Electronic Journal of e-Learning

Development and Validation of an AI Literacy Scale for Pre-Service Teachers in Thailand

2025-10-03T11:41:41+00:00

Artificial intelligence (AI) is having a significant impact on contemporary lives, especially in learning and instruction design. The exploration of AI literacy in teacher education is an essential foundation for the redesign of instructional approaches to enhance pre-service teachers’ AI literacy. This study aimed to develop the scale of AI literacy by employing exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) to develop the items and validate a self-assessment AI literacy scale for pre-service teachers for practical implementation for teacher development courses in undergraduate curricula. In this study, AI literacy, synthesized from relevant studies and drawing on experts in educational technology, includes four constructs: 1) recognition, 2) fundamental comprehension, 3) pedagogy, and 4) ethical use of AI, offering a comprehensive and versatile instrument for the measurement of AI literacy in teaching professional development. The instrument’s reliability and construct validity were confirmed using statistical analyses of data collected from 1,673 undergraduate pre-service students studying teaching and education at Thai universities, including both public and private universities. The findings indicated that the four constructs proposed had a good fit and showed excellent internal consistency (α = 0.94). The average variance extracted, and composite reliability (CR) values met the criteria for validity. In the EFA, the items were reduced from 42 items to 39 items, which had a Kaiser-Meyer-Olkin of 0.993 and a significant test of sphericity (p-value < .0001). The CFA results revealed a chi-Square value of 480 (p < 0.001), an RMSEA of 0.035, an SRMR of 0.022, a comparative fit index (CFI) of 0.974, and a GFI of 0.974. Thus, the AI literacy scale for pre-service teachers developed in this study is a valid and reliable instrument for assessing pre-service teachers’ AI literacy. Although it was not yet implemented in classroom settings, the established validity and reliability of the scale provide a foundation for future research and practical applications in teacher education.

AI-Supported Learning in Online Discussion Forums: A Scoping Review

2025-11-12T20:43:38+00:00

As the popularity and accessibility of artificial intelligence (AI) in learning continue to rise, online education has increasingly incorporated AI. It is imperative to investigate how AI in the scholarly community supports the learning of autonomous students. This scoping review investigated articles that employed AI in discussion forums. The objective of this study is to develop a summary that denotes the effective integration of AI in discussion forums, thereby characterizing the overall learning experience. In accordance with the search, appraisal, synthesis, and analysis (SALSA) framework, the preferred reporting items for systematic reviews and meta-analyses (PRISMA) flow diagram was employed to design the article screening and selection process. Scopus was utilized for the literature search, resulting in the identification of twelve articles that met the predetermined inclusion and exclusion criteria. The extracted articles covered the following six applications: intelligent tutoring systems, AI-assisted apps, chatbots, automatic formative assessment, AI teaching assistants, and AI-assisted lifelong learning assistants. Three types of man-machine partnerships related to the activities are discussed: student-AI partnerships, student-AI-student partnerships, and student-AI-teacher partnerships, the latter being the most commonly observed. The generated content was frequently processed through teacher adjustments and checks. Components of community of inquiry theory were adapted as indicators. Cognitive presence was observed to be more predominant than social presence, with a particular emphasis on individual learning achievements. Three distinct perspectives regarding the role of AI in learning were identified. The first perspective posited that AI functioned as a virtual teacher, supplementing the teaching functions of human teachers and delivering information to students. In the second perspective, AI facilitated students in collecting information by enabling interactions with messages or peers. In the third perspective, the significance of the automatic evaluation function, which assessed learning activities and provided feedback to enhance the system while simultaneously implementing immediate changes in the learning process, was acknowledged. Regarding the role of communication, teachers clearly intended for students to acquire knowledge through it. Despite the focus on assisting individual learners, each article encompassed references from a wide range of fields and exhibited substantial diversity overall. Consequently, the domain of discussion forums with AI was depicted through the complex interplay between technology, pedagogy, and the learning environment. This context is known as entangled pedagogies, which emphasize understanding the interconnections among these elements and their reciprocal influences. In summary, AI was predominantly utilized in the form of chatbots and GenAI in discussion forums. Emerging AI roles included virtual teachers, peer/message matching, and automated evaluation. Aggregated information was presented in a manner that supported student learning. AI also served as a conduit between students and teachers.

