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All Journal Information Technology Education Journal Indonesian Technology and Education Journal Journal of Vocational, Informatics and Computer Education Journal of Applied Artificial Intelligence in Education
Ummul Khaeri Masna
Universitas Negeri Makassar
Computer Science & IT Education

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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
The Concern Over Brain Rot from Generative AI Use Among Preservice Teachers: A UTAUT Approach Ummul Khaeri Masna; Udin Sidik Sidin; Mushaf; Stephen Amukune
Journal of Vocational, Informatics and Computer Education Vol 4, No 1 (2026): March 2026
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/voice.v4i1.347

Abstract

Purpose – The increasing use of generative AI on campus has raised concerns about a potential decline in students’ critical thinking skills. While the UTAUT theory is widely used to examine technology adoption, its relationship with the phenomenon of brain rot remains underexplored, particularly among preservice teachers. This study aims to analyze the factors associated with preservice teachers’ intention to use generative AI within the UTAUT framework, as well as to examine its association with tendencies toward brain rot.Method – A quantitative cross-sectional design was conducted with 243 preservice teachers from Universitas Negeri Makassar. Data were collected via a validated 30 item questionnaire and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine the relationships between technology adoption constructs and brain rot tendencies.Findings – Social influence was the only significant predictor of behavioral intention to use AI (β = 0.269, p = 0.002). