations may approximate real-world scenarios, the absence of haptic sensations can limit students’ preparedness for actual laboratory work. Furthermore, prolonged use of VR equipment has been associated with discomforts such as visual fatigue and motion sickness in some learners (Radianti et al., 2020).\u003c/p\u003e\n\u003cp\u003eAnother challenge is the technological barrier faced by both students and educators. Successful implementation of VR simulations requires access to high-quality hardware, reliable internet connections, and technical support, which may not always be available in all educational institutions, especially in resource-constrained settings (Gunaydin et al., 2022). Additionally, students unfamiliar with VR interfaces may experience cognitive overload or distractions, which could detract from the intended learning outcomes (Makransky et al., 2021).\u003c/p\u003e\n\u003cp\u003e2.1.3. Virtual Reality Laboratory Simulations for Freshmen Students\u003c/p\u003e\n\u003cp\u003eThe transition to higher education presents unique challenges for first-year students, particularly in programs with demanding laboratory components such as Medical Technology. For these students, foundational laboratory skills are essential to future academic and professional success. Virtual reality (VR) laboratory simulations have emerged as valuable tools in addressing these needs by providing immersive and interactive environments that support early skills development and conceptual understanding (Makransky \u0026amp; Mayer, 2022). These simulations play a crucial role in helping freshmen navigate the complexities of laboratory work by bridging the gap between theoretical instruction and practical application.\u003c/p\u003e\n\u003cp\u003eOne of the primary advantages of VR laboratory simulations for freshmen students is their ability to introduce learners to laboratory procedures in a safe, controlled, and accessible environment. Freshmen often enter health science programs with varying levels of familiarity regarding laboratory concepts and equipment, making traditional laboratory environments potentially intimidating or overwhelming (Radianti et al., 2020). By offering realistic and repeatable experiences, VR simulations reduce anxiety and build student confidence, enabling learners to engage with laboratory tasks at their own pace before handling real-life specimens or equipment (Gunaydin et al., 2022).\u003c/p\u003e\n\u003cp\u003eFor freshmen students, early exposure to laboratory processes using VR helps establish a strong cognitive foundation. Studies have shown that students who engage with VR-based laboratories exhibit improved motivation and learning outcomes compared to those exposed solely to conventional methods (Chen et al., 2020). This advantage is particularly significant for first-year students, whose initial academic experiences often shape their attitudes toward their chosen field of study. By integrating VR into early laboratory education, students are empowered to take ownership of their learning, which supports retention and program completion (Lorenzo-Alvarez et al., 2020).\u003c/p\u003e\n\u003cp\u003eThe importance of VR laboratory simulations for freshmen became even more evident during the COVID-19 pandemic. With restrictions on physical classroom access, VR provided a crucial alternative for sustaining laboratory-based education, especially for students in the early stages of their degree programs (Goh \u0026amp; Sandars, 2020). Virtual platforms such as Labster enabled first-year students to engage with diagnostic procedures such as microscopy, hematology testing, and microbiology, ensuring that foundational learning continued despite the disruption of traditional classroom settings (Makransky et al., 2021).\u003c/p\u003e\n\u003cp\u003eAdditionally, VR simulations cater to different learning styles, providing visual, auditory, and interactive feedback that appeals to a wide range of learners (Radianti et al., 2020). This multimodal approach is particularly beneficial for freshmen who are still adjusting to the rigors of tertiary education and need structured, engaging content to maintain focus and build competence.\u003c/p\u003e\n\u003cp\u003eWhile VR cannot fully substitute the tactile experience of hands-on laboratory practice, its early integration into the curriculum provides a scaffolding effect that prepares students for real-world laboratory challenges. As first-year students advance in their studies, the foundational knowledge and confidence gained from VR simulations serve as steppingstones toward mastering more complex laboratory techniques (Makransky \u0026amp; Mayer, 2022).\u003c/p\u003e\n\u003cp\u003e2.1.4. Impact of Virtual Reality Laboratory Simulations between Male and Female\u003c/p\u003e\n\u003cp\u003eAs technological innovations continue to reshape the educational landscape, understanding how various learner demographics respond to instructional tools such as virtual reality (VR) simulations has become increasingly important. One key dimension of learner diversity is gender, with several studies investigating how male and female students differ in their responses to immersive learning environments. In the context of laboratory simulations in health sciences and allied medical programs, examining these differences provides valuable insights into optimizing instructional design and achieving equitable educational outcomes.\u003c/p\u003e\n\u003cp\u003eResearch indicates that gender differences may influence how students experience, interact with, and benefit from VR-based educational tools. Studies have shown that male students often demonstrate greater familiarity and confidence with interactive technology, including VR systems, due to earlier and more frequent exposure to gaming environments and technological devices (Makransky et al., 2019). This prior exposure may contribute to higher engagement levels and comfort when navigating virtual laboratories, particularly during early use (Lamb et al., 2020).\u003c/p\u003e\n\u003cp\u003eConversely, some studies suggest that female students tend to exhibit stronger learning outcomes in structured VR educational settings, particularly when simulations are designed with clear learning objectives and provide consistent feedback (Bucchi et al., 2023). Female learners often emphasize the importance of contextual relevance and clear instructional guidance within VR environments, which can contribute to improved motivation and knowledge retention when these factors are adequately addressed (Cai et al., 2020). Furthermore, female students are reported to excel in collaborative learning tasks within VR platforms, favoring interactions that allow for discussion and reflection on laboratory procedures (Radianti et al., 2020).\u003c/p\u003e\n\u003cp\u003eHowever, while certain trends regarding gender-based differences in VR usage have been observed, research findings remain mixed and context-dependent. For instance, a study by Gunaydin et al. (2022) found no significant difference in the learning outcomes of male and female students using VR-based laboratory simulations when the instructional design was tailored to accommodate diverse user needs. This finding highlights the potential of well-designed VR learning environments to neutralize initial gender-based disparities, offering an equitable platform for laboratory skill acquisition.\u003c/p\u003e\n\u003cp\u003eAdditionally, physiological responses to VR environments have occasionally been observed to differ by gender. Some female learners report greater susceptibility to cybersickness or motion-related discomfort when exposed to immersive VR settings, potentially affecting sustained engagement (Makransky et al., 2021). Nonetheless, improvements in VR hardware and instructional customization continue to mitigate these barriers.\u003c/p\u003e\n\u003cp\u003eUltimately, understanding these gender-based variations is critical, particularly for freshmen students in Medical Technology programs, who may have differing levels of prior exposure to laboratory work and technology-assisted learning. By addressing the unique preferences and challenges of both male and female learners, educators can better leverage VR laboratory simulations to promote balanced academic success across genders (Lamb et al., 2020).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.2. Perceived Learning\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePerceived learning has gained significant attention in educational research as a valuable metric for understanding students’ subjective evaluations of their educational experiences. While academic achievement is typically measured through standardized assessments, perceived learning focuses on learners' self-assessments regarding the extent to which they have acquired knowledge, skills, and competencies from educational activities (Caspi \u0026amp; Blau, 2011). This concept offers educators and researchers insights into students’ internal reflections on their own progress, which may not always align directly with traditional performance metrics.\u003c/p\u003e\n\u003cp\u003eAccording to Alqurashi (2019), perceived learning refers to students' beliefs about how much they have learned, encompassing cognitive, affective, and psychomotor domains. It reflects a learner-centered perspective that highlights the importance of subjective experience in the learning process. The concept emphasizes that learning is not only about knowledge acquisition but also about how students interpret and internalize educational content, particularly in dynamic learning environments such as virtual simulations or online instruction.