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All Journal Journal of Applied Artificial Intelligence in Education
Arum Putri Rahayu
STAI Ma'arif Magetan
Computer Science & IT Education

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Exploring Factors Influencing MOOCs Usage Behavior and Technology Acceptance in Higher Education: An Analysis Using the UTAUT Model Kiki Awaliyah; Arum Putri Rahayu; Putri Olivia; Muh Ma’ruf Asya Perdana
Journal of Applied Artificial Intelligence in Education Vol 1, No 1 (2025): July 2025
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/jaaie.v1i1.1

Abstract

Indonesian higher education still faces uneven adoption and low completion that may be driven by students’ technology acceptance and available support. This study investigated key determinants of Universitas Negeri Makassar students’ MOOCs acceptance and usage behavior using the Unified Theory of Acceptance and Use of Technology (UTAUT). A descriptive quantitative, cross-sectional survey was administered via Google Forms to 33 undergraduate students. The instrument comprised 34 Likert-scale items (1–5) measuring eight UTAUT-related dimensions: performance expectancy, effort expectancy, social influence, facilitating conditions, computer self-efficacy, attitude toward technology, behavioral intention, and actual use; data were analyzed using descriptive statistics. Overall perceptions were fairly positive, with most indicator means in the moderate-to-agree range. Performance expectancy (e.g., perceived usefulness and learning improvement) was moderate (means ≈3.52–3.55) and effort expectancy suggested MOOCs were relatively easy to learn (means ≈3.48–3.51). Social influence was weaker (means ≈3.24–3.30), while facilitating conditions were strongest, including system compatibility (mean ≈3.58). Behavioral intention was moderate (e.g., plan to use MOOCs; mean ≈3.55), yet actual use was comparatively lower (means ≈3.21–3.33), indicating an intention–use gap. Strengthening institutional support (infrastructure, guidance, integration with campus systems) and targeted interventions to convert intention into sustained participation may improve MOOCs uptake and completion; overall, the findings support UTAUT’s usefulness for diagnosing adoption barriers in Indonesian university contexts.
Student Perceptions of AI in Learning: The Role of Credibility and Emo-tional Well-Being in Supporting Critical Thinking Skills Ummul Khaeri Masna; Arum Putri Rahayu; Sakinah Mawaddah; Nurrahmah Agusnaya; Muh. Yusril Anam
Journal of Applied Artificial Intelligence in Education Vol 1, No 1 (2025): July 2025
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/jaaie.v1i1.3

Abstract

The growing use of artificial intelligence (AI) tools (e.g., ChatGPT, Grammarly) in higher education is often claimed to enhance students’ critical thinking, yet perceived benefits remain inconsistent and may depend more on trust and affective experience than on technical features alone. This study aimed to examine students’ perceptions of AI for supporting critical thinking by testing five predictors—perceived AI credibility, AI quality, cognitive absorption, emotional well-being, and satisfaction—and their effects on overall AI perception. A quantitative cross-sectional survey was administered to 90 Indonesian university students (purposive sampling; ages 18–25) using 26 closed-ended Likert items (5-point scale) and three open-ended questions; data were analyzed in Jamovi using descriptive statistics, Pearson correlations, and multiple linear regression. The results indicated generally moderate perceptions of AI (item means ≈2.2–2.8), significant positive correlations among all variables (p < .001), and strong explanatory power of the regression model (R² = 0.737; adjusted R² = 0.720). In the multivariate model, emotional well-being (β_std = 0.267, p = 0.016) and AI credibility (β_std = 0.196, p = 0.043) were the only significant predictors, whereas AI quality, cognitive absorption, and satisfaction showed positive but non-significant effects. These findings imply that AI-supported learning interventions should prioritize credible, trustworthy AI outputs and pedagogical designs that promote positive emotional experiences (e.g., comfort, reduced stress, motivation) to strengthen perceived critical-thinking benefits; overall, affective and trust-related factors appear to be central drivers of students’ positive AI perceptions, warranting validation in larger and longitudinal studies
Co-Authors Kiki Awaliyah Muh Ma’ruf Asya Perdana Muh. Yusril Anam Nurrahmah Agusnaya Putri Olivia Sakinah Mawaddah Ummul Khaeri Masna