Application and effectiveness of blended learning in medical imaging via the technology acceptance model

Application and effectiveness of blended learning in medical imaging via the technology acceptance model | 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 Application and effectiveness of blended learning in medical imaging via the technology acceptance model Xiaofen Sun, Jianghua Wan, Zhiqun Li, Rong Tu, Juan Lin, Xiaohua Li, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4866975/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 21 May, 2025 Read the published version in BMC Medical Education → Version 1 posted 4 You are reading this latest preprint version Abstract Blended learning, a combination of online learning and face-to-face instruction, is becoming an increasingly important component of higher education technology. However, there is currently insufficient research addressing students' perceptions of blended learning. Our study aims to investigate the satisfaction and behavioral intentions of students with blended learning in medical imaging. We employed the Technology Acceptance Model (TAM), which includes four independent variables, to evaluate students' satisfaction and behavioral intentions toward blended learning. The data were collected through the TAM survey, with questionnaires randomly distributed to the students participating in the "Medical Imaging" blended course at Hainan Medical University. A total of 145 valid questionnaires were returned and analysed via SPSS and Smart-PLS 3.3.3. Detailed results. Our results indicate that the practical application of blended learning has a positive and constructive impact and is worth promoting in higher education institutions. The empirical findings could also contribute to the integration of the TAM model to increase the effectiveness of blended learning for students. Blended Learning Technology Acceptance Model Student Behavioral Intention Higher Education Technology Medical Imaging. Figures Figure 1 Figure 2 1. Introduction Currently, the emphasis on innovation in education, especially leveraging technology to adapt teaching methods to modern demands, is fascinating [ 1 ]. Especially in the context of the rapid development of information technology, teaching is vital, along with online training and mobile telecommunications [ 2 ]. While considerable research has been conducted on the impact of mobile learning on teaching effectiveness [ 3 – 5 ], studies investigating the sustainability of mobile learning are relatively limited. The blend of online and offline teaching, known as blended learning, enables teachers to play a leading role and monitor students' learning behaviors through mobile teaching via network platforms and internet technology while embodying a student-centered teaching philosophy [ 6 ]. It indeed offers significant potential for improving teaching effectiveness and meeting students' evolving needs [ 7 ]. Medical imaging, as a critical component bridging basic and clinical medicine, holds significant importance in medical education because of its systematic nature, practical applications, and reliance on information technology. Given the dynamic nature of healthcare education and the evolving demands of the field, traditional offline classroom teaching methods may no longer suffice in fully preparing students for the complexities of medical imaging practice. In response to these challenges, the adoption of a blended teaching model has emerged as a valuable supplement to traditional medical education practices [ 8 – 14 ]. By effectively integrating classroom teaching with information technology, the blended teaching model can revolutionize educational practices, cater to students' developmental needs, and yield optimal teaching outcomes. The focus of this study is to evaluate the application and effectiveness of blended teaching in medical imaging and perform cognitive analysis via the Technology Acceptance Model (TAM). Furthermore, we investigated the advantages and challenges of the blended teaching model in medical imaging education, along with exploring students' cognition and acceptance of this approach. Establishing a new model and conducting confirmatory factor analysis represent rigorous methods to gain deeper insights into how medical imaging students perceive and utilize the blended teaching model. 2. Hypotheses and Model Building This study employed a TAM (Fig. 1 ) to evaluate the impact of the blended teaching mode on personal influence factors (PIFs), external influencing factors (EIFs), and students' behavioral intentions (BIs). Figure 1 also shows the relationships between personal innovation ability and student satisfaction, between task‒technology fit and mobile learning usage intention, and between perceived usefulness and ease of mobile learning in the context of practical student satisfaction (SS). On the basis of this relationship, we propose seven hypotheses concerning how blended teaching may affect the satisfaction and behavioral intentions of students using blended online and offline teaching in medical imaging higher education. 2.1 Personal influence factors (PIFs) PIFs, consisting of individual innovation ability, learning style, and learning desire, have a great impact on blended learning. Individual innovation ability is a crucial factor influencing the success of the blended learning model [ 15 , 16 ]. Students who possess strong innovation abilities are more likely to embrace new technologies and methods. Their sensitivity to innovation makes them more receptive to new technologies, leading to increased creativity and acceptance of new learning approaches [ 17 , 18 ]. Different learning styles can affect students' attitudes and preferences toward blended learning. For example, students with a preference for independent learning may gravitate towards the use of online resources in a blended learning environment. Understanding students' diverse learning styles can help educators tailor their approach to better engage and support learners. The desire to learn through various methods is a significant determinant of the effectiveness of the blended learning model [ 19 ]. Students who exhibit a strong motivation to explore different learning approaches tend to be more engaged and proactive in their learning journeys. This willingness to experiment with diverse learning methods enhances the overall learning experience and outcomes in a blended learning setting. 2.2. External influencing factors (EIFs) EIFs, including environmental pressure, direct experience with individual use, and technological infrastructure, greatly influence the use of blended learning [ 19 – 23 ]. Environmental pressure, which includes social influences and perceptions, can significantly impact the adoption of blended learning models. When individuals perceive social pressure to use specific technologies, such as when peers, school leaders, or teachers endorse certain tools, they may be more inclined to embrace these technologies. Support from the educational community can create an environment conducive to the acceptance and utilization of blended learning approaches [ 20 ]. Direct experience with technology plays a vital role in shaping individuals' attitudes toward digital tools in a blended learning context. Positive experiences with technology usage, supported by adequate training and technical assistance provided by schools, can enhance students' willingness to engage with blended learning resources [ 21 ]. Satisfactory user experiences contribute to increased acceptance and integration of technology into the learning process. Technological infrastructure serves as a critical external factor influencing the successful implementation and sustainability of blended learning initiatives. The availability of reliable and efficient technological resources directly impacts the effectiveness of blended learning programs and enhances the overall learning experience. A well-established technological infrastructure supports the seamless integration of digital tools, facilitating improved learning outcomes and student engagement [ 22 , 23 ]. 2.3 Perceived Ease of Use (PEU) PEU refers to users' perceptions of how easily they can understand and use a particular system [ 24 ]. In the context of blended learning, high perceived ease of use indicates that students find the system easy to learn and operate without facing significant difficulties or complexities. This perception has a significant effect on shaping students' attitudes and behavioral intentions toward the learning platform. When students perceive a system as easy to use, they are more likely to develop a positive attitude towards it. This positive attitude can lead to continued use of the system and even recommendations to others [ 25 ]. Conversely, if they find the system difficult to use, they may develop negative emotions toward it, decrease their usage frequency, or look for alternative solutions. In the context of blended learning, the PEU can greatly enhance the learning experience. A system that is perceived as easy to use can help students more conveniently access learning resources, facilitate communication with teachers and classmates, and navigate the learning platform effectively. These aspects contribute to an overall increase in students' perceived ease of use, positively impacting their engagement with and satisfaction with the blended learning experience [ 25 , 26 ]. 2.4 Perceived usefulness (PU) The PU refers to an individual’s subjective belief regarding the extent to which using a particular technology or system will be beneficial to their work efficiency [ 27 ]. When students perceive a certain technology or system as highly useful, they are more likely to develop a positive attitude towards it and are willing to accept and use this technology. The PU can be influenced by various factors, such as the actual effectiveness of technical functionalities, students’ expectations for work efficiency, and the extent to which the technology aids in task completion [ 28 , 29 ]. 2.5 Student Satisfaction (SS) SS with blended learning refers to students' perceptions of how well the blended learning model aligns with their expectations and fulfils their needs [ 28 , 30 ]. It encompasses students' contentment with learning resources, interactions, and support available within the blended learning environment. It serves as a critical measure of the effectiveness and impact of blended learning initiatives in multiple ways, including the alignment of acquired knowledge and skills with students' expectations, the quality of students' learning experiences during the blended learning process, and the extent to which blended learning addresses learning challenges [ 31 – 34 ]. It is one of the important indicators for evaluating the effectiveness of blended learning. By understanding the SS, teachers and educational institutions can adjust teaching strategies and improve teaching design promptly to enhance students' learning experience and outcomes [ 35 ]. In addition, the SS also serves as an important metric for decision-makers to evaluate the effectiveness and feasibility of blended learning schemes [ 36 ]. 