The metaverse and artificial intelligence (AI) are increasingly intersecting in educational contexts, yet limited empirical research has examined how generative AI avatars function within socially interactive virtual environments. This study investigates the deployment of generative AI avatars within a socio-educational metaverse environment. Using a developmental evaluation approach, data were collected through interviews with seven institutional stakeholders, teacher-generated reflections, internal documentation, embedded user feedback captured through in-platform reporting tools, and longitudinal field memos across an iterative deployment cycle. Findings indicate that the transition from scripted NPCs to generative AI avatars recalibrated users’ attribution of agency, intensified dialogic unpredictability, and elevated social realism beyond visual fidelity. Voice-mediated interaction emerged as a threshold mechanism for co-presence, while algorithmic improvisation exposed tensions between pedagogical intent and stochastic response generation. The deployment further revealed affective frictions, expectation misalignments, and the mediating role of AI literacy in shaping trust, participation, and interpretive coherence. Overall, the study advances a sociotechnical understanding of AI avatars as co-constructors of meaning and interaction, offering implications for the design, implementation, and governance of future AI-enhanced metaverse learning environments.

As artificial intelligence (AI) continues to permeate the education sector, the question is no longer about what it can do but what drives its successful adoption. Despite a growing body of literature on AI in education, research specifically addressing its adoption in developing countries is still lacking, even though the use of AI is potentially even more widely adopted there than in other places. Thus, we examined the critical factors influencing AI adoption in Ghanaian higher education institutions. Anchored in the diffusion of innovation (DoI) Theory and the unified theory of acceptance and use of technology 2 (UTAUT2), we specifically investigated the role of interoperability, relative advantage, pedagogical alignment, accessibility and affordability, and ethical considerations in shaping its adoption in these institutions. Quantitative data from 230 participants across 34 universities in Greater Accra was analyzed using a structural-equation-modeling approach. With an explanatory power of 77.3%, our model confirms the significant role of all five factors in shaping AI adoption. Our findings highlight the necessity for structured AI implementation strategies, including phased rollouts, professional development initiatives, and continuous system optimization to facilitate sustainable integration in resource-limited contexts. This study provides empirical evidence to guide policymakers and institutional leaders in aligning AI-driven educational innovations with strategic and contextual imperatives.

As calls to center lived experience in higher education intensify, so too do concerns about the ethical, emotional, and structural risks involved in integrating real-life narratives into pedagogy. This study introduces Simulated Lived Experience (SLE) as a novel pedagogical modality that leverages the immersive affordances of learning environments like the metaverse to approximate systemic conditions of marginalization without reproducing trauma or requiring emotional labor from marginalized individuals. Drawing on critical pedagogy frameworks and affect theory, the research explores how SLE enables learners to engage with ethical discomfort, narrative complexity, and affective dissonance through the enactment of virtual selves. A qualitative design was employed, with data collected via semi-structured interviews from 12 participants who engaged in metaverse-based simulations portraying exclusionary dynamics related to disability, race, and institutional access. Thematic analysis generated four key findings: (1) virtual simulations evoke affective authenticity but also ethical unease, (2) embodied disorientation fosters structural insight, (3) narrative authorship and representation are ethically contested, and (4) discomfort acts as a catalyst for critical reflection. The study concludes that while SLE cannot replace lived experience, it can function as a powerful epistemic mediator when designed collaboratively, approached reflexively, and grounded in epistemic care.

Social interaction has long been a subject of theoretical inquiry in both Computer-Mediated Communication (CMC) and Human-Computer Interaction (HCI), but seldom has it been examined through the lens of digital embodiment. As the metaverse gains traction as a platform for learning and collaboration, understanding how its affordances construct behavioral engagement demands empirical scrutiny. Thus, this study examines the effects of avatar customization and communication modality on behavioral engagement within a metaverse-based simulation. Using a 2×2 factorial design, participants were randomly assigned to avatar (customized vs. generic) and modality (voice vs. text) conditions, with engagement tracked via a stealth assessment approach across multiple sessions. Findings indicate that avatar customization facilitated broader spatial exploration, while voice-based communication elicited higher interpersonal interaction. Critically, the convergence of both factors produced a compounded effect that yielded selective interaction effects on temporal and social dimensions of engagement. This study contributes a framework of affordance convergence that informs both the theoretical modeling of digital embodiment and the practical design of immersive learning platforms. As educational experiences increasingly unfold within socio-technical systems, the challenge for both HCI and CMC is to design environments where social interaction is both mediated and dynamically co-constructed through the alignment of interactional affordances.

