Adaptive Learning System (ALS) is one of the useful learning tools that has emerged in the technological innovation of the educational sector. Many schools and universities have adopted it for academic use since the prompt of online learning. However, the relative evaluation of ALS has been undermined in the current generation - especially among developing countries. The purpose of this study was to analyze the variables affecting the actual academic use of online ALS among students. A total of 638 students from the Philippines answered an online survey of 50-item questions derived from the eleven constructs used in this study, which were analyzed simultaneously using Structural Equation Modeling. This study utilized two important theories, integrating both the Self-Determination Theory and the Unified Theory of Acceptance and Use of Technology Use in ALS acceptance. The findings showed that autonomy, competence, price value, and facilitating conditions were the significant factors in student's behavioral intention to use the ALS. Since developing countries are trying to adapt to the current trends among developed countries, it was suggested that developers may need to make their ALS accessible through other gadgets like smartphones and tablets. The findings of this study can contribute to the educational context of digital learning to meet the needs of the students by increasing their behavioral intentions to use ALS. Further, the results provided insights and suggestions to universities and ALS developers to collaborate on improving the ALS for the student's welfare in learning.

How does generative AI-mediated informal digital learning of English speaking practice influence intrinsic motivation, self-efficacy and performance of vocational college students?

The present study, traversing Environmental Psychology of Religion within the framework of a religio‑psychological ecology, focuses on Environmental Education as a counterbalance to the ongoing destruction and degradation of the natural environment by contemporary human societies. The study proceeds from the premise that modern philosophical theories, namely utilitarian and deontological approaches, have not succeeded in adequately addressing this problem through effective environmental education. Accordingly, the study analyzes the emerging field of Environmental Psychology of Religion, a contemporary trend combining Environmental Psychology (Ecopsychology) with the Psychology of Religion, systematically examining how these domains contribute to the formation of theological and spiritual perspectives on environmental issues. It is argued that Environmental Psychology of Religion can provide an adequate theoretical framework grounded in the deeper relationship between humans and the environment as articulated in Christian theology.

This study aims to examine the key barriers to the effective implementation of digital learning in Madagascar by identifying the structural, institutional, pedagogical, and socio-economic factors that shape digital education practices within a low-income, capacity-constrained education system. The study adopts a qualitative descriptive research design using an interpretive approach. Data are drawn from peer-reviewed academic literature, empirical studies on digital learning and higher education in Madagascar, and comparative evidence from developing and post-crisis education contexts. The analysis applies a thematic analytical technique, involving systematic coding, categorization, and synthesis of recurring patterns related to infrastructure, governance, teacher capacity, access inequality, and technology adoption mechanisms. The findings reveal that the implementation of digital learning in Madagascar is constrained by interconnected barriers, including inadequate digital and physical infrastructure, limited institutional and governance capacity, insufficient teacher digital competence, and persistent socio-economic inequality that affects access and participation. Advanced technologies such as artificial intelligence offer potential benefits, yet their effectiveness remains limited by unresolved foundational conditions, and their adoption could exacerbate existing disparities if implemented prematurely. This study contributes original value by providing a context-sensitive and integrative analysis of digital learning barriers in Madagascar, moving beyond technology-centered explanations. By linking digital transformation theory with empirical evidence from a structurally constrained education system, the study offers practical insights for policy design and institutional reform. It enriches the literature on the implementation of digital education in low-income and developing contexts.

Purpose This study aims to investigate how employees enact a corporate e-learning platform in everyday work. It further examines how these enactments influence workplace learning and professional development, highlighting the ambivalent dynamics that arise when digital learning technologies become part of organisational routines. By moving beyond behaviourist approaches, this study provides a nuanced account of how digital learning is both enabled and constrained in the work context. Design/methodology/approach Adopting a constructivist, sociomaterial perspective, the case study draws on 17 semi-structured interviews with employees from various departments, including human resource (HR) and the works council, in an international conglomerate. Virtual interviews enabled screen-sharing to support data interpretation. The empirical material was examined through reflexive thematic analysis. Findings The platform configures learning as both ambivalent and increasingly individualised. Through its design and metrics, learning is subtly shaped by datafication, influencing how employees perceive their performance and organisational expectations. Combined with temporal pressures, platform flexibility and work demands, these dynamics shift responsibility for learning onto employees. Limited guidance from HR programs and managers leaves them to navigate and manage learning largely on their own. Originality/value While corporate e-learning is often evaluated quantitatively, this study provides an in-depth, qualitative account of how such platforms are experienced and enacted. It offers new insights into the ambivalent role of digital learning technologies in shaping – not merely delivering – workplace learning.