\u003c/p\u003e\n\u003cp\u003eResearchers have distinguished perceived learning from objective learning outcomes by underscoring that the former is influenced by factors such as motivation, engagement, and the learning environment (Richardson et al., 2017). This subjective evaluation is critical in technology-enhanced educational contexts, where user experience, interface design, and perceived relevance of content can significantly influence students’ perceptions of their learning (Sun \u0026amp; Rueda, 2012).\u003c/p\u003e\n\u003cp\u003eThe multidimensional nature of perceived learning typically involves three key aspects: cognitive learning (knowledge and understanding), affective learning (emotional engagement and attitude formation), and psychomotor learning (practical skill acquisition) (Liaw \u0026amp; Huang, 2013). By capturing these elements, perceived learning provides a holistic perspective on educational effectiveness from the viewpoint of the learner.\u003c/p\u003e\n\u003cp\u003eMoreover, perceived learning has been widely utilized in educational research to evaluate the effectiveness of online platforms, blended learning modalities, and immersive technologies such as virtual reality (Alqurashi, 2019; Sun \u0026amp; Rueda, 2012). Its significance has become even more pronounced in the aftermath of the COVID-19 pandemic, when many educational institutions adopted digital learning technologies that required assessment beyond conventional testing methods (Caspi \u0026amp; Blau, 2011).\u003c/p\u003e\n\u003cp\u003eWhile perceived learning may sometimes be influenced by students’ prior attitudes toward the mode of instruction or technological tools used, its value lies in providing feedback on how learners interpret the educational process itself. Understanding students’ perceptions of their learning helps educators refine instructional strategies and tailor interventions that promote both perceived and actual learning success (Richardson et al., 2017).\u003c/p\u003e\n\u003cp\u003e2.2.1. Intrinsic Motivation Inventory\u003c/p\u003e\n\u003cp\u003eThe Intrinsic Motivation Inventory (IMI) is a multidimensional measurement tool widely used in educational psychology and behavioral science to assess individuals’ subjective experiences related to intrinsic motivation. Developed originally within the framework of self-determination theory (SDT), the IMI has become a foundational instrument in research investigating motivation in various educational, clinical, and recreational settings (Deci \u0026amp; Ryan, 1985). It is particularly valuable in contexts where intrinsic motivation is considered central to sustained engagement and effective learning, such as technology-enhanced or experiential learning environments.\u003c/p\u003e\n\u003cp\u003eIntrinsic motivation refers to engaging in an activity for its inherent satisfaction rather than for some separable consequence, such as rewards or external recognition (Ryan \u0026amp; Deci, 2000). The IMI was specifically designed to assess participants’ interest, enjoyment, perceived competence, effort, value, and relatedness within a given task or activity. As such, it provides a nuanced picture of the motivational drivers influencing learner engagement (McAuley et al., 1989).\u003c/p\u003e\n\u003cp\u003eOne of the strengths of the IMI lies in its multidimensional structure. The most commonly used subscales include Interest/Enjoyment, Perceived Competence, Effort/Importance, Pressure/Tension, Perceived Choice, and Value/Usefulness (Deci \u0026amp; Ryan, 1985). Among these, the Interest/Enjoyment subscale is considered the most direct measure of intrinsic motivation, whereas the other dimensions provide complementary information about factors that support or hinder intrinsic engagement (Tsigilis \u0026amp; Theodosiou, 2003).\u003c/p\u003e\n\u003cp\u003eThe validity and reliability of the IMI have been demonstrated across diverse educational settings, including higher education and immersive learning environments such as virtual reality (VR) simulations (Makransky et al., 2019). Its applicability to technology-assisted learning environments makes it particularly relevant for assessing learner motivation in simulations used in medical and health sciences education (Ryan et al., 2021).\u003c/p\u003e\n\u003cp\u003eMoreover, intrinsic motivation measured by the IMI has been consistently associated with enhanced learning outcomes, deeper engagement, and improved retention of knowledge (Richardson et al., 2017). By capturing the subjective dimensions of learner motivation, the IMI serves as an essential tool for researchers seeking to explore how instructional strategies, including virtual laboratory simulations, impact students' internal motivation to learn.\u003c/p\u003e\n\u003cp\u003e2.2.2. General Self-Efficacy Scale\u003c/p\u003e\n\u003cp\u003eThe General Self-Efficacy Scale (GSES) is a widely recognized psychometric instrument designed to measure an individual’s belief in their ability to cope with a wide variety of challenging demands and novel situations (Schwarzer \u0026amp; Jerusalem, 1995). Rooted in Bandura’s (1977) theory of self-efficacy, the concept underscores the role of personal judgment in one’s ability to organize and execute courses of action required to manage prospective situations. Unlike task-specific self-efficacy measures, the GSES assesses a broad and stable sense of personal competence across various life domains.\u003c/p\u003e\n\u003cp\u003eOriginally developed by Jerusalem and Schwarzer in 1981 and later adapted into English by Schwarzer and Jerusalem (1995), the GSES consists of ten items measured using a Likert scale format. Each item reflects a statement about coping abilities or confidence in addressing obstacles, and higher scores on the scale indicate greater levels of perceived general self-efficacy. The scale has undergone extensive validation across cultural contexts, with reliability coefficients (Cronbach’s alpha) typically ranging from 0.76 to 0.90 (Scholz et al., 2002).\u003c/p\u003e\n\u003cp\u003eSelf-efficacy, as measured by the GSES, has demonstrated significant predictive value in educational, clinical, and occupational settings (Luszczynska et al., 2005). Within the context of education, higher self-efficacy is consistently associated with better academic achievement, increased engagement, and more effective problem-solving skills (Zajacova et al., 2005). Furthermore, in technology-mediated learning environments such as virtual laboratories, students’ self-efficacy often influences their perceived learning outcomes and persistence (Makransky et al., 2019).\u003c/p\u003e\n\u003cp\u003eIn health-related educational programs like medical technology, the GSES is particularly valuable for evaluating how students perceive their ability to engage with complex tasks, including simulations requiring critical thinking and adaptive learning strategies. Its generalizability allows it to be used alongside other instruments, such as the Intrinsic Motivation Inventory (IMI), to provide a comprehensive assessment of learners’ internal capacities for managing academic challenges.\u003c/p\u003e\n\u003cp\u003eGiven the increasing integration of virtual platforms in medical education, particularly in response to the disruptions caused by the COVID-19 pandemic, the GSES remains a relevant tool for assessing students’ psychological readiness for novel instructional approaches (Makransky et al., 2019). By providing insights into learners’ confidence in handling academic demands, the GSES contributes meaningfully to evaluating the effectiveness of innovative teaching modalities such as virtual reality simulations.\u003c/p\u003e\n\u003cp\u003e2.2.3. Learner Satisfaction with Simulation Scale\u003c/p\u003e\n\u003cp\u003eThe Learner Satisfaction with Simulation Scale (LSSS) is a standardized instrument developed to evaluate students’ satisfaction following participation in simulation-based learning activities. Designed specifically for educational contexts utilizing simulations, the LSSS captures learners’ subjective evaluations of the simulation experience, emphasizing factors such as perceived usefulness, realism, clarity of objectives, and overall satisfaction (Jeffries \u0026amp; Rizzolo, 2006). As simulations have become integral to health sciences education, especially in nursing and allied health programs, reliable measures such as the LSSS are necessary to assess the effectiveness of these teaching strategies.\u003c/p\u003e\n\u003cp\u003eLearner satisfaction represents a critical outcome in simulation-based education as it often correlates with higher engagement, improved knowledge retention, and greater confidence in applying learned skills to real-world scenarios (Franklin et al., 2014). The LSSS typically utilizes Likert-scale responses, where participants rate their level of agreement with statements regarding the simulation's instructional value, organization, facilitation, and perceived benefit to their learning process (Hayden et al., 2014).