How diverse learning approaches relate to classroom problem-solving activities and academic self-efficacy

How diverse learning approaches relate to classroom problem-solving activities and academic self-efficacy | 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 How diverse learning approaches relate to classroom problem-solving activities and academic self-efficacy Muhammad Aizri Fadillah, Muhammad Fazlan Akbar, Yul Ifda Tanjung, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6861099/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Problem-solving benefits are well established, yet the relationship between its activities and students' self-efficacy remains underexplored. This study examined the relationship between classroom problem-solving activities and academic self-efficacy across diverse learning approaches in Indonesia. Employed a quantitative approach with a survey research design, data from 458 high school students were analyzed using multiple linear regression. Results showed that investigating real-world problems significantly relationships all aspects of academic self-efficacy, particularly in differentiated learning. Engaging with others' real-world problems fostered the belief that "if others can, so can I," notably in multimedia, culturally responsive, and differentiated learning. However, multiple real-world challenges had no significant overall relationships, except in game-based learning for idea generation. Real-world problem-solving also helped students connect ideas, especially in culturally responsive and differentiated settings. Applying knowledge to solve real problems had a strong positive relation across all learning approaches. These findings highlight the importance of contextualized teaching strategies in strengthening academic self-efficacy and contribute to the limited research on problem-solving in education. Problem-solving self-efficacy learning approaches real-world problems contextualized teaching strategies Figures Figure 1 1. Introduction Problem-solving is a critical 21st-century skill for navigating global transformations and enhancing cognitive abilities, metacognition, and collaborative skills (Güner & Erbay, 2021 ). In educational contexts, it promotes understanding complex concepts by analyzing everyday phenomena (Husin et al., 2025 ), particularly in scientific disciplines requiring visualizations, mathematical reasoning, and conceptual comprehension (Ince, 2018 ). However, many students find these subjects challenging (Argaw et al., 2016 ). Problem-solving demands intensive cognitive engagement and is key to developing science process skills and influencing learning efficacy (Husin et al., 2025 ). Research highlights the benefits of problem-solving as a pedagogical strategy, including enhanced scientific knowledge, reasoning (Cheng et al., 2017 ), critical thinking (Xu et al., 2023 ), self-efficacy (Fitriani et al., 2020 ), knowledge construction (Hwang & Chen, 2023 ), and academic achievement (Aslan, 2021 ). It also improves learning performance (Almulla & Al-Rahmi, 2023 ), scientific writing skills (Sari et al., 2021 ), and overall student outcomes (Harefa & Purba, 2020 ). Despite these findings, a gap exists in understanding how specific classroom problem-solving activities contribute to student efficacy, particularly in diverse learning environments. While studies have explored the general relationship between problem-solving and self-efficacy (Gunawan et al., 2019; Jung et al., 2024 ; Zulkosky, 2009 ), the mechanisms of specific activities remain underexplored. For example, Evans et al. ( 2021 ) examined lateral thinking self-efficacy in mathematics, but broader implications for diverse educational contexts are lacking. Additionally, while instructional approaches like differentiated instruction (Lai et al., 2020 ) and integrated Problem-Based Learning (PBL) have been linked to improved self-efficacy (Fıtrıanı et al., 2020 ), the role of individual problem-solving activities within these approaches is insufficiently studied. Alt ( 2015 ) suggests that constructivist learning environments enhance academic self-efficacy, but further exploration of problem-solving activities is needed. This study addresses this gap by investigating how specific problem-solving activities within diverse learning approaches impact student efficacy in Indonesian high schools. It seeks to answer: (1) What is the relationship between problem-solving activities and academic self-efficacy? and (2) How does this relationship vary across different learning approaches? By exploring these questions, the study contributes to understanding how pedagogical structures influence student outcomes, offering insights for designing learning environments that enhance self-efficacy and academic success. 1.1. Problem-Solving and Academic Self-Efficacy Problem-solving is a critical 21st-century skill, serving as a learning objective, teaching method, and skill (van Merriënboer, 2013 ). It is both an outcome and a process embedded in learning (Armağan et al., 2009 ), developing through practice over time (van Merriënboer, 2013 ). Teachers significantly enhance problem-solving skills by transitioning from instructors to facilitators (Hobri et al., 2020 ). Innovations like contextual-based flipbooks (Maynastiti et al., 2020 ) and inquiry models integrated with advanced organizers have effectively improved these skills (Gunawan et al., 2020 ). Collaborative tools like CPSCoach 2.0 further support problem-solving (D’Mello et al., 2024 ), fostering critical thinking and confidence, key components of self-efficacy (Yustitia et al., 2025 ). Problem-solving engages students in tasks requiring critical thinking and application of concepts, deepening understanding and equipping them with practical skills. It is central to pedagogical methods like project-based learning (PBL) and inquiry-based learning (IBL) (Husin et al., 2025 ; Karamustafaoğlu & Pektaş, 2023 ), which encourage questioning, hypothesis formulation, experimentation, and conclusion drawing. These methods enhance cognitive skills, motivation, and engagement, improving learning outcomes. Academic self-efficacy refers to students' belief in their ability to succeed in academic tasks, influencing goal-setting, strategy development, and persistence (Ritchie, 2017 ). Bandura ( 2006 ) identified it as a key predictor of learning efficiency and motivation. Indicators such as interest, participation, and awareness measure self-efficacy, with most students falling into the moderate category (Agustina et al., 2019 ). Learning facilities, including AI-based experiments (Cai et al., 2021 ) and real-life learning scenarios (Semilarski et al., 2021 ), also contribute to self-efficacy. Zulkosky ( 2009 ) described it as encompassing affective, cognitive, and self-regulation processes, where feedback enhances affective aspects, and problem-solving strengthens cognitive development. Educational approaches like differentiated instruction (Scarparolo & Subban, 2021 ), game-based learning (Lu & Lien, 2020 ), and multimedia-based learning have been shown to enhance academic self-efficacy (Huang et al., 2023 ). Culturally responsive learning also positively impacts self-efficacy across multinational contexts (Yu et al., 2021 ). 1.2. Pedagogy in Indonesian Context Indonesia's multicultural society necessitates innovative learning models to enhance education quality and student engagement. The diverse population, with variations in religion, socio-economic status, and culture, requires an adaptable education system (Raihani, 2018 ). Culturally responsive learning integrates cultural diversity into classrooms through multicultural content, varied assessments, and holistic learning experiences (Howard, 2021 ), fostering critical thinking and social awareness (Shahali et al., 2022 ). Differentiated instruction tailors education to individual needs, ensuring equitable learning opportunities and student development (Mills et al., 2014 ; Tomlinson & Imbeau, 2023 ). Innovative pedagogies like multimedia-based learning promote self-regulation, problem-solving, and conceptual understanding (Suhandi et al., 2018 ), while game-based learning enhances engagement and cognitive, affective, and problem-solving skills (Dewantara et al., 2021 ; Pratama & Setyaningrum, 2018 ; Putranta et al., 2021 ). Chai et al.'s ( 2015 ) authentic problem-solving activity scale integrates real-world, unstructured problems into learning. It is particularly relevant in Indonesia's multicultural context. The scale engages students in exploring causes and solutions to issues like water shortages and environmental concerns, strengthening problem-solving skills and enhancing self-efficacy and learning outcomes. 2. Methods 2.1. Participants This study employed a quantitative approach with a survey research design to collect data from high school students in Indonesia, which was distributed online via social media platforms, such as WhatsApp. We used the convenience sampling method to select respondents based on their availability and willingness to participate. This non-probability sampling method was used due to the vast number, diversity, and geographical dispersion of high schools across Indonesia, which made it challenging to apply a representative sampling approach. This method was chosen because it allows for quick and easy collection of data from a large number of participants who are readily accessible (Etikan, 2016 ). Table 1 presents the demographic information of the 458 students (ages 15–18) from high schools in Indonesia who participated in this study. The sample included 156 males (34.06%) and 302 females (65.94%). Most students reported that their teachers used a differentiated learning approach (70.09%). Other reported approaches included multimedia-based learning (8.52%), culturally responsive learning (11.35%), and game-based learning (5.68%). Additionally, 4.37% of students reported other approaches that were not explicitly mentioned. It is important to note that research used ethical guidelines to safeguard participants' rights and well-being. Before participation, respondents received comprehensive information about the study, including its purpose, procedures, and potential risks or benefits. Informed consent was obtained electronically, ensuring that participants voluntarily agreed to participate and that their responses would remain anonymous for research purposes. No personally identifiable information (PII) was collected, and all data were securely stored to maintain confidentiality. The study received ethical approval from the institutional ethics review board. Furthermore, participants were informed of their right to withdraw from the study without facing any consequences. Table 1 Demographic Information Demographic (n = 458) Number Gender Male 156 (34.06%) Female 302 (65.94%) What learning approaches does your teacher use that you know of? Multimedia-based 39 (8.52%) Culturally responsive 52 (11.35%) Differentiated 321 (70.09%) Game-based 26 (5.68%) Others 20 (4.37%) 2.2. Measures The study included constructs about students' perceptions of the learning process, adopted from previous research: problem-solving activities (Chai et al., 2015 ) and academic self-efficacy (van Zyl et al., 2022 ). We used a 5-point Likert scale ranging from "Strongly disagree" to "Strongly agree" to facilitate easy and accurate responses (Taherdoost, 2022 ). Table 2 displays the validation of each measurement item. All items have factor loadings above 0.50 (Hair et al., 2021 ). Cronbach's alpha (CA) and composite reliability (CR) for all measures exceed 0.80, and the average variance extracted (AVE) is above 0.50, indicating excellent criteria (Hair et al., 2021 ). It confirms the reliability and validity of the data, ensuring credible measurement scales in this study. Table 2 Measurements Scales Code Items Loading CA CR AVE Problem-solving activity PSA1 In class, I investigate the reasons that cause problems in the real world 0.777 0.805 0.865 0.563 PSA2 In class, I learn about real-life problems that people experience 0.761 PSA3 In class, I am challenged by many real-world problems (e.g. water shortages, racial harmony, environmental issues) 0.635 PSA4 In class, I practiced solving real-world problems 0.778 PSA5 In class, I apply my knowledge to solve real-life problems 0.790 Academic self-efficacy ASE1 I generally manage to build explanations/theories about issues I study if I try hard enough 0.722 0.814 0.871 0.575 ASE2 I know I can connect different ideas to form new ideas in my field of study 0.774 ASE3 I will remain calm while creating useful knowledge on my own because I know I have the capability to do it 0.761 ASE4 I know I can generate new ideas about what I study if I put in enough work 0.813 ASE5 The motto 'if others can, I can too' applies to me when it comes to designing things that might be useful 0.717 2.3. Non-Response Bias We also tested for non-response bias, as cross-sectional studies can have this bias. This bias is usually addressed by comparing answers from early and late respondents (Fadillah et al., 2024 ). We compared the first 50 respondents and the last 50 respondents for each item using a t -test. The results showed that the p -values ranged from 0.261 to 0.845, meaning there was no significant difference between the two groups ( p > 0.05), so there was no substantial non-response bias. 2.4. Checking Assumptions for Analysis Before the primary analysis, key assumptions—normality, homoscedasticity, and multicollinearity—were tested to ensure model validity. These tests used cumulative mean scores of problem-solving activity and academic self-efficacy scales. Given that the sample size exceeded 50, normality was assessed using skewness and kurtosis values instead of Kolmogorov-Smirnov or Shapiro-Wilk tests, which are better suited for small samples (Hong et al., 2023 ). Data are normally distributed if skewness is between − 2 and + 2 and kurtosis between − 7 and + 7 (Byrne, 2013 ; Hair et al., 2010 ). The results showed PSA skewness, kurtosis of 0.130 and 0.072, and ASE values of 0.353 and 0.210, confirming normality. Homoscedasticity was tested using a P-P plot and residual scatterplot with ASE as the dependent variable (Hong et al., 2023 ). The P-P plot showed residuals aligning with the diagonal line (Fig. 1 .a), and the scatterplot displayed no distinct pattern (Fig. 1 .b), confirming homoscedasticity. Using tolerance and variance inflation factor (VIF) values, multicollinearity was examined, where tolerance above 0.1 and VIF below 10 indicate no multicollinearity issues (Field, 2024 ; Hair et al., 2010 ). The tolerance and VIF values for PSA and ASE were 1.000, confirming the absence of multicollinearity and validating the model for further analysis. 