Latest open access articles published in Education Science and Management at https://www.acadlore.com/journals/ESM https://www.acadlore.com/journals/ESM Acadlore en Creative Commons Attribution(CC - BY) ESM support@acadlore.com https://www.acadlore.com/article/ESM/2026_4_1/esm040101 The peer review process is a significant aspect of academic publishing, which shoulders the responsibility to ensure the quality and integrity of scholarly work. However, challenges such as a lack of formal peer review training, scarcity of reviewers, and bias in the selection process have posed daunting challenges. This paper explored the potential of PhD candidates and postdoctoral fellows as peer reviewers through academic partnerships with publishing houses. “AI meta-audit test case” was employed to analyze “if there exists any publishing activities, in particular peer review services, involved in academic partnerships as well as the impact of PhD candidates and postdoctoral fellows on peer review activities”. Our objective is to evaluate the extent to which PhD candidates and postdoctoral fellows contribute to academic publishing activities through peer review services facilitated by academic partnerships. The project team defined key metrics in a set scope, determined data sources, designed AI-powered analysis approach, proposed hypotheses, identified risks and challenges, and above all, provided evaluation and recommendations. The study highlights the demand for structured peer review training, incentives for early-career researchers, and institutional collaborations to enhance the quality and efficiency of peer review process. 03-18-2026 <![CDATA[ <p>The peer review process is a significant aspect of academic publishing, which shoulders the responsibility to ensure the quality and integrity of scholarly work. However, challenges such as a lack of formal peer review training, scarcity of reviewers, and bias in the selection process have posed daunting challenges. This paper explored the potential of PhD candidates and postdoctoral fellows as peer reviewers through academic partnerships with publishing houses. “AI meta-audit test case” was employed to analyze “if there exists any publishing activities, in particular peer review services, involved in academic partnerships as well as the impact of PhD candidates and postdoctoral fellows on peer review activities”. Our objective is to evaluate the extent to which PhD candidates and postdoctoral fellows contribute to academic publishing activities through peer review services facilitated by academic partnerships. The project team defined key metrics in a set scope, determined data sources, designed AI-powered analysis approach, proposed hypotheses, identified risks and challenges, and above all, provided evaluation and recommendations. The study highlights the demand for structured peer review training, incentives for early-career researchers, and institutional collaborations to enhance the quality and efficiency of peer review process.</p> ]]> AI Meta-Audit Test Case: Impact of PhD Candidates and Postdoctoral Fellows on Publishing Activities via Academic Partnerships for Peer Review Services pascal muam mah john muzam tambi daniel mbu polycap mudoh mahamane moutari abdou baoua lilian kuyiena song john akoko eric munyeshuri janet awino okello selestine john salema doi: 10.56578/esm040101 Education Science and Management 03-18-2026 Education Science and Management 03-18-2026 2026 4 1 Article 1 10.56578/esm040101 https://www.acadlore.com/article/ESM/2026_4_1/esm040101 https://www.acadlore.com/article/ESM/2025_3_3/esm030305 The aim of the present study is to evaluate the impact of the elements of Information Systems (IS) Success Model i.e., information quality, service quality, and system quality on the learners’ satisfaction with moderating role of teacher in EdTech platforms. Primary data were collected through questionnaire method from 473 students of 5th to 12th standard who were availing services of EdTech platforms. Results of the study substantiated significant positive association between IS success model constructs and learners’ satisfaction. Likewise, moderating role of teachers has been instituted between DeLone and McLean IS Success Model constructs and learners’ satisfaction. Furthermore, results established that the impact of service quality and information quality on learners’ satisfaction is enhanced in the presence of teacher whereas impact of system quality is decreased in teacher’s presence. Present study makes unique addition to the sparse literature on user’s satisfaction in e-learning environment on EdTech platforms by reintroducing the posits of the DeLone and McLean IS Success Model, 2003 and building it on the premise that teacher plays a crucial role in affecting learner’s satisfaction with system, service, and information quality. 09-29-2025 <![CDATA[ The aim of the present study is to evaluate the impact of the elements of Information Systems (IS) Success Model i.e., information quality, service quality, and system quality on the learners’ satisfaction with moderating role of teacher in EdTech platforms. Primary data were collected through questionnaire method from 473 students of 5^th to 12^th standard who were availing services of EdTech platforms. Results of the study substantiated significant positive association between IS success model constructs and learners’ satisfaction. Likewise, moderating role of teachers has been instituted between DeLone and McLean IS Success Model constructs and learners’ satisfaction. Furthermore, results established that the impact of service quality and information quality on learners’ satisfaction is enhanced in the presence of teacher whereas impact of system quality is decreased in teacher’s presence. Present study makes unique addition to the sparse literature on user’s satisfaction in e-learning environment on EdTech platforms by reintroducing the posits of the DeLone and McLean IS Success Model, 2003 and building it on the premise that teacher plays a crucial role in affecting learner’s satisfaction with system, service, and information quality. ]]> Human Touch in EdTech Learning: Does Teacher Presence Boost Satisfaction? manpreet kaur priya manchanda jinesh jain kiran sood doi: /10.56578/esm030305 Education Science and Management 09-29-2025 Education Science and Management 09-29-2025 2025 3 3 Article 194 /10.56578/esm030305 https://www.acadlore.com/article/ESM/2025_3_3/esm030305 https://www.acadlore.com/article/ESM/2025_3_3/esm030304 The rapid expansion of research on academic resilience in Indonesia has been driven by digitalization, hybrid learning, and demands for equitable quality. However, a systematic synthesis of intellectual structure, thematic evolution, collaboration networks, and scholarly impact remains absent. In this study, a comprehensive bibliometric and science mapping analysis of academic resilience research in the Indonesian context from 2000 to 2025 was conducted. Performance analysis and science mapping techniques—including co-word analysis, co-citation analysis, bibliographic coupling, thematic evolution mapping, and burst keyword detection—were integrated and visualized using VOSviewer. Records were retrieved through Publish or Perish based on Google Scholar. The findings reveal three major patterns. First, publication trends indicate a shift from predominantly psychological and pandemic-related online learning themes toward institutional and systemic concerns and culturally embedded educational practices. Second, five dominant thematic clusters were identified: individual capacities, social support, academic outcomes, institutional and learning environments, and Indonesian cultural–linguistic contexts. Third, scholarly influence is concentrated in review articles and pandemic-era empirical studies employing validated measurement scales and mechanism-based structural models. Cross-national comparative studies were found to enhance citation reach. Overall, the intellectual trajectory of academic resilience research in Indonesia is structured around a dominant explanatory pathway linking self-efficacy and support to resilience and subsequent outcomes. Substantive research gaps remain at the lecturer and organizational levels, as well as in the systematic integration of Islamic and Indonesian linguistic–cultural frameworks into resilience theory. These findings provide a systematic intellectual mapping of the field and offer a foundation for advancing contextually grounded and policy-relevant research agendas. 09-23-2025 <![CDATA[ The rapid expansion of research on academic resilience in Indonesia has been driven by digitalization, hybrid learning, and demands for equitable quality. However, a systematic synthesis of intellectual structure, thematic evolution, collaboration networks, and scholarly impact remains absent. In this study, a comprehensive bibliometric and science mapping analysis of academic resilience research in the Indonesian context from 2000 to 2025 was conducted. Performance analysis and science mapping techniques—including co-word analysis, co-citation analysis, bibliographic coupling, thematic evolution mapping, and burst keyword detection—were integrated and visualized using VOSviewer. Records were retrieved through Publish or Perish based on Google Scholar. The findings reveal three major patterns. First, publication trends indicate a shift from predominantly psychological and pandemic-related online learning themes toward institutional and systemic concerns and culturally embedded educational practices. Second, five dominant thematic clusters were identified: individual capacities, social support, academic outcomes, institutional and learning environments, and Indonesian cultural–linguistic contexts. Third, scholarly influence is concentrated in review articles and pandemic-era empirical studies employing validated measurement scales and mechanism-based structural models. Cross-national comparative studies were found to enhance citation reach. Overall, the intellectual trajectory of academic resilience research in Indonesia is structured around a dominant explanatory pathway linking self-efficacy and support to resilience and subsequent outcomes. Substantive research gaps remain at the lecturer and organizational levels, as well as in the systematic integration of Islamic and Indonesian linguistic–cultural frameworks into resilience theory. These findings provide a systematic intellectual mapping of the field and offer a foundation for advancing contextually grounded and policy-relevant research agendas. ]]> A Bibliometric Analysis of Academic Resilience Research in Indonesia (2000–2025): Trends, Thematic Evolution, and Scholarly Impact laksmi evasufi widi fajari moh salimi ganes gunansyah anwar novianto doi: 10.56578/esm030304 Education Science and Management 09-23-2025 Education Science and Management 09-23-2025 2025 3 3 Article 184 10.56578/esm030304 https://www.acadlore.com/article/ESM/2025_3_3/esm030304 https://www.acadlore.com/article/ESM/2025_3_3/esm030303 Proficiency in academic writing is widely recognized as a foundational competence for students enrolled in English-medium instruction programs; however, systematic evidence regarding the nature and distribution of writing difficulties across socio-academic groups remains limited. In the present study, linguistic error patterns in undergraduate academic writing were examined within an English-medium instruction context, with particular attention given to disciplinary background and gender as socio-educational variables. A total of 49 undergraduate students from the University of Dhaka participated in the study, and academic essays were collected as writing samples. A multi-stage analytical framework was employed, combining manual linguistic error analysis with quantitative statistical procedures conducted using SPSS (Version 25). Errors were categorized into four principal domains: grammatical errors, lexical errors, mechanical errors, and discourse-level errors. The distribution of errors revealed that grammatical errors constituted the most frequent category, whereas discourse-level errors occurred least frequently. Independent-samples t-tests were performed to examine differences across gender and disciplinary affiliation. No statistically significant differences were identified between male and female students in overall linguistic error production. In contrast, statistically significant differences were observed between disciplinary groups, with students from social science disciplines producing fewer linguistic errors than their counterparts from science disciplines. The results underscore the importance of discipline-sensitive writing instruction and targeted pedagogical interventions aimed at strengthening grammatical accuracy and genre-specific discourse competence. This study contributes to a more nuanced understanding of academic writing difficulties in English-medium instruction in higher education and provides an empirical foundation for curriculum design and academic writing support programs. 08-19-2025 <![CDATA[ Proficiency in academic writing is widely recognized as a foundational competence for students enrolled in English-medium instruction programs; however, systematic evidence regarding the nature and distribution of writing difficulties across socio-academic groups remains limited. In the present study, linguistic error patterns in undergraduate academic writing were examined within an English-medium instruction context, with particular attention given to disciplinary background and gender as socio-educational variables. A total of 49 undergraduate students from the University of Dhaka participated in the study, and academic essays were collected as writing samples. A multi-stage analytical framework was employed, combining manual linguistic error analysis with quantitative statistical procedures conducted using SPSS (Version 25). Errors were categorized into four principal domains: grammatical errors, lexical errors, mechanical errors, and discourse-level errors. The distribution of errors revealed that grammatical errors constituted the most frequent category, whereas discourse-level errors occurred least frequently. Independent-samples t-tests were performed to examine differences across gender and disciplinary affiliation. No statistically significant differences were identified between male and female students in overall linguistic error production. In contrast, statistically significant differences were observed between disciplinary groups, with students from social science disciplines producing fewer linguistic errors than their counterparts from science disciplines. The results underscore the importance of discipline-sensitive writing instruction and targeted pedagogical interventions aimed at strengthening grammatical accuracy and genre-specific discourse competence. This study contributes to a more nuanced understanding of academic writing difficulties in English-medium instruction in higher education and provides an empirical foundation for curriculum design and academic writing support programs. ]]> Linguistic Difficulties in Undergraduate Academic Writing Within an English-Medium Instruction Context gourob das doi: 10.56578/esm030303 Education Science and Management 08-19-2025 Education Science and Management 08-19-2025 2025 3 3 Article 174 10.56578/esm030303 https://www.acadlore.com/article/ESM/2025_3_3/esm030303 https://www.acadlore.com/article/ESM/2025_3_3/esm030302 With digital-intelligence technologies becoming increasingly embedded in educational practice, limitations in traditional teacher education have gradually emerged, particularly in terms of competency alignment, curriculum organization, and training models. In response to these challenges, this study addresses the professional development requirements of teachers in the digital-intelligence era by proposing a competency framework comprising Digital Literacy, Innovation Literacy, Subject Literacy, Humanistic Literacy, Educational Literacy, and Critical Thinking (DISHEL-CT), and by constructing an integrated training model grounded in technology empowerment, competency foundation, and practice-oriented innovation. Taking the geography teacher education program at Beibu Gulf University as an empirical case, the curriculum system was systematically reorganized into a structured model characterized by dual foundations, three extensions, four modules, and a central practice axis with two supporting wings. During instructional implementation, a double-helix nested case-based approach and a theme-based situational digital teaching model were adopted to integrate digital technologies across the entire teaching, learning, assessment, and instructional management process. Additionally, an evaluation scale grounded in the DISHEL-CT competency structure was developed to examine the outcomes of the training reform. Empirical analysis indicates that the reform measures were associated with observable progress in pre-service teachers’ disciplinary understanding, educational practice awareness, humanistic orientation, and digital-instructional capability. The findings offer a practice-oriented reference for the reform of teacher education programs in the digital-intelligence era. 08-04-2025 <![CDATA[ With digital-intelligence technologies becoming increasingly embedded in educational practice, limitations in traditional teacher education have gradually emerged, particularly in terms of competency alignment, curriculum organization, and training models. In response to these challenges, this study addresses the professional development requirements of teachers in the digital-intelligence era by proposing a competency framework comprising Digital Literacy, Innovation Literacy, Subject Literacy, Humanistic Literacy, Educational Literacy, and Critical Thinking (DISHEL-CT), and by constructing an integrated training model grounded in technology empowerment, competency foundation, and practice-oriented innovation. Taking the geography teacher education program at Beibu Gulf University as an empirical case, the curriculum system was systematically reorganized into a structured model characterized by dual foundations, three extensions, four modules, and a central practice axis with two supporting wings. During instructional implementation, a double-helix nested case-based approach and a theme-based situational digital teaching model were adopted to integrate digital technologies across the entire teaching, learning, assessment, and instructional management process. Additionally, an evaluation scale grounded in the DISHEL-CT competency structure was developed to examine the outcomes of the training reform. Empirical analysis indicates that the reform measures were associated with observable progress in pre-service teachers’ disciplinary understanding, educational practice awareness, humanistic orientation, and digital-instructional capability. The findings offer a practice-oriented reference for the reform of teacher education programs in the digital-intelligence era. ]]> Reframing Teacher Education for the Digital-Intelligence Era: An Empirical Study in Geography Education huirong chen jianzhong yang zhen guan doi: 10.56578/esm030302 Education Science and Management 08-04-2025 Education Science and Management 08-04-2025 2025 3 3 Article 156 10.56578/esm030302 https://www.acadlore.com/article/ESM/2025_3_3/esm030302 https://www.acadlore.com/article/ESM/2025_3_3/esm030301 Scientific literacy is a fundamental twenty-first-century competency, yet Indonesian students’ scientific literacy remains low based on the 2022 PISA results. This study aims to analyze the pedagogical needs of elementary school teachers in developing electronic modules to improve students’ scientific literacy in Grade 5 science learning. This study employed a qualitative approach with a descriptive qualitative design involving eight Grade-5 elementary school teachers in cluster M, Madiun, East Java, Indonesia. Data were collected through semi-structured in-depth interviews and analyzed using thematic analysis to explore in depth the teachers’ pedagogical needs in developing scientific literacy through the use of electronic modules. Results: The findings reveal dimensions of teachers’ pedagogical needs including (1) the need to strengthen teachers’ understanding of scientific literacy concepts, (2) the need for curriculum-aligned and in-depth materials supported by structured scientific readings to facilitate conceptual understanding, (3) the need for methods and learning strategies providing systematic scenarios, supporting differentiation, and improving teachers’ pedagogical competence in teaching scientific literacy, (4) a gap between positive perceptions of electronic modules and the absence of implementation experience due to limited access and digital competence, (5) the need for technical features including contextual multimedia, interactive activities, higher-order thinking skills-based assessments, and lightweight electronic module designs compatible with infrastructure limitations. The findings indicate that the development of electronic modules to improve students’ scientific literacy must be responsive to teachers’ pedagogical needs by integrating conceptual, methodological, and technical aspects. 07-15-2025 <![CDATA[ <p>Scientific literacy is a fundamental twenty-first-century competency, yet Indonesian students’ scientific literacy remains low based on the 2022 PISA results. This study aims to analyze the pedagogical needs of elementary school teachers in developing electronic modules to improve students’ scientific literacy in Grade 5 science learning. This study employed a qualitative approach with a descriptive qualitative design involving eight Grade-5 elementary school teachers in cluster M, Madiun, East Java, Indonesia. Data were collected through semi-structured in-depth interviews and analyzed using thematic analysis to explore in depth the teachers’ pedagogical needs in developing scientific literacy through the use of electronic modules. Results: The findings reveal dimensions of teachers’ pedagogical needs including (1) the need to strengthen teachers’ understanding of scientific literacy concepts, (2) the need for curriculum-aligned and in-depth materials supported by structured scientific readings to facilitate conceptual understanding, (3) the need for methods and learning strategies providing systematic scenarios, supporting differentiation, and improving teachers’ pedagogical competence in teaching scientific literacy, (4) a gap between positive perceptions of electronic modules and the absence of implementation experience due to limited access and digital competence, (5) the need for technical features including contextual multimedia, interactive activities, higher-order thinking skills-based assessments, and lightweight electronic module designs compatible with infrastructure limitations. The findings indicate that the development of electronic modules to improve students’ scientific literacy must be responsive to teachers’ pedagogical needs by integrating conceptual, methodological, and technical aspects.