\u003c/p\u003e\n\u003cp\u003eOriginally validated in nursing education by Jeffries and Rizzolo (2006) through the National League for Nursing (NLN), the scale has demonstrated strong psychometric properties. Studies consistently report Cronbach’s alpha values above 0.85, reflecting high internal consistency and reliability (Franklin et al., 2014). The LSSS has since been adopted and adapted in a variety of healthcare education programs, including medical laboratory science, owing to its flexibility and relevance across clinical simulation settings (Al-Ghareeb \u0026amp; Cooper, 2016).\u003c/p\u003e\n\u003cp\u003eIn recent years, the integration of virtual reality (VR) into simulation-based learning has expanded the applicability of the LSSS. Research indicates that VR-based simulations, when evaluated using the LSSS, often yield comparable or higher satisfaction scores than traditional mannequin-based simulations (Foronda et al., 2020). This suggests that learners find immersive technologies both engaging and educationally valuable, provided that instructional goals and technological execution are clear and coherent.\u003c/p\u003e\n\u003cp\u003eAs healthcare education continues to adapt to technological advancements and post-pandemic educational restructuring, tools like the LSSS play a pivotal role in ensuring that instructional innovations are aligned with learner needs and institutional educational outcomes (Aebersold, 2018).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.3. Global Setting\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eVirtual reality (VR) has emerged globally as a transformative tool in health science education, offering immersive simulations that replicate clinical and laboratory environments with high fidelity. Countries like the United States, the United Kingdom, South Korea, and Australia have integrated VR into Medical Technology curricula to enhance student engagement and competency-based learning (Radianti et al., 2020). VR enables hands-on practice without constraints related to space, safety, or resources—benefits that became especially relevant during the COVID-19 pandemic when physical lab access was restricted (Gunaydin et al., 2022). As a result, VR is increasingly valued not just as a contingency tool but as a lasting pedagogical strategy.\u003c/p\u003e\n\u003cp\u003eStudies affirm VR’s positive impact on student self-efficacy—the belief in one’s ability to manage future challenges (Bandura, 1997). In healthcare education, students with high self-efficacy show better persistence, confidence, and clinical performance. Research in Europe and East Asia found that immersive simulations improve perceived competence by allowing repeated, low-risk practice with immediate feedback (Cai et al., 2020; Koivisto et al., 2021; Makransky \u0026amp; Mayer, 2022). These factors are strongly linked to higher self-efficacy and academic resilience.\u003c/p\u003e\n\u003cp\u003eVR also helps address training gaps in psychomotor skills and lab exposure, particularly in Medical Technology programs where traditional setups require costly reagents and strict safety protocols. Institutions in countries like Denmark, Canada, and Japan have adopted platforms such as Labster to simulate diagnostic workflows and reinforce technical skills (Bucchi et al., 2023). These simulations support both conceptual understanding and performance confidence, contributing to better outcomes during clinical internships and licensure exams (Foronda et al., 2020).\u003c/p\u003e\n\u003cp\u003eGender-based differences in how learners respond to VR have also been noted. Males often show quicker immersion in gamified environments, while females typically display stronger organization, self-reflection, and affective engagement (Makransky et al., 2019; Chen et al., 2020). However, when inclusive design principles—like adaptive pacing and structured guidance—are applied, both genders benefit equally from VR learning experiences (Koivisto et al., 2021; Gunaydin et al., 2022).\u003c/p\u003e\n\u003cp\u003eFor freshmen entering demanding fields like Medical Technology, early experiences with VR-based learning can be pivotal. Positive initial exposure to scaffolded, interactive simulations has been shown to boost student confidence, motivation, and persistence across contexts such as the Philippines, Singapore, and Finland (Alqurashi, 2019; Sun \u0026amp; Rueda, 2012). By reinforcing self-efficacy early on, VR may help students better manage academic and psychological challenges throughout their training.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.4. Philippine Setting\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe Philippine education system has steadily advanced in integrating technology-enhanced learning, especially in health sciences where hands-on experience is vital. Although traditional laboratory methods remain widespread, there is growing interest in simulation-based learning, particularly in Medical Technology programs. Simulations allow students to practice complex procedures safely, addressing limitations in equipment, safety, and logistics (Salvador et al., 2021). However, full adoption of immersive tools like virtual reality (VR) is still limited due to infrastructure, cost, and faculty readiness.\u003c/p\u003e\n\u003cp\u003eThe COVID-19 pandemic accelerated digital learning innovations. Faced with mobility restrictions, several universities piloted virtual simulation platforms such as Labster and Body Interact in Nursing, Pharmacy, and Medical Technology courses. These tools enabled students to enhance their clinical reasoning and lab skills remotely, with positive feedback indicating improved engagement and confidence (Palompon et al., 2021). Still, access disparities, especially in rural areas, and a lack of standardized implementation remain key barriers.\u003c/p\u003e\n\u003cp\u003eSelf-efficacy has emerged as a critical factor in student learning and resilience in rigorous programs like Medical Technology. Filipino students with higher self-efficacy demonstrate greater academic persistence and confidence (Dela Cruz \u0026amp; Tullao, 2020). VR can support this by offering immersive, low-risk environments where learners build competence through realistic repetition, ultimately reducing anxiety and reinforcing performance readiness.\u003c/p\u003e\n\u003cp\u003eStudies also show that multimodal approaches—blending digital simulations with traditional instruction—improve learning outcomes and self-perceived competence among Filipino health science students (Padilla et al., 2022). Though large-scale studies are still emerging, early evidence supports VR’s role in enhancing both technical skills and psychological preparedness in clinical education.\u003c/p\u003e\n\u003cp\u003eGender remains a notable consideration in STEM learning behaviors. While gender enrollment in Medical Technology is relatively balanced, research reveals that female students often exhibit more academic diligence and anxiety, while male students tend to show higher confidence and risk tolerance (Villanueva \u0026amp; Umali, 2019). These tendencies influence how learners interact with VR. Female students tend to prefer structured, guided simulations, whereas males are more inclined toward self-directed exploration (Lopez \u0026amp; Corpuz, 2021). Recognizing these differences is essential for designing inclusive VR learning environments that support all learners equitably.\u003c/p\u003e\n\u003cp\u003eNational policy supports the integration of such innovations. The Commission on Higher Education (CHED) encourages adaptive, tech-driven learning to better prepare students for clinical practice (CHED Memorandum Order No. 13, s. 2017). Similarly, the Department of Science and Technology (DOST) promotes digital tools to strengthen STEM capacity across the country (DOST-PCIEERD, 2022). While momentum is growing, the success of VR in higher education still depends on addressing challenges in access, content localization, and faculty development.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.5. Synthesis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe incorporation of virtual reality (VR) simulations into the learning process has drastically changed laboratory instruction, especially in health sciences like Medical Technology. VR provides interactive and immersive environments where students can interact with laboratory activities securely and in a flexible manner (Makransky \u0026amp; Mayer, 2022; Radianti et al., 2020). Such simulations have been particularly helpful amid the COVID-19 pandemic, when access to physical lab facilities was restricted. Platforms such as Labster have made it possible for students to practice sophisticated diagnostic procedures—microscopy, microbiology, and hematology, for example—remotely and successfully (Gunaydin et al., 2022). VR not only enhances cognitive learning but also develops soft skills like critical thinking and decision-making, hence serving as an indispensable resource when getting students ready for clinical and laboratory practice.\u003c/p\u003e\n\u003cp\u003eIntrinsic motivation, which is doing something for its own sake, is a key factor in student motivation and persistence of learning (Ryan \u0026amp; Deci, 2000). The Intrinsic Motivation Inventory (IMI) is commonly used to assess interest, enjoyment, perceived competence, and value in a learning activity (McAuley et al., 1989). In VR-enriched learning, such motivational factors are further accentuated by elements such as interactivity and instantaneous feedback, factors that enhance higher learner engagement (Chen et al., 2020; Makransky et al., 2019). Gender-based differences in intrinsic motivation in VR environments have provided mixed findings. Whereas some research indicates that males would present higher comfort levels at first from previous interactions with gaming interfaces, others indicate that female students perform at the same level or even better if simulations are well defined and goal-driven (Bucchi et al., 2023; Cai et al., 2020).