Introduction: As digital platforms increasingly mediate language learning, the challenge is no longer simply how to deliver content online but how to design environments that cultivate authentic multilingual practice. While multilingualism has long been linked to enhanced metalinguistic awareness and domain-general cognitive flexibility, the role of multimodal digital environments in fostering these outcomes remains underexplored.

Purpose: Grounded in sociocognitive and multimodal interactionist perspectives, this study examines how a cross-device metaverse platform can support multilingual development through spatially organized, task-based, and avatar-mediated interaction. Specifically, it investigates whether multilingual engagement in language-zoned virtual spaces improves learners' communicative performance, affective engagement, and cognitive control compared to conventional instruction.

Methodology: Using a quasi-experimental cluster-assigned pretest-posttest control group design, learners engaged in communicative scenarios across English, Filipino, and Mandarin within language-zoned virtual spaces that cued role-appropriate language use. Data were collected using performance-based role-play assessments (code-switching accuracy, communicative competence), oral fluency measures (WPM), motivation and anxiety questionnaires, and a Stroop interference task to assess cognitive flexibility.

Findings: Compared to peers in a control condition, learners in the metaverse environment demonstrated significantly greater gains in code-switching accuracy, spoken fluency, motivational engagement, and cognitive control. Specifically, experimental participants showed improved context-appropriate language selection and reduced cross-language interference when shifting between English, Filipino, and Mandarin during task-based role-play scenarios. They also produced more fluent spoken output and demonstrated stronger communicative competence ratings in completing real-world interaction tasks. In addition, learners reported higher motivational engagement and cognitive results, further revealing improvements in inhibitory control and attentional regulation. Collectively, these outcomes suggest that spatially cued multilingual interaction in the metaverse supports integrated gains in linguistic performance and executive functioning.

Originality/Value: This study provides empirical evidence that multilingual development is shaped not only by linguistic input but by how digital learning ecologies choreograph spatial, social, and multimodal cues into context-responsive language use. By operationalizing multilingual interaction through spatial language zoning, avatar-mediated tasks, and AI-supported multilingual dialogue, the study positions the metaverse as a semiotically rich pedagogical ecology that can simultaneously foster code-switching competence, oral fluency, motivational engagement, and domain-general executive control. The findings advance multimodal multilingual education theory by demonstrating how context-sensitive interaction design can generate co-emergent communicative, affective, and cognitive benefits in multilingual learners.

This study sought to understand the experiences of All-but-Dissertation (ABD) students that led them to withdraw from a Doctor of Information Technology (DIT) programme. A total of 27 students from three Philippine universities were interviewed using a semi-structured format. Results show that most participants were driven by extrinsic motivations and viewed graduate education as a pathway to a better life. The challenges they faced were both internal and external in nature (e.g. study-work conflicts and personal problems), which are comparable to those in other disciplines. Most reasons (e.g. limited research experience and dissertation anxiety) for dropping out from this professional doctorate align with findings from studies on Doctor of Philosophy (PhD) programmes. However, two reasons unique to ABD students in the DIT programme were the inclusion of software development and the selection of computing research topics. Overall, these findings provide empirical evidence for addressing issues related to dissertation delays, prolonged doctoral completion times, and attrition in graduate education. Practical and managerial implications derived from this study could inform graduate school policies and practices, with potential applications across other doctoral disciplines.