</p> ]]> What Are the Pedagogical Needs of Teachers in Promoting Scientific Literacy Through Electronic Modules? ning dainty restiani moh salimi kartika chrysti suryandari karsono doi: 10.56578/esm030301 Education Science and Management 07-15-2025 Education Science and Management 07-15-2025 2025 3 3 Article 142 10.56578/esm030301 https://www.acadlore.com/article/ESM/2025_3_3/esm030301 https://www.acadlore.com/article/ESM/2025_3_2/esm030205 Artificial intelligence (AI) changes the way university students learn and improve skills. A total of 476 valid responses were received. This study examined AI anxiety’s dual effect on university students’ proactive skill development and the related mechanisms. The results show that AI anxiety promotes proactive skill development through challenge appraisal and inhibits it through threat appraisal. AI literacy strengthens the positive challenge appraisal and weakens the negative threat appraisal. A high self-driven profile and other profiles driven by resource management, crisis response, and competence are conducive to developing skills proactively. AI anxiety has a complex influence on students’ proactive skill development. At the same time, this provides guidance for universities’ digital transformation and talent cultivation, underscoring the importance of improving AI literacy and fostering constructive mindsets. 06-25-2025 <![CDATA[ Artificial intelligence (AI) changes the way university students learn and improve skills. A total of 476 valid responses were received. This study examined AI anxiety’s dual effect on university students’ proactive skill development and the related mechanisms. The results show that AI anxiety promotes proactive skill development through challenge appraisal and inhibits it through threat appraisal. AI literacy strengthens the positive challenge appraisal and weakens the negative threat appraisal. A high self-driven profile and other profiles driven by resource management, crisis response, and competence are conducive to developing skills proactively. AI anxiety has a complex influence on students’ proactive skill development. At the same time, this provides guidance for universities’ digital transformation and talent cultivation, underscoring the importance of improving AI literacy and fostering constructive mindsets. ]]> The Dual-Edged Effect of Artificial Intelligence Anxiety on University Students’ Proactive Skill Development wenyong liu doi: 10.56578/esm030205 Education Science and Management 06-25-2025 Education Science and Management 06-25-2025 2025 3 2 Article 128 10.56578/esm030205 https://www.acadlore.com/article/ESM/2025_3_2/esm030205 https://www.acadlore.com/article/ESM/2025_3_2/esm030204 Significant regional imbalances have long been observed in China’s development, with the level of educational development in the western region consistently lagging behind the national average. Structural disparities are also evident among the provinces within the region. To systematically identify the determinants of these disparities and to characterize the spatial development patterns, a multidimensional evaluation framework was constructed using six indicators: number of schools, number of teachers, average years of schooling, public library collection size, governmental fiscal education expenditure, and number of internet users. Panel data from 12 western provinces (including municipalities and autonomous regions) for 2008 and 2017 were employed. Indicator weights were determined using the entropy method, followed by cluster analysis to classify the levels of educational development across the region. The findings indicate a steady overall improvement in educational development in western China, although substantial interprovincial disparities persist. Based on these results, policy recommendations are presented, including the optimization of the education policy system, improvement of resource allocation structures, strengthening of high-quality talent recruitment and incentive mechanisms, and coordinated planning of educational resources. The conclusions provide empirical support and policy guidance for enhancing educational equity and promoting balanced development in western China. 06-14-2025 <![CDATA[ Significant regional imbalances have long been observed in China’s development, with the level of educational development in the western region consistently lagging behind the national average. Structural disparities are also evident among the provinces within the region. To systematically identify the determinants of these disparities and to characterize the spatial development patterns, a multidimensional evaluation framework was constructed using six indicators: number of schools, number of teachers, average years of schooling, public library collection size, governmental fiscal education expenditure, and number of internet users. Panel data from 12 western provinces (including municipalities and autonomous regions) for 2008 and 2017 were employed. Indicator weights were determined using the entropy method, followed by cluster analysis to classify the levels of educational development across the region. The findings indicate a steady overall improvement in educational development in western China, although substantial interprovincial disparities persist. Based on these results, policy recommendations are presented, including the optimization of the education policy system, improvement of resource allocation structures, strengthening of high-quality talent recruitment and incentive mechanisms, and coordinated planning of educational resources. The conclusions provide empirical support and policy guidance for enhancing educational equity and promoting balanced development in western China. ]]> A Cluster Analysis of Educational Development Disparities in Western China zhaoxia huang doi: 10.56578/esm030204 Education Science and Management 06-14-2025 Education Science and Management 06-14-2025 2025 3 2 Article 117 10.56578/esm030204 https://www.acadlore.com/article/ESM/2025_3_2/esm030204 https://www.acadlore.com/article/ESM/2025_3_2/esm030203 In the context of the digital era and ongoing reforms in higher education, how to cultivate and enhance university teachers’ digital teaching competence has become a prominent topic among scholars. Accordingly, this study examined the relationships between university assessment mechanisms and teachers’ digital teaching competence based on 422 valid questionnaires. The results indicate that instructional assessment, research assessment, administrative assessment, and qualification assessment all exert positive effects on teachers’ digital teaching competence. Social support moderates the negative relationship between work stress and digital teaching competence, and further moderates the mediating role of work stress in the relationships between the four dimensions of assessment mechanism rationality and digital teaching competence. The findings provide insights and recommendations for optimizing assessment mechanisms and promoting the modern professional development of university teachers. 05-28-2025 <![CDATA[ In the context of the digital era and ongoing reforms in higher education, how to cultivate and enhance university teachers’ digital teaching competence has become a prominent topic among scholars. Accordingly, this study examined the relationships between university assessment mechanisms and teachers’ digital teaching competence based on 422 valid questionnaires. The results indicate that instructional assessment, research assessment, administrative assessment, and qualification assessment all exert positive effects on teachers’ digital teaching competence. Social support moderates the negative relationship between work stress and digital teaching competence, and further moderates the mediating role of work stress in the relationships between the four dimensions of assessment mechanism rationality and digital teaching competence. The findings provide insights and recommendations for optimizing assessment mechanisms and promoting the modern professional development of university teachers. ]]> Assessment Mechanisms as Drivers of University Teachers’ Digital Teaching Competence in the Context of Digital Transformation chunhua mao jinhao liu zhifang zhou doi: 10.56578/esm030203 Education Science and Management 05-28-2025 Education Science and Management 05-28-2025 2025 3 2 Article 106 10.56578/esm030203 https://www.acadlore.com/article/ESM/2025_3_2/esm030203 https://www.acadlore.com/article/ESM/2025_3_2/esm030202 The reduction of excessive academic burden in China’s basic education system has been established as a central objective of national education reform and has become a subject of intense policy debate. To elucidate the complex strategic interactions that shape the implementation of the “Double Reduction” policy, a multi-agent evolutionary game model was constructed incorporating three principal stakeholder groups: government authorities, schools and teachers, and students and parents. Replicator dynamic equations were employed to examine the evolutionary stability of stakeholder strategies and the conditions under which equilibrium outcomes emerge. Through numerical simulations, the influence of regulatory enforcement intensity on behavioral trajectories and convergence patterns was evaluated. The results reveal that asymptotically stable equilibria exist, with optimal system performance achieved when government bodies maintain active and credible regulatory oversight, educational institutions engage in substantive and sustained burden-reduction efforts, and families adopt cooperative and adaptive responses. By clarifying the mechanisms through which stakeholder interactions determine collective outcomes, this study provides theoretical support for the refinement of policy coordination and the long-term enhancement of education governance capacity. These findings contribute not only to the understanding of the “Double Reduction” policy’s systemic impact but also to broader discussions on the role of evolutionary game theory in evaluating multi-agent policy interventions in education systems. 04-14-2025 <![CDATA[ <p>The reduction of excessive academic burden in China’s basic education system has been established as a central objective of national education reform and has become a subject of intense policy debate. To elucidate the complex strategic interactions that shape the implementation of the “Double Reduction” policy, a multi-agent evolutionary game model was constructed incorporating three principal stakeholder groups: government authorities, schools and teachers, and students and parents. Replicator dynamic equations were employed to examine the evolutionary stability of stakeholder strategies and the conditions under which equilibrium outcomes emerge. Through numerical simulations, the influence of regulatory enforcement intensity on behavioral trajectories and convergence patterns was evaluated. The results reveal that asymptotically stable equilibria exist, with optimal system performance achieved when government bodies maintain active and credible regulatory oversight, educational institutions engage in substantive and sustained burden-reduction efforts, and families adopt cooperative and adaptive responses. By clarifying the mechanisms through which stakeholder interactions determine collective outcomes, this study provides theoretical support for the refinement of policy coordination and the long-term enhancement of education governance capacity. These findings contribute not only to the understanding of the “Double Reduction” policy’s systemic impact but also to broader discussions on the role of evolutionary game theory in evaluating multi-agent policy interventions in education systems.</p> ]]> Evolutionary Game Analysis of Stakeholder Strategies in China’s Basic Education under the “Double Reduction” Policy wang dou doi: 10.56578/esm030202 Education Science and Management 04-14-2025 Education Science and Management 04-14-2025 2025 3 2 Article 93 10.56578/esm030202 https://www.acadlore.com/article/ESM/2025_3_2/esm030202 https://www.acadlore.com/article/ESM/2025_3_2/esm030201 The psychometric validity of multiple-choice questions (MCQs) generated by an advanced Artificial Intelligence (AI) language model (ChatGPT) was evaluated in comparison with those developed by experienced human instructors, with a focus on mathematics teacher education. Two parallel 30-item MCQ tests—one human-designed and one AI-generated—were administered to 30 mathematics teacher trainees. A comprehensive psychometric analysis was conducted using six metrics: item difficulty index (Pi), discrimination index (D), point-biserial correlation, item-test correlation (Rit), Cronbach’s alpha (α) for internal consistency, and score variance. The analysis was facilitated by the Analysis of Didactic Items with Excel (AnDIE) tool. Results indicated that the human-authored MCQs exhibited acceptable difficulty (mean Pi = 0.55), moderate discrimination power (mean D = 0.31), and strong internal consistency (Cronbach’s α = 0.752). In contrast, the AI-generated MCQs were found to be substantially more difficult (mean Pi = 0.22), demonstrated weak discrimination (mean D = 0.16), and yielded negative internal consistency reliability (Cronbach’s α = −0.1), raising concerns about their psychometric quality. While AI-generated assessments offer advantages in terms of scalability and speed, the findings underscore the necessity of expert human review to ensure content validity, construct alignment, and pedagogical appropriateness. These results suggest that AI, in its current form, is not yet equipped to autonomously generate assessment instruments of sufficient quality for high-stakes educational settings. A hybrid test design model is therefore advocated, wherein AI is leveraged for initial item drafting, followed by rigorous human refinement. This approach may enhance both efficiency and quality in the development of educational assessments. The implications extend to educators, assessment designers, and developers of educational AI systems, highlighting the need for collaborative human-AI frameworks to achieve reliable, valid, and pedagogically sound testing instruments. 04-10-2025 <![CDATA[ <p>The psychometric validity of multiple-choice questions (MCQs) generated by an advanced Artificial Intelligence (AI) language model (ChatGPT) was evaluated in comparison with those developed by experienced human instructors, with a focus on mathematics teacher education. Two parallel 30-item MCQ tests—one human-designed and one AI-generated—were administered to 30 mathematics teacher trainees. A comprehensive psychometric analysis was conducted using six metrics: item difficulty index (<em>P_i</em>), discrimination index (<em>D</em>), point-biserial correlation, item-test correlation (<em>R_it</em>), Cronbach’s alpha (α) for internal consistency, and score variance. The analysis was facilitated by the Analysis of Didactic Items with Excel (AnDIE) tool. Results indicated that the human-authored MCQs exhibited acceptable difficulty (mean <em>P_i </em>= 0.55), moderate discrimination power (mean <em>D</em> = 0.31), and strong internal consistency (Cronbach’s α = 0.752). In contrast, the AI-generated MCQs were found to be substantially more difficult (mean <em>P_i</em> = 0.22), demonstrated weak discrimination (mean <em>D</em> = 0.16), and yielded negative internal consistency reliability (Cronbach’s α = −0.1), raising concerns about their psychometric quality. While AI-generated assessments offer advantages in terms of scalability and speed, the findings underscore the necessity of expert human review to ensure content validity, construct alignment, and pedagogical appropriateness. These results suggest that AI, in its current form, is not yet equipped to autonomously generate assessment instruments of sufficient quality for high-stakes educational settings. A hybrid test design model is therefore advocated, wherein AI is leveraged for initial item drafting, followed by rigorous human refinement. This approach may enhance both efficiency and quality in the development of educational assessments. The implications extend to educators, assessment designers, and developers of educational AI systems, highlighting the need for collaborative human-AI frameworks to achieve reliable, valid, and pedagogically sound testing instruments.</p> ]]> Psychometric Evaluation of Human-Crafted and AI-Generated Multiple-Choice Questions for Mathematics Instruction rachid el chaal rabei ben seghir moulay othman aboutafail doi: 10.56578/esm030201 Education Science and Management 04-10-2025 Education Science and Management 04-10-2025 2025 3 2 Article 78 10.56578/esm030201 https://www.acadlore.com/article/ESM/2025_3_2/esm030201 https://www.acadlore.com/article/ESM/2025_3_1/esm030105 This study investigates the role of Artificial Intelligence (AI) in sustainable education through a bibliometric analysis, aiming to explore research trends, key contributors, citation analysis, co-authorship, and thematic developments in the field. As AI becomes increasingly integrated into Education, it is crucial to understand its impact on learning personalization, institutional efficiency, and sustainability. The study also identifies research gaps and provides recommendations for future exploration. The study employs a bibliometric and content analysis methodology using Scopus data. Two hundred seventy-six documents (2016-2025) were analyzed through descriptive statistics, citation analysis, co-word analysis, and co-authorship networks, utilizing VOSviewer and Biblioshiny for data visualization. The analysis examines publication trends, top-cited articles, leading institutions, and international collaborations to map the intellectual landscape of AI in sustainable education. The findings indicate a significant increase in AI-related publications after 2019, reflecting growing global interest. India, the USA, and China lead research output, while Sustainability (Switzerland) and Lecture Notes in Networks and Systems are the most prominent publication sources. The co-authorship analysis highlights strong global research collaborations, with the UK, Brazil, and China playing key roles. Thematic clustering reveals four major research areas: AI-driven Environmental Education, AI in Education, sustainable education frameworks, and AI's technical advancements in learning systems. This study provides a comprehensive, macro-level bibliometric analysis that maps global research dynamics, identifies intellectual structures, and visualizes collaborative networks in AI and sustainable education. Despite its contributions, the study has several limitations. First, while Scopus offers broad and reputable coverage of peer-reviewed literature, the exclusive reliance on this database limits the inclusion of potentially relevant studies indexed in other databases such as Web of Science (WoS). This may restrict the diversity and comprehensiveness of the findings. Future research should consider cross-validating results using multiple databases to ensure a more holistic understanding of AI in sustainable education. Second, the exclusion of non-English publications may limit the diversity of perspectives. Third, the study primarily focuses on journal articles and conference papers, excluding books and institutional reports that might offer more profound insights. 03-25-2025 <![CDATA[ This study investigates the role of Artificial Intelligence (AI) in sustainable education through a bibliometric analysis, aiming to explore research trends, key contributors, citation analysis, co-authorship, and thematic developments in the field. As AI becomes increasingly integrated into Education, it is crucial to understand its impact on learning personalization, institutional efficiency, and sustainability. The study also identifies research gaps and provides recommendations for future exploration. The study employs a bibliometric and content analysis methodology using Scopus data. Two hundred seventy-six documents (2016-2025) were analyzed through descriptive statistics, citation analysis, co-word analysis, and co-authorship networks, utilizing VOSviewer and Biblioshiny for data visualization. The analysis examines publication trends, top-cited articles, leading institutions, and international collaborations to map the intellectual landscape of AI in sustainable education. The findings indicate a significant increase in AI-related publications after 2019, reflecting growing global interest. India, the USA, and China lead research output, while Sustainability (Switzerland) and Lecture Notes in Networks and Systems are the most prominent publication sources. The co-authorship analysis highlights strong global research collaborations, with the UK, Brazil, and China playing key roles. Thematic clustering reveals four major research areas: AI-driven Environmental Education, AI in Education, sustainable education frameworks, and AI's technical advancements in learning systems. This study provides a comprehensive, macro-level bibliometric analysis that maps global research dynamics, identifies intellectual structures, and visualizes collaborative networks in AI and sustainable education. Despite its contributions, the study has several limitations. First, while Scopus offers broad and reputable coverage of peer-reviewed literature, the exclusive reliance on this database limits the inclusion of potentially relevant studies indexed in other databases such as Web of Science (WoS). This may restrict the diversity and comprehensiveness of the findings. Future research should consider cross-validating results using multiple databases to ensure a more holistic understanding of AI in sustainable education. Second, the exclusion of non-English publications may limit the diversity of perspectives. Third, the study primarily focuses on journal articles and conference papers, excluding books and institutional reports that might offer more profound insights. ]]> Artificial Intelligence in Sustainable Education: A Bibliometric Analysis and Future Research Directions rahmanwali sahar ismail labib mohammad kazim kazimi hamidullah mobarez mohammad naim kakar doi: 10.56578/esm030105 Education Science and Management 03-25-2025 Education Science and Management 03-25-2025 2025 3 1 Article 57 10.56578/esm030105 https://www.acadlore.com/article/ESM/2025_3_1/esm030105 https://www.acadlore.com/article/ESM/2025_3_1/esm030104 Although methodological innovations have reshaped many aspects of scientific writing, literature reviews remain one of its most structurally underdeveloped and conceptually inconsistent components. Existing approaches often fail to communicate the functional role of individual sources within the research argument, leaving both readers and reviewers without a transparent sense of contribution, coherence, or originality. This paper introduces the Pyramid of Contribution Review (PCR), a novel framework that visually and functionally maps references according to their role in the manuscript (Introduction, Methodology, Results, Discussion, Gap) and their level of relevance. Through a mixed-methods validation process, including expert-based Delphi design (n = 28) and a large-scale evaluation survey (n = 118), the method was rigorously tested across disciplines. Statistical analyses reveal that manuscripts perceived to employ the PCR model are 3.45 times more likely to be rated as publishable compared to those relying on conventional narrative reviews. Experts overwhelmingly endorsed the model for its clarity, strategic value, and pedagogical utility. This study positions the PCR framework not only as a solution to a long-standing structural gap in scientific writing but as a forward-looking standard for literature organization in high-impact research. The future of scholarly communication requires not just citation density but citation precision, exactly what the PCR model provides. 