\u003c/p\u003e\n\u003cp\u003eLearner satisfaction is an essential aspect of simulation-based education, closely associated with heightened engagement, motivation, and performance (Franklin et al., 2014). LSSS assesses students' views on the realism, utility, and instructional quality of simulations (Jeffries \u0026amp; Rizzolo, 2006). Research indicates that VR simulations typically produce high levels of satisfaction, particularly when they are designed to be intuitive and immersive (Foronda et al., 2020). Although female students may initially encounter more difficulties in adapting to VR technology, they often report greater satisfaction when learning objectives are clearly defined and the simulation environment is conducive (Radianti et al., 2020).\u003c/p\u003e\n\u003cp\u003ePerceived learning, which is a subjective evaluation of how much students feel they have learned, includes cognitive, emotional, and psychomotor dimensions of the educational experience (Alqurashi, 2019; Caspi \u0026amp; Blau, 2011). It acts as a significant complement to objective evaluations, especially in VR-enhanced instruction where engagement and user experience significantly affect learning perceptions (Sun \u0026amp; Rueda, 2012). Studies indicate that while female students may prioritize structure and contextual relevance in VR learning settings, well-crafted simulations can promote similar learning perceptions across genders (Makransky et al., 2021).\u003c/p\u003e"},{"header":"3.\tTables and figures","content":"\u003cp\u003eTable 1\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMean, Standard Deviation, and Interpretation of Perceived Learning of First Year BSMT Students (n = 45)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 257px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStatement\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSt. Dev.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInterpretation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" style=\"width: 623px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIntrinsic Motivation Inventory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 257px;\"\u003e\n \u003cp\u003eI enjoyed participating in this VR laboratory activity.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e3.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eStrongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 257px;\"\u003e\n \u003cp\u003eI think I was able to learn important skills from the activity.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e3.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eStrongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 257px;\"\u003e\n \u003cp\u003eI put a lot of effort into this simulation.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e3.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eStrongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 257px;\"\u003e\n \u003cp\u003eI felt tense while using the VR simulation. (R)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e2.47/2.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eAgree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 257px;\"\u003e\n \u003cp\u003eI believe this VR activity was not useful for my learning. (R)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e1.53/3.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eStrongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" style=\"width: 438px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeighted Mean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.26\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStrongly Agree\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" style=\"width: 623px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGeneral Self-Efficacy Scale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 257px;\"\u003e\n \u003cp\u003eI can always manage to solve difficult tasks if I try hard enough.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e3.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eAgree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 257px;\"\u003e\n \u003cp\u003eI am confident in my ability to perform laboratory procedures.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e2.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eAgree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 257px;\"\u003e\n \u003cp\u003eI am doubtful that I can learn technical laboratory tasks. (R)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e2.13/2.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eAgree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 257px;\"\u003e\n \u003cp\u003eIf I am in trouble, I can think of a solution quickly.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e2.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eAgree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 257px;\"\u003e\n \u003cp\u003eI am confident I could master the laboratory tasks with practice.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e3.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eStrongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" style=\"width: 438px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeighted Mean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.02\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAgree\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" style=\"width: 623px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLearner Satisfaction with Simulation Scale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 257px;\"\u003e\n \u003cp\u003eThe VR simulation met my learning needs.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e3.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eAgree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 257px;\"\u003e\n \u003cp\u003eThe objectives of the VR simulation were clear.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e3.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eStrongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 257px;\"\u003e\n \u003cp\u003eThe simulation realistically reflected actual laboratory work.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e3.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eAgree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 257px;\"\u003e\n \u003cp\u003eI feel more prepared to perform laboratory tasks after this.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e3.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eAgree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 257px;\"\u003e\n \u003cp\u003eI am not satisfied with my experience using VR for laboratory skills.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e1.80/3.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eAgree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" style=\"width: 438px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeighted Mean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.18\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAgree\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" style=\"width: 438px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Weighted Mean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.15\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAgree\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eLegend: 1.00 \u0026ndash; 1.74 (Strongly Disagree), 1.75 \u0026ndash; 2.49 (Disagree), 2.50 \u0026ndash; 3.24 (Agree), 3.25 \u0026ndash; 4.00 (Strongly Agree); (R): Reverse Coding\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTable 1 presents the descriptive statistics of first year BSMT students\u0026apos; responses regarding their intrinsic motivation, general self-efficacy, and learning satisfaction during the virtual reality (VR) laboratory activity. The results revealed that students generally had positive perceptions toward the VR simulation across the three measured domains.\u003c/p\u003e\n\u003cp\u003eFor the Intrinsic Motivation Inventory, a weighted mean of 3.26 (SD = 0.73) indicates that participants strongly agreed that they enjoyed the activity, learned important skills, and exerted effort during the simulation. Negative statements were reverse-coded, resulting in favorable agreement (Deci \u0026amp; Ryan, 2000).\u003c/p\u003e\n\u003cp\u003eThe General Self-Efficacy Scale showed a weighted mean of 3.02 (SD = 0.63), corresponding to an \u0026quot;Agree\u0026quot; interpretation. This suggests that participants believed in their capability to solve problems and learn technical laboratory tasks, aligning with previous studies linking self-efficacy to academic performance (Schwarzer \u0026amp; Jerusalem, 1995).\u003c/p\u003e\n\u003cp\u003eFor the Learner Satisfaction with Simulation Scale, the weighted mean was 3.18 (SD = 0.65), indicating an \u0026quot;Agree\u0026quot; response. Students generally felt that the VR simulation met their learning needs, objectives were clear, and they felt somewhat more prepared for laboratory work.