ABSTRACT Purpose While generative AI empowers language learning beyond the classroom, AI-mediated informal digital learning of English (AI-IDLE) speaking practice tends to be aimless and sporadic. Drawing on Activity Theory and the Social Support Framework, this study proposed and empirically validated a teacher support framework designed to resolve the systemic contradictions inherent in self-directed AI-IDLE speaking practice. Methodology Employing a mixed-methods quasi-experimental design over an 18-week intervention, the study involved 108 EFL undergraduates across three conditions: baseline IDLE using non-AI digital resources (CG, n = 34), self-directed AI-IDLE using the AI chatbot Doubao (EG1, n = 32), and teacher-supported AI-IDLE using the same tool (EG2, n = 42). Data on speaking proficiency, speaking self-efficacy, and speaking anxiety were collected via pre- and post-tests, triangulated with semi-structured interviews from 22 participants. Findings ANCOVA results confirmed the framework’s effectiveness, revealing a significant proficiency hierarchy (EG2 > EG1 > CG) in fluency, vocabulary, and grammar, alongside superior gains in speaking self-efficacy and reduced speaking anxiety for EG2. No significant differences were found in pronunciation. Qualitative analysis revealed that the teacher’s’ instrumental, informational, emotional, and appraisal support functioned synergistically to resolve technological and affective tensions. Originality The findings contribute to the understanding of the teacher’s role in the AI era, demonstrating how educators can shift from knowledge transmitters to designers of self-directed learning environments that maximize the pedagogical potential of generative AI.

ABSTRACT This paper develops a dynamic game with incomplete information to examine how digital technology and industrial policy drive nonlinear growth and internationalization for China’s specialized, refined, distinctive, and innovative (SRDI) firms. Three findings emerge: (1) Digital empowerment enables high-ability firms to escape linear trajectories through a convex learning function. (2) Optimal policy constitutes a three-stage subsidy menu: screening → reinforcement → commitment. This structure satisfies incentive compatibility and separates firm types to minimize resource misallocation. (3) Standard-setting power is governed by an endogenous tipping point. Once domestic market share crosses a critical mass, policy support amplifies market gains into durable rule-making advantage via network externalities. The framework complements heterogeneous-firm trade theory by endogenizing the interaction between digital learning speed and strategic technical standards.

Ethnoscience-based digital learning media in science learning is an innovation that integrates science with local culture. This study aims to identify what digital media are used to integrate ethnoscience, relevant science topics, impact on aspects of learning outcomes, and challenges in implementing ethnoscience-based digital media through a systematic literature review using the PRISMA guide. Of the 271 articles identified, 13 articles were selected based on inclusion and exclusion criteria. The results of the study show that ethnoscience-based digital media is effective in improving concept understanding, science literacy, science process skills, motivation, environmental literacy and cultural literacy. The integration of local culture in digital media helps students connect science concepts with everyday life, thus creating more relevant and meaningful learning. However, challenges such as limited technological infrastructure, teacher readiness, and student adaptation to digital learning are still major obstacles. Collaboration between educators, educational institutions, and governments is needed to overcome these constraints, by providing adequate training and resources.

The article addresses the problem of integrating intercultural innovations into the system of training future teachers of arts disciplines in the context of globalization, intercultural communication, and the digital transformation of arts education. It substantiates that the involvement of diverse performance traditions, including academic, ethnic, and contemporary digital practices, creates prerequisites for enriching students’ artistic experience and for developing their vocal and instrumental skills, interpretative autonomy, and intercultural competence. It is proven that productive integration of intercultural practices does not imply mechanical borrowing of performance models, but rather their in-depth artistic and analytical comprehension, comparative analysis of stylistic and technical parameters, as well as conscious and responsible interpretative choice. Particular attention is paid to the formation of the autonomy of the musician-performer as an interpreter capable of critical reflection, self-assessment, and pedagogically motivated adaptation of the composer’s artistic intent. The role of digital technologies and media tools in expanding access to intercultural performance experience and in transforming rehearsal, analytical, and educational-creative activities of students is highlighted. The synthesis of foreign concepts of intercultural and multicultural education makes it possible to outline methodological guidelines for the modernization of arts and pedagogical training and to identify prospects for further research related to the development of integrated intercultural modules and the implementation of blended and digital forms of learning. The prospects for further research are seen in the development and testing of integrated intercultural modules for vocal and instrumental training, as well as in the study of the specific features of forming intercultural artistic competence in conditions of blended and digital learning.