Interactive Edu-Video App for Teaching Electricity and Electronics Principles to Bachelor of Science in Industrial Technology (BSIT) Students

2025-10-31T17:31:01+00:00

Teaching complex electrical and electronic principles to Bachelor of Science in Industrial Technology (BSIT) students presents a significant pedagogical challenge due to the abstract nature of the concepts. Traditional static methods often fail to provide the visualization required for technical mastery. This study aimed to bridge this gap by designing, developing, and evaluating an "Interactive Edu-Video App" for the course Electricity & Electronics Principles at North Eastern Mindanao State University, Philippines. The study utilized a Research and Development (R&D) approach grounded in the ADDIE model, combined with a quasi-experimental design (non-equivalent control group). The participants included 76 BSIT students and 16 experts (instructors and industry practitioners). Data were analyzed using weighted means for validity and t-tests for learning effectiveness. The development phase produced a mobile application integrating interactive hotspots and quizzes based on Cognitive Load Theory. Expert validation rated the app as "Very Satisfactory" (M=3.61) in terms of accessibility and engagement. Experimental results revealed that while baseline knowledge was comparable (p=0.146), the experimental group using the app achieved significantly higher posttest scores (M=25.45) compared to the control group (M=17.39), with a significant learning gain (t=18.781, p<0.001). The findings confirm that interactive video is not merely a supplementary tool but a superior pedagogical strategy for technical education. The study contributes a validated, scalable mobile learning model that enhances conceptual mastery in TVET, offering a practical solution for resource-constrained industrial technology programs.

Medieval-Themed Video Games For History Teaching: A Systematic Review

2025-10-31T16:42:46+00:00

In recent years, medieval-themed video games have emerged as increasingly relevant educational tools, for history teaching, recognised for their ability to foster historical understanding, digital literacy, and critical thinking across a variety of learning environments. This systematic review investigates how these games are incorporated into educational practice and interrogates the narratives they construct about the medieval past. These aims are grounded in prior research on game-based learning and on the cultural analysis of medievalist representations. Guided by the PRISMA protocol, fourteen peer-reviewed studies published in the last ten years were identified, selected, and analysed to provide a structured and critical overview of current research in this area. The findings reveal a strong predominance of commercial titles particularly strategy and role-playing games that reproduce Eurocentric, militarised, and masculinised representations of the Middle Ages. Nevertheless, several studies report innovative pedagogical strategies that embed these digital resources within intentional didactic frameworks, aligning them with curricular objectives and supporting immersive experiences, enquiry-based learning, and the development of disciplinary historical competences. Such practices highlight the capacity of video games to operate as complex cultural artefacts, rather than mere motivational tools. Despite this potential, significant shortcomings remain. These include a lack of sustained critical engagement with symbolic and ideological representations, the scarce incorporation of gender-sensitive or intersectional perspectives, and the limited connection between explicit educational aims and the cultural content of the games. Addressing these gaps requires stronger pedagogical models that connect the analysis of digital representations with the development of historical thinking, digital literacy, and critical reflection. Overall, this study underscores both the opportunities and limitations of medieval-themed video games as didactic resources. It stresses the importance of inclusive, reflexive, and gender-aware approaches that challenge dominant historical imaginaries and contribute to the formation of culturally literate, critical, and democratically engaged citizens.

Improving Critical Thinking Skills through a Flipped Project-Based Learning Model Integrated with Mockup Media and Augmented Reality

2025-10-31T18:57:29+00:00

The rapid advancement of the Industrial Revolution 4.0 demands that vocational high school graduates possess not only technical expertise but also higher-order thinking skills, particularly critical thinking. However, many learning practices in vocational education remain limited to procedural instruction with minimal emphasis on cognitive development. This study aimed to evaluate the effectiveness of the Flipped Project-Based Learning (FPjBL) model integrated with mockup and Augmented Reality (AR) media in enhancing vocational students’ critical thinking skills compared to conventional learning approaches. This study uses a quantitative approach with a quasi-experimental design, namely pretest-posttest control group design. The research sample was grade X and XI students from six state vocational high schools in the Solo Raya area, consisting of 216 students divided into experimental and control groups. The experimental group used the FPjBL model with mockup and AR media, while the control group used conventional learning. Data were collected through critical thinking ability tests and learning motivation questionnaires. Data analysis used ANCOVA and multiple linear regression. The results showed that the experimental group experienced a significant increase in critical thinking skills compared to the control group (F (1,213) = 104.192, p <.001, partial η² = .329). The analysis and explanation indicators showed the greatest increase. Linear regression shows that learning motivation, media perception, and student activity significantly affect critical thinking skills (R²=.613). These results confirm that integrating Integration Media Mockup and Augmented Reality with FPjBL effectively strengthens students’ critical thinking and can be adopted in vocational education curricula to better prepare learners for the complex challenges of Industry 4.0.