2.5. Implementation of Regression Analysis The treatment of ordinal data, such as Likert-scale responses, as continuous is debated. However, research supports this under certain conditions. Norman ( 2010 ) argues that if data distribution is approximately normal and response categories are sufficient, Likert-scale data can be treated as interval data for parametric analysis. Harpe ( 2015 ) also notes that this is often valid, as ordinal data rarely affects parametric test reliability. To confirm suitability, we examined data distribution, as detailed in "Checking Assumptions for Analysis." The results showed approximate normality, justifying the treatment of Likert-scale items as continuous in regression analysis. Norman ( 2010 ) emphasizes that parametric methods like regression and ANOVA are robust to minor violations of normality and remain effective even for ordinal data. Harpe ( 2015 ) notes that while some researchers prefer ordinal-based methods, parametric approaches are valid if the sample size is large and the data distribution is symmetrical. Non-parametric methods remain an alternative if ordinal data poses concerns. Although Norman and Harpe support parametric methods, we acknowledge that Likert-scale data are inherently ordinal. However, given statistical evidence and data characteristics, regression analysis is appropriate. We used multiple linear regression (univariate) with the ENTER model to examine the relationship between problem-solving activities and self-efficacy. The ENTER model enters all predictors simultaneously to assess their contributions while controlling for other variables (Field, 2024 ). Analysis was conducted using SPSS V.26 to determine significance, including coefficient (B) for effect size and standard error (SE) for uncertainty. 3. Results 3.1. Descriptive Information Table 3 presents descriptive data for each item across different learning approaches, showing mean and standard deviation values overall and by approach. The learning approaches include multimedia-based, culturally responsive, differentiated, game-based, and others. The sample consists of 458 respondents, with subgroups: multimedia-based (39), culturally responsive (52), differentiated (321), game-based (26), and other (20). PSA5, "In class, I apply my knowledge to solve real-life problems," had the highest mean for problem-solving activities overall (M = 3.35, SD = 0.969) and in multimedia (M = 3.85, SD = 0.844), culturally responsive (M = 3.63, SD = 1.048), and differentiated (M = 3.67, SD = 0.868) approaches. PSA2, "In class, I learn about real-life problems people experience," had the highest mean in game-based (M = 3.65, SD = 1.129) and other (M = 3.60, SD = 0.754) approaches. Overall, self-efficacy mean values ranged from 3.47 to 3.69, varying by learning approach. Table 3 Descriptive statistics of each item: mean and standard deviation (in parentheses) Items Overall (n = 458) Learning approach Multimedia (n = 39) Culturally responsive (n = 52) Differentiated (n = 321) Game-based (n = 26) Others (n = 20) PSA1 3.35 (0.969) 3.54 (0.969) 3.17 (1.216) 3.37 (0.916) 3.38 (0.941) 3.20 (1.105) PSA2 3.64 (0.974) 3.74 (1.019) 3.46 (1.146) 3.65 (0.940) 3.65 (1.129) 3.60 (0.754) PSA3 3.25 (1.183) 3.74 (1.229) 3.10 (1.317) 3.22 (1.139) 3.15 (1.287) 3.20 (1.152) PSA4 3.51 (0.934) 3.67 (0.955) 3.52 (1.111) 3.49 (0.909) 3.62 (0.804) 3.50 (1.000) PSA5 3.67 (0.900) 3.85 (0.844) 3.63 (1.048) 3.67 (0.868) 3.58 (0.945) 3.45 (1.050) ASE1 3.47 (0.816) 3.62 (0.815) 3.54 (0.999) 3.46 (0.774) 3.35 (0.936) 3.20 (0.768) ASE2 3.57 (0.829) 3.67 (0.869) 3.63 (0.971) 3.55 (0.793) 3.38 (0.983) 3.65 (0.745) ASE3 3.46 (0.872) 3.62 (0.747) 3.48 (1.057) 3.45 (0.872) 3.50 (0.812) 3.35 (0.671) ASE4 3.58 (0.801) 3.82 (0.790) 3.62 (0.889) 3.55 (0.769) 3.50 (1.068) 3.65 (0.671) ASE5 3.69 (0.819) 3.74 (0.751) 3.85 (0.998) 3.66 (0.798) 3.50 (0.906) 3.80 (0.616) 3.2. The Relationship Between Problem-Solving Activities and Academic Self-Efficacy Table 4 presents multiple linear regression results on problem-solving activities and academic self-efficacy. PSA1, which involves investigating real-world problems, significantly relates all aspects of academic self-efficacy: constructing explanations (ASE1) (B = 0.209, p < 0.001), connecting ideas (ASE2) (B = 0.113, p < 0.05), staying calm while creating knowledge (ASE3) (B = 0.130, p < 0.01), generating new ideas (ASE4) (B = 0.147, p < 0.01), and believing "if others can, I can too" (ASE5) (B = 0.133, p < 0.01). PSA2, which focuses on real-life problems, significantly relates ASE2 (B = 0.107, p < 0.05) and ASE5 (B = 0.103, p 0.05). PSA4, involving hands-on problem-solving, is significant for ASE2 (B = 0.229, p < 0.001). PSA5, applying knowledge to solve real problems, strongly significant ASE1 (B = 0.313, p < 0.001), ASE3 (B = 0.193, p < 0.001), ASE4 (B = 0.208, p < 0.001), and ASE5 (B = 0.217, p < 0.001). Table 4 Overall results of the multiple linear regression approach Items ASE1 ASE2 ASE3 ASE4 ASE5 B SE B SE B SE B SE B SE PSA1 0.209 *** 0.043 0.113 * 0.046 0.130 ** 0.050 0.147 ** 0.046 0.133 ** 0.047 PSA2 0.026 0.042 0.107 * 0.046 0.055 0.049 0.004 0.045 0.103 * 0.046 PSA3 -0.052 0.031 -0.064 0.034 0.018 0.036 0.030 0.033 -0.010 0.034 PSA4 0.054 0.045 0.229 *** 0.049 0.082 0.052 0.041 0.048 -0.020 0.049 PSA5 0.313 *** 0.047 0.087 0.051 0.193 *** 0.054 0.208 *** 0.050 0.217 *** 0.051 Note: * p < 0.05, ** p < 0.01, *** p < 0.001. 3.3. The Relationship Between Problem-Solving Activities and Academic Self-Efficacy with Various Approaches Table 5 presents the relationship between problem-solving activities and academic self-efficacy across different learning approaches. In multimedia-based learning, PSA1 and PSA4 were not significant ( p > 0.05), while PSA2 was significant for ASE4 (B = 0.324, p < 0.05). PSA3 was significant but negative for ASE2 (B = -0.292, p < 0.05). PSA5 showed significance for ASE2 (B = 0.380, p < 0.05), ASE3 (B = 0.649, p < 0.001), ASE4 (B = 0.569, p < 0.001), and ASE5 (B = 0.429, p 0.05). PSA2 was significant for ASE1 (B = 0.324, p < 0.05), while PSA3 was significant but negative for ASE1 (B = -0.235, p < 0.05). PSA4 was significant for ASE1 (B = 0.417, p < 0.01) and ASE2 (B = 0.438, p < 0.01). PSA5 was significant for ASE4 (B = 0.451, p < 0.01) and ASE5 (B = 0.537, p < 0.01). In differentiated learning, PSA1 was significant for ASE1 (B = 0.251, p < 0.001), ASE3 (B = 0.152, p < 0.05), ASE4 (B = 0.151, p < 0.01), and ASE5 (B = 0.132, p < 0.05), while PSA2 was significant for ASE2 (B = 0.108, p < 0.05) and ASE5 (B = 0.152, p 0.05), but PSA4 was significant for ASE2 (B = 0.208, p < 0.001). PSA5 was significant for ASE1 (B = 0.320, p < 0.001), ASE4 (B = 0.135, p < 0.05), and ASE5 (B = 0.170, p 0.05). However, PSA3 was significant for ASE4 (B = 0.358, p < 0.05), and PSA5 was significant for ASE1 (B = 0.546, p < 0.05) and ASE3 (B = 0.463, p < 0.05). Table 5 Results of multiple linear regression approach based on various learning approaches Items ASE1 ASE2 ASE3 ASE4 ASE5 B SE B SE B SE B SE B SE Multimedia PSA1 0.141 0.156 0.265 0.149 0.029 0.128 0.048 0.119 0.226 0.145 PSA2 0.110 0.177 0.230 0.169 0.270 0.145 0.324 * 0.134 0.206 0.164 PSA3 -0.207 0.114 -0.292 * 0.109 -0.006 0.093 0.157 0.086 0.076 0.106 PSA4 0.410 0.243 0.208 0.232 -0.208 0.199 -0.258 0.184 -0.244 0.225 PSA5 0.207 0.167 0.380 * 0.159 0.649 *** 0.137 0.569 *** 0.127 0.429 ** 0.155 Culturally responsive PSA1 -0.119 0.173 -0.116 0.176 -0.062 0.219 0.208 0.139 -0.060 0.169 PSA2 0.324 * 0.143 0.184 0.145 0.023 0.181 -0.076 0.115 0.061 0.139 PSA3 -0.235 * 0.114 -0.192 0.116 0.100 0.144 -0.033 0.091 -0.071 0.111 PSA4 0.417 ** 0.142 0.438 ** 0.145 0.163 0.18 0.068 0.114 0.206 0.139 PSA5 0.241 0.162 0.239 0.165 0.243 0.205 0.451 ** 0.130 0.537 ** 0.158 Differentiated PSA1 0.251 *** 0.049 0.092 0.054 0.152 * 0.060 0.151 ** 0.054 0.132 * 0.055 PSA2 -0.026 0.049 0.108 * 0.055 0.049 0.061 -0.009 0.055 0.152 ** 0.056 PSA3 -0.017 0.036 -0.033 0.040 0.035 0.044 -0.028 0.040 -0.037 0.041 PSA4 0.006 0.053 0.208 *** 0.059 0.098 0.065 0.079 0.059 -0.042 0.060 PSA5 0.320 *** 0.056 0.052 0.062 0.133 0.069 0.135 * 0.062 0.170 ** 0.063 Game-based PSA1 0.271 0.203 0.518 0.273 0.092 0.198 0.086 0.279 0.452 0.253 PSA2 -0.019 0.160 -0.164 0.215 0.204 0.156 -0.020 0.220 -0.252 0.199 PSA3 0.136 0.123 0.153 0.165 -0.193 0.120 0.358 * 0.169 0.263 0.153 PSA4 -0.219 0.194 -0.012 0.262 -0.087 0.190 -0.372 0.267 -0.178 0.242 PSA5 0.546 * 0.196 0.148 0.264 0.463 * 0.192 0.457 0.270 0.113 0.245 Others PSA1 0.078 0.298 0.122 0.242 0.148 0.249 0.038 0.263 0.036 0.242 PSA2 0.025 0.298 0.221 0.242 0.170 0.249 -0.009 0.263 -0.023 0.242 PSA3 -0.117 0.199 -0.096 0.162 -0.082 0.166 0.307 0.175 0.295 0.162 PSA4 0.228 0.356 0.411 0.289 0.080 0.297 -0.155 0.314 -0.166 0.289 PSA5 0.150 0.210 -0.265 0.171 0.121 0.175 -0.175 0.185 -0.079 0.171 Note: * p < 0.05, ** p < 0.01, *** p < 0.001. 4. Discussions This study reveals key findings on the relationship between problem-solving activities and academic self-efficacy, offering insights for effective learning design. PSA1, which involves investigating real-world problems, significantly enhances all aspects of ASE, indicating that engaging with real-world contexts builds student confidence. Analyzing real problems helps students construct explanations, connect ideas, and manage cognitive challenges (Sarathy, 2018 ; Schoenherr, 2024 ). It aligns with constructivist theory, which suggests that learning is more meaningful when students relate new knowledge to prior experiences, boosting motivation and self-efficacy (Andresen et al., 2020 ). PSA2, which focuses on real-life problems, enhances students' ability to connect ideas and believe in their potential (ASE2, ASE5). Contextualized problem-solving increases motivation and a sense of accomplishment (Güth & van Vorst, 2024 ). It highlights intrinsic motivation, which strengthens when students see learning as relevant to personal goals (Lin & Wang, 2021 ). However, PSA3, which presents numerous complex problems, does not significantly relate to ASE, possibly due to excessive difficulty lowering confidence (Beckmann et al., 2017 ; Pelánek et al., 2022 ). Cognitive load theory explains that overwhelming tasks divert cognitive resources from problem-solving (Chen et al., 2023 ; Hanham et al., 2023 ; Sweller, 2011 ). PSA4, which emphasizes hands-on practice, significantly improves the ability to connect ideas (ASE2). Practical application helps integrate theoretical concepts into solutions, enhancing confidence (Shanta, 2022 ; Shanta & Wells, 2022 ). However, its limited relation to other ASE aspects suggests a need for more varied and in-depth practices. PSA5, which applies knowledge to real problems, has related most ASE aspects (ASE1, ASE3, ASE4, ASE5), reinforcing that practical application boosts confidence in constructing explanations, staying calm under pressure, generating ideas, and achieving success (Dignath & Veenman, 2021 ; Shana & Abulibdeh, 2020 ). Different learning environments influence how PSAs affect ASE. In multimedia-based learning, PSA2 and PSA5 enhance idea connection and generation, supporting the notion that multimedia aids comprehension and engagement (Çeken & Taşkın, 2022 ; Noetel et al., 2022 ; VanUitert et al., 2024 ). In culturally responsive learning, PSA2, PSA4, and PSA5 help students integrate and apply knowledge, highlighting the role of culturally relevant pedagogy in engagement and confidence (Tanase, 2022 ). Recognizing students' cultural backgrounds enhances their ability to connect learning to experiences (Wallace et al., 2022 ). In differentiated learning, PSA1, PSA2, PSA4, and PSA5 significantly relate to ASE, showing that personalized instruction improves academic outcomes. Tailoring teaching to students' needs fosters inclusivity and cognitive development (Handa, 2019 ; Thapliyal et al., 2022 ). Game-based learning has a more focused relation, with PSA3 and PSA5 helping students stay calm while generating knowledge. Game elements create a low-pressure environment for experimentation, resilience, and confidence (Chase et al., 2021 ; Govender & Arnedo-Moreno, 2021 ). However, balancing entertainment and cognitive engagement is crucial (Jääskä & Aaltonen, 2022 ). This study underscores the importance of relevant, practical problem-solving activities in fostering ASE. Tailored teaching strategies that align with students' contexts maximize these benefits, contributing to the broader discourse on learning environments by illustrating the complex relationship between instructional design and student confidence. 