03-02-2025 <![CDATA[ <p style="text-align: justify">Although methodological innovations have reshaped many aspects of scientific writing, literature reviews remain one of its most structurally underdeveloped and conceptually inconsistent components. Existing approaches often fail to communicate the functional role of individual sources within the research argument, leaving both readers and reviewers without a transparent sense of contribution, coherence, or originality. This paper introduces the Pyramid of Contribution Review (PCR), a novel framework that visually and functionally maps references according to their role in the manuscript (Introduction, Methodology, Results, Discussion, Gap) and their level of relevance. Through a mixed-methods validation process, including expert-based Delphi design (n = 28) and a large-scale evaluation survey (n = 118), the method was rigorously tested across disciplines. Statistical analyses reveal that manuscripts perceived to employ the PCR model are 3.45 times more likely to be rated as publishable compared to those relying on conventional narrative reviews. Experts overwhelmingly endorsed the model for its clarity, strategic value, and pedagogical utility. This study positions the PCR framework not only as a solution to a long-standing structural gap in scientific writing but as a forward-looking standard for literature organization in high-impact research. The future of scholarly communication requires not just citation density but citation precision, exactly what the PCR model provides.</p> ]]> Pyramid of Contribution Review: A Structured Model for Functional Literature Integration in Scientific Writing aleksandar trifunović aleksandar senić doi: 10.56578/esm030104 Education Science and Management 03-02-2025 Education Science and Management 03-02-2025 2025 3 1 Article 40 10.56578/esm030104 https://www.acadlore.com/article/ESM/2025_3_1/esm030104 https://www.acadlore.com/article/ESM/2025_3_1/esm030103 The extent to which students’ cultural values influence mathematical problem-solving skills was investigated, with emphasis placed on the moderating effect of prior mathematical knowledge and the mediating role of student motivation. A mixed-methods design was employed to ensure both quantitative and qualitative dimensions of the inquiry were addressed, enabling a comprehensive understanding of the underlying relationships. A purposive sample of 370 students from culturally diverse regions of Ghana was selected to ensure contextual validity and sociocultural relevance. It was found that students’ cultural values significantly shaped their problem-solving performance, particularly in relation to cognitive processing strategies and the selection of problem-solving heuristics. The relationship between cultural values and problem-solving skills was moderated by students’ prior knowledge, with students possessing a stronger foundational understanding of mathematics deriving greater benefit from cultural alignment. Contrary to expectations, the mediating effect of student motivation on this relationship was not supported, suggesting that while motivation is influenced by cultural values, it does not serve as a direct conduit for enhanced problem-solving capability. These findings underscore the necessity of incorporating culturally responsive pedagogical strategies that recognize and harness cultural value systems as cognitive assets. Furthermore, implications for curriculum development and teacher training were discussed, with a recommendation that future research explore context-specific interventions that operationalize cultural capital to improve mathematical learning trajectories. 03-02-2025 <![CDATA[ The extent to which students’ cultural values influence mathematical problem-solving skills was investigated, with emphasis placed on the moderating effect of prior mathematical knowledge and the mediating role of student motivation. A mixed-methods design was employed to ensure both quantitative and qualitative dimensions of the inquiry were addressed, enabling a comprehensive understanding of the underlying relationships. A purposive sample of 370 students from culturally diverse regions of Ghana was selected to ensure contextual validity and sociocultural relevance. It was found that students’ cultural values significantly shaped their problem-solving performance, particularly in relation to cognitive processing strategies and the selection of problem-solving heuristics. The relationship between cultural values and problem-solving skills was moderated by students’ prior knowledge, with students possessing a stronger foundational understanding of mathematics deriving greater benefit from cultural alignment. Contrary to expectations, the mediating effect of student motivation on this relationship was not supported, suggesting that while motivation is influenced by cultural values, it does not serve as a direct conduit for enhanced problem-solving capability. These findings underscore the necessity of incorporating culturally responsive pedagogical strategies that recognize and harness cultural value systems as cognitive assets. Furthermore, implications for curriculum development and teacher training were discussed, with a recommendation that future research explore context-specific interventions that operationalize cultural capital to improve mathematical learning trajectories. ]]> Cultural Values and Mathematical Problem-Solving in Ghana: The Interplay of Motivation and Prior Knowledge dilor isaiah dookurong doi: 10.56578/esm030103 Education Science and Management 03-02-2025 Education Science and Management 03-02-2025 2025 3 1 Article 23 10.56578/esm030103 https://www.acadlore.com/article/ESM/2025_3_1/esm030103 https://www.acadlore.com/article/ESM/2025_3_1/esm030102 The effectiveness of a microlearning-supported flipped classroom model in improving learning achievement and student attitudes was investigated among vocational college students enrolled in Information Technology (IT) courses in Zibo City, China. While the flipped classroom model—characterized by pre-class engagement with instructional content and in-class participatory learning—has been widely adopted in vocational education, concerns regarding cognitive overload and limited student engagement persist. To address these challenges, microlearning was integrated to deliver content in concise, targeted segments intended to enhance comprehension and reduce extraneous cognitive load. A quasi-experimental design was employed involving 60 first-year students, who were randomly assigned to either an experimental group (microlearning-supported flipped classroom) or a control group (traditional flipped classroom). Learning outcomes were evaluated using a 50-item IT achievement test, while student attitudes were assessed through a 20-item Likert-scale questionnaire covering four attitudinal dimensions. High instrument validity, i.e., average Scale-level Content Validity Index (SCVI/ave) = 0.977, and internal reliability (Cronbach’s α = 0.958) were established. No significant differences were observed in the pre-test scores between groups, confirming baseline equivalence. Post-intervention results demonstrated a statistically significant improvement in the experimental group (M = 52.733, SD = 3.805) compared to the control group (M = 49.600, SD = 3.838), t (58) = 3.376, p = 0.002), indicating enhanced academic performance. Favorable shifts in learning attitudes were also observed among students exposed to the microlearning-enhanced model, although the four-week intervention period constrained the generalizability of these attitudinal outcomes. These findings suggest that the incorporation of microlearning elements into flipped classroom pedagogies can foster more effective engagement and lead to measurable improvements in academic performance within vocational IT education contexts. Future research involving extended implementation periods and larger, more diverse sample populations is recommended to further validate the durability and scalability of these effects. 02-16-2025 <![CDATA[ The effectiveness of a microlearning-supported flipped classroom model in improving learning achievement and student attitudes was investigated among vocational college students enrolled in Information Technology (IT) courses in Zibo City, China. While the flipped classroom model—characterized by pre-class engagement with instructional content and in-class participatory learning—has been widely adopted in vocational education, concerns regarding cognitive overload and limited student engagement persist. To address these challenges, microlearning was integrated to deliver content in concise, targeted segments intended to enhance comprehension and reduce extraneous cognitive load. A quasi-experimental design was employed involving 60 first-year students, who were randomly assigned to either an experimental group (microlearning-supported flipped classroom) or a control group (traditional flipped classroom). Learning outcomes were evaluated using a 50-item IT achievement test, while student attitudes were assessed through a 20-item Likert-scale questionnaire covering four attitudinal dimensions. High instrument validity, i.e., average Scale-level Content Validity Index (SCVI/ave) = 0.977, and internal reliability (Cronbach’s α = 0.958) were established. No significant differences were observed in the pre-test scores between groups, confirming baseline equivalence. Post-intervention results demonstrated a statistically significant improvement in the experimental group (M = 52.733, SD = 3.805) compared to the control group (M = 49.600, SD = 3.838), t (58) = 3.376, p = 0.002), indicating enhanced academic performance. Favorable shifts in learning attitudes were also observed among students exposed to the microlearning-enhanced model, although the four-week intervention period constrained the generalizability of these attitudinal outcomes. These findings suggest that the incorporation of microlearning elements into flipped classroom pedagogies can foster more effective engagement and lead to measurable improvements in academic performance within vocational IT education contexts. Future research involving extended implementation periods and larger, more diverse sample populations is recommended to further validate the durability and scalability of these effects. ]]> Enhancing Learning Outcomes through Microlearning-Supported Flipped Classrooms: Evidence from Vocational IT Education in Zibo, China wen zhao puteri roslina abdul wahid doi: 10.56578/esm030102 Education Science and Management 02-16-2025 Education Science and Management 02-16-2025 2025 3 1 Article 11 10.56578/esm030102 https://www.acadlore.com/article/ESM/2025_3_1/esm030102 https://www.acadlore.com/article/ESM/2025_3_1/esm030101 A scientifically rigorous evaluation of college teachers’ engagement is essential for enhancing human resource management practices within higher education institutions. In this study, a fuzzy decision-making framework was constructed to facilitate the objective assessment of college teachers’ engagement in Chinese universities. Drawing on Rich’s tripartite conceptualization of engagement—comprising cognitive focus, emotional involvement, and behavioral effort—a hierarchical evaluation index system was developed, consisting of three primary dimensions and seventeen secondary indicators. To address the inherent uncertainty and subjectivity in engagement assessment, a fuzzy entropy weight method was employed to determine the relative importance of each indicator. Subsequently, a novel fuzzy-grey correlation evaluation method was proposed, integrating grey and fuzzy mathematics theories to comprehensively assess engagement levels. The applicability and robustness of the proposed framework were demonstrated through a case study involving four university instructors from a higher education institution in Tianjin. The results revealed that the fuzzy-grey correlation approach effectively distinguished varying levels of engagement among the sampled instructors, offering a more nuanced and data-driven foundation for engagement-based performance evaluations. This methodological framework provides a practical tool for decision-makers and education administrators aiming to implement equitable and evidence-based faculty management strategies. 02-07-2025 <![CDATA[ <p>A scientifically rigorous evaluation of college teachers’ engagement is essential for enhancing human resource management practices within higher education institutions. In this study, a fuzzy decision-making framework was constructed to facilitate the objective assessment of college teachers’ engagement in Chinese universities. Drawing on Rich’s tripartite conceptualization of engagement—comprising cognitive focus, emotional involvement, and behavioral effort—a hierarchical evaluation index system was developed, consisting of three primary dimensions and seventeen secondary indicators. To address the inherent uncertainty and subjectivity in engagement assessment, a fuzzy entropy weight method was employed to determine the relative importance of each indicator. Subsequently, a novel fuzzy-grey correlation evaluation method was proposed, integrating grey and fuzzy mathematics theories to comprehensively assess engagement levels. The applicability and robustness of the proposed framework were demonstrated through a case study involving four university instructors from a higher education institution in Tianjin. The results revealed that the fuzzy-grey correlation approach effectively distinguished varying levels of engagement among the sampled instructors, offering a more nuanced and data-driven foundation for engagement-based performance evaluations. This methodological framework provides a practical tool for decision-makers and education administrators aiming to implement equitable and evidence-based faculty management strategies.</p> ]]> Evaluation of College Teachers’ Engagement in Chinese Higher Education Using a Fuzzy Entropy Weight and Fuzzy-Grey Correlation Approach yue ma doi: 10.56578/esm030101 Education Science and Management 02-07-2025 Education Science and Management 02-07-2025 2025 3 1 Article 1 10.56578/esm030101 https://www.acadlore.com/article/ESM/2025_3_1/esm030101 https://www.acadlore.com/article/ESM/2024_2_4/esm020405 The role of cognitive and affective dimensions in mathematical modeling education was investigated, with a particular emphasis on the influence of mathematical values on student engagement and learning outcomes. A mixed-methods approach was employed, incorporating surveys and interviews with students from diverse educational contexts. This approach enabled the quantitative assessment of cognitive competencies alongside qualitative exploration of attitudes and values toward mathematics. It was found that values associated with realism and cognitive engagement significantly shape students’ approaches to mathematical modeling, with cultural differences playing a critical role in the expression and prioritization of these values. The study highlights the necessity of cross-cultural research to elucidate how these values are cultivated across varying educational settings. Furthermore, it is argued that mathematical modeling instruction must be culturally responsive and attuned to the affective dimensions of learning to promote deeper engagement and enhance educational outcomes. The findings underscore the importance of integrating both cognitive and affective factors in the design of educational frameworks, offering insights for optimizing teaching strategies and fostering more effective learning environments. 12-30-2024 <![CDATA[ The role of cognitive and affective dimensions in mathematical modeling education was investigated, with a particular emphasis on the influence of mathematical values on student engagement and learning outcomes. A mixed-methods approach was employed, incorporating surveys and interviews with students from diverse educational contexts. This approach enabled the quantitative assessment of cognitive competencies alongside qualitative exploration of attitudes and values toward mathematics. It was found that values associated with realism and cognitive engagement significantly shape students’ approaches to mathematical modeling, with cultural differences playing a critical role in the expression and prioritization of these values. The study highlights the necessity of cross-cultural research to elucidate how these values are cultivated across varying educational settings. Furthermore, it is argued that mathematical modeling instruction must be culturally responsive and attuned to the affective dimensions of learning to promote deeper engagement and enhance educational outcomes. The findings underscore the importance of integrating both cognitive and affective factors in the design of educational frameworks, offering insights for optimizing teaching strategies and fostering more effective learning environments. ]]> A Mathematical Modeling Framework for Analyzing and Optimizing Education Systems wasi ur rahman ishfaq ahmad muhammad khan doi: 10.56578/esm020405 Education Science and Management 12-30-2024 Education Science and Management 12-30-2024 2024 2 4 Article 241 10.56578/esm020405 https://www.acadlore.com/article/ESM/2024_2_4/esm020405 https://www.acadlore.com/article/ESM/2024_2_4/esm020404 The selection of appropriate digital platforms (DPs) for enhancing the learning process at universities in the Brčko District, Bosnia and Herzegovina (BiH), was explored through the application of fuzzy multi-criteria decision-making (MCDM) methods. This region, with a rich academic heritage, presents a complex landscape of available DPs, each offering varying features and functionalities. Given the diversity of platforms and evaluation criteria, expert-based fuzzy methods were employed to assess and rank potential DPs. Specifically, the Simple Weight Calculation (SiWeC) method was utilized to determine the relative importance of the evaluation criteria, while the Compromise Ranking of Alternatives from Distance to Ideal Solution (CRADIS) method was applied to rank the platforms based on their proximity to an ideal solution. Expert evaluations from three universities in the region indicated that key characteristics of effective DPs include high interactivity, customizable user interfaces, and advanced tools for monitoring student progress. The results highlighted that DPDL 4 emerged as the highest-ranked platform, followed closely by DPDL 1. These findings underscore the significance of integrating interactive and customizable features in DPs to enhance the educational experience. This research contributes to the optimization of e-learning environments at universities in the Brčko District, thus supporting the region’s efforts to improve academic competitiveness and attract prospective students. 12-30-2024 <![CDATA[ The selection of appropriate digital platforms (DPs) for enhancing the learning process at universities in the Brčko District, Bosnia and Herzegovina (BiH), was explored through the application of fuzzy multi-criteria decision-making (MCDM) methods. This region, with a rich academic heritage, presents a complex landscape of available DPs, each offering varying features and functionalities. Given the diversity of platforms and evaluation criteria, expert-based fuzzy methods were employed to assess and rank potential DPs. Specifically, the Simple Weight Calculation (SiWeC) method was utilized to determine the relative importance of the evaluation criteria, while the Compromise Ranking of Alternatives from Distance to Ideal Solution (CRADIS) method was applied to rank the platforms based on their proximity to an ideal solution. Expert evaluations from three universities in the region indicated that key characteristics of effective DPs include high interactivity, customizable user interfaces, and advanced tools for monitoring student progress. The results highlighted that DPDL 4 emerged as the highest-ranked platform, followed closely by DPDL 1. These findings underscore the significance of integrating interactive and customizable features in DPs to enhance the educational experience. This research contributes to the optimization of e-learning environments at universities in the Brčko District, thus supporting the region’s efforts to improve academic competitiveness and attract prospective students. ]]> The Application of Fuzzy Multi-Criteria Methods for the Selection of Digital Platforms for the Improvement of the Learning Process at Universities in the Brčko District of BiH edisa puška adis puška doi: 10.56578/esm020404 Education Science and Management 12-30-2024 Education Science and Management 12-30-2024 2024 2 4 Article 230 10.56578/esm020404 https://www.acadlore.com/article/ESM/2024_2_4/esm020404 https://www.acadlore.com/article/ESM/2024_2_4/esm020403 In the context of rapidly advancing digital technology, where touchscreen interactions dominate, the tactile sensory development of children is increasingly compromised. This shift towards digital media can hinder the ability of children to effectively engage with and observe their surroundings. One promising solution to this issue is the integration of art appreciation into educational practices. However, in regions such as Indonesia, there is a noticeable scarcity of comprehensive learning kits aimed at teaching art appreciation. This study addresses this gap by designing and developing an art appreciation learning kit intended for children aged 7 to 11, aiming to teach art appreciation through artful thinking (AT). The kit employs the “see, think, wonder” (STW) thinking routine, a structured three-step process that encourages children to observe art, analyze their observations, and engage with the art through inquiry. The analysis, design, development, implementation, and evaluation (ADDIE) framework was employed as the instructional design model. Additionally, a qualitative research through design (RtD) methodology was adopted to guide the design process and ensure the creation of an innovative educational tool. The developed learning kit integrates physical components, multimedia resources, and hands-on arts and crafts activities that complement the STW routine, thereby fostering deeper engagement and critical thinking skills among young learners. The study emphasizes the value of employing the ADDIE model to assess the learning needs and challenges faced by children, particularly during the STW activity. Collaboration with educators during the design and development phases was identified as crucial for refining the learning kit. Key recommendations include the integration of graphic visualizations, clear demonstrations, and interactive activities to enhance children’s engagement and enthusiasm for art appreciation. The findings offer empirical evidence supporting the effective use of the ADDIE model in educational kit design, providing a valuable reference for future product designers in the educational technology field. 