2.6 Behavioral Intention (BI) Student BI in blended learning refers to students' willingness and inclination to use specific technologies or tools within the learning environment [ 37 ]. It reflects students' attitudes towards their interest and active engagement with these technologies or tools [ 38 ]. Student BI is one of the important factors influencing the actual adoption and utilization of blended learning technologies [ 39 ]. When students perceive the technology as easy to use and beneficial, they are more likely to show positive behavioral intentions. This means that they are more willing to accept and use the technologies in blended learning, thereby achieving better learning outcomes and experiences [ 40 ]. Therefore, understanding and promoting students' BI is crucial for effectively implementing blended learning. The model in Fig. 1 addresses the relationships among different variables, proposing a close connection between perceived usefulness and ease of use with personal influencing factors and external influencing factors. Furthermore, the model traced the relationship between perceived usefulness and ease of use with student satisfaction. Ultimately, it focused on the relationship between student satisfaction and students' intention to use. Therefore, we propose the following hypotheses: H1: Personal influencing factors have a positive effect on perceived ease of use. H2: External influencing factors have a positive effect on perceived ease of use. H3: Personally influencing factors have a positive effect on perceived usefulness. H4: External influencing factors have a positive effect on perceived usefulness. H5: Perceived ease of use has a positive effect on student satisfaction. H6: Perceived usefulness has a positive effect on student satisfaction. H7: Student satisfaction has a positive effect on students’ intention to use. 3. Research Methodology 3.1 Research Design Blended learning is a teaching model that uses online platforms and digital teaching resources, combining traditional face-to-face teaching with online learning to provide a more enriched, flexible, and personalized learning experience. The advantage of blended learning lies in its full utilization of network technology and digital resources, providing a more flexible and personalized learning method [ 41 , 42 ]. Students can learn at their own pace and according to their learning needs while also interacting and collaborating with teachers and classmates [ 43 ]. Blended learning can also improve the development and utilization efficiency of educational resources and promote the development of educational informatization [ 44 ]. This study aims to investigate students' satisfaction with their intention to use blended learning and their perceptions of actual usage in higher education through online teaching. The entire analysis in this study was divided into two stages. The first stage involved collecting data from university students through a questionnaire survey. The target student group includes undergraduate students majoring in medical imaging and clinical medicine who participate in medical imaging courses and have been fully exposed to blended learning. The questionnaire was designed with a five-point Likert scale [ 45 , 46 ]. The second stage involved analysing the collected data with the structural equation modelling software Smart-PLS 3.3.3 and SPSS software [ 47 ]. The Smart-PLS was used to construct and evaluate the structural equation model on the basis of the survey responses. The validity and reliability of the data in the measurement model were assessed. SPSS was employed to calculate correlations between variables, descriptive statistics, regression analysis, and other statistical tests. Figure 1 describes the proposed model, which consists of six components: PIF, EIF, PEU, PU, SS, and BI. Seven path lines were proposed between the six groups. Two path lines were proposed for PIF, EIF, PEU, PU, and SS, and one path line was proposed for BI. All the hypotheses were used to predict the six structures [ 48 ]. The original survey questionnaire is provided in Supplement Document 1. 3.2 Data collection and demographic characteristics In this study, 256 surveys based on the TAM model (Table 1 ) were distributed to undergraduate students majoring in medical imaging and a small portion of clinical undergraduate students who had taken blended learning courses in medical imaging at Hainan Medical University via Questionnaire Star. The anonymous questionnaire focused on students’ opinions on the use of blended learning in terms of student satisfaction and behavioral intentions, as well as the impact of blended learning on sustainable learning measures. A total of 145 valid questionnaires were collected after screening [ 49 ]. The sample size can be used to evaluate the structural equation model [ 50 ]. Among the 145 collected questionnaires, 57 were from male participants and 88 were from female participants. The participants are between the ages of 18 and 25. The student grades (years of admission) ranged from 2018–2022 (Table 2 ). Table 1 Questionnaire Design Based on the TAM Question Design Strongly Agree Agree Neutral Disagree Strongly Disagree Perceived Usefulness (PU) PEU 1 The content of blended teaching is rich and practical. PEU 2 Blended teaching can improve learning efficiency. PEU 3 Blended teaching can enhance learning interest. Perceived Ease of Use (PEU) PU 1 Blended teaching makes it easier to find the necessary learning resources. PU 2 Blended teaching facilitates communication and interaction with teachers and classmates. PU 3 Blended teaching can improve learning effectiveness. Personal Influencing Factors (PIF) PIF 1 You are more willing to use new technologies and methods in daily learning. PIF 2 You prefer independent learning over collaborative learning. PIF 3 You hope to better grasp knowledge through different learning methods. External Influencing Factors (EIF) EIF 1 School leaders and teachers encourage the use of blended teaching. EIF 2 You have participated in blended teaching training and received technical support provided by the school. EIF 3 You believe that the technological infrastructure provided by the school makes blended teaching easier to implement. Student Satisfaction (SS) SS 1 Blended teaching improves learning effectiveness, increases learning enjoyment, and enhances learning motivation. SS 2 Blended teaching can enhance learning experience and efficiency. SS 3 Blended teaching provides sufficient technical support to help you solve problems encountered in learning. Behavioral Intention (BI) BI 1 You are willing to continue using this teaching method in the future. BI 2 You are willing to actively participate in learning in blended teaching. BI 3 You are willing to recommend the blended teaching model to others. Table 2 Demographic characteristics Category Number Percentage (%) Gender Male 57 39.31 Female 88 60.69 Age 18–19 35 24.14 20–21 35 24.14 22–23 57 39.31 23–25 18 12.41 Academic Year 2018 47 32.41 2019 26 17.93 2020 19 13.10 2021 15 10.34 2022 38 26.21 Major Medical Imaging 134 92.41 Clinical Medicine 11 7.59 3.3 Data analysis Smart-PLS 3.3.3 and IBM SPSS 26 software were used to perform structural equation modelling analysis on the collected data [ 51 , 52 ]. To test the validity of the data, we reported the convergence validity and discriminant validity. Convergence validity was calculated via the average variance extracted (AVE) formula, with an AVE value of 0.500 indicating satisfactory convergence validity. Discriminant validity was obtained via the Fornell–Larcker criterion and cross-loading analysis. Moreover, internal consistency reliability (ICR), an essential measure of data reliability, was evaluated via two methods: composite reliability (CR) and Cronbach's alpha (CA). Both CA and CR values exceeding 0.700 indicated satisfactory reliability. For model evaluation, the significance of the relationship within the structural equation model was assessed through path coefficients, t values, and P values. 4. Results 4.1 Loadings of reflective indicators Confirmatory factor analysis was carried out by constructing a structural equation. Items with low standardized factor loading coefficients of measurement variables and latent variables were deleted [ 51 ]. The standardized factor loading coefficients of all the observed variables were greater than 0.7, indicating good reliability [ 53 , 54 ]. Except for the loading of PIF2 (0.470), all the other indicators had loadings greater than 0.7 (Table 3 ). The 17 indicators were included for further analysis. Table 3 Summary of Reliability and Validity Indicators Constructs Indicators Cronbach's alpha Composite reliability (rho_a) Composite reliability (rho_c) Average variance extracted (AVE) BI BI 1 - BI 3 0.925 0.934 0.952 0.869 EIF EIF 1 - EIF 3 0.857 0.865 0.913 0.777 PEU PEU 1 - PEU 3 0.928 0.932 0.954 0.875 PIF PIF 1, PIF 3 0.810 0.818 0.913 0.840 PU PU 1 - PU 3 0.942 0.943 0.963 0.896 SS SS 1 - SS 3 0.962 0.963 0.976 0.930 4.2 Internal Consistency Reliability Table 3 provides the CA and CR values of all the structures greater than 0.7 [ 51 ]. The CA and CR values of the PIF method were 0.810 and 0.818, as well as 0.857 and 0.865 for the EIF, 0.928 and 0.932 for the PEU, 0.942 and 0.943 for the PU, 0.962 and 0.963 for the SS, and 0.925 and 0.934 for the BI. 4.3 Convergent Validity Test The AVE values of all the structures exceeded 0.500. Specifically, the AVE values of PIF, EIF, PEU, PU, SS, and BI were 0.840, 0.777, 0.875, 0.896, 0.930, and 0.869, respectively. (Table 3 ) 4.4 Discriminant validity test According to the Fornell–Larcker criterion, to judge whether two latent constructs have discriminant validity, the following conditions must be met: (1) the AVE value of each latent structure must be greater than the square of its correlation coefficient with other constructs; (2) the AVE value of the latent structure must be greater than its cross-loadings with other constructs. The Fornell‒Larcker correlation matrix between each variable value is shown in Table 4 . Table 4 Fornell–Larcker correlation matrix. BI EIF PEU PIF PU SS BI 0.932 EIF 0.838 0.882 PEU 0.835 0.732 0.935 PIF 0.756 0.724 0.726 0.917 PU 0.869 0.710 0.874 0.685 0.946 SS 0.937 0.833 0.840 0.708 0.850 0.964 In addition, the discriminant validity of items can also be evaluated by calculating cross-loadings [ 51 , 55 ], that is, correlating each item with its own latent variable and other latent variables to evaluate the relationships between the item and other latent variables. If the correlation coefficient between an item and its latent variable is significantly greater than the correlation coefficient with other latent variables, then the item can be considered to have good discriminant validity, as shown in Table 5 . Table 5 Summary of Cross-Loadings BI EIF PEU PIF PU SS BI1 0.954 0.775 0.797 0.681 0.809 0.899 BI2 0.949 0.811 0.782 0.676 0.827 0.933 BI3 0.893 0.759 0.757 0.770 0.796 0.776 EIF1 0.776 0.880 0.707 0.738 0.657 0.729 EIF2 0.686 0.863 0.532 0.605 0.579 0.672 EIF3 0.748 0.902 0.680 0.566 0.636 0.795 PEU1 0.734 0.615 0.915 0.624 0.785 0.749 PEU2 0.801 0.728 0.945 0.701 0.843 0.802 PEU3 0.804 0.706 0.945 0.709 0.822 0.804 PIF1 0.712 0.668 0.681 0.926 0.684 0.656 PIF3 0.671 0.660 0.650 0.907 0.566 0.643 PU1 0.799 0.644 0.782 0.659 0.940 0.751 PU2 0.843 0.689 0.830 0.652 0.960 0.837 PU3 0.823 0.683 0.867 0.635 0.939 0.824 SS1 0.876 0.812 0.772 0.653 0.801 0.955 SS2 0.905 0.792 0.832 0.714 0.834 0.976 SS3 0.928 0.807 0.825 0.681 0.825 0.963 4.5 Structural Model and Collinearity The predictive ability of the structural model was tested as a part of the evaluation. Collinearity is represented by reporting the variance inflation factor (VIF) values. A VIF greater than 5 is usually considered to indicate multicollinearity [ 56 ]. In this study, the VIF values of all the structures were less than 5 (Table 6 ). Table 6 Variance inflation factor (VIF). BI EIF PEU PIF PU SS BI EIF 2.105 2.105 PEU 4.232 PIF 2.105 2.105 PU 4.232 SS 1.000 4.6 Structural Model Hypothesis Testing Table 7 and Fig. 2 show the bootstrap calculation results for all the structures. Generally, an absolute value greater than 0.3 can be considered to have a significant impact, and an absolute value greater than 0.5 can be considered to have a major impact [ 57 – 60 ]. For PIF → PEU (PC = 