The metaverse is reshaping interaction, learning, and community-building in immersive virtual environments. While interest in metaverse adoption is growing, most research has focused on technological predictors and has overlooked the experiential dimensions that are central to sustained engagement in these spaces. This gap limits understanding of how users develop and maintain meaningful virtual existence in the metaverse. Therefore, this study develops the Metaverse Experience and Technology Acceptance (META) model by integrating the principles of the Technology Acceptance Model (TAM) and Embodied Social Presence Theory (ESPT). Structural equation modeling (SEM) was used to analyze data collected from 924 students with metaverse experience. The META model demonstrates strong explanatory power in accounting for both technology acceptance and user experience in virtual worlds. Moreover, the findings indicate that adoption of the metaverse as a digital university extends beyond the functional focus of TAM to include the immersive, social, and embodied elements emphasized in ESPT. By bridging technological and experiential determinants, the META model advances theoretical understanding and offers actionable insights for creating metaverse environments that promote conducive digital existence.

As higher education increasingly adopts hybrid learning models, understanding the role of digital environments in supporting student well-being has become essential. While prior studies have examined the clinical and instructional applications of the metaverse, little attention has been given to its informal, socially immersive uses. This study explores how voluntary participation in a beach-themed, off-campus metaverse environment relates to students' perceived stress, mental health, social connectedness, and academic belonging. Using a quantitative observational design, data were collected from validated psychological scales and behavioral engagement metrics. Correlational analyses revealed that greater time spent in the metaverse was significantly associated with lower perceived stress and higher social connectedness. Multiple regression indicated that recurring peer interactions and event attendance were significant predictors of academic belonging, while time spent alone was not. ANOVA results showed that students with higher levels of metaverse engagement reported significantly greater perceived social support, with a trend toward lower psychological distress. These findings highlight the psychosocial value of informal metaverse spaces. When designed to support peer interaction and voluntary participation, such environments can serve as digital third places that promote emotional resilience, connection, and belonging in hybrid academic settings. Overall, this study extends the current literature by foregrounding the affective and social affordances of metaverse environments beyond structured therapeutic or instructional contexts.

This study examines the Canvas’ usability in Learning Management System (LMS) from the perspectives of students and teachers, focusing on experiences across Progressive Web App (PWA) and native mobile platforms. A task-based usability testing approach was employed, combining quantitative measures of task completion and time with qualitative insights from observations and participant feedback. Findings indicate that both platforms supported high task completion, though clear differences emerged in efficiency and feature accessibility. Teachers achieved a 91.7% completion rate on the mobile app compared to 100% on the PWA. The mobile app was faster for grading and assignment creation, while the PWA provided broader feature coverage, particularly for analytics, though some users reported navigation difficulties. For students, performance differences were more pronounced: average task completion time on the PWA was 1.24 minutes compared to 5.72 minutes on the mobile app. Tasks such as replying to announcements and checking grades were completed up to ten times faster on the PWA. Overall, the mobile app demonstrated greater stability and efficiency for routine functions, whereas the PWA offered extended functionality and cross-platform access but with tradeoffs in responsiveness and interface clarity. These results highlight the role of platform choice in shaping user experience and suggest directions for optimizing Canvas LMS for both teaching and learning contexts. By advancing usability in digital learning platforms, this research contributes to Sustainable Development Goal (SDG) 4: Quality Education, while also supporting SDG 9: Industry, Innovation, and Infrastructure through insights on mobile technology design, and SDG 10: Reduced Inequalities by emphasizing accessibility across diverse devices and connectivity conditions.

Video-based learning (VBL) is a cornerstone of modern education. With the rise of artificial intelligence (AI), tools such as AI-generated video summaries are increasingly used to enhance learner efficiency and streamline content delivery. However, little is known about how such summaries influence learner behavior, cognitive engagement, and motivation during exposure to instructional materials. The present study examined the impact of AI-generated summaries on engagement, comprehension, and intrinsic motivation in a controlled VBL environment. Sixty participants were randomly assigned to either a control group (video only) or a summary group (video plus AIgenerated summary). Results showed that summary access led to significantly reduced video viewing time, suggesting that learners treated the summary as a substitute rather than a complement. While comprehension scores were only moderately lower in the summary group, deeper analysis revealed underperformance on conceptual transfer items. Intrinsic motivation was also significantly lower, particularly in interest and perceived value. These findings underscore the need for intentional design when integrating AI-generated support, as unstructured summary access may promote shallow engagement and diminish learning outcomes. The study concludes with design implications, recommended strategies for integrating AI-generated supports, and directions for future research in VBL environments.