12-30-2024 <![CDATA[ In the context of rapidly advancing digital technology, where touchscreen interactions dominate, the tactile sensory development of children is increasingly compromised. This shift towards digital media can hinder the ability of children to effectively engage with and observe their surroundings. One promising solution to this issue is the integration of art appreciation into educational practices. However, in regions such as Indonesia, there is a noticeable scarcity of comprehensive learning kits aimed at teaching art appreciation. This study addresses this gap by designing and developing an art appreciation learning kit intended for children aged 7 to 11, aiming to teach art appreciation through artful thinking (AT). The kit employs the “see, think, wonder” (STW) thinking routine, a structured three-step process that encourages children to observe art, analyze their observations, and engage with the art through inquiry. The analysis, design, development, implementation, and evaluation (ADDIE) framework was employed as the instructional design model. Additionally, a qualitative research through design (RtD) methodology was adopted to guide the design process and ensure the creation of an innovative educational tool. The developed learning kit integrates physical components, multimedia resources, and hands-on arts and crafts activities that complement the STW routine, thereby fostering deeper engagement and critical thinking skills among young learners. The study emphasizes the value of employing the ADDIE model to assess the learning needs and challenges faced by children, particularly during the STW activity. Collaboration with educators during the design and development phases was identified as crucial for refining the learning kit. Key recommendations include the integration of graphic visualizations, clear demonstrations, and interactive activities to enhance children’s engagement and enthusiasm for art appreciation. The findings offer empirical evidence supporting the effective use of the ADDIE model in educational kit design, providing a valuable reference for future product designers in the educational technology field. ]]> Design and Development of an Art Appreciation Learning Kit for Children Aged 7-11: Enhancing Aesthetic Engagement Through the “See, Think, Wonder” Thinking Routine devanny gumulya christina renata gultom doi: 10.56578/esm020403 Education Science and Management 12-30-2024 Education Science and Management 12-30-2024 2024 2 4 Article 215 10.56578/esm020403 https://www.acadlore.com/article/ESM/2024_2_4/esm020403 https://www.acadlore.com/article/ESM/2024_2_4/esm020402 The evolution of educational systems, marked by an increasing number of institutions, has prompted the integration of advanced data mining techniques to address the limitations of traditional pedagogical models. Predicting students’ academic performance, derived from large-scale educational data, has emerged as a critical application within educational data mining (EDM), a multidisciplinary field combining education and computational science. As educational institutions seek to enhance student outcomes and reduce the risk of failure, the ability to anticipate academic performance has gained considerable attention. A novel methodology, employing cluster analysis in combination with Bayesian networks, was introduced to predict student performance and classify academic quality. Students were first categorized into two distinct clusters, followed by the use of Bayesian networks to model and predict academic performance within each cluster. The proposed framework was evaluated against existing approaches using several standard performance metrics, demonstrating its superior accuracy and robustness. This method not only enhances predictive capabilities but also provides a valuable tool for early intervention in educational settings. The results underscore the potential of integrating machine learning techniques with educational data to foster more effective and personalized learning environments. 12-22-2024 <![CDATA[ The evolution of educational systems, marked by an increasing number of institutions, has prompted the integration of advanced data mining techniques to address the limitations of traditional pedagogical models. Predicting students’ academic performance, derived from large-scale educational data, has emerged as a critical application within educational data mining (EDM), a multidisciplinary field combining education and computational science. As educational institutions seek to enhance student outcomes and reduce the risk of failure, the ability to anticipate academic performance has gained considerable attention. A novel methodology, employing cluster analysis in combination with Bayesian networks, was introduced to predict student performance and classify academic quality. Students were first categorized into two distinct clusters, followed by the use of Bayesian networks to model and predict academic performance within each cluster. The proposed framework was evaluated against existing approaches using several standard performance metrics, demonstrating its superior accuracy and robustness. This method not only enhances predictive capabilities but also provides a valuable tool for early intervention in educational settings. The results underscore the potential of integrating machine learning techniques with educational data to foster more effective and personalized learning environments. ]]> Strategic Analytics for Predicting Students’ Academic Performance Using Cluster Analysis and Bayesian Networks shamila saeedi darko božanić ramin safa doi: 10.56578/esm020402 Education Science and Management 12-22-2024 Education Science and Management 12-22-2024 2024 2 4 Article 197 10.56578/esm020402 https://www.acadlore.com/article/ESM/2024_2_4/esm020402 https://www.acadlore.com/article/ESM/2024_2_4/esm020401 This scoping review aims to investigate the current applications of Digital Twin (DT) technology within the field of medical education, evaluating its advantages, limitations, and implications for future research and practice. A comprehensive search was conducted across seven authoritative databases, including PubMed, Web of Science, and China National Knowledge Infrastructure (CNKI), covering the period from the inception of each database until November 20, 2024. Data extraction was carried out using NoteExpress and EndNote software, and studies were selected based on strict inclusion and exclusion criteria. A total of 112 articles were identified in the initial search, of which eight met the criteria for final inclusion in the analysis. These studies predominantly addressed the application of DT in medical imaging education, critical care training, and medical education for individuals with disabilities. The findings reveal that DT technology has shown significant promise in enhancing teaching effectiveness, improving student engagement, and increasing overall satisfaction. However, several limitations were identified, including the nascent stage of the technology, challenges related to system integration, high resource demands, and the difficulties faced by educators in mastering and implementing the technology. Despite these challenges, the application of DT in medical education is progressing, demonstrating substantial potential to advance the modernization of educational practices, improve learning outcomes, and enhance educational efficiency. To fully realize the benefits of DT, further research is needed to address the technological, economic, and pedagogical barriers currently limiting its widespread adoption. Additionally, the development of more effective “digital-physical fusion” teaching models is essential for maximizing the utility and scalability of DT technology in medical education. 12-16-2024 <![CDATA[ This scoping review aims to investigate the current applications of Digital Twin (DT) technology within the field of medical education, evaluating its advantages, limitations, and implications for future research and practice. A comprehensive search was conducted across seven authoritative databases, including PubMed, Web of Science, and China National Knowledge Infrastructure (CNKI), covering the period from the inception of each database until November 20, 2024. Data extraction was carried out using NoteExpress and EndNote software, and studies were selected based on strict inclusion and exclusion criteria. A total of 112 articles were identified in the initial search, of which eight met the criteria for final inclusion in the analysis. These studies predominantly addressed the application of DT in medical imaging education, critical care training, and medical education for individuals with disabilities. The findings reveal that DT technology has shown significant promise in enhancing teaching effectiveness, improving student engagement, and increasing overall satisfaction. However, several limitations were identified, including the nascent stage of the technology, challenges related to system integration, high resource demands, and the difficulties faced by educators in mastering and implementing the technology. Despite these challenges, the application of DT in medical education is progressing, demonstrating substantial potential to advance the modernization of educational practices, improve learning outcomes, and enhance educational efficiency. To fully realize the benefits of DT, further research is needed to address the technological, economic, and pedagogical barriers currently limiting its widespread adoption. Additionally, the development of more effective “digital-physical fusion” teaching models is essential for maximizing the utility and scalability of DT technology in medical education. ]]> Digital Twin Applications in Medical Education: A Scoping Review wangxu yang shiyi shen dunchun yang shiyi yu zhiwei yao shihua cao doi: 10.56578/esm020401 Education Science and Management 12-16-2024 Education Science and Management 12-16-2024 2024 2 4 Article 188 10.56578/esm020401 https://www.acadlore.com/article/ESM/2024_2_4/esm020401 https://www.acadlore.com/article/ESM/2024_2_3/esm020305 An Integer Linear Programming (ILP) model was proposed to optimize academic timetables, with a focus on the School of Management at Western Galilee Academic College. The model was designed to address the dual challenges of course scheduling and faculty availability while incorporating a minor structural adjustment to enhance computational efficiency and accelerate convergence, particularly for large-scale problems. By employing this model, optimal scheduling solutions were generated within minutes, even in scenarios involving over 200 classes and 100 lecturers. The approach effectively minimizes planning time, identifies unavoidable scheduling conflicts, and highlights unschedulable classes due to constraint violations. Furthermore, the model provides actionable insights into staffing requirements, ensuring a comprehensive resource allocation strategy. Results from the application of the model during the 2023 winter semester demonstrated its capability to efficiently schedule 236 classes across multiple programs and instructional modalities. The method achieved adherence to predefined constraints, optimized the utilization of institutional resources, and enhanced overall scheduling efficiency. This case study underscores the potential of the proposed ILP framework to streamline academic timetabling processes, particularly in environments with diverse programmatic needs and complex resource interdependencies. The findings indicate that the model can be readily adapted to other academic institutions seeking to improve the effectiveness and precision of their scheduling systems. 09-29-2024 <![CDATA[ An Integer Linear Programming (ILP) model was proposed to optimize academic timetables, with a focus on the School of Management at Western Galilee Academic College. The model was designed to address the dual challenges of course scheduling and faculty availability while incorporating a minor structural adjustment to enhance computational efficiency and accelerate convergence, particularly for large-scale problems. By employing this model, optimal scheduling solutions were generated within minutes, even in scenarios involving over 200 classes and 100 lecturers. The approach effectively minimizes planning time, identifies unavoidable scheduling conflicts, and highlights unschedulable classes due to constraint violations. Furthermore, the model provides actionable insights into staffing requirements, ensuring a comprehensive resource allocation strategy. Results from the application of the model during the 2023 winter semester demonstrated its capability to efficiently schedule 236 classes across multiple programs and instructional modalities. The method achieved adherence to predefined constraints, optimized the utilization of institutional resources, and enhanced overall scheduling efficiency. This case study underscores the potential of the proposed ILP framework to streamline academic timetabling processes, particularly in environments with diverse programmatic needs and complex resource interdependencies. The findings indicate that the model can be readily adapted to other academic institutions seeking to improve the effectiveness and precision of their scheduling systems. ]]> Optimizing Academic Timetables Using Integer Linear Programming: A Case Study irit talmor doi: 10.56578/esm020305 Education Science and Management 09-29-2024 Education Science and Management 09-29-2024 2024 2 3 Article 176 10.56578/esm020305 https://www.acadlore.com/article/ESM/2024_2_3/esm020305 https://www.acadlore.com/article/ESM/2024_2_3/esm020304 The rapid advancement of artificial intelligence (AI) technology has significantly impacted the higher education sector, creating an urgent demand for composite talents equipped with interdisciplinary knowledge. The cultivation of “AI + X” talents, combining AI expertise with various domain-specific skills, has been increasingly recognized as a critical educational goal. This study explores the development and implementation of teaching practices aimed at fostering such composite talents in higher education institutions. The growing integration of AI into diverse fields necessitates the construction of a robust curriculum that combines AI technology with other disciplines, thereby enhancing students’ interdisciplinary capabilities. A comprehensive literature review and experimental research methods were employed to analyze both domestic and international trends in AI-related talent development. Additionally, a predictive model of student learning performance was developed through exploratory data analysis (EDA) and machine learning (ML), with results validating the efficacy of linear regression models in performance prediction. The research identifies key strategies for enhancing teaching practices, including reinforcing theoretical and technological knowledge, promoting personalized and practical teaching approaches, strengthening foundational disciplinary learning, and encouraging cross-disciplinary synergies. These strategies were designed to enhance students’ critical thinking and practical competencies, with the aim of preparing them for the complex challenges of a rapidly evolving workforce. Furthermore, the paper discusses how AI-driven educational reforms can support the development of key industries, such as smart cities, smart finance, and the broader digital economy. The findings suggest that integrating AI technology into educational practices is essential for the effective cultivation of “AI + X” talents. However, significant challenges remain, including the scarcity of educational resources and the need for more contemporary teaching methodologies. Further research is required to refine talent training systems and to optimize institutional mechanisms, ensuring that higher education institutions can meet the demands of future technological and economic transformations. Through sustained educational innovation, it is envisaged that a new generation of innovative and versatile professionals will be equipped to contribute to societal advancement. 09-29-2024 <![CDATA[ The rapid advancement of artificial intelligence (AI) technology has significantly impacted the higher education sector, creating an urgent demand for composite talents equipped with interdisciplinary knowledge. The cultivation of “AI + X” talents, combining AI expertise with various domain-specific skills, has been increasingly recognized as a critical educational goal. This study explores the development and implementation of teaching practices aimed at fostering such composite talents in higher education institutions. The growing integration of AI into diverse fields necessitates the construction of a robust curriculum that combines AI technology with other disciplines, thereby enhancing students’ interdisciplinary capabilities. A comprehensive literature review and experimental research methods were employed to analyze both domestic and international trends in AI-related talent development. Additionally, a predictive model of student learning performance was developed through exploratory data analysis (EDA) and machine learning (ML), with results validating the efficacy of linear regression models in performance prediction. The research identifies key strategies for enhancing teaching practices, including reinforcing theoretical and technological knowledge, promoting personalized and practical teaching approaches, strengthening foundational disciplinary learning, and encouraging cross-disciplinary synergies. These strategies were designed to enhance students’ critical thinking and practical competencies, with the aim of preparing them for the complex challenges of a rapidly evolving workforce. Furthermore, the paper discusses how AI-driven educational reforms can support the development of key industries, such as smart cities, smart finance, and the broader digital economy. The findings suggest that integrating AI technology into educational practices is essential for the effective cultivation of “AI + X” talents. However, significant challenges remain, including the scarcity of educational resources and the need for more contemporary teaching methodologies. Further research is required to refine talent training systems and to optimize institutional mechanisms, ensuring that higher education institutions can meet the demands of future technological and economic transformations. Through sustained educational innovation, it is envisaged that a new generation of innovative and versatile professionals will be equipped to contribute to societal advancement. ]]> Teaching Practices for the Cultivation of “AI + X” Composite Talents in Higher Education: Challenges and Strategies zhuang wu haiyong liu xiaoyan deng doi: 10.56578/esm020304 Education Science and Management 09-29-2024 Education Science and Management 09-29-2024 2024 2 3 Article 156 10.56578/esm020304 https://www.acadlore.com/article/ESM/2024_2_3/esm020304 https://www.acadlore.com/article/ESM/2024_2_3/esm020303 Returnee faculty play a pivotal role in international knowledge transfer and the advancement of scientific research within domestic universities. However, the effectiveness of returnees in enhancing institutional research performance remains inadequately understood. This study seeks to quantify and examine the collaborative academic networks of returnee faculty, assessing their impact on research output and funding performance. Based on an extensive academic dataset, comprehensive scientific collaboration networks (SCN) of returnees were constructed and empirically analyzed to elucidate the influence mechanisms underpinning research performance. The findings indicate that the presence of returnee faculty substantially enhances overall publication output and funding acquisition. Further, within the SCN of returnees, both academic influence and network expansion positively correlate with research productivity and funding success, whereas an increase in cooperation density appears to exert a negative effect. Additionally, the evolution of these collaboration networks was explored, revealing that returnees’ SCN display lower similarity and retention over time compared to those of native faculty. These insights offer a valuable theoretical basis for improving the management and integration of returnee faculty and optimizing the allocation of higher education resources, thereby fostering more effective pathways for enhancing institutional research outcomes. 