\u003c/p\u003e\n\u003cp\u003eThe overall weighted mean of 3.15 demonstrates an \u0026quot;Agree\u0026quot; interpretation across all scales. This suggests that VR simulation as a laboratory learning tool provided a generally satisfying experience with favorable motivation and self-efficacy outcomes.\u003c/p\u003e\n\u003cp\u003eThese findings support the potential of VR integration in laboratory education, as suggested by prior research emphasizing the effectiveness of simulation-based learning in enhancing motivation, competence, and learner satisfaction (Cook et al., 2011; Santiago \u0026amp; Mercado, 2023).\u003c/p\u003e\n\u003cp\u003eTable 2\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMean, Standard Deviation, and Interpretation of Perceived Learning of Female BSMT Students (n = 33)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 254px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStatement\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSt. Dev.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInterpretation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" style=\"width: 619px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIntrinsic Motivation Inventory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 254px;\"\u003e\n \u003cp\u003eI enjoyed participating in this VR laboratory activity.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e3.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eStrongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 254px;\"\u003e\n \u003cp\u003eI think I was able to learn important skills from the activity.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e3.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eStrongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 254px;\"\u003e\n \u003cp\u003eI put a lot of effort into this simulation.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e3.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eStrongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 254px;\"\u003e\n \u003cp\u003eI felt tense while using the VR simulation. (R)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e2.45/2.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eAgree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 254px;\"\u003e\n \u003cp\u003eI believe this VR activity was not useful for my learning. (R)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e1.42/3.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eStrongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" style=\"width: 435px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeighted Mean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.30\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStrongly Agree\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" style=\"width: 619px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGeneral Self-Efficacy Scale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 254px;\"\u003e\n \u003cp\u003eI can always manage to solve difficult tasks if I try hard enough.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e3.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eAgree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 254px;\"\u003e\n \u003cp\u003eI am confident in my ability to perform laboratory procedures.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e3.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eAgree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 254px;\"\u003e\n \u003cp\u003eI am doubtful that I can learn technical laboratory tasks. (R)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e2.12/2.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eAgree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 254px;\"\u003e\n \u003cp\u003eIf I am in trouble, I can think of a solution quickly.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e2.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eAgree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 254px;\"\u003e\n \u003cp\u003eI am confident I could master the laboratory tasks with practice.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e3.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eAgree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" style=\"width: 435px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeighted Mean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.04\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAgree\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" style=\"width: 619px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLearner Satisfaction with Simulation Scale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 254px;\"\u003e\n \u003cp\u003eThe VR simulation met my learning needs.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e3.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eAgree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 254px;\"\u003e\n \u003cp\u003eThe objectives of the VR simulation were clear.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e3.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eStrongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 254px;\"\u003e\n \u003cp\u003eThe simulation realistically reflected actual laboratory work.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e3.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eAgree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 254px;\"\u003e\n \u003cp\u003eI feel more prepared to perform laboratory tasks after this.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e3.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eAgree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 254px;\"\u003e\n \u003cp\u003eI am not satisfied with my experience using VR for laboratory skills.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e1.70/3.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eStrongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" style=\"width: 435px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeighted Mean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.21\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAgree\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" style=\"width: 435px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Weighted Mean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.18\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAgree\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eLegend: 1.00 \u0026ndash; 1.74 (Strongly Disagree), 1.75 \u0026ndash; 2.49 (Disagree), 2.50 \u0026ndash; 3.24 (Agree), 3.25 \u0026ndash; 4.00 (Strongly Agree); (R): Reverse Coding\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTable 2 summarizes the descriptive statistics of first year female BSMT students\u0026apos; perceptions regarding intrinsic motivation, general self-efficacy, and learning satisfaction after engaging in a VR laboratory simulation. The findings indicate generally positive perceptions of the VR simulation experience.\u003c/p\u003e\n\u003cp\u003eFor the Intrinsic Motivation Inventory, the weighted mean was 3.30 (SD \u0026asymp; 0.73), corresponding to a \u0026ldquo;Strongly Agree\u0026rdquo; interpretation. This suggests that students found the VR laboratory engaging, skill-enhancing, and worthy of effort. Statements that were negatively worded were reverse-coded, further strengthening the overall favorable responses (Deci \u0026amp; Ryan, 2000).\u003c/p\u003e\n\u003cp\u003eThe General Self-Efficacy Scale showed a weighted mean of 3.04 (SD \u0026asymp; 0.67), interpreted as \u0026ldquo;Agree.\u0026rdquo; This indicates that students generally believed in their ability to perform and learn laboratory-related skills, which is consistent with literature emphasizing the role of self-efficacy in academic performance (Schwarzer \u0026amp; Jerusalem, 1995).\u003c/p\u003e\n\u003cp\u003eFor the Learner Satisfaction with Simulation Scale, the weighted mean was 3.21 (SD \u0026asymp; 0.64), interpreted as \u0026ldquo;Agree.\u0026rdquo; This suggests that the VR simulation generally met the learners\u0026rsquo; needs and objectives and contributed positively to their perceived preparedness for laboratory work.\u003c/p\u003e\n\u003cp\u003eThe overall weighted mean was 3.18, suggesting that students had an overall positive experience (Agree) with the VR laboratory simulation, indicating its potential as an effective educational tool in laboratory education, supported by prior findings on simulation-based learning (Cook et al., 2011; Santiago \u0026amp; Mercado, 2023).\u003c/p\u003e\n\u003cp\u003eTable 3\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMean, Standard Deviation, and Interpretation of Perceived Learning of Male BSMT Students (n = 12)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 254px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStatement\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSt. Dev.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInterpretation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" style=\"width: 619px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIntrinsic Motivation Inventory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 254px;\"\u003e\n \u003cp\u003eI enjoyed participating in this VR laboratory activity.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e3.