This study addresses the role of knowledge management in enhancing e-learning systems in Jordanian public universities. A questionnaire was distributed to a sample of students, where 610 questionnaires were collected to analyze students’ opinions about the impact of knowledge management on the usefulness of e-learning systems. The results showed significant positive effects of knowledge management, knowledge acquisition, and knowledge sharing on the usefulness of e-learning systems. Students indicated that knowledge management facilitates the educational process, enhances their ability to access knowledge, and increases the value of knowledge exchange among them. The findings further reveal that effective knowledge acquisition practices improve students’ engagement with digital platforms, while knowledge sharing strengthens collaboration and interactive learning experiences. The results also showed that e-learning systems are easy to use and save time for students, contributing to greater flexibility and improved academic performance. Moreover, the integration of knowledge management practices within e-learning environments supports continuous learning and promotes better communication between students and faculty members. Based on these results, the study recommended enhancing knowledge management training programs, encouraging a culture of participation among students and faculty members, and developing effective strategies for using e-learning systems. Such initiatives are expected to strengthen institutional capabilities, maximize the benefits of digital learning technologies, and contribute to improving the overall quality of education in Jordanian universities.

The present study examined the influence of Explainable Artificial Intelligence (XAI) on user trust, cognitive load, and learning outcomes in digital education environments. With the rapid integration of AI technologies in online learning systems, understanding how transparency in AI decision-making affects learners’ perceptions and performance has become increasingly important. This study adopted a quantitative research design and utilized a cross-sectional survey method to collect data from 247 university students enrolled in higher education institutions, including two universities from Punjab and one university from Karachi, Pakistan. The explainable AI, user trust, cognitive load, and learning outcomes of the students actively using digital learning platforms were measured using a structured questionnaire. The results of the collected data analyzed were done using descriptive statistics, correlation analysis, multiple regression, and chi-square tests. The findings showed that Explainable AI was significantly positively correlated with user trust (r = 0.64, p < 0.01), which implies that AI system transparency increases the levels of confidence of learners in digital learning technologies. Also, a regression analysis showed that Explainable AI led to a considerable decrease in cognitive load (b = -0.45, p < 0.001), which means that clear explanations contribute to the fact that learners interpret AI-generated results better and avoid spending extra mental energy. Moreover, chi-square tests revealed significant correlations between user trust and learning outcomes (kh2 = 21.84, p < 0.05) and cognitive load and learning outcomes (kh2 = 18.27, p < 0.05). These results indicate that the better trust and less cognitive load leads to performance improvement in AI-based learning settings. In general, this research paper demonstrates that explainable AI features should be incorporated into digital education platforms to include a higher level of transparency, build on user trust, reduce cognitive load, and, ultimately, increase the learning outcomes.

Digital textbooks are now an integral component of EFL learning environments, yet the underlying psychological mechanisms that influence digital textbook usage outcomes are still clearly unknown. This study constructs a model using the Stimulus–Organism–Response (S–O–R) theory to show how task-technology fit (TTF), which is an external stimulus variable, affects the outcomes of digital textbook usage (DTUO) by influencing the mediating role of positive emotion (POE). In this model, DTUO is defined as a second-order construct consisting of learning effectiveness (LEE) and continuance intention (COI). Using cross-sectional questionnaire data from 259 undergraduates in China, the paper employed structural equation modeling (SEM) for empirical investigation. Findings indicated that TTF positively predicted both POE and DTUO. Furthermore, POE was found to be positively associated with DTUO and played a significant mediating role in the relationship between TTF and DTUO. These findings confirm that the S-O-R theory is applicable in digital textbook learning and underscore the significance of a task-technology fit and emotional engagement. Theoretical and empirical contributions are offered for educational content developers and policymakers.

With the rapid expansion of digital learning in education, Massive Open Online Courses (MOOCs) have emerged as valuable platforms for enhancing access and quality in teacher education. This study investigates the perception of secondary grade prospective teachers towards MOOCs, with a focus on how gender and academic stream influence these perceptions. The study employed a quantitative cross-sectional survey research design. A total of 259 B.Ed. students from Mysore were selected using a stratified random sampling technique and surveyed using a validated 30-item perception scale covering five domains: study habits, learning outcomes, benefits and accessibility, usability and experience, and multimedia and resource sharing. The instrument demonstrated good reliability (Cronbach’s alpha = 0.843). The data were analyzed using descriptive statistics and independent samples t-tests followed by Cohen’s d for effect size. Results indicated that a majority of participants (79.9%) held a moderate perception of MOOCs. While gender differences in overall perception were not statistically significant, female participants rated higher in benefits and multimedia-related domains. Science stream students exhibited significantly more positive perceptions across multiple dimensions compared to their humanities counterparts. The findings suggest integrating structured MOOC orientation within B.Ed. programs, curricular integration of platforms such as SWAYAM for supplementary learning, and institutional initiatives to strengthen the digital competencies of prospective teachers for effective engagement with online learning environments.