09-29-2024 <![CDATA[ Returnee faculty play a pivotal role in international knowledge transfer and the advancement of scientific research within domestic universities. However, the effectiveness of returnees in enhancing institutional research performance remains inadequately understood. This study seeks to quantify and examine the collaborative academic networks of returnee faculty, assessing their impact on research output and funding performance. Based on an extensive academic dataset, comprehensive scientific collaboration networks (SCN) of returnees were constructed and empirically analyzed to elucidate the influence mechanisms underpinning research performance. The findings indicate that the presence of returnee faculty substantially enhances overall publication output and funding acquisition. Further, within the SCN of returnees, both academic influence and network expansion positively correlate with research productivity and funding success, whereas an increase in cooperation density appears to exert a negative effect. Additionally, the evolution of these collaboration networks was explored, revealing that returnees’ SCN display lower similarity and retention over time compared to those of native faculty. These insights offer a valuable theoretical basis for improving the management and integration of returnee faculty and optimizing the allocation of higher education resources, thereby fostering more effective pathways for enhancing institutional research outcomes. ]]> Exploring the Influence of Returnees’ Scientific Collaboration Networks on Research Performance jing li yanchun zhu chunlei qin wei zhang huiping zhang fuze li doi: 10.56578/esm020303 Education Science and Management 09-29-2024 Education Science and Management 09-29-2024 2024 2 3 Article 145 10.56578/esm020303 https://www.acadlore.com/article/ESM/2024_2_3/esm020303 https://www.acadlore.com/article/ESM/2024_2_3/esm020302 This study investigates the differences in the factors contributing to school dropout between rural and urban educational institutions in Romania, focusing on individual, family, school, and community dimensions. A sample of 557 participants, including educational directors, teachers, and administrators, was surveyed to assess the prevalence of various dropout causes. The Mann-Whitney U test was employed to identify statistically significant differences between rural and urban schools in specific dropout factors. The findings indicate that urban schools report higher incidences of individual-level issues such as substance abuse, juvenile delinquency, teenage pregnancy, and health-related problems. At the family level, urban institutions were more likely to encounter students with incarcerated parents or those placed in alternative care. School-related factors also varied, with urban schools being characterised by larger class sizes and insufficient access to counselling and guidance services, while rural schools were more affected by early school start times. In the community dimension, urban schools faced greater challenges with negative peer influences and a lack of educational facilities near students’ homes. These results suggest that the causes of dropout in urban settings are more complex, necessitating tailored interventions and resources. It is recommended that context-specific strategies be developed to address the distinct dropout factors in both rural and urban environments, thereby supporting more inclusive and effective educational policies in Romania. 09-19-2024 <![CDATA[ This study investigates the differences in the factors contributing to school dropout between rural and urban educational institutions in Romania, focusing on individual, family, school, and community dimensions. A sample of 557 participants, including educational directors, teachers, and administrators, was surveyed to assess the prevalence of various dropout causes. The Mann-Whitney U test was employed to identify statistically significant differences between rural and urban schools in specific dropout factors. The findings indicate that urban schools report higher incidences of individual-level issues such as substance abuse, juvenile delinquency, teenage pregnancy, and health-related problems. At the family level, urban institutions were more likely to encounter students with incarcerated parents or those placed in alternative care. School-related factors also varied, with urban schools being characterised by larger class sizes and insufficient access to counselling and guidance services, while rural schools were more affected by early school start times. In the community dimension, urban schools faced greater challenges with negative peer influences and a lack of educational facilities near students’ homes. These results suggest that the causes of dropout in urban settings are more complex, necessitating tailored interventions and resources. It is recommended that context-specific strategies be developed to address the distinct dropout factors in both rural and urban environments, thereby supporting more inclusive and effective educational policies in Romania. ]]> A Comparative Analysis of School Dropout Causes in Rural and Urban Romania mihaela miron larisa mistrean doi: 10.56578/esm020302 Education Science and Management 09-19-2024 Education Science and Management 09-19-2024 2024 2 3 Article 134 10.56578/esm020302 https://www.acadlore.com/article/ESM/2024_2_3/esm020302 https://www.acadlore.com/article/ESM/2024_2_3/esm020301 This study aims to investigate the academic community’s engagement with research on green policies within higher education institutions. The study examines the evolving landscape of green policy research in universities, seeking to elucidate trends in academic interest, key contributors, and thematic developments. Employing bibliometric analysis, this research scrutinizes publications indexed in the Web of Science database from 1994 to 2024, with a particular focus on keywords, co-authorship networks, and institutional affiliations. The findings indicate a notable increase in publications, particularly post-2016, reflecting a transition from broad conceptual themes to more specific applications of green policies, including sustainable management practices and performance evaluation. Central themes identified include “green”, “sustainability”, “performance”, and “management”, highlighting a shift from theoretical exploration to practical implementation. Prominent contributors, such as Wang Y and Zhang Y, alongside institutions like Tsinghua University, have significantly advanced the field. Furthermore, the study underscores a robust correlation between the growth in scientific output and the emergence of specialized sustainability journals, indicating an escalating academic demand for focused publication platforms. The results suggest that research on green policies in universities is increasingly characterized by interdisciplinary collaboration and the integration of innovative technologies and methodologies to effectively address sustainability challenges. The field of green policy application in higher education is rapidly expanding, with a well-connected, collaborative research community generating impactful work that harmonizes modern technologies and methodologies to confront sustainability issues at both global and local levels. 09-14-2024 <![CDATA[ This study aims to investigate the academic community’s engagement with research on green policies within higher education institutions. The study examines the evolving landscape of green policy research in universities, seeking to elucidate trends in academic interest, key contributors, and thematic developments. Employing bibliometric analysis, this research scrutinizes publications indexed in the Web of Science database from 1994 to 2024, with a particular focus on keywords, co-authorship networks, and institutional affiliations. The findings indicate a notable increase in publications, particularly post-2016, reflecting a transition from broad conceptual themes to more specific applications of green policies, including sustainable management practices and performance evaluation. Central themes identified include “green”, “sustainability”, “performance”, and “management”, highlighting a shift from theoretical exploration to practical implementation. Prominent contributors, such as Wang Y and Zhang Y, alongside institutions like Tsinghua University, have significantly advanced the field. Furthermore, the study underscores a robust correlation between the growth in scientific output and the emergence of specialized sustainability journals, indicating an escalating academic demand for focused publication platforms. The results suggest that research on green policies in universities is increasingly characterized by interdisciplinary collaboration and the integration of innovative technologies and methodologies to effectively address sustainability challenges. The field of green policy application in higher education is rapidly expanding, with a well-connected, collaborative research community generating impactful work that harmonizes modern technologies and methodologies to confront sustainability issues at both global and local levels. ]]> Green Policies in Higher Education Institutions: A Bibliometric Review ina nimerenco gyöngyi toró doi: 10.56578/esm020301 Education Science and Management 09-14-2024 Education Science and Management 09-14-2024 2024 2 3 Article 122 10.56578/esm020301 https://www.acadlore.com/article/ESM/2024_2_3/esm020301 https://www.acadlore.com/article/ESM/2024_2_2/esm020205 This study aims to explore and analyze the profile of UPGRIS character values within the context of campus culture development. A mixed-method approach, integrating both qualitative and quantitative methodologies, was employed. The quantitative analysis focused on identifying which UPGRIS character values—Unggul (excellence), Peduli (caring), Gigih (persistence), Religius (religion), Integritas (integrity), Sinergis (synergy)—are most prominent among students, utilizing percentage analysis. The qualitative approach involved a more in-depth examination through Focus Group Discussions (FGDs) to elucidate the meaning and manifestation of these values. A purposive sampling technique was used to select 2,554 students from seven faculties. Data were collected through psychological scales and FGDs. The findings indicate that the most pronounced character value, based on quantitative data, is religion, while excellence ranks the lowest. Notably, persistence is the highest-rated value in first-year students, whereas character traits such as excellence, caring, and integrity peak in the fifth semester. Conversely, it was observed that nearly all character values, including excellence, caring, persistence, religion and integrity, show a significant decline by the seventh semester. These results provide crucial insights into the fluctuations in character development across different stages of academic progression, offering implications for future educational and institutional interventions. 06-29-2024 <![CDATA[ This study aims to explore and analyze the profile of UPGRIS character values within the context of campus culture development. A mixed-method approach, integrating both qualitative and quantitative methodologies, was employed. The quantitative analysis focused on identifying which UPGRIS character values—Unggul (excellence), Peduli (caring), Gigih (persistence), Religius (religion), Integritas (integrity), Sinergis (synergy)—are most prominent among students, utilizing percentage analysis. The qualitative approach involved a more in-depth examination through Focus Group Discussions (FGDs) to elucidate the meaning and manifestation of these values. A purposive sampling technique was used to select 2,554 students from seven faculties. Data were collected through psychological scales and FGDs. The findings indicate that the most pronounced character value, based on quantitative data, is religion, while excellence ranks the lowest. Notably, persistence is the highest-rated value in first-year students, whereas character traits such as excellence, caring, and integrity peak in the fifth semester. Conversely, it was observed that nearly all character values, including excellence, caring, persistence, religion and integrity, show a significant decline by the seventh semester. These results provide crucial insights into the fluctuations in character development across different stages of academic progression, offering implications for future educational and institutional interventions. ]]> Profile of “UPGRIS” Character Values in Campus Culture Development titik haryati agung handayanto arri handayani padmi dhyah yulianti yanuar hery murtianto nor khoiriyah doi: 10.56578/esm020205 Education Science and Management 06-29-2024 Education Science and Management 06-29-2024 2024 2 2 Article 114 10.56578/esm020205 https://www.acadlore.com/article/ESM/2024_2_2/esm020205 https://www.acadlore.com/article/ESM/2024_2_2/esm020204 This study investigates the intricate relationships among workplace deviance, employee engagement, and research quality within the context of higher education institutions (HEIs) in Nigeria, specifically in Sokoto State. Grounded in dynamic capability theory, the normative perspective, and employee engagement theory, this study posits that workplace deviance detrimentally influences employee engagement, which in turn adversely impacts research quality. A moderated-mediation model was proposed, suggesting that employee engagement mediates the relationship between workplace deviance and research quality, while also being moderated by institutional support mechanisms. The analysis, conducted using SmartPLS 4, includes an examination of response rates, preliminary data assessment, validation of measurement instruments, and hypothesis testing. The findings reveal a complex dynamic where workplace deviance, when moderated by a supportive institutional environment, indirectly enhances research quality through increased employee engagement. This paradoxical outcome underscores the significance of fostering a positive work culture that can mitigate the adverse effects of deviant behavior, thereby promoting research excellence. The study's theoretical and practical implications suggest that mitigating workplace deviance, enhancing employee engagement, and encouraging participatory decision-making are crucial for improving research outcomes. Future research is encouraged to further explore the interplay between workplace deviance and employee engagement and to assess the generalizability of these findings across diverse institutional contexts. 06-29-2024 <![CDATA[ This study investigates the intricate relationships among workplace deviance, employee engagement, and research quality within the context of higher education institutions (HEIs) in Nigeria, specifically in Sokoto State. Grounded in dynamic capability theory, the normative perspective, and employee engagement theory, this study posits that workplace deviance detrimentally influences employee engagement, which in turn adversely impacts research quality. A moderated-mediation model was proposed, suggesting that employee engagement mediates the relationship between workplace deviance and research quality, while also being moderated by institutional support mechanisms. The analysis, conducted using SmartPLS 4, includes an examination of response rates, preliminary data assessment, validation of measurement instruments, and hypothesis testing. The findings reveal a complex dynamic where workplace deviance, when moderated by a supportive institutional environment, indirectly enhances research quality through increased employee engagement. This paradoxical outcome underscores the significance of fostering a positive work culture that can mitigate the adverse effects of deviant behavior, thereby promoting research excellence. The study's theoretical and practical implications suggest that mitigating workplace deviance, enhancing employee engagement, and encouraging participatory decision-making are crucial for improving research outcomes. Future research is encouraged to further explore the interplay between workplace deviance and employee engagement and to assess the generalizability of these findings across diverse institutional contexts. ]]> Exploring the Relationships among Workplace Deviance, Employee Engagement and Research Quality in Higher Education Institutions: A Moderated-Mediation Study in Sokoto State, Nigeria nura abubakar allumi musa muhammad lawal muhammad zayyanu doi: 10.56578/esm020204 Education Science and Management 06-29-2024 Education Science and Management 06-29-2024 2024 2 2 Article 99 10.56578/esm020204 https://www.acadlore.com/article/ESM/2024_2_2/esm020204 https://www.acadlore.com/article/ESM/2024_2_2/esm020203 A comprehensive Water Conservation Awareness Scale was developed to assess the awareness levels of preschool children regarding water conservation. This scale encompasses four distinct dimensions: personal action awareness, daily activity awareness, outdoor water use awareness, and shared responsibility awareness. The study involved 471 children from four kindergartens located in Uşak Province. The four-factor structure of the scale was validated through both exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), confirming its reliability and construct validity. The overall scale demonstrated a Cronbach’s alpha coefficient of 0.79, indicating a high level of internal consistency. The developed scale is intended to serve as a critical tool for evaluating the effectiveness of educational programs aimed at fostering water conservation awareness among young children. Additionally, it provides valuable insights for the design and implementation of early childhood education initiatives focused on environmental sustainability. The findings are expected to contribute significantly to the promotion of water-saving behaviors from an early age. 06-29-2024 <![CDATA[ A comprehensive Water Conservation Awareness Scale was developed to assess the awareness levels of preschool children regarding water conservation. This scale encompasses four distinct dimensions: personal action awareness, daily activity awareness, outdoor water use awareness, and shared responsibility awareness. The study involved 471 children from four kindergartens located in Uşak Province. The four-factor structure of the scale was validated through both exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), confirming its reliability and construct validity. The overall scale demonstrated a Cronbach’s alpha coefficient of 0.79, indicating a high level of internal consistency. The developed scale is intended to serve as a critical tool for evaluating the effectiveness of educational programs aimed at fostering water conservation awareness among young children. Additionally, it provides valuable insights for the design and implementation of early childhood education initiatives focused on environmental sustainability. The findings are expected to contribute significantly to the promotion of water-saving behaviors from an early age. ]]> Measuring Water Saving Awareness in Preschool Children gamzegül tetik metin tetik doi: 10.56578/esm020203 Education Science and Management 06-29-2024 Education Science and Management 06-29-2024 2024 2 2 Article 92 10.56578/esm020203 https://www.acadlore.com/article/ESM/2024_2_2/esm020203 https://www.acadlore.com/article/ESM/2024_2_2/esm020202 In an increasingly competitive market landscape, companies must innovate by allocating a significant portion of product sales revenue, specifically at least 22%, towards research and development (R&amp;D). Collaboration between companies and universities, which actively engage in R&amp;D, is crucial in this context. At Andalas University, the Research and Community Service Institute (LPPM) oversees R&amp;D initiatives and community services, including the management of the Science Techno Park. To achieve commercialization objectives, it is imperative to identify and address the factors that inhibit the commercialization of research products at Andalas University. The Fuzzy Analytical Hierarchy Process (FAHP) method has been employed to ascertain the primary factors impeding commercialization. The research findings indicate that the foremost factor inhibiting commercialization is resource availability, assigned a weight of 0.221. This is followed by intellectual property considerations, with a weight of 0.215, and marketing challenges, with a weight of 0.160. These insights provide a foundational basis for the development of strategies aimed at enhancing the commercialization of research products at Andalas University. 06-29-2024 <![CDATA[ In an increasingly competitive market landscape, companies must innovate by allocating a significant portion of product sales revenue, specifically at least 22%, towards research and development (R&amp;D). Collaboration between companies and universities, which actively engage in R&amp;D, is crucial in this context. At Andalas University, the Research and Community Service Institute (LPPM) oversees R&amp;D initiatives and community services, including the management of the Science Techno Park. To achieve commercialization objectives, it is imperative to identify and address the factors that inhibit the commercialization of research products at Andalas University. The Fuzzy Analytical Hierarchy Process (FAHP) method has been employed to ascertain the primary factors impeding commercialization. The research findings indicate that the foremost factor inhibiting commercialization is resource availability, assigned a weight of 0.221. This is followed by intellectual property considerations, with a weight of 0.215, and marketing challenges, with a weight of 0.160. These insights provide a foundational basis for the development of strategies aimed at enhancing the commercialization of research products at Andalas University. ]]> Obstacle Factors of Research Product Commercialization in Andalas University prima fithri alizar hasan syafrizal donard games doi: 10.56578/esm020202 Education Science and Management 06-29-2024 Education Science and Management 06-29-2024 2024 2 2 Article 79 10.56578/esm020202 https://www.acadlore.com/article/ESM/2024_2_2/esm020202 https://www.acadlore.com/article/ESM/2024_2_2/esm020201 The rapid advancement of the internet industry and the emergence of intelligent production models necessitate a transformative approach to talent cultivation in global universities. The Outcomes-Based Education (OBE) model demonstrates distinct advantages and adaptability within this evolving landscape. By defining explicit learning outcomes, incorporating flexible curriculum designs, emphasizing practical skills, adopting a philosophy of continuous improvement, implementing multi-dimensional evaluation mechanisms, and employing student-centered teaching methods, OBE establishes a robust theoretical framework and practical methodology for developing high-quality artificial intelligence (AI) talents suited to the demands of the new era. This study, centered on graduate students at the Capital University of Economics and Business, proposes three strategic dimensions for curriculum reform grounded in the OBE concept: the objectives of curriculum reform, innovative teaching models, and the implementation of the curriculum. The investigation highlights the significance of value cultivation in discipline construction, the establishment of a diversified talent training system, and the optimization of a scientifically integrated teaching framework. This research offers valuable insights, ranging from policy recommendations to practical applications, aimed at advancing the high-quality development of computer science disciplines in a contemporary context. 