2026-02-24
Yuxin Zhang
Artificial Intelligence Generated Content (AIGC) is becoming a valuable tool in education. It supports personalized, interactive, and scalable learning. However, little is known about how preschool teachers continue using AIGC in their daily practice. This study explores the key factors that influence their sustained intention to use AIGC technologies. It integrates three theoretical models, including Technology Acceptance Model (TAM), Expectation Confirmation Model (ECM), and Flow Theory, into a unified framework. Data were collected through a questionnaire survey of 433 preschool teachers in China. The results were analyzed using both Partial Least Squares Structural Equation Modeling (PLS-SEM) and Fuzzy Set Qualitative Comparative Analysis (fsQCA). Results indicate that confirmation and perceived usefulness are robust predictors of continuance, whereas perceived ease of use exerts a comparatively smaller effect. The fsQCA uncovers three equifinal configurations that lead to high continuance intention, highlighting complementary pathways that combine confirmation, usefulness, attitude, satisfaction, and flow experience. These findings offer both theoretical and practical implications. The stronger influence of flow experience and satisfaction over perceived usefulness challenges the rational evaluation assumption of classic technology adoption models. This underscores that affective engagement, not rational utility, plays the critical role in shaping long-term adoption. To promote the effective integration of AIGC in preschool contexts, administrators could adopt differentiated support strategies tailored to teachers’ motivational profiles. They should strengthen confirmation through real-time feedback and targeted training that aligns with expectations. Systems should deliver stable performance and preschool-suited interfaces to raise satisfaction. Platforms must cultivate flow by incorporating gamified interaction, adaptive content creation, and visually engaging features. While these findings are grounded in the Chinese preschool setting, they may inform AIGC adoption strategies in similar educational contexts.
2026-02-24
Mpho-Entle Puleng Modise, Ntandokamenzi Penelope Dlamini
The shift to distance learning is the reality of many higher education institutions. The COVID-19 pandemic emphasised to higher education institutions (HEIs) the value of combining several teaching and learning modalities to provide high-quality education to the general public. Numerous studies have been conducted worldwide on blended education; however, the focus has been mainly on alternating online and face-to-face sessions and rarely on concurrently using these two modes of teaching and learning, especially HEIs in the Global South and Asia. This study focuses on the HyFlex learning model, which entails a multimodal delivery solution and approach, providing students with a combination of face-to-face and distance teaching and learning through a mix of contact, online synchronous, and asynchronous classes. Unlike the blended learning model, HyFlex offers students the greatest flexibility to decide and choose their educational experiences, including how, where and when they would like to learn, which may support consistent learning outcomes across different modalities. This review aims to explore the implementation and impact of HyFlex learning in higher education in the Global South and Asia. Through a systematic review, this research examined peer-reviewed papers on HyFlex, published between 2010 and 2024, and sourced from Scopus, Web of Science and ProQuest. The findings highlight the contextual nature of HyFlex and identify research gaps, including the longer-term impact of HyFlex learning approaches. The study advances knowledge on how HyFlex can be successfully implemented in higher education settings in developing countries, thereby meeting the needs of diverse students and providing them with the necessary support.
2026-02-24
Stefan Stenbom, D. Randy Garrison, Aras Bozkurt
This dialogue with D. Randy Garrison and Stefan Stenbom revisits the foundational Community of Inquiry (CoI) framework in the context of rapid digital transformation and the rise of artificial intelligence (AI). Originally conceived for text-based online learning, the framework’s core elements—Social, Cognitive, and Teaching Presence—remain robust guides for fostering deep, collaborative learning in today’s complex multimodal and multilayered environments. The conversation explores how these presences manifest differently across various media, acknowledging that while indicators may evolve, the underlying structure remains constant. A central theme is the integration of AI, viewed primarily as a tool capable of augmenting human roles within the existing CoI structure. AI can support teaching presence tasks, simulate social cues, and even assist cognitive processes, but rather than constituting a new presence, it highlights the robustness and adaptability of the existing model in accommodating new technologies. However, maintaining the authenticity of community and safeguarding genuine emotional connection in AI-rich environments are critical challenges. The conversation highlights the potential risk of AI flattening inquiry into mere information assimilation if not implemented thoughtfully. Ultimately, the CoI framework is presented as an essential guide, emphasising the preservation of human agency, critical reflection, and collaborative meaning-making as core educational purposes, even as technology advances. The need to deliberately slow down inquiry for reflection in fast-paced, AI-driven contexts is further stressed.