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eStrongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 254px;\"\u003e\n \u003cp\u003eI think I was able to learn important skills from the activity.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e3.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eStrongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 254px;\"\u003e\n \u003cp\u003eI put a lot of effort into this simulation.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e3.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eAgree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 254px;\"\u003e\n \u003cp\u003eI felt tense while using the VR simulation. (R)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e2.50/2.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eAgree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 254px;\"\u003e\n \u003cp\u003eI believe this VR activity was not useful for my learning. (R)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e1.83/3.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eAgree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" style=\"width: 435px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeighted Mean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.13\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAgree\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" style=\"width: 619px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGeneral Self-Efficacy Scale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 254px;\"\u003e\n \u003cp\u003eI can always manage to solve difficult tasks if I try hard enough.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e3.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eStrongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 254px;\"\u003e\n \u003cp\u003eI am confident in my ability to perform laboratory procedures.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e2.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eAgree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 254px;\"\u003e\n \u003cp\u003eI am doubtful that I can learn technical laboratory tasks. (R)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e2.17/2.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eAgree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 254px;\"\u003e\n \u003cp\u003eIf I am in trouble, I can think of a solution quickly.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e2.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eAgree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 254px;\"\u003e\n \u003cp\u003eI am confident I could master the laboratory tasks with practice.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e3.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eStrongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" style=\"width: 435px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeighted Mean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.97\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAgree\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" style=\"width: 619px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLearner Satisfaction with Simulation Scale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 254px;\"\u003e\n \u003cp\u003eThe VR simulation met my learning needs.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e3.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eAgree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 254px;\"\u003e\n \u003cp\u003eThe objectives of the VR simulation were clear.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e3.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eStrongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 254px;\"\u003e\n \u003cp\u003eThe simulation realistically reflected actual laboratory work.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e3.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eStrongly Agree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 254px;\"\u003e\n \u003cp\u003eI feel more prepared to perform laboratory tasks after this.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e2.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eAgree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 254px;\"\u003e\n \u003cp\u003eI am not satisfied with my experience using VR for laboratory skills.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e2.08/2.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eAgree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" style=\"width: 435px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeighted Mean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAgree\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" style=\"width: 435px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Weighted Mean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.07\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAgree\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eLegend: 1.00 \u0026ndash; 1.74 (Strongly Disagree), 1.75 \u0026ndash; 2.49 (Disagree), 2.50 \u0026ndash; 3.24 (Agree), 3.25 \u0026ndash; 4.00 (Strongly Agree); (R): Reverse Coding\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTable 3 presents the descriptive statistics of first-year male BSMT students\u0026rsquo; responses regarding intrinsic motivation, general self-efficacy, and learner satisfaction during the VR laboratory simulation. The results reveal that the participants generally had a positive perception of the VR learning activity.\u003c/p\u003e\n\u003cp\u003eFor the Intrinsic Motivation Inventory, the weighted mean was 3.13 (SD \u0026asymp; 0.71), corresponding to an \u0026ldquo;Agree\u0026rdquo; interpretation. While students generally agreed that they enjoyed the activity and learned important skills, their effort exerted during the activity was slightly lower compared to enjoyment and skill acquisition. Despite the presence of negatively worded items, responses remained generally favorable after reverse scoring (Deci \u0026amp; Ryan, 2000).\u003c/p\u003e\n\u003cp\u003eThe General Self-Efficacy Scale produced a weighted mean of 2.97 (SD \u0026asymp; 0.56), also interpreted as \u0026ldquo;Agree\u0026rdquo;. This suggests that students were moderately confident in their ability to learn and perform laboratory-related tasks. These findings are consistent with the established role of self-efficacy in facilitating student engagement and performance (Schwarzer \u0026amp; Jerusalem, 1995).\u003c/p\u003e\n\u003cp\u003eFor the Learner Satisfaction with Simulation Scale, a weighted mean of 3.10 (SD \u0026asymp; 0.68) was observed, interpreted as \u0026ldquo;Agree\u0026rdquo;. Male students reported that the VR simulation generally met their learning needs and that its objectives were clear. They also perceived the simulation as realistically reflecting laboratory work.\u003c/p\u003e\n\u003cp\u003eThe overall weighted mean of 3.07 indicates that male BSMT students agreed that the VR simulation was beneficial and contributed positively to their learning experience. This aligns with prior studies that highlight the value of simulation-based instruction in medical education (Cook et al., 2011; Santiago \u0026amp; Mercado, 2023).\u003c/p\u003e\n\u003cp\u003eTable 4\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eIndependent Sample T-Test of Intrinsic Motivation Inventory Between Gender\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroup\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003en\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003et(df)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI for Mean Difference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCohen\u0026rsquo;s d\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.18 (43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.246\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e[-0.11, 0.45]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 4 shows an independent samples t-test which was conducted to determine whether there was a significant difference in perceived learning, measured using the Intrinsic Motivation Inventory (IMI), between female and male students who participated in VR laboratory simulations. The analysis revealed that female students (M = 3.30, SD = 0.44, n = 33) had slightly higher perceived learning scores than male students (M = 3.13, SD = 0.38, n = 12). However, this difference was not statistically significant\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003et(43) = 1.18, p = .246, 95% CI [-0.11, 0.45]\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003ewith a small effect size\u003cstrong\u003e\u0026nbsp;(\u003c/strong\u003eCohen\u0026rsquo;s d = 0.40\u003cstrong\u003e).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThese findings suggest that gender did not have a significant influence on students\u0026rsquo; perceived learning in VR laboratory simulations. This result is consistent with the notion that intrinsic motivation toward learning, including in technology-enhanced environments, is influenced more by individual interest and perceived competence rather than demographic factors such as gender (Deci \u0026amp; Ryan, 2000).