4.1. Theoretical and Practical Implications Theoretically, this study adds to the growing literature on learning environments by showing how contextualized and relevant problem-solving activities significantly enhance academic self-efficacy. While existing research acknowledges the benefits of problem-solving in education, this study specifically addresses the variation in efficacy across different learning approaches. It demonstrates the need to balance task complexity with student readiness, as overly difficult challenges can hinder learning and reduce confidence. The study also highlights the importance of multimedia, culturally responsive, and differentiated learning environments in facilitating the development of academic self-efficacy, thus expanding the understanding of how different instructional designs can be optimized to meet diverse student needs. Practically, the findings suggest that educators should focus on designing learning environments that incorporate real-world problem-solving tasks aligned with students' abilities and cultural contexts. Problem-solving activities relevant to students' personal experiences, such as PSA1 and PSA2, are particularly effective in enhancing self-efficacy, while multimedia elements can support the comprehension of abstract concepts. Teachers should carefully manage the complexity of problem-solving tasks to ensure that students are challenged but not overwhelmed. Furthermore, differentiated instruction adapts learning strategies to individual student needs, promotes inclusivity, and fosters academic confidence across diverse student populations. 4.2. Implications for Indonesian Pedagogy This study has important implications for Indonesian education, which faces diverse social, economic, and cultural challenges. Integrating problem-solving activities focused on local and real-life contexts can make learning more relevant, engaging, and effective in enhancing motivation and self-efficacy. Culturally responsive learning can leverage Indonesia's diversity by incorporating local values, fostering identity and connection to the material. Technology and multimedia-based learning can enhance interactivity and engagement, broadening access to resources and improving digital skills essential in today’s world. Differentiated learning promotes inclusivity by addressing individual needs and reducing achievement gaps. Game-based education, while not equally influencing all aspects of self-efficacy, fosters resilience—an essential trait for navigating life’s complexities in Indonesia’s diverse society. By effectively implementing these strategies, Indonesian education can become more inclusive, relevant, and responsive, ultimately improving quality and preparing students for an interconnected world. 5. Conclusion This study highlights the relationship between problem-solving activities and students' self-efficacy. The findings show that relevant, contextualized problem-solving activities significantly boost academic self-efficacy, while overly complex challenges can hinder learning. The study also identifies variations in effectiveness across different learning approaches, including multimedia, culturally responsive, differentiated, and game-based strategies, emphasizing the need for tailored teaching methods. However, this study has limitations. The sample, limited to high school students in Indonesia, may affect generalizability. The cross-sectional design requires caution in interpreting results, and factors like cultural background and urban-rural differences were not addressed. Future research should include longitudinal studies to examine long-term effects, experimental studies to assess intervention effectiveness, and cross-cultural research to explore how cultural factors shape student responses. Additionally, further investigation into the role of technology and media in supporting problem-solving activities could offer valuable insights for more inclusive educational practices. Declarations Ethical approval The study received ethical clearance from the Ethics Committee of Universitas Negeri Padang. All procedures were performed in accordance with the relevant guidelines and regulations. Consent to participate Written informed consent was obtained from all participants and their parents or legal guardians prior to participation. Participation was voluntary and anonymous. Consent to publish The authors affirm that human research participants and their legal guardians provided informed consent for the publication of anonymized data from this study. Availability of data and materials Data will be made available on reasonable request. Competing Interests The author declares no conflict of interest. Funding Not applicable. Author's Contribution Muhammad Aizri Fadillah: Conceptualization, Methodology, Formal analysis, Investigation, Writing – original draft Muhammad Fazlan Akbar: Formal analysis, Investigation, Writing – original draft Yul Ifda Tanjung: Formal analysis, Writing – original draft Sahyar: Methodology, Writing – review and editing Usmeldi: Methodology, Writing – review and editing. Acknowledgements We would like to thank the Institute of Research and Community Service of Universitas Negeri Padang and Universitas Negeri Medan for providing support for this research. We would also like to thank Ms. Febry Azmiana and Ms. Sindy Puspita for helping distribute our survey to the target population. References Agustina, R. D., Minan Chusni, M., & Ijharudin, M. (2019). Efficacy and potential of physics education students in mathematical physics subject. Journal of Physics: Conference Series , 1175 , 012178. https://doi.org/10.1088/1742-6596/1175/1/012178 Almulla, M. A., & Al-Rahmi, W. M. (2023). Integrated Social Cognitive Theory with Learning Input Factors: The Effects of Problem-Solving Skills and Critical Thinking Skills on Learning Performance Sustainability. Sustainability , 15 (5), 3978. https://doi.org/10.3390/su15053978 Alt, D. (2015). Assessing the contribution of a constructivist learning environment to academic self-efficacy in higher education. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6861099","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":485863254,"identity":"54f6da00-185a-4678-9222-a7bef81f2240","order_by":0,"name":"Muhammad Aizri Fadillah","email":"","orcid":"","institution":"Universitas Negeri Padang","correspondingAuthor":false,"prefix":"","firstName":"Muhammad","middleName":"Aizri","lastName":"Fadillah","suffix":""},{"id":485863255,"identity":"fbaea131-47b1-4b8a-899f-6488e78c83c4","order_by":1,"name":"Muhammad Fazlan Akbar","email":"","orcid":"","institution":"Universitas Negeri Medan","correspondingAuthor":false,"prefix":"","firstName":"Muhammad","middleName":"Fazlan","lastName":"Akbar","suffix":""},{"id":485863256,"identity":"4ac27760-17aa-4ec4-815f-5b1bf9a4b696","order_by":2,"name":"Yul Ifda Tanjung","email":"","orcid":"","institution":"Universitas Negeri Medan","correspondingAuthor":false,"prefix":"","firstName":"Yul","middleName":"Ifda","lastName":"Tanjung","suffix":""},{"id":485863257,"identity":"715a536e-fbe1-4df9-8d2a-e68d832fd712","order_by":3,"name":"Sahyar Sahyar","email":"","orcid":"","institution":"Universitas Negeri Medan","correspondingAuthor":false,"prefix":"","firstName":"Sahyar","middleName":"","lastName":"Sahyar","suffix":""},{"id":485863258,"identity":"aca663de-39db-49a4-a4d0-5661238acec7","order_by":4,"name":"Usmeldi Usmeldi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA00lEQVRIiWNgGAWjYLCCB2wScuwNcC5jgwRBLQlsEsY8x0jUwpDYcwxJAK8Wg/OnEx8klFmk98g3sEkX7mCQ529gbryBV8uN3M0GCeckcnvYGNikZ55hMJxxgLHZAr8W3m0SiW0SuftBWnjbGBg3MDC2EXDY2e0/gFrSeaBa7AlrOZC7jQGoJQGmJZGgFkmgXySAfjHsYUtstuY9I5E84zABv/CdP7vxw4eyOnke5sMHb/PusLHtb29/iDfEkABjAyQSmYlUD9c1CkbBKBgFowADAAB/BEHQ37afBQAAAABJRU5ErkJggg==","orcid":"","institution":"Universitas Negeri Padang","correspondingAuthor":true,"prefix":"","firstName":"Usmeldi","middleName":"","lastName":"Usmeldi","suffix":""}],"badges":[],"createdAt":"2025-06-10 08:53:34","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6861099/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6861099/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86933565,"identity":"f3f1fa43-44be-41ec-b616-a0be8e02bea7","added_by":"auto","created_at":"2025-07-17 10:11:54","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":130113,"visible":true,"origin":"","legend":"\u003cp\u003ePlots of standardized residuals with academic self-efficacy (ASE) as the dependent variable: a) P-P plot, and b) Scatterplot\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6861099/v1/077326c8af1418e9f92b0873.png"},{"id":92406341,"identity":"f9abfe9e-50d9-4d70-b0e9-b87bd1da2f6c","added_by":"auto","created_at":"2025-09-29 11:17:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1472292,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6861099/v1/a5c39acd-a39c-419a-b5df-a0de9a188745.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"How diverse learning approaches relate to classroom problem-solving activities and academic self-efficacy","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eProblem-solving is a critical 21st-century skill for navigating global transformations and enhancing cognitive abilities, metacognition, and collaborative skills (G\u0026uuml;ner \u0026amp; Erbay, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In educational contexts, it promotes understanding complex concepts by analyzing everyday phenomena (Husin et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), particularly in scientific disciplines requiring visualizations, mathematical reasoning, and conceptual comprehension (Ince, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). However, many students find these subjects challenging (Argaw et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Problem-solving demands intensive cognitive engagement and is key to developing science process skills and influencing learning efficacy (Husin et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eResearch highlights the benefits of problem-solving as a pedagogical strategy, including enhanced scientific knowledge, reasoning (Cheng et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), critical thinking (Xu et al., \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), self-efficacy (Fitriani et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), knowledge construction (Hwang \u0026amp; Chen, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and academic achievement (Aslan, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). It also improves learning performance (Almulla \u0026amp; Al-Rahmi, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), scientific writing skills (Sari et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and overall student outcomes (Harefa \u0026amp; Purba, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDespite these findings, a gap exists in understanding how specific classroom problem-solving activities contribute to student efficacy, particularly in diverse learning environments. While studies have explored the general relationship between problem-solving and self-efficacy (Gunawan et al., 2019; Jung et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Zulkosky, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), the mechanisms of specific activities remain underexplored. For example, Evans et al. (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) examined lateral thinking self-efficacy in mathematics, but broader implications for diverse educational contexts are lacking.