Purpose The Fourth Industrial Revolution (Industry 4.0) is reshaping higher education institutions (HEIs) through the integration of advanced digital technologies. This study aims to examine how HEIs are responding to this transformation by analyzing institutional strategies, pedagogical shifts, faculty readiness, curriculum alignment, equity considerations and long-term policy implications. Design/methodology/approach A systematic literature review was conducted following the preferred reporting items for systematic reviews and meta-analyses protocol. Peer-reviewed studies published between 2020 and 2024 were retrieved from Scopus, Web of Science, ScienceDirect and Google Scholar. After screening and eligibility assessment, 89 high-quality studies were included for thematic synthesis. The analysis was guided by six research questions addressing strategic adoption, learning outcomes, faculty challenges, curriculum redesign, inclusion and policy frameworks. Findings The review indicates that Industry 4.0 technologies such as artificial intelligence, the Internet of Things, learning analytics and immersive systems can significantly enhance student engagement, personalization and future-oriented skill development. However, their effectiveness is constrained by persistent challenges, including uneven institutional readiness, limited faculty digital competencies, infrastructural disparities and risks of digital exclusion. Successful transformation requires coordinated institutional strategies, continuous faculty development, curriculum modernization and equity-focused digital governance. Practical implications The findings provide actionable guidance for higher education leaders and policymakers on designing scalable digital transformation strategies, strengthening faculty capacity, aligning curricula with Industry 4.0 competencies and ensuring inclusive access to digital learning environments. Originality/value This study contributes a six-dimensional integrative framework that synthesizes fragmented research on Industry 4.0 adoption in higher education, offering a holistic perspective to support future empirical research and policy development.

This study investigates the effectiveness of analogue and digital reading interventions in heterogeneous primary school classes, examining how student characteristics influence intervention outcomes. Using data from 15 third-grade classes participating in the «Digital Equity» project, we implemented collaborative, student-centred reading interventions in both analogue and digital formats. The study employed a quasi-experimental pre-post design with multilevel modeling and recursive partitioning to identify differential intervention effects. Results reveal that intervention effectiveness varies significantly across student subgroups. While conventional analyses showed only marginal effects, algorithm-based subgroup analyses identified that highly motivated girls benefited significantly from analogue interventions. Digital interventions showed no positive effects, and surprisingly, frequent digital media users responded negatively to digital reading formats. These findings challenge assumptions about universal classroom interventions and digital learning, suggesting the need for more targeted, differentiated approaches to reading instruction that account for individual student characteristics.

General Background: The growing integration of Artificial Intelligence (AI) in higher education has introduced new opportunities for digital learning and academic support. Specific Background: Along with AI adoption, students’ academic achievement is also associated with internal learning capacity such as self-regulated learning, digital literacy, and the management of study load. Knowledge Gap: However, limited studies examine these variables simultaneously within a single analytical framework to understand their relationship with academic achievement. Aims: This study analyzes the relationship between Artificial Intelligence usage frequency, self-regulated learning, digital literacy, study load, and student academic achievement. Results: The findings indicate that the frequency of AI usage does not show a significant relationship with academic achievement, while self-regulated learning, digital literacy, and study load show significant positive relationships with student academic achievement. Digital literacy and study load also do not moderate the relationship between AI usage frequency and academic achievement. Novelty: This study proposes an integrated conceptual examination of Artificial Intelligence usage together with self-regulated learning, digital literacy, and study load in explaining student academic achievement. Implications: The results suggest that universities should prioritize strengthening self-regulated learning, improving critical digital literacy, and designing proportional study loads to support the optimal use of AI in the academic learning process. Highlights • Self-regulated learning shows a positive relationship with student academic performance.• Digital literacy and study load are associated with higher academic achievement levels.• Artificial intelligence usage frequency is not the primary determinant of academic scores. Keywords Artificial Intelligence; Self-Regulated Learning; Digital Literacy; Study Load; Academic Achievement

In the context of rapid digitalization, social media has become an important channel for Thai undergraduates to access diverse cultures and engage in intercultural communication. For students majoring in Chinese, social media not only provides opportunities for language input and cultural experience but may also influence the development of their intercultural communicative competence. This study targeted undergraduate students majoring in Chinese at a university in Thailand and collected data using a questionnaire survey, yielding 416 valid responses. Data was analyzed using SPSS. Through regression analysis, this study examined the predictive effect of social media use frequency on intercultural communicative competence. The findings reveal that the frequency of using social media has a significant positive impact on students' intercultural communication competence and can accurately predict their performance in cultural understanding, intercultural sensitivity, and communication strategies. From a digital learning perspective, this study reveals the relationship between social media use and intercultural communicative competence and provides empirical implications for Chinese language teaching and intercultural education in Thai universities.