2026-02-24
Eric Awi, Audrey Joyce Valderrama, Geraldine Lagmay
This study investigated the effectiveness of Open Educational Resources (OERs) in enhancing science learning outcomes and student perceptions within a Hyflex instructional setup, characterized by limited face-to-face interaction. Using a quantitative one-group pretest-posttest quasi-experimental design, the research was conducted at Colegio de San Juan de Letran and involved 724 students from Grades 7 to 12. Participants completed pre- and post-tests in science, along with perception surveys administered before and after the OER intervention. Quantitative analysis revealed statistically significant improvements in post-test scores across all grade levels (p < .001), with effect sizes ranging from moderate (d = 0.50) to large (d = 1.39). These gains highlight the positive impact of OERs on student academic performance. In parallel, the Wilcoxon Signed-Rank Test on survey responses showed significant increases in student engagement, enjoyment, and perceived learning quality, with several items reaching very large effect sizes, particularly in Grades 8 and 9. The findings suggest that OERs are not only effective in promoting academic achievement but are also well-received by students in a flexible learning context. This research contributes to the growing literature advocating for OER adoption in secondary science education and underscores its value in supporting accessible, engaging, and high-quality instruction in blended learning environments.
2026-02-24
Karina Jackson, Royce Kimmons, Heather Leary, Richard West
Open educational resources (OER) have the potential to significantly impact the landscape of higher education. However, many users of OER find it difficult to adopt programmatically due to the barriers of awareness, quality assurance, institutional culture, and sustainability. This case study of the successful adoption of OER in an education department serves as a look into the conditions and practices that allowed for the promotion, continued use, and significant production of open educational resources. Six faculty members in the department were interviewed about their experiences with OER. The results indicate that the climate, technology, and opportunity costs surrounding tenure and promotion were key factors in the faculty’s experience with acting on their inclinations toward openness.
2025-11-25
Mncedisi Christian Maphalala, Ntombikayise Nkosi
This conceptual study explores and proposes strategies for enhancing security and academic integrity within the Open and Distance e-learning (ODeL) context, adhering to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocols. As higher education continues to evolve, the reliance on online assessments has become more prominent, necessitating robust measures to uphold the security and integrity of the assessment processes. The study analysed peer-reviewed empirical research published from 2014 to 2024 and explored unique challenges in the ODeL environment. It provides an in-depth analysis of various proctoring methods, their applicability, and the ethical considerations inherent in their implementation. The findings emphasise the importance of strategically integrating proctoring technologies tailored to meet the specific needs of ODeL students. This includes implementing asynchronous proctoring and offering flexible scheduling. They highlight the need to balance security measures and create a supportive learning environment. It also advocates for transparency, ethical use, and inclusivity. The experiences of stakeholders draw attention to concerns regarding highly anxious students and the limitations of technical support. Ethical considerations indicate the importance of addressing the digital divide and promoting fairness. The study suggests continuously adapting proctoring strategies to ensure both integrity and a positive user experience. The study contributes to the ongoing discourse on proctoring in online assessments within the ODeL context. This study contributes a framework-guided synthesis of proctoring practices in ODeL. Highlighting the balance between technological enforcement and inclusive, ethical learning environments.
2025-11-25
Malissa Maria Mahmud, Wali Khan Monib, Atika Qazi, Shiau Foong Wong, Chandra Reka Ramachandiran, Siti Norbaya Azizan
Artificial Intelligence (AI) is rapidly transforming education, yet many institutions lack a comprehensive framework to integrate AI effectively. This paper develops an AI Education Competency Framework to guide the integration of AI in educational settings through a systematic literature review. Methodologically, a rigorous systematic literature review (SLR) was conducted following PRISMA guidelines, ensuring methodological rigor and empirical grounding. Key databases (e.g., Google Scholar, IEEE Xplore, SpringerLink) were searched for studies on AI frameworks in education, yielding 21 relevant sources. The analysis resulted in a novel framework which is built on four pillars—Foundation, Integration, Innovation, and AI Citizenship, encompassing fundamental AI knowledge, curricular and administrative integration, AI-driven innovation in pedagogy, and ethical AI use. The proposed framework informed by findings from these studies, addressing gaps such as the lack of unified approaches that combine technical, pedagogical, and ethical dimensions. The framework provides a holistic strategy for AI integration in education, including for open and distance education contexts, bridging theoretical and practical aspects. In discussion, we highlight the framework’s contributions in filling identified gaps, its potential implementation challenges, and recommendations for educators and policymakers. The study concludes that the AI Education Competency Framework offers significant contributions by aligning AI advancements with educational competencies, ensuring stakeholders are prepared to navigate AI’s complexities responsibly and effectively.
2025-11-25
Aras Bozkurt
Generative Artificial Intelligence (GenAI) is being rapidly adopted by academic and policy leaders, often with a focus on its revolutionary benefits while overlooking its significant, undisclosed environmental costs. This paper deconstructs the physical footprint of GenAI, moving beyond the abstract cloud to analyze its resource-intensive infrastructure. It synthesizes current research into four key areas of concern. First, it reframes the energy debate, demonstrating that the operational inference (use) phase is the dominant long-term cost, with one study estimating its carbon footprint to be 25 times higher than the one-time training cost. Second, it reveals the hidden water footprint, which includes both direct Scope 1 consumption for cooling and the larger Scope 2 consumption from offsite electricity generation, a critical issue as two-thirds of new US data centers are in water-stressed areas. Third, it examines the systemic and material impacts, including the full Life Cycle Assessment (LCA) of hardware (e-waste, raw material extraction) and the rebound effect (Jevons’ Paradox), where efficiency gains increase overall demand. A new side effect includes AI tools propagating non-green code. Finally, the paper highlights the critical lack of corporate transparency, a black box of proprietary data that prevents effective governance. This paper argues that a full-cost accounting is necessary and concludes by proposing actionable recommendations from the Green AI and Green Lean movements. Solutions include mandating public reporting, prioritizing smaller models, and implementing sustainable techniques like model pruning and quantization.