05-16-2024 <![CDATA[ The rapid advancement of the internet industry and the emergence of intelligent production models necessitate a transformative approach to talent cultivation in global universities. The Outcomes-Based Education (OBE) model demonstrates distinct advantages and adaptability within this evolving landscape. By defining explicit learning outcomes, incorporating flexible curriculum designs, emphasizing practical skills, adopting a philosophy of continuous improvement, implementing multi-dimensional evaluation mechanisms, and employing student-centered teaching methods, OBE establishes a robust theoretical framework and practical methodology for developing high-quality artificial intelligence (AI) talents suited to the demands of the new era. This study, centered on graduate students at the Capital University of Economics and Business, proposes three strategic dimensions for curriculum reform grounded in the OBE concept: the objectives of curriculum reform, innovative teaching models, and the implementation of the curriculum. The investigation highlights the significance of value cultivation in discipline construction, the establishment of a diversified talent training system, and the optimization of a scientifically integrated teaching framework. This research offers valuable insights, ranging from policy recommendations to practical applications, aimed at advancing the high-quality development of computer science disciplines in a contemporary context. ]]> Research on the Training Mode of Innovative and Practical High-End Talents Based on the OBE Concept zheng sun hao xu doi: 10.56578/esm020201 Education Science and Management 05-16-2024 Education Science and Management 05-16-2024 2024 2 2 Article 61 10.56578/esm020201 https://www.acadlore.com/article/ESM/2024_2_2/esm020201 https://www.acadlore.com/article/ESM/2024_2_1/esm020105 The purpose of this article is to explore the multifaceted approach required to address the alarming dropout rates and early leavers from education and training in Romanian pre-university education. We emphasize the necessity of collaborative efforts among families, educational institutions, and policymakers to implement effective strategies. As the method used, the bibliographic research was carried out, developed in parallel with the research on the realities in the field in order to provide data for their processing, accumulating data by interviewing stakeholders, analysis and interpretation. By surveying 557 internal stakeholders, primarily teachers, the research identifies critical elements in successful dropout prevention strategies, such as consistent evaluation, clear organizational environments, and strategic communication. The findings reveal significant gaps, particularly in the analysis of external factors and the recruitment and training of stakeholders, suggesting areas for improvement. Implications: Enhancing dropout prevention efforts requires a holistic approach, incorporating thorough environmental analyses, a shared mission and vision among stakeholders, and improved communication and training initiatives. We conclude that a comprehensive and adaptable strategy, inclusive of all educational stakeholders, is crucial for reducing dropout rates and fostering a supportive educational environment. 03-30-2024 <![CDATA[ The purpose of this article is to explore the multifaceted approach required to address the alarming dropout rates and early leavers from education and training in Romanian pre-university education. We emphasize the necessity of collaborative efforts among families, educational institutions, and policymakers to implement effective strategies. As the method used, the bibliographic research was carried out, developed in parallel with the research on the realities in the field in order to provide data for their processing, accumulating data by interviewing stakeholders, analysis and interpretation. By surveying 557 internal stakeholders, primarily teachers, the research identifies critical elements in successful dropout prevention strategies, such as consistent evaluation, clear organizational environments, and strategic communication. The findings reveal significant gaps, particularly in the analysis of external factors and the recruitment and training of stakeholders, suggesting areas for improvement. Implications: Enhancing dropout prevention efforts requires a holistic approach, incorporating thorough environmental analyses, a shared mission and vision among stakeholders, and improved communication and training initiatives. We conclude that a comprehensive and adaptable strategy, inclusive of all educational stakeholders, is crucial for reducing dropout rates and fostering a supportive educational environment. ]]> Dimensions of the Dropout Prevention and Early Leavers from Education and Training Strategy in Romanian Pre-University Education mihaela miron larisa mistrean doi: 10.56578/esm020105 Education Science and Management 03-30-2024 Education Science and Management 03-30-2024 2024 2 1 Article 50 10.56578/esm020105 https://www.acadlore.com/article/ESM/2024_2_1/esm020105 https://www.acadlore.com/article/ESM/2024_2_1/esm020104 In the digital age, technological advancements have reshaped the global educational landscape, prompting governments and educational institutions to recognize the critical role of research and innovative talent in driving societal progress and economic growth. Undergraduate education, as a pivotal phase for cultivating future innovators, faces unprecedented opportunities for transformation. The rise of online teaching models has catalyzed a profound pedagogical revolution, offering both flexibility in learning and significant potential for educational innovation. This study investigates the current state and influencing factors of research quality among undergraduates at the Capital University of Economics and Business within the online teaching model. The analysis is structured around four key dimensions: research preparation, research motivation, research communication, and research organization and management. Targeted recommendations are proposed to enhance these aspects, providing valuable insights for the reform of undergraduate education in the context of online learning. The findings underscore the potential of educational transformation as a development opportunity, advocating for the integration of innovative educational models with technological advancements to better align with the talent cultivation needs of the contemporary era. 03-30-2024 <![CDATA[ In the digital age, technological advancements have reshaped the global educational landscape, prompting governments and educational institutions to recognize the critical role of research and innovative talent in driving societal progress and economic growth. Undergraduate education, as a pivotal phase for cultivating future innovators, faces unprecedented opportunities for transformation. The rise of online teaching models has catalyzed a profound pedagogical revolution, offering both flexibility in learning and significant potential for educational innovation. This study investigates the current state and influencing factors of research quality among undergraduates at the Capital University of Economics and Business within the online teaching model. The analysis is structured around four key dimensions: research preparation, research motivation, research communication, and research organization and management. Targeted recommendations are proposed to enhance these aspects, providing valuable insights for the reform of undergraduate education in the context of online learning. The findings underscore the potential of educational transformation as a development opportunity, advocating for the integration of innovative educational models with technological advancements to better align with the talent cultivation needs of the contemporary era. ]]> A Study on the Influencing Factors and Enhancement Strategies of Undergraduates’ Research Quality in the Context of Online Education yating wang jiaqi du doi: 10.56578/esm020104 Education Science and Management 03-30-2024 Education Science and Management 03-30-2024 2024 2 1 Article 35 10.56578/esm020104 https://www.acadlore.com/article/ESM/2024_2_1/esm020104 https://www.acadlore.com/article/ESM/2024_2_1/esm020103 The widespread adoption of Learning Management Systems (LMSs) in educational contexts, underscored by their critical role in facilitating cloud-based training across diverse settings, serves as the foundation of this investigation. In the era of increasing integration of technology within higher education, a notable reduction in the costs associated with the creation of online content has been observed. The shift towards remote learning, precipitated by the COVID-19 pandemic, has highlighted the indispensable nature of LMSs in the delivery of specialized content, the application of varied pedagogical strategies, and the promotion of student engagement. Adaptability, defined as the ability to adjust behavior, cognition, and emotional responses in the face of new circumstances, has been recognized as a key factor in the success of online learning. This study employs sophisticated Machine Learning Techniques (MLTs) to explore the determinants of student adaptability, introducing the novel framework of Online Learner Adaptability Assessment using MLTs (OLAMLTs). Through the analysis of comprehensive datasets, which include indicators of student behavior, performance, and engagement within online platforms, MLTs facilitate the identification of patterns and correlations pertinent to adaptability. The OLAMLTs framework applies a retrospective analysis to variables such as technological proficiency, motivation, and self-regulatory capabilities, enabling the provision of customized recommendations for educators. By facilitating targeted educational interventions, the study seeks to address the disparity between the need for adaptable learners and the availability of tools designed to foster this critical attribute. The ultimate aim is to augment the resilience and efficacy of online learning platforms in anticipation of future disruptions, including pandemics or other unforeseen challenges. This research contributes to the ongoing efforts to develop a more adaptive and resilient online learning landscape, marking a significant advancement in the fields of educational technology and pedagogy. 03-12-2024 <![CDATA[ The widespread adoption of Learning Management Systems (LMSs) in educational contexts, underscored by their critical role in facilitating cloud-based training across diverse settings, serves as the foundation of this investigation. In the era of increasing integration of technology within higher education, a notable reduction in the costs associated with the creation of online content has been observed. The shift towards remote learning, precipitated by the COVID-19 pandemic, has highlighted the indispensable nature of LMSs in the delivery of specialized content, the application of varied pedagogical strategies, and the promotion of student engagement. Adaptability, defined as the ability to adjust behavior, cognition, and emotional responses in the face of new circumstances, has been recognized as a key factor in the success of online learning. This study employs sophisticated Machine Learning Techniques (MLTs) to explore the determinants of student adaptability, introducing the novel framework of Online Learner Adaptability Assessment using MLTs (OLAMLTs). Through the analysis of comprehensive datasets, which include indicators of student behavior, performance, and engagement within online platforms, MLTs facilitate the identification of patterns and correlations pertinent to adaptability. The OLAMLTs framework applies a retrospective analysis to variables such as technological proficiency, motivation, and self-regulatory capabilities, enabling the provision of customized recommendations for educators. By facilitating targeted educational interventions, the study seeks to address the disparity between the need for adaptable learners and the availability of tools designed to foster this critical attribute. The ultimate aim is to augment the resilience and efficacy of online learning platforms in anticipation of future disruptions, including pandemics or other unforeseen challenges. This research contributes to the ongoing efforts to develop a more adaptive and resilient online learning landscape, marking a significant advancement in the fields of educational technology and pedagogy. ]]> Evaluating Online Learning Adaptability in Students Using Machine Learning-Based Techniques: A Novel Analytical Approach a.b feroz khan saleem raja abdul samad doi: 10.56578/esm020103 Education Science and Management 03-12-2024 Education Science and Management 03-12-2024 2024 2 1 Article 25 10.56578/esm020103 https://www.acadlore.com/article/ESM/2024_2_1/esm020103 https://www.acadlore.com/article/ESM/2024_2_1/esm020102 Course evaluation, a critical component for the implementation of outcome-based education (OBE), provides substantial data support. The reliability, validity, and discriminative power of evaluation results are significantly influenced by the choice of course evaluation methods. An effective course evaluation method identifies weak links in the teaching process, offering a foundation and reference for continuous course improvement. This study introduces a course evaluation method based on achievement pathways, establishing the supportive relationship among course-related graduation requirement indicators, course objectives, and achievement pathways. Grounded on formative assessment, a system to quantify the achievement of teaching objectives in courses is constructed. The method has been applied to courses, such as Data Visualization and Software Engineering, at the Beijing Institute of Petrochemical Technology. Practice demonstrates that this method is capable of identifying weaknesses in the course implementation process, providing theoretical foundation and reliable assurance for ongoing course improvement. 01-30-2024 <![CDATA[ Course evaluation, a critical component for the implementation of outcome-based education (OBE), provides substantial data support. The reliability, validity, and discriminative power of evaluation results are significantly influenced by the choice of course evaluation methods. An effective course evaluation method identifies weak links in the teaching process, offering a foundation and reference for continuous course improvement. This study introduces a course evaluation method based on achievement pathways, establishing the supportive relationship among course-related graduation requirement indicators, course objectives, and achievement pathways. Grounded on formative assessment, a system to quantify the achievement of teaching objectives in courses is constructed. The method has been applied to courses, such as Data Visualization and Software Engineering, at the Beijing Institute of Petrochemical Technology. Practice demonstrates that this method is capable of identifying weaknesses in the course implementation process, providing theoretical foundation and reliable assurance for ongoing course improvement. ]]> Enhancing Course Evaluation with Achievement Pathways in Outcome-Based Education Frameworks fei yang doi: 10.56578/esm020102 Education Science and Management 01-30-2024 Education Science and Management 01-30-2024 2024 2 1 Article 10 10.56578/esm020102 https://www.acadlore.com/article/ESM/2024_2_1/esm020102 https://www.acadlore.com/article/ESM/2024_2_1/esm020101 In today’s digital age, new technological tools are increasingly becoming an indispensable part of the educational process, particularly in educating children. The development of technology, including tablet computers, and mobile phones, offers numerous opportunities for enhancing teaching methods and fostering children’s development. These technologies offer access to a wide array of digital resources, interactive content, and personalized educational experiences, thereby opening up new methods in education. However, despite the benefits, many studies underscore the potential negative impacts of utilizing new technologies in children’s education. For the above reasons, a study was conducted to examine how new technologies influence children’s learning of geometric shapes. Forty children, evenly distributed by gender and place of residence, participated in the study, undergoing testing using both mobile phones and Tablet PCs. The results revealed statistically significant differences based on the respondents’ gender, place of residence, and the devices through which the tasks were presented, particularly for certain geometric shapes. 01-24-2024 <![CDATA[ In today’s digital age, new technological tools are increasingly becoming an indispensable part of the educational process, particularly in educating children. The development of technology, including tablet computers, and mobile phones, offers numerous opportunities for enhancing teaching methods and fostering children’s development. These technologies offer access to a wide array of digital resources, interactive content, and personalized educational experiences, thereby opening up new methods in education. However, despite the benefits, many studies underscore the potential negative impacts of utilizing new technologies in children’s education. For the above reasons, a study was conducted to examine how new technologies influence children’s learning of geometric shapes. Forty children, evenly distributed by gender and place of residence, participated in the study, undergoing testing using both mobile phones and Tablet PCs. The results revealed statistically significant differences based on the respondents’ gender, place of residence, and the devices through which the tasks were presented, particularly for certain geometric shapes. ]]> Education of Children on the Recognition of Geometric Shapes Using New Technologies aleksandar trifunović svetlana čičević tijana ivanišević sreten simović slobodan mitrović doi: 10.56578/esm020101 Education Science and Management 01-24-2024 Education Science and Management 01-24-2024 2024 2 1 Article 1 10.56578/esm020101 https://www.acadlore.com/article/ESM/2024_2_1/esm020101 https://www.acadlore.com/article/ESM/2023_1_3/esm010305 Purpose: To provide reference promoting the construction of nursing courses through the analysis of research hot spots on ideological and political education in nursing courses in China; Methodology: CiteSpace and VOSviewer software were used to visualize the pertinent literature that was downloaded from CNKI, Wanfang, VIP database before December 31, 2023; Results: A total of 918 literatures were included, and the publications, authors, institutions, journals, course type, keywords of the literature were analyzed. The number of published papers had increased year by year. Publishing institutions were primarily schools, authors were mostly independent researchers, published journals were relatively concentrated, with most of them being general or provincial journals, and courses are mostly theoretical. Hotspots for current research include the integration of nursing courses in higher vocational colleges and the mining of Ideological and political elements; Conclusions: Curriculum ideology and politics have received extensive attention from nursing educators. In the future, it is necessary to strengthen the exchanges between different research institutions such as schools and hospitals, pay attention to the depth of research, develop educators' political and ideological ability, actively use a variety of teaching methods, and integrate political and ideological elements into the teaching of a diversified curriculum, so as to provide talent guarantee for the realization of "Healthy China". 12-30-2023 <![CDATA[ <p><strong>Purpose:</strong> To provide reference promoting the construction of nursing courses through the analysis of research hot spots on ideological and political education in nursing courses in China; <strong>Methodology:</strong> CiteSpace and VOSviewer software were used to visualize the pertinent literature that was downloaded from CNKI, Wanfang, VIP database before December 31, 2023; <strong>Results:</strong> A total of 918 literatures were included, and the publications, authors, institutions, journals, course type, keywords of the literature were analyzed. The number of published papers had increased year by year. Publishing institutions were primarily schools, authors were mostly independent researchers, published journals were relatively concentrated, with most of them being general or provincial journals, and courses are mostly theoretical. Hotspots for current research include the integration of nursing courses in higher vocational colleges and the mining of Ideological and political elements; <strong>Conclusions:</strong> Curriculum ideology and politics have received extensive attention from nursing educators. In the future, it is necessary to strengthen the exchanges between different research institutions such as schools and hospitals, pay attention to the depth of research, develop educators'<span style="font-family: 等线"> </span>political and ideological ability, actively use a variety of teaching methods, and integrate political and ideological elements into the teaching of a diversified curriculum, so as to provide talent guarantee for the realization of "Healthy China".</p> ]]> Research Status and Emerging Trends of Ideological and Political Education in Nursing in China: A Bibliometric Analysis xiajing lou shihua cao yangfeng shao jiani yao yankai shi bingsheng wang xiaohong zhu wenhao qi doi: 10.56578/esm010305 Education Science and Management 12-30-2023 Education Science and Management 12-30-2023 2023 1 3 Article 169 10.56578/esm010305 https://www.acadlore.com/article/ESM/2023_1_3/esm010305 https://www.acadlore.com/article/ESM/2023_1_3/esm010304 This investigation examines the influence of ChatGPT on mathematics achievement, with a specific focus on the moderating role of students’ interest in mathematics. A sample of 250 students, encompassing undergraduates pursuing a Bachelor of Science and postgraduates engaged in Masters of Philosophy and Doctor of Philosophy programs in Mathematics Education at Akenten Appiah-Menka University of Skills Training and Entrepreneurial Development (AAMUSTED), Kumasi-Ghana, was selected through random sampling. Employing a quantitative methodology, data were collected via structured questionnaires and analyzed using Amos software, version 23, to test the hypothesized relationships. The findings revealed that student interest in mathematics significantly and positively correlates with the use of ChatGPT, as evidenced by a p-value of less than 1%. Conversely, ChatGPT’s direct influence on mathematics achievement was found to be negative, though not statistically significant, with a p-value of less than 1%. Furthermore, a direct, positive, and statistically significant relationship between students’ interest in mathematics and their achievement in the subject was observed, with a p-value of less than 1%. Notably, the study identified a statistically significant positive moderation effect of students’ interest on the association between ChatGPT usage and mathematics achievement, underlined by a p-value of less than 1%. The findings advocate for a cautious integration of ChatGPT in mathematics education, emphasizing that reliance on artificial intelligence should complement, not replace, traditional learning modalities. Additionally, it is suggested that future research might benefit from employing surveys or self-evaluation tools beyond questionnaires to gather data. This study contributes to the existing body of knowledge by highlighting the nuanced role of student interest in leveraging technology-enhanced learning tools for academic success in mathematics. 