0.412; t = 3.659; P < 0.001), the corresponding hypothesis (H1) was supported. For PIF → PU (PC = 0.359; t = 3.506; P < 0.001), the corresponding hypothesis (H2) was supported. For hypotheses H3 and H4, EIF → PEU (PC = 0.434; t = 4.132; P < 0.001) and EIF → PU (PC = 0.450; t = 4.028; P < 0.001), the corresponding hypotheses were supported. Moreover, there was a significant influence between PEU → SS (PC = 0.410; t = 2.737; P = 0.006) and PU → SS (PC = 0.492; t = 3.338; P = 0.001); thus, the corresponding hypothesis (H5, H6) was supported. The relationship between SS → BI (PC = 0.937; t = 68.891; P < 0.001) indicated that the corresponding hypothesis (H7) was supported. Table 7 Model Hypothesis Testing Path of Hypotheses Path coefficients Original sample (O) Sample mean (M) Standard deviation (STDEV) T statistics (|O/STDEV|) P values Results SS → BI 0.937 0.937 0.937 0.014 68.891 < 0.001 Supported EIF → PEU 0.434 0.434 0.432 0.105 4.132 < 0.001 Supported EIF → PU 0.450 0.45 0.446 0.112 4.028 < 0.001 Supported PEU → SS 0.410 0.41 0.409 0.15 2.737 0.006 Supported PIF → PEU 0.412 0.412 0.418 0.113 3.659 < 0.001 Supported PIF → PU 0.359 0.359 0.366 0.102 3.506 < 0.001 Supported PU → SS 0.492 0.492 0.492 0.147 3.338 0.001 Supported 5. Discussion The evolution of technology has profoundly influenced universities and the education system, necessitating the adoption of advanced technological systems. The digital transformation has revolutionized the flow of information, enabling innovative interactions among users through engaging multimedia applications [ 61 – 63 ]. Building on these technological advancements, this study developed a conceptual model to explore the continued use of teaching methods in the educational environment, with a particular focus on online training and mobile telecommunications. PEU is considered one of the key factors in the conceptual model, influencing both internal students and external teaching factors. It encompasses students' innovativeness, learning aspirations, environmental pressures, direct user experience, and technology infrastructure development [ 64 – 65 ]. On the other hand, it directly influences students’ satisfaction with continuing to use educational technologies, subsequently affecting their behavioral intentions toward blended learning [ 66 ]. By elucidating the relationships between perceived ease of use, student satisfaction, and behavioral intentions, this study sheds light on the critical role of technology acceptance and usability in promoting effective blended learning practices. Understanding these dynamics can inform educational strategies, instructional design, and technology integration efforts to optimize student learning outcomes and experiences. The goal of this study was to evaluate students' perceptions of blended learning via the TAM framework. Despite its limited adoption in higher education, the findings indicated that students perceived value in blended learning and were open to embracing it. Constructs from the TAM model, such as PIF, EIF, PU, PEU, SS, and BI, were identified as positive factors driving the use of blended learning among university students, especially in medical imaging courses. Unlike previous research on mobile learning, this study highlighted the importance of investigating student satisfaction and intentions regarding blended learning. These findings suggest that universities should prioritize PU, PEU, and SS to foster student acceptance of blended learning. Future researchers should focus on the broad implementation of blended learning, explore planning strategies for PIFs and EIFs, and assess their potential in education. By integrating various internal and external factors with TAM structures, this study contributes to facilitating the adoption and acceptance of research. It distinguished itself by examining individual differences such as student satisfaction and behavioral intentions, thereby enhancing the understanding of blended learning models. Overall, this study advances empirical research in the application and promotion of blended learning. The present study had several limitations. First, the conceptual model was confined to a specific set of internal and external factors directly linked to the TAM constructs. Future research could integrate additional influencing factors to provide a more comprehensive understanding of relevant technologies. Second, the sample is restricted to the students enrolled in a medical imaging course, which primarily consists of medical imaging majors. To gain insights into the attitudes of students from diverse majors towards blended learning, future investigations could consider exploring attitudinal differences across various courses and majors. Third, the survey was conducted via internet and social media platforms. There is potential for future research to explore alternative survey distribution methods to enhance data collection strategies and reach a more diverse participant pool. 6. Conclusion Our results revealed that students exhibited belief in and readiness to accept the blended learning model, indicating a positive outlook towards this innovative approach to learning. The TAM has made significant contributions to understanding students' perceptions in this context. Future research should focus on investigating planning recommendations for PIFs and EIFs and evaluating the anticipated effectiveness of PIFs and EIFs in educational settings, considering the widespread adoption of blended learning. Declarations Acknowledgements The authors extend their appreciation to the teachers at Hainan Medical University who have conducted blended teaching in medical imaging. Author contributions Xiaofen Sun: Conceptualization, Data curation, Formal Analysis, Methodology, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing. Jianghua Wan: Conceptualization, Data curation, Formal Analysis, Investigation, Software, Supervision, Writing – original draft, Writing – review & editing. Zhiqun Li: Formal Analysis, Investigation, Methodology, Validation. Rong Tu: Conceptualization, Project administration, Supervision. Juan Lin: Data curation, Investigation. Xiaohua Li: Data curation, Investigation, Methodology. Jianqiang Chen: Conceptualization, Data curation, Project administration, Writing – review & editing. Funding This work was supported by the Education Department of Hainan Province (Grant Numbers: Hnjg2024ZC-70, Hnjgzc2023-20, 22A200069), and Hainan Medical University (Grant Numbers: HYYB202230, HYYB202380, HYKCPY202307, RZ2300005679). These institutions provided financial support but did not involve in study design, data collection, analysis, or interpretation. The financial supporters had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Data availability The data used to support the findings of this study are included within the article. Ethical approval and consent to participate This study has been approved by the Biomedical Ethics Committee of the First Affiliated Hospital of Hainan Medical University (Approval No: 2024-KYL-176). To ensure confidentiality, the collection of participants’ questionnaires and the related analysis were conducted anonymously. We provided a detailed explanation of the study objectives to all students who participated in the blended teaching of medical imaging. Informed consent forms were distributed to all students, and written informed consent was obtained from all participants before their participation in the questionnaire survey. The survey was conducted under conditions that protected the privacy, confidentiality, and anonymity of participant information. Participants voluntarily chose whether or not to participate in the research and were informed of their right to withdraw from the study at any time without penalty. Human Ethics and Consent to Participate declarations The ethical aspects of this study have been reviewed and approved by the Biomedical Ethics Committee of the First Affiliated Hospital of Hainan Medical University, and informed consent was obtained from all individual participants involved in the study. Competing interests The authors declare no competing interests. References Martin S, Lopez-Martin E, Lopez-Rey A, Cubillo J, Moreno-Pulido A, Castro M. Analysis of New Technology Trends in Education: 2010–2015. IEEE Access. 2018;6:36840–8. Al-Rahmi AM, Al-Rahmi WM, Alturki U, Aldraiweesh A, Almutairy S, Al-Adwan AS. Exploring the factors affecting mobile learning for sustainability in higher education. Sustainability. 2021;13:7893. Li R, Meng Z, Tian M, Zhang Z, Ni C, Xiao W. 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Blended learning model via small private online course improves active learning and academic performance of embryology. Clin Anat. 2022;35(2):211–21. 10.1002/ca.23818 . Epub 2021 Dec 17. Moafa FA, Ahmad K, Al-Rahmi W, Yahaya N, Kamin Y, Alamri MM. Develop a Model to Measure the Ethical Effects of Students through Social Media Use. IEEE Access. 2018;6:56685–99. Al-Samarraie H, Teng BK, Alzahrani AI, Alalwan N. E-learning continuance satisfaction in higher education: A unified perspective from instructors and students. Stud High Educ. 2018;43:2003–19. Alyoussef IY, Alamri MM, Al-Rahmi WM. Social media use (SMU) for teaching and learning in Saudi Arabia. Int J Recent Technol Eng. 2019;8:942–6. Hassanzadeh A, Kanaani F, Elahi S. A model for measuring e-learning systems success in universities. Expert Syst Appl. 2012;39:10959–66. Althunibat A, Altarawneh F, Dawood R, Almaiah MA. Propose a New Quality Model for M-Learning Application in Light of COVID-19. Mob. Inf. 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Comparing the effects of blended learning and traditional instruction on basic life support for laypersons: A randomized controlled trial. J Formos Med Assoc 2023 Nov 22:S0929-6646(23)00435-7. Shoukat R, Ismayil I, Huang Q, Oubibi M, Younas M, Munir R. A comparative analysis of blended learning and traditional instruction: Effects on academic motivation and learning outcomes. PLoS ONE. 2024;19(3):e0298220. Marques-Sule E, Sánchez-González JL, Carrasco JJ, Pérez-Alenda S, Sentandreu-Mañó T, Moreno-Segura N, Cezón-Serrano N. Ruiz de Viñaspre-Hernández R, Juárez-Vela R, Muñoz-Gómez E. Effectiveness of a blended learning intervention in cardiac physiotherapy. A randomized controlled trial. Front Public Health. 2023;11:1145892. Eichelberger A, Ngo HT. College students’ perception of an online course in special education. Int J Educ Media Technol. 2018;12:123–33. Joo YJ, Joung S, Shin EK, Lim E, Choi M. Factors Influencing Actual Use of Mobile Learning Connected with e-Learning. Int J Comput Sci Inf Technol. 2014;6:169–76. Hair JF, Risher JJ, Sarstedt M, Ringle CM. When to use and how to report the results of PLS-SEM. In European Business Review. Volume 31. Bingley, UK: Emerald Group Publishing Ltd.; 2019. pp. 2–24. Haftador AM, Tehranineshat B, Keshtkaran Z, Mohebbi Z. A study of the effects of blended learning on university students' critical thinking: A systematic review. J Educ Health Promot. 2023;12:95. Chuan CL, Penyelidikan J. Sample size estimation using Krejcie and Morgan and Cohen statistical power analysis: A comparison. J Penyelid IPBL. 2006;7:78–86. Dhawan S, Online Learning. A Panacea in the Time of COVID-19 Crisis. J Educ Technol Syst. 2020;49:5–22. Hair JF, Risher JJ, Sarstedt M, Ringle CM. When to use and how to report the results of PLS-SEM. In European Business Review. Volume 31. Bingley, UK: Emerald Group Publishing Ltd.; 2019. pp. 2–24. Vargo SL, Lusch RF. Service-dominant logic: Continuing the evolution. J Acad Mark Sci. 2008;36:1–10. Reigeluth CM. Instructional Design Theories and Models: An Overview of Their Current Status. London, UK: Routledge; 1983. Donkor F. Assessment of learner acceptance and satisfaction with video-based instructional materials for teaching practical skills at a distance. Int Rev Res Open Distrib Learn. 