\u003c/p\u003e\n\u003cp\u003eTable 5\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eIndependent Sample T-Test of General Self-Efficacy Scale Between Gender\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroup\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003en\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003et(df)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI for Mean Difference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCohen\u0026rsquo;s d\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.52 (43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.604\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e[-0.19, 0.33]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 5 shows an independent samples t-test which was conducted to determine whether there was a significant difference in general self-efficacy between female and male students who engaged in VR laboratory simulations. The results showed that female students (M = 3.04, SD = 0.43, n = 33) reported slightly higher levels of general self-efficacy compared to male students (M = 2.97, SD = 0.28, n = 12); however, this difference was not statistically significant\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003et(43) = 0.52, p = .604, 95% CI [-0.19, 0.33], with a\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003esmall effect size\u003cstrong\u003e\u0026nbsp;(\u003c/strong\u003eCohen\u0026rsquo;s d = 0.18\u003cstrong\u003e).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThese findings indicate that gender was not a significant factor influencing general self-efficacy in the context of VR laboratory simulations. This is consistent with previous research suggesting that general self-efficacy is shaped more by individual psychological resources and task-related experiences than by demographic characteristics (Schwarzer \u0026amp; Jerusalem, 1995).\u003c/p\u003e\n\u003cp\u003eTable 6\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eIndependent Sample T-Test of Learner Satisfaction with Simulation Scale Between Gender\u003c/em\u003e\u003c/p\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroup\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.5565%;\"\u003e\n \u003cp\u003e\u003cstrong\u003en\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.0669%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003et(df)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI for Mean Difference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCohen\u0026rsquo;s d\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.5565%;\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.0669%;\"\u003e\n \u003cp\u003e3.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.72 (43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.483\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e[-0.21, 0.44]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.5565%;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.0669%;\"\u003e\n \u003cp\u003e3.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 6 shows an independent sample t-test which was conducted to examine whether there is a significant difference in learning satisfaction with simulation between female and male participants. The results revealed no statistically significant difference between the two groups, t(43) = 0.82, p = .483, with females (M = 3.21, SD = 0.47) reporting slightly higher mean satisfaction compared to males (M = 3.10, SD = 0.46). The 95% confidence interval for the mean difference ranged from -0.21 to 0.44 (Cohen\u0026rsquo;s d = 0.24).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThese findings suggest that gender does not meaningfully influence perceived satisfaction with simulation-based learning, consistent with previous studies on learner engagement and gender-neutral instructional design (Santos et al., 2021).\u003c/p\u003e\n\u003cp\u003eTable 7\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eIndependent Sample T-Test of Overall Perceived Learning Using VR Laboratory Simulations Between Gender\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroup\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003en\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003et(df)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI for Mean Difference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCohen\u0026rsquo;s d\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e[\u0026ndash;0.10, 0.34]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.284\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 7 shows an independent samples \u003cem\u003et\u003c/em\u003e-test which was conducted to compare overall perceived learning between female and male students using a simulation-based learning scale. The analysis revealed that there was no statistically significant difference in overall perceived learning between the female group (\u003cem\u003eM\u003c/em\u003e = 3.18, \u003cem\u003eSD\u003c/em\u003e = 0.38) and the male group (\u003cem\u003eM\u003c/em\u003e = 3.07, \u003cem\u003eSD\u003c/em\u003e = 0.29), \u003cem\u003et\u003c/em\u003e(43) = 1.09, \u003cem\u003ep\u003c/em\u003e = .284. The 95% confidence interval for the mean difference was [\u0026ndash;0.10, 0.34], indicating that the true difference in perceived learning may be minimal. The effect size, as measured by Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e, was 0.32, suggesting a small to moderate effect (Cohen, 1988; Lakens, 2013). These findings imply that gender may not play a significant role in influencing students\u0026rsquo; overall perceived learning within simulation-based environments.\u003c/p\u003e\n\u003cp\u003eThis result aligns with previous studies that found no significant gender differences in perceived learning outcomes in technology-enhanced learning environments (Kay et al., 2009; Liaw \u0026amp; Huang, 2013). However, other research has reported significant differences, with females often perceiving higher levels of learning and engagement, possibly due to differences in learning strategies or affective responses to instructional design (Papastergiou, 2009; Alghamdi et al., 2020). These mixed findings suggest that contextual factors such as instructional method, subject matter, and technological familiarity may moderate the relationship between gender and perceived learning\u003c/p\u003e"},{"header":"4.\tDiscussion","content":"\u003cp\u003eThis study adds to the growing literature on simulation-based education by highlighting how Virtual Reality (VR) influences self-efficacy among freshmen Medical Technology students in the Philippines, particularly through a gender lens. While VR has been widely applied in global health education, its integration into entry-level MedTech programs in the local context remains sparse. By introducing gender as a variable, this study offers a fresh approach to understanding learner diversity in immersive environments.\u003c/p\u003e\n\u003cp\u003eAddressing a gap in the literature, this research shifts focus from advanced simulations typically used in nursing and medical programs to the foundational phase of Medical Technology education. This is a critical stage for building technical confidence and professional identity. Moreover, analyzing gender-based learning patterns supports the demand for inclusive instructional strategies in STEM (Koivisto et al., 2021; Makransky \u0026amp; Mayer, 2022).\u003c/p\u003e\n\u003cp\u003eThe findings present practical value for educators and curriculum developers. VR serves as an effective supplemental tool, fostering both skill acquisition and learner confidence—traits essential for clinical preparedness. Customizing VR experiences based on gender-related learning preferences may further enhance outcomes (Lopez \u0026amp; Corpuz, 2021). These insights align with national priorities on educational technology integration (CHED, 2017; DOST-PCIEERD, 2022).\u003c/p\u003e\n\u003cp\u003eFor students, particularly beginners, VR provides a low-risk environment that encourages hands-on learning, repetition, and immediate feedback. This not only simplifies complex laboratory tasks but also builds the self-efficacy needed for academic persistence and success in board exams and clinical practice (Bandura, 1997; Dela Cruz \u0026amp; Tullao, 2020).\u003c/p\u003e\n\u003cp\u003eUltimately, by contributing localized, gender-responsive data, the study reinforces the need for context-aware innovations in health education. As institutions strive for global competitiveness, the thoughtful use of VR can help bridge educational gaps, foster engagement, and improve student performance across diverse groups.\u003c/p\u003e"},{"header":"6.\tRecommendation","content":"\u003col\u003e\n \u003cli\u003e\u003cstrong\u003eIntegrate VR Simulation Regularly in Laboratory Courses\u003c/strong\u003e. Since students generally demonstrated positive perceptions toward the VR simulation regardless of gender, academic programs should consider integrating VR-based activities regularly into medical technology laboratory subjects. This will enhance engagement and perceived learning across all students.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eEnhance Realism and Interactivity of VR Simulations\u003c/strong\u003e. Although students agreed on the usefulness of VR, refining the realism and interactivity of simulations may further increase perceived preparedness and engagement. Including modules that mimic complex laboratory tasks and introducing adaptive feedback could enhance perceived learning outcomes.