\u003c/p\u003e\u003cp\u003eAdditionally, while instructional approaches like differentiated instruction (Lai et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and integrated Problem-Based Learning (PBL) have been linked to improved self-efficacy (Fıtrıanı et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), the role of individual problem-solving activities within these approaches is insufficiently studied. Alt (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) suggests that constructivist learning environments enhance academic self-efficacy, but further exploration of problem-solving activities is needed.\u003c/p\u003e\u003cp\u003eThis study addresses this gap by investigating how specific problem-solving activities within diverse learning approaches impact student efficacy in Indonesian high schools. It seeks to answer: (1) What is the relationship between problem-solving activities and academic self-efficacy? and (2) How does this relationship vary across different learning approaches? By exploring these questions, the study contributes to understanding how pedagogical structures influence student outcomes, offering insights for designing learning environments that enhance self-efficacy and academic success.\u003c/p\u003e\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\u003ch2\u003e1.1. Problem-Solving and Academic Self-Efficacy\u003c/h2\u003e\u003cp\u003eProblem-solving is a critical 21st-century skill, serving as a learning objective, teaching method, and skill (van Merri\u0026euml;nboer, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). It is both an outcome and a process embedded in learning (Armağan et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), developing through practice over time (van Merri\u0026euml;nboer, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Teachers significantly enhance problem-solving skills by transitioning from instructors to facilitators (Hobri et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Innovations like contextual-based flipbooks (Maynastiti et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and inquiry models integrated with advanced organizers have effectively improved these skills (Gunawan et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Collaborative tools like CPSCoach 2.0 further support problem-solving (D\u0026rsquo;Mello et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), fostering critical thinking and confidence, key components of self-efficacy (Yustitia et al., \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eProblem-solving engages students in tasks requiring critical thinking and application of concepts, deepening understanding and equipping them with practical skills. It is central to pedagogical methods like project-based learning (PBL) and inquiry-based learning (IBL) (Husin et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Karamustafaoğlu \u0026amp; Pektaş, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), which encourage questioning, hypothesis formulation, experimentation, and conclusion drawing. These methods enhance cognitive skills, motivation, and engagement, improving learning outcomes.\u003c/p\u003e\u003cp\u003eAcademic self-efficacy refers to students' belief in their ability to succeed in academic tasks, influencing goal-setting, strategy development, and persistence (Ritchie, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Bandura (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) identified it as a key predictor of learning efficiency and motivation. Indicators such as interest, participation, and awareness measure self-efficacy, with most students falling into the moderate category (Agustina et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Learning facilities, including AI-based experiments (Cai et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and real-life learning scenarios (Semilarski et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), also contribute to self-efficacy. Zulkosky (\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) described it as encompassing affective, cognitive, and self-regulation processes, where feedback enhances affective aspects, and problem-solving strengthens cognitive development.\u003c/p\u003e\u003cp\u003eEducational approaches like differentiated instruction (Scarparolo \u0026amp; Subban, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), game-based learning (Lu \u0026amp; Lien, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), and multimedia-based learning have been shown to enhance academic self-efficacy (Huang et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Culturally responsive learning also positively impacts self-efficacy across multinational contexts (Yu et al., \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e1.2. Pedagogy in Indonesian Context\u003c/h2\u003e\u003cp\u003eIndonesia's multicultural society necessitates innovative learning models to enhance education quality and student engagement. The diverse population, with variations in religion, socio-economic status, and culture, requires an adaptable education system (Raihani, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Culturally responsive learning integrates cultural diversity into classrooms through multicultural content, varied assessments, and holistic learning experiences (Howard, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), fostering critical thinking and social awareness (Shahali et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDifferentiated instruction tailors education to individual needs, ensuring equitable learning opportunities and student development (Mills et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Tomlinson \u0026amp; Imbeau, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Innovative pedagogies like multimedia-based learning promote self-regulation, problem-solving, and conceptual understanding (Suhandi et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), while game-based learning enhances engagement and cognitive, affective, and problem-solving skills (Dewantara et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Pratama \u0026amp; Setyaningrum, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Putranta et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eChai et al.'s (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) authentic problem-solving activity scale integrates real-world, unstructured problems into learning. It is particularly relevant in Indonesia's multicultural context. The scale engages students in exploring causes and solutions to issues like water shortages and environmental concerns, strengthening problem-solving skills and enhancing self-efficacy and learning outcomes.\u003c/p\u003e\u003c/div\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Participants\u003c/h2\u003e\u003cp\u003eThis study employed a quantitative approach with a survey research design to collect data from high school students in Indonesia, which was distributed online via social media platforms, such as WhatsApp. We used the convenience sampling method to select respondents based on their availability and willingness to participate. This non-probability sampling method was used due to the vast number, diversity, and geographical dispersion of high schools across Indonesia, which made it challenging to apply a representative sampling approach. This method was chosen because it allows for quick and easy collection of data from a large number of participants who are readily accessible (Etikan, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the demographic information of the 458 students (ages 15\u0026ndash;18) from high schools in Indonesia who participated in this study. The sample included 156 males (34.06%) and 302 females (65.94%). Most students reported that their teachers used a differentiated learning approach (70.09%). Other reported approaches included multimedia-based learning (8.52%), culturally responsive learning (11.35%), and game-based learning (5.68%). Additionally, 4.37% of students reported other approaches that were not explicitly mentioned.\u003c/p\u003e\u003cp\u003e It is important to note that research used ethical guidelines to safeguard participants' rights and well-being. Before participation, respondents received comprehensive information about the study, including its purpose, procedures, and potential risks or benefits. Informed consent was obtained electronically, ensuring that participants voluntarily agreed to participate and that their responses would remain anonymous for research purposes. No personally identifiable information (PII) was collected, and all data were securely stored to maintain confidentiality. The study received ethical approval from the institutional ethics review board. Furthermore, participants were informed of their right to withdraw from the study without facing any consequences.\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\u003eDemographic Information\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=\"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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDemographic (n\u0026thinsp;=\u0026thinsp;458)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNumber\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\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e156 (34.06%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e302 (65.94%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eWhat learning approaches does your teacher use that you know of?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMultimedia-based\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e39 (8.52%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCulturally responsive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e52 (11.35%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDifferentiated\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e321 (70.09%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGame-based\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e26 (5.68%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOthers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e20 (4.37%)\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=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Measures\u003c/h2\u003e\u003cp\u003eThe study included constructs about students' perceptions of the learning process, adopted from previous research: problem-solving activities (Chai et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) and academic self-efficacy (van Zyl et al., \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). We used a 5-point Likert scale ranging from \"Strongly disagree\" to \"Strongly agree\" to facilitate easy and accurate responses (Taherdoost, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e displays the validation of each measurement item. All items have factor loadings above 0.50 (Hair et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Cronbach's alpha (CA) and composite reliability (CR) for all measures exceed 0.80, and the average variance extracted (AVE) is above 0.50, indicating excellent criteria (Hair et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). It confirms the reliability and validity of the data, ensuring credible measurement scales in this study.\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\u003eMeasurements\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=\"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=\"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\u003cp\u003eScales\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCode\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eItems\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLoading\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCA\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eCR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eAVE\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eProblem-solving activity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePSA1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIn class, I investigate the reasons that cause problems in the real world\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.777\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.805\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.865\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.563\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePSA2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIn class, I learn about real-life problems that people experience\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.761\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=\"c2\"\u003e\u003cp\u003ePSA3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIn class, I am challenged by many real-world problems (e.g. water shortages, racial harmony, environmental issues)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.635\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=\"c2\"\u003e\u003cp\u003ePSA4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIn class, I practiced solving real-world problems\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.778\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\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePSA5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIn class, I apply my knowledge to solve real-life problems\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.790\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\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eAcademic self-efficacy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eASE1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI generally manage to build explanations/theories about issues I study if I try hard enough\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.722\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.814\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.871\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.575\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eASE2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI know I can connect different ideas to form new ideas in my field of study\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.774\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\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eASE3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI will remain calm while creating useful knowledge on my own because I know I have the capability to do it\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.761\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\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eASE4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI know I can generate new ideas about what I study if I put in enough work\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.813\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\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eASE5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eThe motto 'if others can, I can too' applies to me when it comes to designing things that might be useful\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.717\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\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Non-Response Bias\u003c/h2\u003e\u003cp\u003eWe also tested for non-response bias, as cross-sectional studies can have this bias. This bias is usually addressed by comparing answers from early and late respondents (Fadillah et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). We compared the first 50 respondents and the last 50 respondents for each item using a \u003cem\u003et\u003c/em\u003e-test. The results showed that the \u003cem\u003ep\u003c/em\u003e-values ranged from 0.261 to 0.845, meaning there was no significant difference between the two groups (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), so there was no substantial non-response bias.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.4. Checking Assumptions for Analysis\u003c/h2\u003e\u003cp\u003eBefore the primary analysis, key assumptions\u0026mdash;normality, homoscedasticity, and multicollinearity\u0026mdash;were tested to ensure model validity. These tests used cumulative mean scores of problem-solving activity and academic self-efficacy scales. Given that the sample size exceeded 50, normality was assessed using skewness and kurtosis values instead of Kolmogorov-Smirnov or Shapiro-Wilk tests, which are better suited for small samples (Hong et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Data are normally distributed if skewness is between \u0026minus;\u0026thinsp;2 and +\u0026thinsp;2 and kurtosis between \u0026minus;\u0026thinsp;7 and +\u0026thinsp;7 (Byrne, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Hair et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The results showed PSA skewness, kurtosis of 0.130 and 0.072, and ASE values of 0.353 and 0.210, confirming normality. Homoscedasticity was tested using a P-P plot and residual scatterplot with ASE as the dependent variable (Hong et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The P-P plot showed residuals aligning with the diagonal line (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.a), and the scatterplot displayed no distinct pattern (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.b), confirming homoscedasticity. Using tolerance and variance inflation factor (VIF) values, multicollinearity was examined, where tolerance above 0.1 and VIF below 10 indicate no multicollinearity issues (Field, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Hair et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The tolerance and VIF values for PSA and ASE were 1.000, confirming the absence of multicollinearity and validating the model for further analysis.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e\u003cb\u003e2.5. Implementation of Regression Analysis\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eThe treatment of ordinal data, such as Likert-scale responses, as continuous is debated. However, research supports this under certain conditions. Norman (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) argues that if data distribution is approximately normal and response categories are sufficient, Likert-scale data can be treated as interval data for parametric analysis. Harpe (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) also notes that this is often valid, as ordinal data rarely affects parametric test reliability.\u003c/p\u003e\u003cp\u003eTo confirm suitability, we examined data distribution, as detailed in \"Checking Assumptions for Analysis.\" The results showed approximate normality, justifying the treatment of Likert-scale items as continuous in regression analysis. Norman (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) emphasizes that parametric methods like regression and ANOVA are robust to minor violations of normality and remain effective even for ordinal data. Harpe (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) notes that while some researchers prefer ordinal-based methods, parametric approaches are valid if the sample size is large and the data distribution is symmetrical. Non-parametric methods remain an alternative if ordinal data poses concerns.\u003c/p\u003e\u003cp\u003eAlthough Norman and Harpe support parametric methods, we acknowledge that Likert-scale data are inherently ordinal. However, given statistical evidence and data characteristics, regression analysis is appropriate. We used multiple linear regression (univariate) with the ENTER model to examine the relationship between problem-solving activities and self-efficacy. The ENTER model enters all predictors simultaneously to assess their contributions while controlling for other variables (Field, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Analysis was conducted using SPSS V.26 to determine significance, including coefficient (B) for effect size and standard error (SE) for uncertainty.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.1. Descriptive Information\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents descriptive data for each item across different learning approaches, showing mean and standard deviation values overall and by approach. The learning approaches include multimedia-based, culturally responsive, differentiated, game-based, and others. The sample consists of 458 respondents, with subgroups: multimedia-based (39), culturally responsive (52), differentiated (321), game-based (26), and other (20).\u003c/p\u003e\u003cp\u003ePSA5, \"In class, I apply my knowledge to solve real-life problems,\" had the highest mean for problem-solving activities overall (M\u0026thinsp;=\u0026thinsp;3.35, SD\u0026thinsp;=\u0026thinsp;0.969) and in multimedia (M\u0026thinsp;=\u0026thinsp;3.85, SD\u0026thinsp;=\u0026thinsp;0.844), culturally responsive (M\u0026thinsp;=\u0026thinsp;3.63, SD\u0026thinsp;=\u0026thinsp;1.048), and differentiated (M\u0026thinsp;=\u0026thinsp;3.67, SD\u0026thinsp;=\u0026thinsp;0.868) approaches. PSA2, \"In class, I learn about real-life problems people experience,\" had the highest mean in game-based (M\u0026thinsp;=\u0026thinsp;3.65, SD\u0026thinsp;=\u0026thinsp;1.129) and other (M\u0026thinsp;=\u0026thinsp;3.60, SD\u0026thinsp;=\u0026thinsp;0.754) approaches. Overall, self-efficacy mean values ranged from 3.47 to 3.69, varying by learning approach.\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\u003eDescriptive statistics of each item: mean and standard deviation (in parentheses)\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\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eItems\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eOverall\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;458)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"5\" nameend=\"c7\" namest=\"c3\"\u003e\u003cp\u003eLearning approach\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eMultimedia\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e(n\u0026thinsp;=\u0026thinsp;39)\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003eCulturally responsive\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e(n\u0026thinsp;=\u0026thinsp;52)\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003eDifferentiated\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e(n\u0026thinsp;=\u0026thinsp;321)\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003eGame-based\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e(n\u0026thinsp;=\u0026thinsp;26)\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003eOthers\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e(n\u0026thinsp;=\u0026thinsp;20)\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.35 (0.969)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.54 (0.969)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.17 (1.216)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.37 (0.916)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.38 (0.941)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.20 (1.105)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.64 (0.974)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.74 (1.019)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.46 (1.146)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.65 (0.940)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.65 (1.129)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.60 (0.754)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.25 (1.183)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.74 (1.229)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.10 (1.317)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.22 (1.139)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.15 (1.287)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.20 (1.152)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.51 (0.934)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.67 (0.955)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.52 (1.111)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.49 (0.909)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.62 (0.804)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.50 (1.000)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.67 (0.900)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.85 (0.844)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.63 (1.048)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.67 (0.868)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.58 (0.945)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.45 (1.050)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eASE1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.47 (0.816)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.62 (0.815)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.54 (0.999)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.46 (0.774)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.35 (0.936)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.20 (0.768)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eASE2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.57 (0.829)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.67 (0.869)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.63 (0.971)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.55 (0.793)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.38 (0.983)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.65 (0.745)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eASE3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.46 (0.872)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.62 (0.747)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.48 (1.057)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.45 (0.872)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.50 (0.812)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.35 (0.671)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eASE4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.58 (0.801)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.82 (0.790)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.62 (0.889)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.55 (0.769)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.50 (1.068)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.65 (0.671)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eASE5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.69 (0.819)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.74 (0.751)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.85 (0.998)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.66 (0.798)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.50 (0.906)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.80 (0.616)\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\u003e3.2. The Relationship Between Problem-Solving Activities and Academic Self-Efficacy\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e presents multiple linear regression results on problem-solving activities and academic self-efficacy. PSA1, which involves investigating real-world problems, significantly relates all aspects of academic self-efficacy: constructing explanations (ASE1) (B\u0026thinsp;=\u0026thinsp;0.209, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), connecting ideas (ASE2) (B\u0026thinsp;=\u0026thinsp;0.113, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), staying calm while creating knowledge (ASE3) (B\u0026thinsp;=\u0026thinsp;0.130, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), generating new ideas (ASE4) (B\u0026thinsp;=\u0026thinsp;0.147, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and believing \"if others can, I can too\" (ASE5) (B\u0026thinsp;=\u0026thinsp;0.133, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). PSA2, which focuses on real-life problems, significantly relates ASE2 (B\u0026thinsp;=\u0026thinsp;0.107, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and ASE5 (B\u0026thinsp;=\u0026thinsp;0.103, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). PSA3 presents multiple complex problems with no significant relation (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). PSA4, involving hands-on problem-solving, is significant for ASE2 (B\u0026thinsp;=\u0026thinsp;0.229, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). PSA5, applying knowledge to solve real problems, strongly significant ASE1 (B\u0026thinsp;=\u0026thinsp;0.313, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), ASE3 (B\u0026thinsp;=\u0026thinsp;0.193, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), ASE4 (B\u0026thinsp;=\u0026thinsp;0.208, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and ASE5 (B\u0026thinsp;=\u0026thinsp;0.217, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\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\u003eOverall results of the multiple linear regression approach\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"11\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eItems\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eASE1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eASE2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eASE3\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003eASE4\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003eASE5\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eB\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eSE\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003eB\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003eSE\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003eB\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003eSE\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003eB\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003eSE\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u003cb\u003eB\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003e\u003cb\u003eSE\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.209\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.043\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.113\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.046\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.130\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.050\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.147\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.046\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.133\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.047\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.026\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.042\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.107\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.046\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.055\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.049\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.045\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.103\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.046\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.052\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.031\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.064\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.034\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.036\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.030\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.033\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e-0.010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.034\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.054\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.045\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.229\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.049\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.082\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.052\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.041\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.048\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e-0.020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.049\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.313\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.047\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.087\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.051\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.193\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.054\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.208\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.050\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.217\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.051\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"11\"\u003eNote: \u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, \u003csup\u003e\u003cb\u003e**\u003c/b\u003e\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, \u003csup\u003e\u003cb\u003e***\u003c/b\u003e\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.3. The Relationship Between Problem-Solving Activities and Academic Self-Efficacy with Various Approaches\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e presents the relationship between problem-solving activities and academic self-efficacy across different learning approaches. In multimedia-based learning, PSA1 and PSA4 were not significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), while PSA2 was significant for ASE4 (B\u0026thinsp;=\u0026thinsp;0.324, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). PSA3 was significant but negative for ASE2 (B = -0.292, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). PSA5 showed significance for ASE2 (B\u0026thinsp;=\u0026thinsp;0.380, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), ASE3 (B\u0026thinsp;=\u0026thinsp;0.649, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), ASE4 (B\u0026thinsp;=\u0026thinsp;0.569, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and ASE5 (B\u0026thinsp;=\u0026thinsp;0.429, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In culturally responsive learning, PSA1 was not significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). PSA2 was significant for ASE1 (B\u0026thinsp;=\u0026thinsp;0.324, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while PSA3 was significant but negative for ASE1 (B = -0.235, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). PSA4 was significant for ASE1 (B\u0026thinsp;=\u0026thinsp;0.417, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and ASE2 (B\u0026thinsp;=\u0026thinsp;0.438, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). PSA5 was significant for ASE4 (B\u0026thinsp;=\u0026thinsp;0.451, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and ASE5 (B\u0026thinsp;=\u0026thinsp;0.537, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). In differentiated learning, PSA1 was significant for ASE1 (B\u0026thinsp;=\u0026thinsp;0.251, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), ASE3 (B\u0026thinsp;=\u0026thinsp;0.152, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), ASE4 (B\u0026thinsp;=\u0026thinsp;0.151, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and ASE5 (B\u0026thinsp;=\u0026thinsp;0.132, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while PSA2 was significant for ASE2 (B\u0026thinsp;=\u0026thinsp;0.108, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and ASE5 (B\u0026thinsp;=\u0026thinsp;0.152, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). PSA3 was not significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), but PSA4 was significant for ASE2 (B\u0026thinsp;=\u0026thinsp;0.208, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). PSA5 was significant for ASE1 (B\u0026thinsp;=\u0026thinsp;0.320, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), ASE4 (B\u0026thinsp;=\u0026thinsp;0.135, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and ASE5 (B\u0026thinsp;=\u0026thinsp;0.170, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). In game-based learning, PSA1, PSA2, and PSA4 were not significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). However, PSA3 was significant for ASE4 (B\u0026thinsp;=\u0026thinsp;0.358, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and PSA5 was significant for ASE1 (B\u0026thinsp;=\u0026thinsp;0.546, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and ASE3 (B\u0026thinsp;=\u0026thinsp;0.463, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\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\u003eResults of multiple linear regression approach based on various learning approaches\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"11\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eItems\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eASE1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eASE2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eASE3\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003eASE4\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003eASE5\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eB\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eB\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eB\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eB\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eB\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eMultimedia\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.141\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.156\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.265\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.149\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.029\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.128\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.048\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.119\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.226\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.145\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.110\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.177\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.230\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.169\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.270\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.145\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.324\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.134\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.206\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.164\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.207\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.114\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.292\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.109\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.093\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.157\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.086\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.076\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.106\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA4\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\u003e0.243\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.208\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.232\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.208\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.199\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-0.258\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.184\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e-0.244\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.225\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.207\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.167\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.380\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.159\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.649\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.137\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.569\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.127\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.429\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.155\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCulturally responsive\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\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.119\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.173\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.116\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.176\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.062\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.219\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.208\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.139\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e-0.060\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.169\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.324\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.143\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.184\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.145\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.181\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-0.076\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.115\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.061\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.139\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.235\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.114\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.192\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.116\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.144\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-0.033\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.091\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e-0.071\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.111\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.417\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.142\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.438\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.145\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.163\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.068\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.114\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.206\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.139\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.241\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.162\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.239\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.165\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.243\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.205\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.451\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.130\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.537\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.158\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDifferentiated\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\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.251\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.049\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.092\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.054\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.152\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.060\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.151\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.054\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.132\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.055\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.026\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.049\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.108\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.055\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.049\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.061\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-0.009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.055\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.152\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.056\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.036\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.033\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.040\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.035\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.044\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-0.028\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.040\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e-0.037\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.041\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.053\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.208\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.059\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.098\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.065\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.079\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.059\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e-0.042\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.060\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.320\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.056\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.052\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.062\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.133\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.069\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.135\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.062\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.170\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.063\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGame-based\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\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.271\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.203\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.518\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.273\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.092\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.198\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.086\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.279\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.452\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.253\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.160\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.164\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.215\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.204\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.156\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-0.020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.220\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e-0.252\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.199\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.136\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.123\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.153\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.165\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.193\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.120\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.358\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.169\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.263\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.153\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.219\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.194\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.262\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.087\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.190\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-0.372\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.267\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e-0.178\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.242\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.546\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.196\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.148\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.264\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.463\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.192\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.457\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.270\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.113\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.245\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eOthers\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\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.078\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.298\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.122\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.242\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.148\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.249\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.038\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.263\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.036\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.242\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.298\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.221\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.242\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.170\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.249\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-0.009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.263\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e-0.023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.242\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.117\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.199\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.096\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.162\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.082\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.166\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.307\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.175\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.295\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.162\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.228\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.356\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.411\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.289\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.080\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.297\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-0.155\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.314\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e-0.166\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.289\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSA5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.150\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.210\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.265\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.171\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.121\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.175\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-0.175\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.185\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e-0.079\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.171\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"11\"\u003eNote: \u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, \u003csup\u003e\u003cb\u003e**\u003c/b\u003e\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, \u003csup\u003e\u003cb\u003e***\u003c/b\u003e\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussions","content":"\u003cp\u003eThis study reveals key findings on the relationship between problem-solving activities and academic