CHAPTER 1 – INTRODUCTION 1.1 Background of the Study In the last decade, digital learning has rapidly transformed the education landscape. Traditional classroom-based teaching has been supplemented—and in many cases replaced—by online platforms, virtual classrooms, and intelligent learning systems. With the increasing availability of digital devices and the rise of high-speed internet, learners today have access to a vast amount of educational content anytime, anywhere. However, the biggest challenge in digital learning is personalization. Most learning management systems (LMS) still operate using a one-size-fits-all approach, where every learner receives the same content, difficulty level, and learning path regardless of their unique needs. This results in reduced engagement, uneven learning progress, and difficulty in addressing individual weaknesses. To overcome these limitations, Intelligent Tutoring Systems (ITS) have emerged. ITS uses artificial intelligence techniques to simulate the role of a human tutor by monitoring student performance, predicting learning needs, and adapting content accordingly. Modern ITS platforms apply Machine Learning (ML), Deep Learning (DL), NLP, and recommendation algorithms to deliver customized content. The evolution of AI-driven learning has led to the development of AI tutors—systems capable of understanding learner profiles, predicting performance, recommending suitable content, and providing real-time feedback. Although many AI tutors exist, most rely on single-model approaches such as Collaborative Filtering or Content-Based Filtering, which often suffer from cold-start issues, limited personalization depth, and low accuracy. To address these issues, researchers have begun exploring Hybrid Machine Learning Models that combine the strengths of multiple algorithms. A hybrid approach enhances personalization quality, improves prediction accuracy, and adapts effectively to diverse learning behaviors. This thesis explores the development of an Intelligent AI Tutor that uses a Hybrid Machine Learning Model to deliver personalized content recommendations and adaptive learning experiences for students.

Digital technology has significantly broadened educational prospects in science, with gamification emerging as a vital instrument. However, its full potential in advancing science education remains predominantly unexamined. This study examines the influence of digital game-based learning on the motivation of junior secondary school students in fundamental science in Gombe State, Nigeria. The study utilises a quasi-experimental methodology including 140 people. The experimental group utilised a 3D instructional digital game through Cospaces Edu, specifically tailored for designated themes within the junior secondary II fundamental science curriculum. The control group engaged in a tabletop game encompassing identical principles. Participants were randomly allocated to the treatment and control groups. Eight fundamental science educators submitted comprehensive studies regarding their pupils' motivation to comprehend scientific concepts. The research employed the validated Basic Science Students’ Motivation Questionnaire (BSSMQ, r = 0.91), which was administered following a six-week intervention period. Data were examined using descriptive analysis for research questions and the Mann-Whitney statistical test for hypotheses at a significance level of 0.05. Data from in-depth interviews were manually transcribed, analysed, and coded to discern patterns. The results indicated the superiority of the CoSpaces Edu application compared to conventional in-person activities. The main result is that incorporating digital games into fundamental science classes markedly increases students' motivation to comprehend scientific concepts compared to conventional tabletop games. This study emphasises the importance of technological integration in science education and stresses the need for varied instructional approaches.

The COVID-19 pandemic significantly accelerated digital transformation in education. Traditional face-to-face learning was rapidly replaced by e-learning, highlighting the urgent need for digital competence among educators and students. The present study examines how the pandemic acted as a catalyst for the development of digital competencies within the educational sectors in post-Yugoslav states. It explores the challenges and opportunities presented by e-learning during the pandemic period and considers its long-term implications. Online surveys with 424 educators and 1,549 students were conducted in Bosnia and Herzegovina, Croatia, North Macedonia, Montenegro and Slovenia to assess their experiences with digital learning tools and platforms. In addition, statistical data on e-learning adoption rates and technological advancements in education were analysed. The findings indicate a notable increase in digital competence among both educators and students, while also revealing persistent gaps in digital readiness. The most significant improvements were observed in digitally less-developed countries, where reliance on free-of-charge software played a crucial role. Looking ahead, it is essential to integrate digital competency training into educational curricula to ensure sustainable and effective use of technology in education. The study underscores the importance of institutional investment in digital training and infrastructure to support long-term digital learning strategies. It also offers insights into how a crisis can accelerate digital transformation in education, highlighting both the benefits and challenges of e-learning adoption.