12-30-2023 <![CDATA[ This investigation examines the influence of ChatGPT on mathematics achievement, with a specific focus on the moderating role of students’ interest in mathematics. A sample of 250 students, encompassing undergraduates pursuing a Bachelor of Science and postgraduates engaged in Masters of Philosophy and Doctor of Philosophy programs in Mathematics Education at Akenten Appiah-Menka University of Skills Training and Entrepreneurial Development (AAMUSTED), Kumasi-Ghana, was selected through random sampling. Employing a quantitative methodology, data were collected via structured questionnaires and analyzed using Amos software, version 23, to test the hypothesized relationships. The findings revealed that student interest in mathematics significantly and positively correlates with the use of ChatGPT, as evidenced by a p-value of less than 1%. Conversely, ChatGPT’s direct influence on mathematics achievement was found to be negative, though not statistically significant, with a p-value of less than 1%. Furthermore, a direct, positive, and statistically significant relationship between students’ interest in mathematics and their achievement in the subject was observed, with a p-value of less than 1%. Notably, the study identified a statistically significant positive moderation effect of students’ interest on the association between ChatGPT usage and mathematics achievement, underlined by a p-value of less than 1%. The findings advocate for a cautious integration of ChatGPT in mathematics education, emphasizing that reliance on artificial intelligence should complement, not replace, traditional learning modalities. Additionally, it is suggested that future research might benefit from employing surveys or self-evaluation tools beyond questionnaires to gather data. This study contributes to the existing body of knowledge by highlighting the nuanced role of student interest in leveraging technology-enhanced learning tools for academic success in mathematics. ]]> Exploring the Impact of ChatGPT on Mathematics Performance: The Influential Role of Student Interest bright asare yarhands dissou arthur francis ohene boateng doi: 10.56578/esm010304 Education Science and Management 12-30-2023 Education Science and Management 12-30-2023 2023 1 3 Article 158 10.56578/esm010304 https://www.acadlore.com/article/ESM/2023_1_3/esm010304 https://www.acadlore.com/article/ESM/2023_1_3/esm010303 Teachers face challenges when conducting their jobs (stress, work overload, lack of resources, lack of time, etc.), which may lead them to psychological problems. With the current information overload and sparsity of resources, it can be challenging to find relevant educational resources promptly. Recommender systems are designed to address the issue of information overload by filtering relevant information from a large volume of data based on user preferences, interests, or observed behavior. A recommender system can help mitigate teachers’ struggles by recommending personalized resources based on teachers’ needs. This paper presents previous works related to recommender systems in education. It highlights their techniques and limitations. Some papers relied on machine learning and/or ontology for building recommender systems, while others relied on a hybrid system comprising several techniques. The most employed recommendation techniques include collaborative filtering (CF), content-based (CB), and knowledge-based (KB) approaches. Each approach has its advantages and limitations. To overcome these limitations, several advanced recommendation methods have been proposed, such as social network-based recommender systems, fuzzy recommender systems, context awareness-based recommender systems, and group recommender systems. Our analysis reveals that existing recommender systems are learner-centered, often lacking an understanding of the teacher’s context. The continuous advancement of recommendation approaches and techniques has led to the implementation of numerous recommender systems and the development of numerous real-world applications. A context-aware personalized recommender system for teachers should consider personal and professional development goals and psychosocial state when presenting a recommendation. Years of experience, access to equipment, and commute time are some of the aspects that should be considered when designing such a system. Moreover, the studies surveyed provided detailed information about their evaluation methodologies. However, the evaluation of these systems is typically conducted using simulated or nonreal students, along with various assessment approaches such as algorithmic performance tests, statistical analysis, questionnaires, and qualitative observations. 12-30-2023 <![CDATA[ Teachers face challenges when conducting their jobs (stress, work overload, lack of resources, lack of time, etc.), which may lead them to psychological problems. With the current information overload and sparsity of resources, it can be challenging to find relevant educational resources promptly. Recommender systems are designed to address the issue of information overload by filtering relevant information from a large volume of data based on user preferences, interests, or observed behavior. A recommender system can help mitigate teachers’ struggles by recommending personalized resources based on teachers’ needs. This paper presents previous works related to recommender systems in education. It highlights their techniques and limitations. Some papers relied on machine learning and/or ontology for building recommender systems, while others relied on a hybrid system comprising several techniques. The most employed recommendation techniques include collaborative filtering (CF), content-based (CB), and knowledge-based (KB) approaches. Each approach has its advantages and limitations. To overcome these limitations, several advanced recommendation methods have been proposed, such as social network-based recommender systems, fuzzy recommender systems, context awareness-based recommender systems, and group recommender systems. Our analysis reveals that existing recommender systems are learner-centered, often lacking an understanding of the teacher’s context. The continuous advancement of recommendation approaches and techniques has led to the implementation of numerous recommender systems and the development of numerous real-world applications. A context-aware personalized recommender system for teachers should consider personal and professional development goals and psychosocial state when presenting a recommendation. Years of experience, access to equipment, and commute time are some of the aspects that should be considered when designing such a system. Moreover, the studies surveyed provided detailed information about their evaluation methodologies. However, the evaluation of these systems is typically conducted using simulated or nonreal students, along with various assessment approaches such as algorithmic performance tests, statistical analysis, questionnaires, and qualitative observations. ]]> Ontology and Machine Learning-Based Recommender System for Teacher Resource Personalization shehab eldeen ayman ayah abo el rejal doi: 10.56578/esm010303 Education Science and Management 12-30-2023 Education Science and Management 12-30-2023 2023 1 3 Article 145 10.56578/esm010303 https://www.acadlore.com/article/ESM/2023_1_3/esm010303 https://www.acadlore.com/article/ESM/2023_1_3/esm010302 Starting from social identity theory, this article explores the importance of interpersonal relationships to the work performance of teachers in private colleges and universities born in the 1990s, and examines the relationship among interpersonal relationship, organizational commitment and work performance. After conducting a questionnaire survey and analysis of 951 teachers from 19 private Colleges and Universities, the results show that aspects of interpersonal relationships, specifically caring for others and self-image, exert a significant positive impact on organizational commitment and work performance; and these factors can enhance the work performance of post-1990s teachers in these institutions through the partial mediating role of organizational commitment. Research shows that the interpersonal relationships established and maintained from public goals or private goals can promote the organizational commitment and work performance of post-1990s teachers in private colleges and universities. Higher level of interpersonal relationship can improve teachers’ identification and sense of belonging to the organization, and then improve their work performance. 12-30-2023 <![CDATA[ Starting from social identity theory, this article explores the importance of interpersonal relationships to the work performance of teachers in private colleges and universities born in the 1990s, and examines the relationship among interpersonal relationship, organizational commitment and work performance. After conducting a questionnaire survey and analysis of 951 teachers from 19 private Colleges and Universities, the results show that aspects of interpersonal relationships, specifically caring for others and self-image, exert a significant positive impact on organizational commitment and work performance; and these factors can enhance the work performance of post-1990s teachers in these institutions through the partial mediating role of organizational commitment. Research shows that the interpersonal relationships established and maintained from public goals or private goals can promote the organizational commitment and work performance of post-1990s teachers in private colleges and universities. Higher level of interpersonal relationship can improve teachers’ identification and sense of belonging to the organization, and then improve their work performance. ]]> Influence of Interpersonal Relationships and Organizational Commitment on Work Performance: An Analysis of Post-1990s Educators in Private Higher Education Institutions huaping zhang feifei wei doi: 10.56578/esm010302 Education Science and Management 12-30-2023 Education Science and Management 12-30-2023 2023 1 3 Article 132 10.56578/esm010302 https://www.acadlore.com/article/ESM/2023_1_3/esm010302 https://www.acadlore.com/article/ESM/2023_1_3/esm010301 The efficacy of political education is pivotal in developing critical thinkers and informed citizens. Traditional methods, however, face challenges such as low engagement, accessibility issues, slow adaptation to changes, and underutilization of technological advancements. This research investigates the transformative impact of integrating Artificial Intelligence (AI) and cutting-edge design strategies into political education courses at Pakistani universities. The study adopts a methodological approach that synergizes AI-based network media with traditional educational practices, subsequently evaluating the implementation’s outcomes through empirical data. The integration of AI into the educational framework has shown remarkable results: a 57% increase in the rate of education post-implementation, a 71% satisfaction rate among students regarding their learning experience, and a political accomplishment (PA) score of 81±4. These metrics indicate a substantial enhancement in the quality of political education. The research underscores the potency of AI-supported communication coaching in elevating political education standards, thereby nurturing political and ideological competencies among students. This modernization, characterized by dynamic, interactive, and globally accessible learning experiences, promises to redefine political education. It effectively dismantles historical barriers, equipping individuals to navigate the complexities of the contemporary geopolitical landscape. 12-29-2023 <![CDATA[ The efficacy of political education is pivotal in developing critical thinkers and informed citizens. Traditional methods, however, face challenges such as low engagement, accessibility issues, slow adaptation to changes, and underutilization of technological advancements. This research investigates the transformative impact of integrating Artificial Intelligence (AI) and cutting-edge design strategies into political education courses at Pakistani universities. The study adopts a methodological approach that synergizes AI-based network media with traditional educational practices, subsequently evaluating the implementation’s outcomes through empirical data. The integration of AI into the educational framework has shown remarkable results: a 57% increase in the rate of education post-implementation, a 71% satisfaction rate among students regarding their learning experience, and a political accomplishment (PA) score of 81±4. These metrics indicate a substantial enhancement in the quality of political education. The research underscores the potency of AI-supported communication coaching in elevating political education standards, thereby nurturing political and ideological competencies among students. This modernization, characterized by dynamic, interactive, and globally accessible learning experiences, promises to redefine political education. It effectively dismantles historical barriers, equipping individuals to navigate the complexities of the contemporary geopolitical landscape. ]]> Revolutionizing Political Education in Pakistan: An AI-Integrated Approach muhammad saqlain doi: 10.56578/esm010301 Education Science and Management 12-29-2023 Education Science and Management 12-29-2023 2023 1 3 Article 122 10.56578/esm010301 https://www.acadlore.com/article/ESM/2023_1_3/esm010301 https://www.acadlore.com/article/ESM/2023_1_2/esm010205 The field of educational research increasingly emphasizes predictive modeling of academic performance, focusing on identifying determinants of student success and crafting models to forecast future achievements. This investigation evaluates the efficacy of different feature selection techniques in predicting mathematics performance among Ecuadorian students, based on data from the 2021-2022 cycle of the Ser Estudiante test. Employing supervised logistic regression for classification, the study compares three feature selection methods: selection based on the highest k-scores, recursive feature elimination with cross-validation (RFECV), and recursive feature elimination (RFE). The assessment reveals that both the highest k-scores and RFECV methods are highly effective in isolating the most pertinent features for predicting mathematical prowess. These methods achieved prediction accuracies exceeding 90%, with k-scores attaining 96% and RFECV 92%. Furthermore, they demonstrated remarkable recall (94% and 97%, respectively) and F1-Score (96% and 91%, respectively). Additionally, both methods presented Receiver Operating Characteristic (ROC) curves with an area under the curve (AUC) of 99%, signifying superior discriminatory capability. The findings illuminate the critical role of judicious feature selection in enhancing the precision of predictive models for academic performance, particularly in mathematics. The results advocate for the application of these techniques in pinpointing key factors contributing to student success. This study not only contributes to the methodological discourse in educational data analysis but also provides practical insights for the Ecuadorian education system in leveraging data-driven approaches to enhance student outcomes. 09-29-2023 <![CDATA[ <p>The field of educational research increasingly emphasizes predictive modeling of academic performance, focusing on identifying determinants of student success and crafting models to forecast future achievements. This investigation evaluates the efficacy of different feature selection techniques in predicting mathematics performance among Ecuadorian students, based on data from the 2021-2022 cycle of the Ser Estudiante test. Employing supervised logistic regression for classification, the study compares three feature selection methods: selection based on the highest k-scores, recursive feature elimination with cross-validation (RFECV), and recursive feature elimination (RFE). The assessment reveals that both the highest k-scores and RFECV methods are highly effective in isolating the most pertinent features for predicting mathematical prowess. These methods achieved prediction accuracies exceeding 90%, with k-scores attaining 96% and RFECV 92%. Furthermore, they demonstrated remarkable recall (94% and 97%, respectively) and F1-Score (96% and 91%, respectively). Additionally, both methods presented Receiver Operating Characteristic (ROC) curves with an area under the curve (AUC) of 99%, signifying superior discriminatory capability. The findings illuminate the critical role of judicious feature selection in enhancing the precision of predictive models for academic performance, particularly in mathematics. The results advocate for the application of these techniques in pinpointing key factors contributing to student success. This study not only contributes to the methodological discourse in educational data analysis but also provides practical insights for the Ecuadorian education system in leveraging data-driven approaches to enhance student outcomes.</p> ]]> Comparative Analysis of Feature Selection Techniques in Predictive Modeling of Mathematics Performance: An Ecuadorian Case Study nadia n. sánchez-pozo liliana m. chamorro-hernández jorge mina javier montalvo márquez doi: 10.56578/esm010205 Education Science and Management 09-29-2023 Education Science and Management 09-29-2023 2023 1 2 Article 111 10.56578/esm010205 https://www.acadlore.com/article/ESM/2023_1_2/esm010205 https://www.acadlore.com/article/ESM/2023_1_2/esm010204 In educational settings of Pakistan, where English is utilized as the primary medium of instruction but not as an official language, the assessment of instructional text readability is crucial. This research investigates the impact of text readability on student comprehension and achievement by integrating deep learning methods with mathematical and statistical approaches. It has been observed that when suitably trained, deep learning models exhibit a significant correlation with human assessments of text readability. The investigation further illuminates the linguistic and structural elements influencing readability. Such insights are instrumental for educators and content developers in establishing standards to craft more accessible educational materials. Emphasis is placed on the exploration of Advanced Natural Language Processing (NLP) techniques, the incorporation of multilingual models, and the refinement of curricular structures to enhance readability assessments. Additionally, the study underscores the necessity of engaging with educational policymakers in Pakistan to implement accessibility guidelines. These efforts aim to reduce linguistic barriers, amplify student potential, and foster an inclusive educational ecosystem. The findings and methodologies presented in this study offer a comprehensive understanding of the challenges and solutions in optimizing English language instructional materials for non-native speakers, with potential applications in diverse multilingual educational contexts. 09-29-2023 <![CDATA[ In educational settings of Pakistan, where English is utilized as the primary medium of instruction but not as an official language, the assessment of instructional text readability is crucial. This research investigates the impact of text readability on student comprehension and achievement by integrating deep learning methods with mathematical and statistical approaches. It has been observed that when suitably trained, deep learning models exhibit a significant correlation with human assessments of text readability. The investigation further illuminates the linguistic and structural elements influencing readability. Such insights are instrumental for educators and content developers in establishing standards to craft more accessible educational materials. Emphasis is placed on the exploration of Advanced Natural Language Processing (NLP) techniques, the incorporation of multilingual models, and the refinement of curricular structures to enhance readability assessments. Additionally, the study underscores the necessity of engaging with educational policymakers in Pakistan to implement accessibility guidelines. These efforts aim to reduce linguistic barriers, amplify student potential, and foster an inclusive educational ecosystem. The findings and methodologies presented in this study offer a comprehensive understanding of the challenges and solutions in optimizing English language instructional materials for non-native speakers, with potential applications in diverse multilingual educational contexts. ]]> Evaluating the Readability of English Instructional Materials in Pakistani Universities: A Deep Learning and Statistical Approach muhammad saqlain doi: 10.56578/esm010204 Education Science and Management 09-29-2023 Education Science and Management 09-29-2023 2023 1 2 Article 101 10.56578/esm010204 https://www.acadlore.com/article/ESM/2023_1_2/esm010204 https://www.acadlore.com/article/ESM/2023_1_2/esm010203 In the epoch where globalization and knowledge economy predominate, mastery of English, fortified by its potent global stance, emerges as pivotal for multinational communication. Pursuant to this paradigm, English educators are impelled to refine teaching methodologies and accentuate perpetual learning. A comprehensive investigation into bilingual learning outcomes and efficacy employing Grammar Translation Method (GTM), Cognitive Direct Method (CDM), and Eclectic Bilingual Approaches (EBA) is herein presented. Methodologically, a quantitative experimental design complemented by qualitative interviewing was employed over a six-month experimental project, involving ninety-three university students enrolled in an intensive English language programme. The cohort was stratified into three distinctive learning groups: those exposed to GTM, CDM, and EBA, respectively. A determination of the most potent approach for English instruction represented the focal intent of this inquiry. Interviews, conducted by the researcher and teaching assistants, aimed to unearth the motivational substrates underpinning students’ English language acquisition endeavors. A meticulous cross-analysis proffers efficient language learning models, underscoring the pertinence of innovative learning approaches for English. 