Towards Smart and Socially Integrated Learning: A Systematic Review of LMS, Social Media and Artificial Intelligence Synergies

2025-11-26T19:54:33+00:00

This systematic literature review investigates the synergistic role of Learning Management Systems (LMS), social media (SM) and artificial intelligence (AI) in enhancing student engagement, satisfaction, and academic success within smart online and blended learning environments. LMS platforms are highlighted as the backbone of digital pedagogy, offering increasingly personalized, interactive, and adaptive experiences. The paper examines 34 peer-reviewed articles sourced from Scopus and Web of Science that address the connection between LMS and SM in higher education. In addition, a separate search query was conducted for research question 3, resulting in 11 studies that focus specifically on the intersection of AI, LMS, and SM. Findings indicate that LMS tools such as discussion forums, automated assessment, learning analytics, and interactive content modules consistently support motivation, timely feedback, and improved academic outcomes. The integration of SM enhances these outcomes by introducing familiar, interactive and collaborative dynamics that foster peer engagement and community - building. Case studies- including platforms like Moodle-VKontakte, KnowMore, and my.eskwela - show how features like newsfeeds, chatbots, and analytics can transform static learning portals into autonomous learning ecosystems. Looking ahead, the review also identifies significant potential for emerging technologies - particularly AI - to elevate the effectiveness of LMS and SM integrations. Future learning environments may incorporate AI-driven personalization, predictive analytics for early intervention, and chatbot assistants that provide academic guidance or direct students to well-being resources in an empathetic, non-diagnostic manner, influencing their engagement and overall satisfaction with learning. Immersive virtual spaces such as metaverse-based classrooms also offer new avenues for simulation-based learning and collaborative engagement. Together, these developments signal a shift toward digital ecosystems that are adaptive, community-oriented, emotionally supportive, and grounded in evidence-based design principles. Overall, this review contributes a consolidated understanding of how LMS and SM can jointly advance the quality of digital education, supported by emerging technologies such as AI. By outlining both current practices and future opportunities, it offers a clear foundation for the development of next-generation learning systems that are more engaging, equitable, and responsive to the diverse needs of today's learners.

Fostering Creativity Through Meta Virtual Project-Based Networked Learning: An In-Depth Examination

2025-10-31T17:09:51+00:00

This research explores the effectiveness of Meta Virtual Project-Based Networked Learning (Meta VPNL) in fostering student creativity in a fully digital, project-based environment. In the context of 21st-century education, creativity has become an essential skill, driving both economic progress and social innovation. However, traditional education systems often prioritize rote learning and standardized testing, leaving little room for creative exploration. This study investigates how integrating digital tools and collaborative virtual learning can overcome these constraints, thereby offering a more dynamic learning model that promotes creative thinking across domains. The Meta VPNL model was designed to create a flexible, collaborative, and interdisciplinary project environment where students can engage with real-world problems, generate novel ideas, and refine their creative processes. Using an explanatory sequential mixed-methods design, the study combines quantitative and qualitative approaches to assess the impact of the Meta VPNL model on creativity. The quantitative phase involved pre- and post-tests using the Torrance Tests of Creative Thinking (TTCT), assessing four core dimensions of creativity: originality, fluency, flexibility, and elaboration. The qualitative phase included interviews and participant observations to gain deeper insights into student experiences, perceptions, and challenges during the learning process. Results from the study reveal a significant improvement in student creativity across all four dimensions, with fluency and originality showing the most substantial gains. Furthermore, the research highlights the role of prior experience in digital project-based learning, where students with higher levels of prior experience demonstrated enhanced creative performance. Despite the positive outcomes, challenges such as technical issues, inadequate hardware, and group dynamics in virtual settings were reported. However, students were able to overcome these obstacles through collaborative efforts, peer support, and adaptive problem-solving strategies. This study demonstrates that the Meta VPNL model is an effective pedagogical strategy for nurturing creativity in the digital age. It offers valuable insights for educators aiming to integrate technology-driven, project-based learning in classrooms, paving the way for more creative, engaged, and self-directed learners.

From Assistance to Autonomy: AI Integration in Structured Research-Based Learning for Higher Education

2025-10-12T07:21:15+00:00

Despite the growing interest in artificial intelligence (AI) for science education, little is known about its role within structured research-based learning (RBL) frameworks that balance technological assistance with developing independent research competencies. Existing studies often focus on AI as an isolated tool or a single-stage intervention, leaving a gap in understanding how AI can be systematically embedded across the research process without diminishing students’ cognitive engagement. This study addresses that gap by implementing the newly developed IFTAR model, which organizes RBL into five sequential phases—Identification, Find Literature, Determine Methodology, Accommodate/Analyze/Interpret Data, and Report & Present—with AI selectively integrated into the literature search and data analysis stages. A quasi-experimental, non-equivalent control group PreTest–PostTest design was conducted with ninety undergraduate physics education students assigned to one control and two experimental groups. Cognitive outcomes were measured using a validated instrument and analyzed through classical ANCOVA, rank-based ANCOVA, and robust ANCOVA to account for assumption violations. Across all analytical approaches, both experimental groups significantly outperformed the control group, with no significant difference between the experimental conditions. These findings demonstrate that phase-specific AI integration within a transparent and scaffolded RBL framework can enhance cognitive performance while preserving methodological autonomy, offering a replicable model for purposeful AI use in STEM higher education.