2011;12:74–92. Ringle CM, Wende S, Becker J-M. SmartPLS 3; SmartPLS: Bönningstedt, Germany, 2015. James G, Witten D, Hastie T, Tibshirani R. An Introduction to Statistical Learning: With Applications in R. 1st ed. Corr. 7th printing 2017 edition. Springer; 2013. Urbach N, Ahlemann F. Structural equation modelling in information systems research using partial least squares. J Inf Technol theory Appl. 2010;11:5–40. Goodhue DL, Lewis W, Thompson R. Does PLS have adavantages for small sample size or nonnormal data? MIS Q. 2012;36:981–1001. Hair JF, Ringle CM, Sarstedt M. PLS-SEM: Indeed a Silver Bullet. J Mark Theory Pract. 2011;19:139–52. Henseler J, Ringle CM, Sinkovics RR. The use of partial least squares path modelling in international marketing. In New Challenges to International Marketing; Emerald Group Publishing Limited: Bingley, UK, 2009; Volume 20, pp. 277–319. Tonbuloğlu B, Tonbuloğlu İ. Trends and patterns in blended learning research (1965–2022). Educ Inf Technol (Dordr). 2023 Apr 3:1–32. 10.1007/s10639-023-11754-0 . Epub ahead of print. William HD, Ephraim RM. The DeLone and McLean Model of Information Systems Success: A Ten-Year Update. J Manag Inf Syst. 2003;19:9–30. Alhamad BR, Agha S. Comparing Knowledge Acquisition and Retention Between Mobile Learning and Traditional Learning in Teaching Respiratory Therapy Students: A Randomized Control Trial. Adv Med Educ Pract. 2023;14:333–42. Martinengo L, Yeo NJY, Tang ZQ, Markandran KD, Kyaw BM, Tudor Car L. Digital Education for the Management of Chronic Wounds in Health Care Professionals: Protocol for a Systematic Review by the Digital Health Education Collaboration. JMIR Res Protoc. 2019;8(3):e12488. Windisch O, Zamberg I, Iselin C, Schiffer E. Head To Toe, une plateforme de distribution de connaissances médicales : exemple pratique en urologie [Head To Toe, a medical knowledge distribution platform : a practical example in urology]. Rev Med Suisse. 2019;15(673):2205–8. Wang YT, Lin KY. Understanding Continuance Usage of Mobile Learning Applications: The Moderating Role of Habit. Front Psychol. 2021;12:736051. Additional Declarations No competing interests reported. Supplementary Files SupplementDocument1.docx Cite Share Download PDF Status: Published Journal Publication published 21 May, 2025 Read the published version in BMC Medical Education → Version 1 posted Editorial decision: Revision requested 21 Aug, 2024 Editor assigned by journal 16 Aug, 2024 Submission checks completed at journal 16 Aug, 2024 First submitted to journal 06 Aug, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-4866975","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":343278460,"identity":"1e548a7d-4d59-4773-b1f4-960ff6dc2994","order_by":0,"name":"Xiaofen Sun","email":"","orcid":"","institution":"The First Affiliated Hospital of Hainan Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xiaofen","middleName":"","lastName":"Sun","suffix":""},{"id":343278461,"identity":"45edac2a-8dd7-4ed6-babe-84df8efd5dcc","order_by":1,"name":"Jianghua Wan","email":"","orcid":"","institution":"Hainan Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jianghua","middleName":"","lastName":"Wan","suffix":""},{"id":343278462,"identity":"cee8cd91-9cf4-48b6-bd46-017be48b4186","order_by":2,"name":"Zhiqun Li","email":"","orcid":"","institution":"The First Affiliated Hospital of Hainan Medical University","correspondingAuthor":false,"prefix":"","firstName":"Zhiqun","middleName":"","lastName":"Li","suffix":""},{"id":343278463,"identity":"d23ee63d-264a-44e4-b111-7c126d45ad34","order_by":3,"name":"Rong Tu","email":"","orcid":"","institution":"The First Affiliated Hospital of Hainan Medical University","correspondingAuthor":false,"prefix":"","firstName":"Rong","middleName":"","lastName":"Tu","suffix":""},{"id":343278464,"identity":"4abf7678-39ad-44fa-9135-42609ce2218c","order_by":4,"name":"Juan Lin","email":"","orcid":"","institution":"The First Affiliated Hospital of Hainan Medical 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Design.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4866975/v1/b58a711db1cad7897acde27f.jpg"},{"id":66543002,"identity":"332d109f-f2a4-4844-b8f1-0a14cbce4f88","added_by":"auto","created_at":"2024-10-14 07:56:08","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":33533,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic diagram of path coefficients in the TAM model.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4866975/v1/3def11d78c09c2c4693b94c0.jpg"},{"id":83460072,"identity":"8d4b16d5-1c91-43bf-959b-d4fecedd25b2","added_by":"auto","created_at":"2025-05-26 16:09:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1366950,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4866975/v1/e4907f22-bda4-4059-a5c7-79550a743703.pdf"},{"id":66543004,"identity":"94369a17-2ae2-4245-9ada-9ccd3253e64b","added_by":"auto","created_at":"2024-10-14 07:56:08","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":18760,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementDocument1.docx","url":"https://assets-eu.researchsquare.com/files/rs-4866975/v1/1c6527030b2ff0cde025dafd.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Application and effectiveness of blended learning in medical imaging via the technology acceptance model","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eCurrently, the emphasis on innovation in education, especially leveraging technology to adapt teaching methods to modern demands, is fascinating [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Especially in the context of the rapid development of information technology, teaching is vital, along with online training and mobile telecommunications [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. While considerable research has been conducted on the impact of mobile learning on teaching effectiveness [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], studies investigating the sustainability of mobile learning are relatively limited. The blend of online and offline teaching, known as blended learning, enables teachers to play a leading role and monitor students' learning behaviors through mobile teaching via network platforms and internet technology while embodying a student-centered teaching philosophy [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. It indeed offers significant potential for improving teaching effectiveness and meeting students' evolving needs [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Medical imaging, as a critical component bridging basic and clinical medicine, holds significant importance in medical education because of its systematic nature, practical applications, and reliance on information technology. Given the dynamic nature of healthcare education and the evolving demands of the field, traditional offline classroom teaching methods may no longer suffice in fully preparing students for the complexities of medical imaging practice. In response to these challenges, the adoption of a blended teaching model has emerged as a valuable supplement to traditional medical education practices [\u003cspan additionalcitationids=\"CR9 CR10 CR11 CR12 CR13\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. By effectively integrating classroom teaching with information technology, the blended teaching model can revolutionize educational practices, cater to students' developmental needs, and yield optimal teaching outcomes. The focus of this study is to evaluate the application and effectiveness of blended teaching in medical imaging and perform cognitive analysis via the Technology Acceptance Model (TAM). Furthermore, we investigated the advantages and challenges of the blended teaching model in medical imaging education, along with exploring students' cognition and acceptance of this approach. Establishing a new model and conducting confirmatory factor analysis represent rigorous methods to gain deeper insights into how medical imaging students perceive and utilize the blended teaching model.\u003c/p\u003e"},{"header":"2. Hypotheses and Model Building","content":"\u003cp\u003eThis study employed a TAM (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) to evaluate the impact of the blended teaching mode on personal influence factors (PIFs), external influencing factors (EIFs), and students' behavioral intentions (BIs). Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e also shows the relationships between personal innovation ability and student satisfaction, between task‒technology fit and mobile learning usage intention, and between perceived usefulness and ease of mobile learning in the context of practical student satisfaction (SS). On the basis of this relationship, we propose seven hypotheses concerning how blended teaching may affect the satisfaction and behavioral intentions of students using blended online and offline teaching in medical imaging higher education.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Personal influence factors (PIFs)\u003c/h2\u003e \u003cp\u003ePIFs, consisting of individual innovation ability, learning style, and learning desire, have a great impact on blended learning. Individual innovation ability is a crucial factor influencing the success of the blended learning model [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Students who possess strong innovation abilities are more likely to embrace new technologies and methods. Their sensitivity to innovation makes them more receptive to new technologies, leading to increased creativity and acceptance of new learning approaches [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Different learning styles can affect students' attitudes and preferences toward blended learning. For example, students with a preference for independent learning may gravitate towards the use of online resources in a blended learning environment. Understanding students' diverse learning styles can help educators tailor their approach to better engage and support learners. The desire to learn through various methods is a significant determinant of the effectiveness of the blended learning model [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Students who exhibit a strong motivation to explore different learning approaches tend to be more engaged and proactive in their learning journeys. This willingness to experiment with diverse learning methods enhances the overall learning experience and outcomes in a blended learning setting.