self-efficacy, offering insights for effective learning design. PSA1, which involves investigating real-world problems, significantly enhances all aspects of ASE, indicating that engaging with real-world contexts builds student confidence. Analyzing real problems helps students construct explanations, connect ideas, and manage cognitive challenges (Sarathy, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Schoenherr, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). It aligns with constructivist theory, which suggests that learning is more meaningful when students relate new knowledge to prior experiences, boosting motivation and self-efficacy (Andresen et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePSA2, which focuses on real-life problems, enhances students' ability to connect ideas and believe in their potential (ASE2, ASE5). Contextualized problem-solving increases motivation and a sense of accomplishment (G\u0026uuml;th \u0026amp; van Vorst, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). It highlights intrinsic motivation, which strengthens when students see learning as relevant to personal goals (Lin \u0026amp; Wang, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, PSA3, which presents numerous complex problems, does not significantly relate to ASE, possibly due to excessive difficulty lowering confidence (Beckmann et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Pel\u0026aacute;nek et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Cognitive load theory explains that overwhelming tasks divert cognitive resources from problem-solving (Chen et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Hanham et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Sweller, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePSA4, which emphasizes hands-on practice, significantly improves the ability to connect ideas (ASE2). Practical application helps integrate theoretical concepts into solutions, enhancing confidence (Shanta, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Shanta \u0026amp; Wells, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, its limited relation to other ASE aspects suggests a need for more varied and in-depth practices. PSA5, which applies knowledge to real problems, has related most ASE aspects (ASE1, ASE3, ASE4, ASE5), reinforcing that practical application boosts confidence in constructing explanations, staying calm under pressure, generating ideas, and achieving success (Dignath \u0026amp; Veenman, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Shana \u0026amp; Abulibdeh, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDifferent learning environments influence how PSAs affect ASE. In multimedia-based learning, PSA2 and PSA5 enhance idea connection and generation, supporting the notion that multimedia aids comprehension and engagement (\u0026Ccedil;eken \u0026amp; Taşkın, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Noetel et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; VanUitert et al., \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In culturally responsive learning, PSA2, PSA4, and PSA5 help students integrate and apply knowledge, highlighting the role of culturally relevant pedagogy in engagement and confidence (Tanase, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Recognizing students' cultural backgrounds enhances their ability to connect learning to experiences (Wallace et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn differentiated learning, PSA1, PSA2, PSA4, and PSA5 significantly relate to ASE, showing that personalized instruction improves academic outcomes. Tailoring teaching to students' needs fosters inclusivity and cognitive development (Handa, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Thapliyal et al., \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Game-based learning has a more focused relation, with PSA3 and PSA5 helping students stay calm while generating knowledge. Game elements create a low-pressure environment for experimentation, resilience, and confidence (Chase et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Govender \u0026amp; Arnedo-Moreno, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, balancing entertainment and cognitive engagement is crucial (J\u0026auml;\u0026auml;sk\u0026auml; \u0026amp; Aaltonen, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThis study underscores the importance of relevant, practical problem-solving activities in fostering ASE. Tailored teaching strategies that align with students' contexts maximize these benefits, contributing to the broader discourse on learning environments by illustrating the complex relationship between instructional design and student confidence.\u003c/p\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e4.1. Theoretical and Practical Implications\u003c/h2\u003e\u003cp\u003eTheoretically, this study adds to the growing literature on learning environments by showing how contextualized and relevant problem-solving activities significantly enhance academic self-efficacy. While existing research acknowledges the benefits of problem-solving in education, this study specifically addresses the variation in efficacy across different learning approaches. It demonstrates the need to balance task complexity with student readiness, as overly difficult challenges can hinder learning and reduce confidence. The study also highlights the importance of multimedia, culturally responsive, and differentiated learning environments in facilitating the development of academic self-efficacy, thus expanding the understanding of how different instructional designs can be optimized to meet diverse student needs.\u003c/p\u003e\u003cp\u003ePractically, the findings suggest that educators should focus on designing learning environments that incorporate real-world problem-solving tasks aligned with students' abilities and cultural contexts. Problem-solving activities relevant to students' personal experiences, such as PSA1 and PSA2, are particularly effective in enhancing self-efficacy, while multimedia elements can support the comprehension of abstract concepts. Teachers should carefully manage the complexity of problem-solving tasks to ensure that students are challenged but not overwhelmed. Furthermore, differentiated instruction adapts learning strategies to individual student needs, promotes inclusivity, and fosters academic confidence across diverse student populations.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e4.2. Implications for Indonesian Pedagogy\u003c/h2\u003e\u003cp\u003eThis study has important implications for Indonesian education, which faces diverse social, economic, and cultural challenges. Integrating problem-solving activities focused on local and real-life contexts can make learning more relevant, engaging, and effective in enhancing motivation and self-efficacy. Culturally responsive learning can leverage Indonesia's diversity by incorporating local values, fostering identity and connection to the material. Technology and multimedia-based learning can enhance interactivity and engagement, broadening access to resources and improving digital skills essential in today\u0026rsquo;s world. Differentiated learning promotes inclusivity by addressing individual needs and reducing achievement gaps. Game-based education, while not equally influencing all aspects of self-efficacy, fosters resilience\u0026mdash;an essential trait for navigating life\u0026rsquo;s complexities in Indonesia\u0026rsquo;s diverse society. By effectively implementing these strategies, Indonesian education can become more inclusive, relevant, and responsive, ultimately improving quality and preparing students for an interconnected world.\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study highlights the relationship between problem-solving activities and students' self-efficacy. The findings show that relevant, contextualized problem-solving activities significantly boost academic self-efficacy, while overly complex challenges can hinder learning. The study also identifies variations in effectiveness across different learning approaches, including multimedia, culturally responsive, differentiated, and game-based strategies, emphasizing the need for tailored teaching methods. However, this study has limitations. The sample, limited to high school students in Indonesia, may affect generalizability. The cross-sectional design requires caution in interpreting results, and factors like cultural background and urban-rural differences were not addressed. Future research should include longitudinal studies to examine long-term effects, experimental studies to assess intervention effectiveness, and cross-cultural research to explore how cultural factors shape student responses. Additionally, further investigation into the role of technology and media in supporting problem-solving activities could offer valuable insights for more inclusive educational practices.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study received ethical clearance from the Ethics Committee of Universitas Negeri Padang. All procedures were performed in accordance with the relevant guidelines and regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWritten informed consent was obtained from all participants and their parents or legal guardians prior to participation. Participation was voluntary and anonymous.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors affirm that human research participants and their legal guardians provided informed consent for the publication of anonymized data from this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData will be made available on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author declares no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor's Contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMuhammad Aizri Fadillah: Conceptualization, Methodology, Formal analysis, Investigation, Writing – original draft\u003c/p\u003e\n\u003cp\u003eMuhammad Fazlan Akbar: Formal analysis, Investigation, Writing – original draft\u003c/p\u003e\n\u003cp\u003eYul Ifda Tanjung: Formal analysis, Writing – original draft\u003c/p\u003e\n\u003cp\u003eSahyar: Methodology, Writing – review and editing\u003c/p\u003e\n\u003cp\u003eUsmeldi: Methodology, Writing – review and editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank the Institute of Research and Community Service of Universitas Negeri Padang and Universitas Negeri Medan for providing support for this research. 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Self‐efficacy: a concept analysis. \u003cem\u003eNursing Forum\u003c/em\u003e, \u003cem\u003e44\u003c/em\u003e(2), 93\u0026ndash;102.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Problem-solving, self-efficacy, learning approaches, real-world problems, contextualized teaching strategies","lastPublishedDoi":"10.21203/rs.3.rs-6861099/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6861099/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eProblem-solving benefits are well established, yet the relationship between its activities and students' self-efficacy remains underexplored. This study examined the relationship between classroom problem-solving activities and academic self-efficacy across diverse learning approaches in Indonesia. Employed a quantitative approach with a survey research design, data from 458 high school students were analyzed using multiple linear regression. Results showed that investigating real-world problems significantly relationships all aspects of academic self-efficacy, particularly in differentiated learning. Engaging with others' real-world problems fostered the belief that \"if others can, so can I,\" notably in multimedia, culturally responsive, and differentiated learning. However, multiple real-world challenges had no significant overall relationships, except in game-based learning for idea generation. Real-world problem-solving also helped students connect ideas, especially in culturally responsive and differentiated settings. Applying knowledge to solve real problems had a strong positive relation across all learning approaches. These findings highlight the importance of contextualized teaching strategies in strengthening academic self-efficacy and contribute to the limited research on problem-solving in education.\u003c/p\u003e","manuscriptTitle":"How diverse learning approaches relate to classroom problem-solving activities and academic self-efficacy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-17 10:11:50","doi":"10.21203/rs.3.rs-6861099/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"637d2082-0b9d-45f5-9e9c-a35479baa626","owner":[],"postedDate":"July 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-29T11:08:54+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-17 10:11:50","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6861099","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6861099","identity":"rs-6861099","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}