Understanding Teacher Workload in Blended Learning: Insights Through the Job Demands-Resources Model

2025-12-06T14:45:48+00:00

Blended learning (BL) has become an increasingly prevalent instructional model in primary and secondary education, yet its implementation has intensified concerns about teacher workload and well-being. While prior research has documented workload pressures associated with digitalization and AI integration, there remains limited empirical insight into how teachers experience, interpret, and manage these demands in blended learning environments. Guided by the Job Demands-Resources (JD-R) model, this qualitative study investigates how BL reshapes teachers’ job demands and resources, and how educators respond to these changes in practice. Specifically, this study explores how BL influences teachers’ perceived workload (RQ1), the specific challenges they encounter during BL implementation (RQ2), and the strategies and resources they employ to manage these demands effectively (RQ3). Semi-structured interviews were conducted with ten primary and secondary schoolteachers in Flanders (Belgium) who had experience implementing blended learning. Data were analysed using a reflexive thematic analysis supported by NVivo, following a systematic and iterative coding process. The JD-R model informed the analytical lens, enabling the identification of workload-related demands, available resources, challenges and coping strategies within teachers’ everyday practice. Regarding RQ1, the findings demonstrate the dual nature of blended learning as both intensifying workload and providing supportive resources. Teachers reported increased demands from dual-mode lesson design, technological integration, expanded assessment requirements, and institutional platform mandates, leading to cognitive and emotional strain. Conversely, automated assessment, reusable digital materials, learning platforms, and inclusive tools reduced administrative effort and supported organization, partially decreasing these heightened demands. With regard to RQ2, workload pressures were intensified by challenges in digital classroom management, frequent technical disruptions, and the continuous need to learn and support new technologies. Teachers also reported emotional and organizational strain linked to ineffective collaboration, time constraints, infrastructural shortcomings, and resistance to pedagogical change, particularly during early stages of blended learning (BL) adoption. In response to RQ3, teachers described a range of coping strategies and supportive resources. These included reusing and adapting digital materials, employing AI-supported tools for automated assessment, developing digital skills through peer support, and implementing structured classroom routines. Institutional resources, such as reliable IT support, modular professional development, collaborative planning, clear BL guidelines, and leadership support, functioned as key job resources that buffered workload pressures and supported sustainable BL practices. This study contributes to the literature by applying the JD-R model to the K-12 blended learning context, offering a theoretically grounded account of how workload pressures and supports interact in teachers’ daily work. Beyond documenting challenges, the findings generate actionable insights for school leaders and policymakers, highlighting the need for systemic workload-sensitive BL implementation, structured collaborative planning, and sustained professional development aligned with instructional realities. By reframing blended learning through a job demands-resources perspective, this study advances understanding of sustainable technology integration in compulsory education.

Analysis of Blended Learning in Higher Education Based on CiteSpace (2001-2024)

2025-10-31T19:03:29+00:00

This study presents a comprehensive bibliometric analysis of blended learning in higher education (BLHE) research published between 2001 and 2024. Using CiteSpace, 2,125 publications retrieved from the Web of Science Core Collection were analyzed to map the intellectual structure, thematic evolution, and research dynamics of the field. The results indicate a sustained growth in BLHE research since 2013, with peak productivity in 2018 and 2019, reflecting the increasing academic and institutional attention to blended learning in higher education. Conference proceedings emerged as prominent publication venues, underscoring the field's strong orientation toward practice-related innovation and the rapid dissemination of emerging ideas. Document co-citation analysis identified several that have shaped the development of BLHE, with Garrison and Kanuka's (2004) Community of Inquiry framework forming a central theoretical foundation. Cluster analysis revealed 11 major research themes, demonstrating a clear evolution from foundational models of blended learning toward more learner-centered and process-oriented approaches, including blended learning foundations, self-regulated learning, game-based learning, and work-integrated learning. These clusters highlight the multifaceted nature of BLHE research and its integration with various pedagogical approaches and technologies. Our analysis also uncovered several research gaps, including a need for more diverse cultural perspectives, longitudinal studies examining long-term impacts, and research on innovative assessment strategies in blended environments. While the field has made significant progress in understanding BLHE implementation, challenges remain in addressing cultural diversity and long-term effectiveness. This study provides researchers, educators, and policymakers with insights into the field's intellectual structure, emerging trends, and future directions. Beyond mapping research trends, the findings offer practical guidance for e-learning and blended learning practice by informing course design, supporting learner self-regulation, and guiding teacher development, while methodologically advancing the field through CiteSpace-based longitudinal and structural analysis that outlines a clear future research agenda. As blended learning continues to shape higher education, addressing identified research gaps will be crucial for developing more effective, inclusive, and transformative learning experiences.