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. External influencing factors (EIFs)\u003c/h2\u003e \u003cp\u003eEIFs, including environmental pressure, direct experience with individual use, and technological infrastructure, greatly influence the use of blended learning [\u003cspan additionalcitationids=\"CR20 CR21 CR22\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Environmental pressure, which includes social influences and perceptions, can significantly impact the adoption of blended learning models. When individuals perceive social pressure to use specific technologies, such as when peers, school leaders, or teachers endorse certain tools, they may be more inclined to embrace these technologies. Support from the educational community can create an environment conducive to the acceptance and utilization of blended learning approaches [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Direct experience with technology plays a vital role in shaping individuals' attitudes toward digital tools in a blended learning context. Positive experiences with technology usage, supported by adequate training and technical assistance provided by schools, can enhance students' willingness to engage with blended learning resources [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Satisfactory user experiences contribute to increased acceptance and integration of technology into the learning process. Technological infrastructure serves as a critical external factor influencing the successful implementation and sustainability of blended learning initiatives. The availability of reliable and efficient technological resources directly impacts the effectiveness of blended learning programs and enhances the overall learning experience. A well-established technological infrastructure supports the seamless integration of digital tools, facilitating improved learning outcomes and student engagement [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Perceived Ease of Use (PEU)\u003c/h2\u003e \u003cp\u003ePEU refers to users' perceptions of how easily they can understand and use a particular system [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. In the context of blended learning, high perceived ease of use indicates that students find the system easy to learn and operate without facing significant difficulties or complexities. This perception has a significant effect on shaping students' attitudes and behavioral intentions toward the learning platform. When students perceive a system as easy to use, they are more likely to develop a positive attitude towards it. This positive attitude can lead to continued use of the system and even recommendations to others [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Conversely, if they find the system difficult to use, they may develop negative emotions toward it, decrease their usage frequency, or look for alternative solutions. In the context of blended learning, the PEU can greatly enhance the learning experience. A system that is perceived as easy to use can help students more conveniently access learning resources, facilitate communication with teachers and classmates, and navigate the learning platform effectively. These aspects contribute to an overall increase in students' perceived ease of use, positively impacting their engagement with and satisfaction with the blended learning experience [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Perceived usefulness (PU)\u003c/h2\u003e \u003cp\u003eThe PU refers to an individual\u0026rsquo;s subjective belief regarding the extent to which using a particular technology or system will be beneficial to their work efficiency [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. When students perceive a certain technology or system as highly useful, they are more likely to develop a positive attitude towards it and are willing to accept and use this technology. The PU can be influenced by various factors, such as the actual effectiveness of technical functionalities, students\u0026rsquo; expectations for work efficiency, and the extent to which the technology aids in task completion [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Student Satisfaction (SS)\u003c/h2\u003e \u003cp\u003eSS with blended learning refers to students' perceptions of how well the blended learning model aligns with their expectations and fulfils their needs [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. It encompasses students' contentment with learning resources, interactions, and support available within the blended learning environment. It serves as a critical measure of the effectiveness and impact of blended learning initiatives in multiple ways, including the alignment of acquired knowledge and skills with students' expectations, the quality of students' learning experiences during the blended learning process, and the extent to which blended learning addresses learning challenges [\u003cspan additionalcitationids=\"CR32 CR33\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. It is one of the important indicators for evaluating the effectiveness of blended learning. By understanding the SS, teachers and educational institutions can adjust teaching strategies and improve teaching design promptly to enhance students' learning experience and outcomes [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. In addition, the SS also serves as an important metric for decision-makers to evaluate the effectiveness and feasibility of blended learning schemes [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Behavioral Intention (BI)\u003c/h2\u003e \u003cp\u003eStudent BI in blended learning refers to students' willingness and inclination to use specific technologies or tools within the learning environment [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. It reflects students' attitudes towards their interest and active engagement with these technologies or tools [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Student BI is one of the important factors influencing the actual adoption and utilization of blended learning technologies [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. When students perceive the technology as easy to use and beneficial, they are more likely to show positive behavioral intentions. This means that they are more willing to accept and use the technologies in blended learning, thereby achieving better learning outcomes and experiences [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Therefore, understanding and promoting students' BI is crucial for effectively implementing blended learning.\u003c/p\u003e \u003cp\u003eThe model in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e addresses the relationships among different variables, proposing a close connection between perceived usefulness and ease of use with personal influencing factors and external influencing factors. Furthermore, the model traced the relationship between perceived usefulness and ease of use with student satisfaction. Ultimately, it focused on the relationship between student satisfaction and students' intention to use. Therefore, we propose the following hypotheses:\u003c/p\u003e \u003cp\u003eH1: Personal influencing factors have a positive effect on perceived ease of use.\u003c/p\u003e \u003cp\u003eH2: External influencing factors have a positive effect on perceived ease of use.\u003c/p\u003e \u003cp\u003eH3: Personally influencing factors have a positive effect on perceived usefulness.\u003c/p\u003e \u003cp\u003eH4: External influencing factors have a positive effect on perceived usefulness.\u003c/p\u003e \u003cp\u003eH5: Perceived ease of use has a positive effect on student satisfaction.\u003c/p\u003e \u003cp\u003eH6: Perceived usefulness has a positive effect on student satisfaction.\u003c/p\u003e \u003cp\u003eH7: Student satisfaction has a positive effect on students\u0026rsquo; intention to use.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Research Methodology","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Research Design\u003c/h2\u003e \u003cp\u003eBlended learning is a teaching model that uses online platforms and digital teaching resources, combining traditional face-to-face teaching with online learning to provide a more enriched, flexible, and personalized learning experience. The advantage of blended learning lies in its full utilization of network technology and digital resources, providing a more flexible and personalized learning method [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Students can learn at their own pace and according to their learning needs while also interacting and collaborating with teachers and classmates [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Blended learning can also improve the development and utilization efficiency of educational resources and promote the development of educational informatization [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. This study aims to investigate students' satisfaction with their intention to use blended learning and their perceptions of actual usage in higher education through online teaching.\u003c/p\u003e \u003cp\u003eThe entire analysis in this study was divided into two stages. The first stage involved collecting data from university students through a questionnaire survey. The target student group includes undergraduate students majoring in medical imaging and clinical medicine who participate in medical imaging courses and have been fully exposed to blended learning. The questionnaire was designed with a five-point Likert scale [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. The second stage involved analysing the collected data with the structural equation modelling software Smart-PLS 3.3.3 and SPSS software [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. The Smart-PLS was used to construct and evaluate the structural equation model on the basis of the survey responses. The validity and reliability of the data in the measurement model were assessed. SPSS was employed to calculate correlations between variables, descriptive statistics, regression analysis, and other statistical tests.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e describes the proposed model, which consists of six components: PIF, EIF, PEU, PU, SS, and BI. Seven path lines were proposed between the six groups. Two path lines were proposed for PIF, EIF, PEU, PU, and SS, and one path line was proposed for BI. All the hypotheses were used to predict the six structures [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. The original survey questionnaire is provided in Supplement Document 1.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Data collection and demographic characteristics\u003c/h2\u003e \u003cp\u003eIn this study, 256 surveys based on the TAM model (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) were distributed to undergraduate students majoring in medical imaging and a small portion of clinical undergraduate students who had taken blended learning courses in medical imaging at Hainan Medical University via Questionnaire Star. The anonymous questionnaire focused on students\u0026rsquo; opinions on the use of blended learning in terms of student satisfaction and behavioral intentions, as well as the impact of blended learning on sustainable learning measures. A total of 145 valid questionnaires were collected after screening [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. The sample size can be used to evaluate the structural equation model [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Among the 145 collected questionnaires, 57 were from male participants and 88 were from female participants. The participants are between the ages of 18 and 25. The student grades (years of admission) ranged from 2018\u0026ndash;2022 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eQuestionnaire Design Based on the TAM\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eQuestion Design\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStrongly Agree\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAgree\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNeutral\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDisagree\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eStrongly Disagree\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePerceived Usefulness (PU)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePEU 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe content of blended teaching is rich and practical.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePEU 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBlended teaching can improve learning efficiency.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePEU 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBlended teaching can enhance learning interest.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePerceived Ease of Use (PEU)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePU 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBlended teaching makes it easier to find the necessary learning resources.