2025-11-25
Terry Anderson, Aras Bozkurt
This scholarly dialogue captures the critical perspective of Dr. Terry Anderson, a foundational theorist in online and distance education, at a time when the field faces a paradigm shift driven by artificial intelligence. The conversation revisits Anderson's seminal contributions, including the Interaction Equivalency Theorem and the Community of Inquiry (CoI) framework, examining their relevance and limitations in an era where AI can mediate all forms of educational interaction. A central theme emerges from Anderson's analysis: a sharp distinction between AI's immense potential in the cognitive domain—offering personalized content and scalable learning support—and its profound inability to replicate the affective and intuitive roles of human teachers and peers. He argues that while AI will dominate cognitive presence, the inspiration, care, and deep social connection vital for motivation remain uniquely human endeavors. Looking forward, Anderson presents a vision where AI's greatest promise lies in enabling personalized learning and forcing a long-overdue revolution in assessment, potentially scaling ancient methods like the viva voce. However, he issues a stark warning against the risks of information monopolies and highlights the field’s abiding responsibility to ensure equitable access, championing social justice as a core principle for the next generation of online education.
2025-08-10
Tony Bates, Aras Bozkurt
This scholarly conversation features Dr. Tony Bates, a leading voice in educational technology, discussing the future of online and digital learning. The conversation, led by Aras Bozkurt, explores the multifaceted impact of digital transformation and artificial intelligence (AI) on higher education. Dr. Bates argues that while technology offers transformative potential, it is often superficially “grafted on to traditional ways of teaching,” thereby failing to enhance learner agency. He identifies a critical pedagogical tension between behaviorist approaches, which align with the content-delivery strengths of current Large Language Models (LLMs), and constructivist approaches needed to develop higher-order skills. Dr. Bates posits that the rise of AI necessitates a fundamental shift for instructors—away from content delivery and toward facilitating skills such as critical thinking, problem-solving, and digital literacy. He advises institutional leaders to foster team-based course design, advocate for the regulation of AI to prevent monopolies, and build in-house expertise to strategically evaluate and integrate emerging technologies. The dialogue concludes with a pragmatic vision for a future where human educators focus on uniquely human skills, using AI as a powerful tool to support, rather than supplant, meaningful learning.
2025-08-10
Oluyemi A. Adegbite, Agnieszka Palalas
The reported study investigated the availability of institution-wide mental health support services and action plans for online students to address mental health impairments in Nigerian universities. The research questions explored how Nigerian online students perceived the mental health support services provided by their institutions before, during, and after mental health crises. Employing a descriptive phenomenological paradigm, semi-structured interviews were conducted with nine online students from Nigerian universities. The findings revealed a limited understanding of mental health issues among online students. Additionally, they highlighted the absence of institutional support services or action plans for promoting mental health wellness among Nigerian online students. To address these issues, the study recommends a pre-admission assessment of students’ readiness to succeed in the online learning environment, an online learner orientation program, and mental health education to raise awareness of mental health impairment symptoms. This study contributes to the scarce literature on online students’ mental health policy and support systems in Nigeria’s distance education platforms. Also, it provides online education stakeholders with insights to inform online students’ mental health policy. Ultimately, it may foster innovative practices and capacity-building programs among the online learning providers in Nigeria.
2025-07-09
Tian Belawati, Dimas Prasetyo
This paper presents the findings of a pilot study on the use of generative AI (GAI) in tutorial sessions within a large-scale distance education institution in Indonesia. The primary aim of the experiment was to assess the impact of GAI-based tutoring on student engagement and academic achievement. A secondary objective was to explore how GAI could reduce the workload of human tutors by automating routine tasks, such as responding to frequently asked questions and providing initial feedback, thereby allowing human tutors to concentrate more on moderation and higher-order teaching tasks. The development team adopted a modular design approach, utilizing OpenAI’s ChatGPT models (versions 3.5 and 4.0) and integrating them with the Moodle learning management system. The resulting system consisted of three core modules: Management, LMS Integration, and Backend. These modules enabled efficient administration, seamless integration with the existing learning platform, and effective generation of AI responses for student interactions. The study involved data collection from four online courses with a total of 37,743 students. The results indicated that students in GAI-assisted classes participated more actively in discussion forums and achieved slightly higher scores in their assignments compared to those in non-GAI-assisted settings. These findings suggest that GAI-based tutor assistants can provide considerable enhancements in online learning environments, particularly in fostering engagement and improving student outcomes. The study suggest further improvement to make it more effective and have a greater positive impact on student engagement and achievement.