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eProvide Orientation and Skill-Building Workshops\u003c/strong\u003e. To maximize the benefits of VR simulations, orientation sessions and preparatory workshops should be conducted before VR exposure. These can help students, especially those less confident, to familiarize themselves with the interface and maximize learning gains.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eIncorporate VR as a Supplement, Not a Replacement\u003c/strong\u003e. While VR is effective in improving perceived learning, it should serve as a complementary tool to physical laboratory sessions. Combining both modalities can bridge gaps in skill acquisition, especially for technical laboratory procedures.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eConduct Continuous Evaluation and Improvement\u003c/strong\u003e. Regular feedback mechanisms should be established to monitor students' evolving needs and satisfaction with VR simulations. Incorporating student suggestions can guide curriculum adjustments and ensure that VR integration remains aligned with learning goals.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003ePromote Inclusive Learning Practices\u003c/strong\u003e. Despite no significant gender difference in perceived learning, it is recommended that educators remain sensitive to varied student learning styles. Inclusive teaching strategies should be employed to ensure that all students—regardless of gender, prior experience, or confidence level—benefit equally from VR-based learning environments.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eAdd Qualitative Feedback.\u0026nbsp;\u003c/strong\u003eIncluding qualitative feedback offers richer insights into students’ learning experiences beyond numerical data. It captures personal perceptions, challenges, and suggestions that can guide future improvements in the implementation of VR simulations. These narratives help contextualize the quantitative findings and can uncover themes or issues that standardized instruments may overlook.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eConsider the Role of Other Demographic Factors.\u0026nbsp;\u003c/strong\u003eAnalyzing additional demographic variables—such as socioeconomic status, prior exposure to technology, or learning preferences—provides a more nuanced understanding of how VR simulations influence self-efficacy. This broader perspective can reveal subgroup differences and enhance the generalizability and inclusiveness of the intervention across diverse student populations.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research maintained the highest level of ethical practices in carrying out the research with human respondents. Before proceeding with data collection, an ethical clearance application was secured from the National University-Clark Research Ethics Committee with an expedited review in accordance with the ethical guidelines. All participants were informed by the researcher about the nature, purpose, and procedures of the research, as well as any risks or benefits associated with it. Informed consent was elicited from all participants before their engagement in the study. Participation was purely voluntary, and respondents will be made aware of their right to withdraw at any time without any type of penalty. Confidentiality was assured by not collecting any identifying information and reporting data in aggregate form. Data collected was stored safely and accessible only by the researchers.\u003c/p\u003e\n\u003cp\u003eArtificial Intelligence (AI), specifically OpenAI’s ChatGPT, was used as a writing support tool. The AI was utilized to assist in structuring the proposal and enhancing the academic tone of selected sections. However, all content was critically reviewed, revised, and validated by the researcher to ensure accuracy, ethical compliance, and scholarly integrity. The application of AI does not substitute for the researcher's analytical duty but facilitates means to enhance lucidity and coherence in written communication.\u003c/p\u003e\n\u003cp\u003eAll research practices were followed in conformity with the ethical guidelines of autonomy, beneficence, non-maleficence, and justice, as per the Declaration of Helsinki and local ethical guidelines.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAvailable from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAebersold M. Simulation-based learning: No longer a novelty in undergraduate education. Online J Issues Nurs. 2018;23(2). ttps://doi.org/10.3912/OJIN.Vol23No02PPT39.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAl-Ghareeb AZ, Cooper SJ. A literature review of simulation-based education for medical laboratory technologists. J Med Educ Curric Dev. 2016;3:77\u0026ndash;85. ttps://doi.org/10.4137/JMECD.S34503.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAl-Saud LM, Mushtaq F, Allsop MJ, Culmer PR, Mirghani I, Yates E, Gallagher JE, Manogue M. Feedback and motor skill acquisition using a haptic dental simulator. Eur J Dent Educ. 2017;21(4):240\u0026ndash;7. ttps://doi.org/10.1111/eje.12225.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlqurashi E. Predicting student satisfaction and perceived learning within online learning environments. 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Comput Educ. 2020;147:103778. ttps://doi.org/10.1016/j.compedu.2019.103778.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSun JCY, Rueda R. Situational interest, computer self-efficacy and self-regulation: Their impact on student engagement in distance education. Br J Edu Technol. 2012;43(2):191\u0026ndash;204. ttps://doi.org/10.1111/j.1467-8535.2010.01157.x.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"meed","sideBox":"Learn more about [BMC Medical Education](http://bmcmededuc.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/meed/default.aspx","title":"BMC Medical Education","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"virtual reality, laboratory simulations, medical technology, gender, self-efficacy","lastPublishedDoi":"10.21203/rs.3.rs-9034418/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9034418/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe integration of virtual reality (VR) in laboratory education has emerged as a promising strategy to enhance student engagement, motivation, and satisfaction, particularly in health sciences programs. This study examined the perceived learning outcomes of first-year Bachelor of Science in Medical Technology (BSMT) students following their participation in VR-based laboratory simulations. It assessed levels of intrinsic motivation (m\u0026thinsp;=\u0026thinsp;3.26), general self-efficacy (m\u0026thinsp;=\u0026thinsp;3.02), and learner satisfaction (m\u0026thinsp;=\u0026thinsp;3.18), and investigated potential differences in perceptions between male and female students. A descriptive-comparative research design was utilized, with data collected through adapted standardized instruments. Results revealed positive perceptions across all measured domains. Students agreed that the VR simulations addressed their learning needs, provided clear objectives, and contributed to their sense of preparedness for actual laboratory work. An independent samples t-test showed no statistically significant difference between male and female students in terms of their perceived learning outcomes [t(43)\u0026thinsp;=\u0026thinsp;1.09, p = .284]. This indicates that VR simulations provide a consistent educational benefit regardless of gender. The findings highlight the potential of VR simulations as a supplementary instructional approach in medical laboratory education, supporting their integration alongside traditional methods. The study recommends sustained implementation of VR in laboratory instruction, coupled with ongoing program evaluation and refinement to optimize its educational impact. These results contribute to the growing body of evidence supporting the effectiveness of simulation-based learning in improving student experiences in medical and allied health education.\u003c/p\u003e","manuscriptTitle":"Virtual Reality (VR) laboratory simulations: Self-efficacy outcomes in freshmen MedTech students: A gender-based comparison","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-24 09:56:08","doi":"10.21203/rs.3.rs-9034418/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"197636268547389019926024088978010118846","date":"2026-04-27T07:14:14+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-17T06:54:06+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-17T05:40:46+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-16T06:33:16+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-16T06:32:25+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medical Education","date":"2026-03-05T00:05:26+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"meed","sideBox":"Learn more about [BMC Medical Education](http://bmcmededuc.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/meed/default.aspx","title":"BMC Medical Education","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"46fda783-6a9d-4ac9-8b8f-dceb0a5cc6c4","owner":[],"postedDate":"April 24th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-24T09:56:08+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-24 09:56:08","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9034418","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9034418","identity":"rs-9034418","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}