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePU 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBlended teaching facilitates communication and interaction with teachers and classmates.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePU 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBlended teaching can improve learning effectiveness.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePersonal Influencing Factors (PIF)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePIF 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYou are more willing to use new technologies and methods in daily learning.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePIF 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYou prefer independent learning over collaborative learning.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePIF 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYou hope to better grasp knowledge through different learning methods.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eExternal Influencing Factors (EIF)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEIF 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSchool leaders and teachers encourage the use of blended teaching.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEIF 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYou have participated in blended teaching training and received technical support provided by the school.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEIF 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYou believe that the technological infrastructure provided by the school makes blended teaching easier to implement.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eStudent Satisfaction (SS)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSS 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBlended teaching improves learning effectiveness, increases learning enjoyment, and enhances learning motivation.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSS 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBlended teaching can enhance learning experience and efficiency.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSS 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBlended teaching provides sufficient technical support to help you solve problems encountered in learning.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eBehavioral Intention (BI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBI 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYou are willing to continue using this teaching method in the future.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBI 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYou are willing to actively participate in learning in blended teaching.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBI 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYou are willing to recommend the blended teaching model to others.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercentage (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u0026ndash;19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22\u0026ndash;23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u0026ndash;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcademic Year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMajor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedical Imaging\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e92.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinical Medicine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Data analysis\u003c/h2\u003e \u003cp\u003eSmart-PLS 3.3.3 and IBM SPSS 26 software were used to perform structural equation modelling analysis on the collected data [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. To test the validity of the data, we reported the convergence validity and discriminant validity. Convergence validity was calculated via the average variance extracted (AVE) formula, with an AVE value of 0.500 indicating satisfactory convergence validity. Discriminant validity was obtained via the Fornell\u0026ndash;Larcker criterion and cross-loading analysis. Moreover, internal consistency reliability (ICR), an essential measure of data reliability, was evaluated via two methods: composite reliability (CR) and Cronbach's alpha (CA). Both CA and CR values exceeding 0.700 indicated satisfactory reliability. For model evaluation, the significance of the relationship within the structural equation model was assessed through path coefficients, t values, and P values.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Results","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Loadings of reflective indicators\u003c/h2\u003e \u003cp\u003eConfirmatory factor analysis was carried out by constructing a structural equation. Items with low standardized factor loading coefficients of measurement variables and latent variables were deleted [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. The standardized factor loading coefficients of all the observed variables were greater than 0.7, indicating good reliability [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Except for the loading of PIF2 (0.470), all the other indicators had loadings greater than 0.7 (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The 17 indicators were included for further analysis.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of Reliability and Validity Indicators\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstructs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndicators\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCronbach's alpha\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eComposite reliability (rho_a)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eComposite reliability (rho_c)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAverage variance extracted (AVE)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBI 1 - BI 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.925\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.934\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.952\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.869\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEIF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEIF 1 - EIF 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.857\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.865\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.913\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.777\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePEU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePEU 1 - PEU 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.928\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.932\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.954\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.875\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePIF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePIF 1, PIF 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.810\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.818\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.913\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.840\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePU 1 - PU 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.942\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.943\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.963\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.896\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSS 1 - SS 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.962\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.963\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.976\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.930\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Internal Consistency Reliability\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e provides the CA and CR values of all the structures greater than 0.7 [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. The CA and CR values of the PIF method were 0.810 and 0.818, as well as 0.857 and 0.865 for the EIF, 0.928 and 0.932 for the PEU, 0.942 and 0.943 for the PU, 0.962 and 0.963 for the SS, and 0.925 and 0.934 for the BI.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Convergent Validity Test\u003c/h2\u003e \u003cp\u003eThe AVE values of all the structures exceeded 0.500. Specifically, the AVE values of PIF, EIF, PEU, PU, SS, and BI were 0.840, 0.777, 0.875, 0.896, 0.930, and 0.869, respectively. (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Discriminant validity test\u003c/h2\u003e \u003cp\u003eAccording to the Fornell\u0026ndash;Larcker criterion, to judge whether two latent constructs have discriminant validity, the following conditions must be met: (1) the AVE value of each latent structure must be greater than the square of its correlation coefficient with other constructs; (2) the AVE value of the latent structure must be greater than its cross-loadings with other constructs. The Fornell‒Larcker correlation matrix between each variable value is shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFornell\u0026ndash;Larcker correlation matrix.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEIF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePEU\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePIF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePU\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSS\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.932\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEIF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.838\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.882\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePEU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.835\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.732\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.935\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePIF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.756\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.724\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.726\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.917\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.869\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.710\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.874\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.685\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.946\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.937\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.833\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.840\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.708\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.850\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.964\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn addition, the discriminant validity of items can also be evaluated by calculating cross-loadings [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e], that is, correlating each item with its own latent variable and other latent variables to evaluate the relationships between the item and other latent variables. If the correlation coefficient between an item and its latent variable is significantly greater than the correlation coefficient with other latent variables, then the item can be considered to have good discriminant validity, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of