09-29-2023 <![CDATA[ In the epoch where globalization and knowledge economy predominate, mastery of English, fortified by its potent global stance, emerges as pivotal for multinational communication. Pursuant to this paradigm, English educators are impelled to refine teaching methodologies and accentuate perpetual learning. A comprehensive investigation into bilingual learning outcomes and efficacy employing Grammar Translation Method (GTM), Cognitive Direct Method (CDM), and Eclectic Bilingual Approaches (EBA) is herein presented. Methodologically, a quantitative experimental design complemented by qualitative interviewing was employed over a six-month experimental project, involving ninety-three university students enrolled in an intensive English language programme. The cohort was stratified into three distinctive learning groups: those exposed to GTM, CDM, and EBA, respectively. A determination of the most potent approach for English instruction represented the focal intent of this inquiry. Interviews, conducted by the researcher and teaching assistants, aimed to unearth the motivational substrates underpinning students’ English language acquisition endeavors. A meticulous cross-analysis proffers efficient language learning models, underscoring the pertinence of innovative learning approaches for English. ]]> Cognitive Perspectives on English Learning Methods: Efficiency and Achievements Under Task-Based Instruction han-kwang chen doi: 10.56578/esm010203 Education Science and Management 09-29-2023 Education Science and Management 09-29-2023 2023 1 2 Article 86 10.56578/esm010203 https://www.acadlore.com/article/ESM/2023_1_2/esm010203 https://www.acadlore.com/article/ESM/2023_1_2/esm010202 This study aimed to ascertain the learning model adopted by university lecturers in the digital era. Utilising an action research design, a mixed-method approach was employed with 32 students participating. Data were collected through two cycles of learning outcomes using online informal language learning (OILL) integrated with smartphones. These outcomes and observations were documented through photographs, video recordings, and classroom observation forms. Descriptive and content analyses were employed for evaluation and interpretation. The results revealed that a majority of students perceived the collaborative learning model, which integrates OILL with smartphones, as a technology-driven process that facilitated more flexible learning in the classroom. Crucial to this model's success was the level of student engagement, which influenced their behaviour towards OILL and smartphone use. Students in this study exhibited positive attitudes, evidenced by their enhanced self-direction, motivation, and improvements in various linguistic skills, critical thinking, and teamwork. The persistent use of the OILL and smartphone collaborative learning model by lecturers during the pandemic was observed, indicating its perceived superiority over traditional learning models, especially given the technological communication and interaction challenges experienced during the pandemic. The study underscores the importance of considering behavioural factors and the quality of OILL and smartphone applications in influencing student learning behaviour and teaching models. Therefore, the integration of OILL applications into a blended or hybrid teaching environment is suggested as an effective strategy for enhancing the quality of education in today's digital classrooms. It is recommended that future research adopt a quantitative approach with a more extensive sample to further elucidate the dynamics of learning outcomes associated with the use of OILL integrated with smartphones in the digital age. 09-20-2023 <![CDATA[ This study aimed to ascertain the learning model adopted by university lecturers in the digital era. Utilising an action research design, a mixed-method approach was employed with 32 students participating. Data were collected through two cycles of learning outcomes using online informal language learning (OILL) integrated with smartphones. These outcomes and observations were documented through photographs, video recordings, and classroom observation forms. Descriptive and content analyses were employed for evaluation and interpretation. The results revealed that a majority of students perceived the collaborative learning model, which integrates OILL with smartphones, as a technology-driven process that facilitated more flexible learning in the classroom. Crucial to this model's success was the level of student engagement, which influenced their behaviour towards OILL and smartphone use. Students in this study exhibited positive attitudes, evidenced by their enhanced self-direction, motivation, and improvements in various linguistic skills, critical thinking, and teamwork. The persistent use of the OILL and smartphone collaborative learning model by lecturers during the pandemic was observed, indicating its perceived superiority over traditional learning models, especially given the technological communication and interaction challenges experienced during the pandemic. The study underscores the importance of considering behavioural factors and the quality of OILL and smartphone applications in influencing student learning behaviour and teaching models. Therefore, the integration of OILL applications into a blended or hybrid teaching environment is suggested as an effective strategy for enhancing the quality of education in today's digital classrooms. It is recommended that future research adopt a quantitative approach with a more extensive sample to further elucidate the dynamics of learning outcomes associated with the use of OILL integrated with smartphones in the digital age. ]]> Effectiveness of Online Informal Language Learning Applications in English Language Teaching: A Behavioral Perspective muthmainnah supaprawat siripipatthanakul eka apriani ahmad al yakin doi: 10.56578/esm010202 Education Science and Management 09-20-2023 Education Science and Management 09-20-2023 2023 1 2 Article 73 10.56578/esm010202 https://www.acadlore.com/article/ESM/2023_1_2/esm010202 https://www.acadlore.com/article/ESM/2023_1_2/esm010201 During the COVID-19 pandemic, a profound impact was experienced in various domains, including education. The abrupt shift to remote learning presented challenges, especially in subjects necessitating practical problem-solving, commonly executed on traditional boards. It was observed that students at the College of Economics particularly grappled with Mathematics and Statistics during online sessions. This study aims to demonstrate the effectiveness of MS Excel in facilitating online, application-driven learning in Mathematics and Statistics. Initially, emphasis is placed on articulating basic mathematical expressions, ensuring full visibility of formulae for students. Subsequently, an illustrative approach is adopted to elucidate the resolution of intricate systems characterized by multiple equations and variables. This framework provides students with a foundation, aiding in the application of the acquired knowledge. Additionally, the versatility of MS Excel is highlighted by detailing its potential in deploying various statistical functions. For contextual relevance, data concerning human mobility during the pandemic, disseminated by Google for 135 nations globally, is employed. This research not only bridges the pedagogical gap but also offers a resilient teaching tool in uncertain times. 08-27-2023 <![CDATA[ During the COVID-19 pandemic, a profound impact was experienced in various domains, including education. The abrupt shift to remote learning presented challenges, especially in subjects necessitating practical problem-solving, commonly executed on traditional boards. It was observed that students at the College of Economics particularly grappled with Mathematics and Statistics during online sessions. This study aims to demonstrate the effectiveness of MS Excel in facilitating online, application-driven learning in Mathematics and Statistics. Initially, emphasis is placed on articulating basic mathematical expressions, ensuring full visibility of formulae for students. Subsequently, an illustrative approach is adopted to elucidate the resolution of intricate systems characterized by multiple equations and variables. This framework provides students with a foundation, aiding in the application of the acquired knowledge. Additionally, the versatility of MS Excel is highlighted by detailing its potential in deploying various statistical functions. For contextual relevance, data concerning human mobility during the pandemic, disseminated by Google for 135 nations globally, is employed. This research not only bridges the pedagogical gap but also offers a resilient teaching tool in uncertain times. ]]> Employing Microsoft Excel for Enhanced Mathematical and Statistical Online Pedagogy in Economics Amidst a Pandemic srdjan damjanovic predrag katanic doi: 10.56578/esm010201 Education Science and Management 08-27-2023 Education Science and Management 08-27-2023 2023 1 2 Article 58 10.56578/esm010201 https://www.acadlore.com/article/ESM/2023_1_2/esm010201 https://www.acadlore.com/article/ESM/2023_1_1/esm010105 This study investigates the correlation between familial backgrounds and academic performance among secondary school students. Previous research supports the assertion that parental involvement constitutes a significant factor in a child's educational journey, representing their primary exposure to societal and educational structures. To achieve the research objective, three main research questions were addressed. A survey-based approach was adopted, implementing a random sampling technique to select a total of 66 respondents, consisting of 40 females and 26 males. Data were gathered through questionnaires and subsequently analyzed using descriptive statistics. The data were presented in tabular form to facilitate a clearer understanding of students' perceptions of familial background and its potential effects on academic achievement. The study revealed a pronounced positive correlation between family background and student academic performance within the learning institution. The study concludes that familial socioeconomic status plays a pivotal role in student academic outcomes. Thus, a collaborative approach involving both parents and educators in children's educational activities is recommended to enhance academic achievement. 06-29-2023 <![CDATA[ <p>This study investigates the correlation between familial backgrounds and academic performance among secondary school students. Previous research supports the assertion that parental involvement constitutes a significant factor in a child's educational journey, representing their primary exposure to societal and educational structures. To achieve the research objective, three main research questions were addressed. A survey-based approach was adopted, implementing a random sampling technique to select a total of 66 respondents, consisting of 40 females and 26 males. Data were gathered through questionnaires and subsequently analyzed using descriptive statistics. The data were presented in tabular form to facilitate a clearer understanding of students' perceptions of familial background and its potential effects on academic achievement. The study revealed a pronounced positive correlation between family background and student academic performance within the learning institution. The study concludes that familial socioeconomic status plays a pivotal role in student academic outcomes. Thus, a collaborative approach involving both parents and educators in children's educational activities is recommended to enhance academic achievement.</p> ]]> Influence of Familial Socioeconomic Status on Academic Outcomes in Secondary Education: A Comparative Study lilian kuyiena song killian yuh nfu doi: 10.56578/esm010105 Education Science and Management 06-29-2023 Education Science and Management 06-29-2023 2023 1 1 Article 43 10.56578/esm010105 https://www.acadlore.com/article/ESM/2023_1_1/esm010105 https://www.acadlore.com/article/ESM/2023_1_1/esm010104 This study aimed to examine the correlation among motivation, organizational culture and employee performance and the mediation role of job satisfaction in higher education. A more productive and positive work environment was created by organizations by understanding the connection among these factors. This study provided valuable insight into how to create a culture of motivation and satisfaction to improve employee performance. 364 participants were selected from Yemeni and Omani universities, including academics and staff. A cross-sectional survey design was employed, with participants selected using stratified random sampling. Questionnaires were contributed online using emails and social media applications and analyzed by PLS-4. Results of Partial Least Squares Structural Equation Modeling (PLS-SEM) revealed that extrinsic motivation had a negative impact on employee performance while organizational culture had a significant positive impact in dynamic environment. Results also highlighted the positive role of job satisfaction represented by supervisor-employee engagement, incentives and promotion in enhancing performance in dynamic environment. Researchers recommended to aggressively increase job satisfaction and employee performance with extrinsic motivation in dynamic environment in Arabic region. 06-24-2023 <![CDATA[ <p>This study aimed to examine the correlation among motivation, organizational culture and employee performance and the mediation role of job satisfaction in higher education. A more productive and positive work environment was created by organizations by understanding the connection among these factors. This study provided valuable insight into how to create a culture of motivation and satisfaction to improve employee performance. 364 participants were selected from Yemeni and Omani universities, including academics and staff. A cross-sectional survey design was employed, with participants selected using stratified random sampling. Questionnaires were contributed online using emails and social media applications and analyzed by PLS-4. Results of Partial Least Squares Structural Equation Modeling (PLS-SEM) revealed that extrinsic motivation had a negative impact on employee performance while organizational culture had a significant positive impact in dynamic environment. Results also highlighted the positive role of job satisfaction represented by supervisor-employee engagement, incentives and promotion in enhancing performance in dynamic environment. Researchers recommended to aggressively increase job satisfaction and employee performance with extrinsic motivation in dynamic environment in Arabic region.</p> ]]> Examining the Mediating Role of Job Satisfaction between Motivation, Organizational Culture, and Employee Performance in Higher Education: A Case Study in the Arab Region abdullah m. al-ansi mohammed jaboob ali mohsin salim ba awain doi: 10.56578/esm010104 Education Science and Management 06-24-2023 Education Science and Management 06-24-2023 2023 1 1 Article 30 10.56578/esm010104 https://www.acadlore.com/article/ESM/2023_1_1/esm010104 https://www.acadlore.com/article/ESM/2023_1_1/esm010103 This study aimed to investigate the impact of using ChatGPT as an auxiliary learning tool on university students' learning motivation. Structural equation modeling and regression analysis were employed as the data analysis methods. Questionnaire surveys were conducted to collect data on 196 university students. The results indicated that after using ChatGPT, a negative correlation was found between tension-pressure and interest-enjoyment. Perceived competence was significantly positively correlated with interest-enjoyment, while the correlation between perceived value and interest-enjoyment was insignificant. These three variables were found to have varying degrees of influence on interest-enjoyment in the regression analysis. The study concluded that ChatGPT had a certain impact on learning motivation, but university students' frequency of use and proficiency was relatively low, requiring further training. The significance of this study lies in providing a new pedagogical approach that enables students to keep up with contemporary trends. The findings of this study have substantial theoretical and practical implications, offering novel perspectives and avenues for research on university students' learning motivation and contributing to educational reforms by providing valuable insights and directions. 05-17-2023 <![CDATA[ This study aimed to investigate the impact of using ChatGPT as an auxiliary learning tool on university students' learning motivation. Structural equation modeling and regression analysis were employed as the data analysis methods. Questionnaire surveys were conducted to collect data on 196 university students. The results indicated that after using ChatGPT, a negative correlation was found between tension-pressure and interest-enjoyment. Perceived competence was significantly positively correlated with interest-enjoyment, while the correlation between perceived value and interest-enjoyment was insignificant. These three variables were found to have varying degrees of influence on interest-enjoyment in the regression analysis. The study concluded that ChatGPT had a certain impact on learning motivation, but university students' frequency of use and proficiency was relatively low, requiring further training. The significance of this study lies in providing a new pedagogical approach that enables students to keep up with contemporary trends. The findings of this study have substantial theoretical and practical implications, offering novel perspectives and avenues for research on university students' learning motivation and contributing to educational reforms by providing valuable insights and directions. ]]> The Impact of ChatGPT on Learning Motivation: A Study Based on Self-Determination Theory lian zhou junjun li doi: 10.56578/esm010103 Education Science and Management 05-17-2023 Education Science and Management 05-17-2023 2023 1 1 Article 19 10.56578/esm010103 https://www.acadlore.com/article/ESM/2023_1_1/esm010103 https://www.acadlore.com/article/ESM/2023_1_1/esm010102 In view of the knowledge gap between what students learn in a design studio and what they do in their future work in the labor market, this study assumed that live projects supported architectural education, contributed to the development of students' capabilities, prepared them to enter the labor market, and were complementary to their knowledge acquired in traditional design studio. This study aimed to evaluate the importance of live projects and find out the extent to which students benefit from them in overcoming employment difficulties to easily get into the labor market. A descriptive and analytical approach similar to global experiences was used to monitor the progress of senior students in live projects. Measurement mechanism, such as questionnaire and observation, was used to know the skills of students acquired during the experiment. The experiment results showed that most of the students agreed that live projects provided realistic learning experiences different from the traditional design studio. In addition, the results showed that live projects helped students develop many skills, such as negotiation, persuasion, teamwork, etc. which they did not acquire through virtual projects. In the design studio, live projects were considered as a successful educational method that simulated reality and prepared the students for their professional practice. 05-15-2023 <![CDATA[ In view of the knowledge gap between what students learn in a design studio and what they do in their future work in the labor market, this study assumed that live projects supported architectural education, contributed to the development of students' capabilities, prepared them to enter the labor market, and were complementary to their knowledge acquired in traditional design studio. This study aimed to evaluate the importance of live projects and find out the extent to which students benefit from them in overcoming employment difficulties to easily get into the labor market. A descriptive and analytical approach similar to global experiences was used to monitor the progress of senior students in live projects. Measurement mechanism, such as questionnaire and observation, was used to know the skills of students acquired during the experiment. The experiment results showed that most of the students agreed that live projects provided realistic learning experiences different from the traditional design studio. In addition, the results showed that live projects helped students develop many skills, such as negotiation, persuasion, teamwork, etc. which they did not acquire through virtual projects. In the design studio, live projects were considered as a successful educational method that simulated reality and prepared the students for their professional practice. ]]> Importance and Role of Live Projects in Architectural Education Using a Descriptive and Analytical Approach merna sabree mozahim mohammed mustafa doi: 10.56578/esm010102 Education Science and Management 05-15-2023 Education Science and Management 05-15-2023 2023 1 1 Article 7 10.56578/esm010102 https://www.acadlore.com/article/ESM/2023_1_1/esm010102 https://www.acadlore.com/article/ESM/2023_1_1/esm010101 The article presents the results of the second stage of a sociological survey among students of the Russian Technological University (RTU MIREA) about their attitude to distance e-learning, problems and positive experience gained during 2020-2022. The authors examined the impact of distance e-learning through the prism of the individual qualities of students and their tendency to attribute the results of their activities to external or internal factors. 03-29-2023 <![CDATA[ The article presents the results of the second stage of a sociological survey among students of the Russian Technological University (RTU MIREA) about their attitude to distance e-learning, problems and positive experience gained during 2020-2022. The authors examined the impact of distance e-learning through the prism of the individual qualities of students and their tendency to attribute the results of their activities to external or internal factors. ]]> Students’ Attitude Towards E-Learning in Russia after Pandemic lioudmila baturina andrey simakov doi: 10.56578/esm010101 Education Science and Management 03-29-2023 Education Science and Management 03-29-2023 2023 1 1 Article 1 10.56578/esm010101 https://www.acadlore.com/article/ESM/2023_1_1/esm010101