Cross-Loadings\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEIF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePEU\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePIF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePU\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSS\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBI1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.954\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.775\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.797\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.681\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.809\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.899\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBI2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.949\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.811\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.782\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.676\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.827\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.933\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBI3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.893\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.759\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.757\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.770\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.796\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.776\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEIF1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.776\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.880\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.738\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.657\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.729\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEIF2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.686\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.863\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.532\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.605\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.579\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.672\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEIF3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.748\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.902\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.680\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.566\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.636\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.795\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePEU1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.734\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.615\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.915\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.624\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.785\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.749\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePEU2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.801\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.728\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.945\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.701\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.843\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.802\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePEU3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.804\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.706\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.945\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.709\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.822\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.804\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePIF1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.712\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.668\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.681\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.926\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.656\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePIF3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.671\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.660\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.650\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.907\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.566\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.643\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePU1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.799\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.644\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.782\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.659\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.940\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.751\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePU2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.843\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.689\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.830\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.652\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.960\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.837\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePU3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.823\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.683\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.867\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.635\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.939\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.824\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSS1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.876\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.812\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.772\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.653\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.801\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.955\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSS2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.792\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.832\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.714\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.834\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.976\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSS3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.928\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.807\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.825\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.681\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.825\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.963\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.5 Structural Model and Collinearity\u003c/h2\u003e \u003cp\u003eThe predictive ability of the structural model was tested as a part of the evaluation. Collinearity is represented by reporting the variance inflation factor (VIF) values. A VIF greater than 5 is usually considered to indicate multicollinearity [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. In this study, the VIF values of all the structures were less than 5 (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eVariance inflation factor (VIF).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEIF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePEU\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePIF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePU\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSS\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEIF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePEU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.232\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePIF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.232\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e4.6 Structural Model Hypothesis Testing\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e show the bootstrap calculation results for all the structures. Generally, an absolute value greater than 0.3 can be considered to have a significant impact, and an absolute value greater than 0.5 can be considered to have a major impact [\u003cspan additionalcitationids=\"CR58 CR59\" citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. For PIF \u0026rarr; PEU (PC\u0026thinsp;=\u0026thinsp;0.412; t\u0026thinsp;=\u0026thinsp;3.659; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), the corresponding hypothesis (H1) was supported. For PIF \u0026rarr; PU (PC\u0026thinsp;=\u0026thinsp;0.359; t\u0026thinsp;=\u0026thinsp;3.506; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), the corresponding hypothesis (H2) was supported. For hypotheses H3 and H4, EIF \u0026rarr; PEU (PC\u0026thinsp;=\u0026thinsp;0.434; t\u0026thinsp;=\u0026thinsp;4.132; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and EIF \u0026rarr; PU (PC\u0026thinsp;=\u0026thinsp;0.450; t\u0026thinsp;=\u0026thinsp;4.028; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), the corresponding hypotheses were supported. Moreover, there was a significant influence between PEU \u0026rarr; SS (PC\u0026thinsp;=\u0026thinsp;0.410; t\u0026thinsp;=\u0026thinsp;2.737; P\u0026thinsp;=\u0026thinsp;0.006) and PU \u0026rarr; SS (PC\u0026thinsp;=\u0026thinsp;0.492; t\u0026thinsp;=\u0026thinsp;3.338; P\u0026thinsp;=\u0026thinsp;0.001); thus, the corresponding hypothesis (H5, H6) was supported. The relationship between SS \u0026rarr; BI (PC\u0026thinsp;=\u0026thinsp;0.937; t\u0026thinsp;=\u0026thinsp;68.891; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) indicated that the corresponding hypothesis (H7) was supported.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eModel Hypothesis Testing\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePath of Hypotheses\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePath coefficients\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOriginal sample (O)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSample mean (M)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStandard deviation (STDEV)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eT statistics (|O/STDEV|)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e values\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eResults\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSS \u0026rarr; BI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.937\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.937\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.937\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e68.891\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSupported\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEIF \u0026rarr; PEU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.434\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.434\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.432\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSupported\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEIF \u0026rarr; PU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.450\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.446\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSupported\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePEU \u0026rarr; SS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.410\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.409\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.737\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSupported\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePIF \u0026rarr; PEU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.412\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.412\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.418\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.659\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSupported\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePIF \u0026rarr; PU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.359\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.359\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.366\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.506\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSupported\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePU \u0026rarr; SS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.492\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.492\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.492\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSupported\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"5. Discussion","content":"\u003cp\u003eThe evolution of technology has profoundly influenced universities and the education system, necessitating the adoption of advanced technological systems. The digital transformation has revolutionized the flow of information, enabling innovative interactions among users through engaging multimedia applications [\u003cspan additionalcitationids=\"CR62\" citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. Building on these technological advancements, this study developed a conceptual model to explore the continued use of teaching methods in the educational environment, with a particular focus on online training and mobile telecommunications. PEU is considered one of the key factors in the conceptual model, influencing both internal students and external teaching factors. It encompasses students' innovativeness, learning aspirations, environmental pressures, direct user experience, and technology infrastructure development [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. On the other hand, it directly influences students\u0026rsquo; satisfaction with continuing to use educational technologies, subsequently affecting their behavioral intentions toward blended learning [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. By elucidating the relationships between perceived ease of use, student satisfaction, and behavioral intentions, this study sheds light on the critical role of technology acceptance and usability in promoting effective blended learning practices. Understanding these dynamics can inform educational strategies, instructional design, and technology integration efforts to optimize student learning outcomes and experiences.\u003c/p\u003e \u003cp\u003eThe goal of this study was to evaluate students' perceptions of blended learning via the TAM framework. Despite its limited adoption in higher education, the findings indicated that students perceived value in blended learning and were open to embracing it. Constructs from the TAM model, such as PIF, EIF, PU, PEU, SS, and BI, were identified as positive factors driving the use of blended learning among university students, especially in medical imaging courses. Unlike previous research on mobile learning, this study highlighted the importance of investigating student satisfaction and intentions regarding blended learning. These findings suggest that universities should prioritize PU, PEU, and SS to foster student acceptance of blended learning. Future researchers should focus on the broad implementation of blended learning, explore planning strategies for PIFs and EIFs, and assess their potential in education. By integrating various internal and external factors with TAM structures, this study contributes to facilitating the adoption and acceptance of research. It distinguished itself by examining individual differences such as student satisfaction and behavioral intentions, thereby enhancing the understanding of blended learning models. Overall, this study advances empirical research in the application and promotion of blended learning.\u003c/p\u003e \u003cp\u003eThe present study had several limitations. First, the conceptual model was confined to a specific set of internal and external factors directly linked to the TAM constructs. Future research could integrate additional influencing factors to provide a more comprehensive understanding of relevant technologies. Second, the sample is restricted to the students enrolled in a medical imaging course, which primarily consists of medical imaging majors. To gain insights into the attitudes of students from diverse majors towards blended learning, future investigations could consider exploring attitudinal differences across various courses and majors. Third, the survey was conducted via internet and social media platforms. There is potential for future research to explore alternative survey distribution methods to enhance data collection strategies and reach a more diverse participant pool.\u003c/p\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eOur results revealed that students exhibited belief in and readiness to accept the blended learning model, indicating a positive outlook towards this innovative approach to learning. The TAM has made significant contributions to understanding students' perceptions in this context. Future research should focus on investigating planning recommendations for PIFs and EIFs and evaluating the anticipated effectiveness of PIFs and EIFs in educational settings, considering the widespread adoption of blended learning.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors extend their appreciation to the teachers at Hainan Medical University who have conducted blended teaching in medical imaging.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eXiaofen Sun: Conceptualization, Data curation, Formal Analysis, Methodology, Software, Supervision, Validation, Visualization, Writing \u0026ndash; original draft, Writing \u0026ndash; review \u0026amp; editing. Jianghua Wan: Conceptualization, Data curation, Formal Analysis, Investigation, Software, Supervision, Writing \u0026ndash; original draft, Writing \u0026ndash; review \u0026amp; editing. Zhiqun Li: Formal Analysis, Investigation, Methodology, Validation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRong Tu: Conceptualization, Project administration, Supervision. Juan Lin: Data curation, Investigation. Xiaohua Li: Data curation, Investigation, Methodology. Jianqiang Chen: Conceptualization, Data curation, Project administration, Writing \u0026ndash; review \u0026amp; editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Education Department of Hainan Province (Grant Numbers: Hnjg2024ZC-70, Hnjgzc2023-20, 22A200069), and Hainan Medical University (Grant Numbers: HYYB202230, HYYB202380, HYKCPY202307, RZ2300005679). These institutions provided financial support but did not involve in study design, data collection, analysis, or interpretation. The financial supporters had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data used to support the findings of this study are included within the article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study has been approved by the Biomedical Ethics Committee of the First Affiliated Hospital of Hainan Medical University (Approval No: 2024-KYL-176). To ensure confidentiality, the collection of participants\u0026rsquo; questionnaires and the related analysis were conducted anonymously. We provided a detailed explanation of the study objectives to all students who participated in the blended teaching of medical imaging. Informed consent forms were distributed to all students, and written informed consent was obtained from all participants before their participation in the questionnaire survey. The survey was conducted under conditions that protected the privacy, confidentiality, and anonymity of participant information. Participants voluntarily chose whether or not to participate in the research and were informed of their right to withdraw from the study at any time without penalty.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHuman Ethics and Consent to Participate declarations\u003cbr\u003e\u0026nbsp;\u003c/strong\u003eThe ethical aspects of this study have been reviewed and approved by the Biomedical Ethics Committee of the First Affiliated Hospital of Hainan Medical University, and informed consent was obtained from all individual participants involved in the study.\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"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMartin S, Lopez-Martin E, Lopez-Rey A, Cubillo J, Moreno-Pulido A, Castro M. Analysis of New Technology Trends in Education: 2010\u0026ndash;2015. 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Front Psychol. 2021;12:736051.\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":true,"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":"Blended Learning, Technology Acceptance Model, Student Behavioral Intention, Higher Education Technology, Medical Imaging.","lastPublishedDoi":"10.21203/rs.3.rs-4866975/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4866975/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBlended learning, a combination of online learning and face-to-face instruction, is becoming an increasingly important component of higher education technology. However, there is currently insufficient research addressing students' perceptions of blended learning. Our study aims to investigate the satisfaction and behavioral intentions of students with blended learning in medical imaging. We employed the Technology Acceptance Model (TAM), which includes four independent variables, to evaluate students' satisfaction and behavioral intentions toward blended learning. The data were collected through the TAM survey, with questionnaires randomly distributed to the students participating in the \"Medical Imaging\" blended course at Hainan Medical University. A total of 145 valid questionnaires were returned and analysed via SPSS and Smart-PLS 3.3.3. Detailed results. Our results indicate that the practical application of blended learning has a positive and constructive impact and is worth promoting in higher education institutions. The empirical findings could also contribute to the integration of the TAM model to increase the effectiveness of blended learning for students.\u003c/p\u003e","manuscriptTitle":"Application and effectiveness of blended learning in medical imaging via the technology acceptance model","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-14 07:56:03","doi":"10.21203/rs.3.rs-4866975/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-08-21T14:58:15+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-08-16T12:44:59+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-08-16T12:41:38+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medical Education","date":"2024-08-06T08:41:22+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":"26b315d3-2c5a-4a03-89b2-6b88cbd9b552","owner":[],"postedDate":"October 14th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-05-26T16:02:56+00:00","versionOfRecord":{"articleIdentity":"rs-4866975","link":"https://doi.org/10.1186/s12909-025-07293-6","journal":{"identity":"bmc-medical-education","isVorOnly":false,"title":"BMC Medical Education"},"publishedOn":"2025-05-21 15:57:07","publishedOnDateReadable":"May 21st, 2025"},"versionCreatedAt":"2024-10-14 07:56:03","video":"","vorDoi":"10.1186/s12909-025-07293-6","vorDoiUrl":"https://doi.org/10.1186/s12909-025-07293-6","workflowStages":[]},"version":"v1","identity":"rs-4866975","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4866975","identity":"rs-4866975","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}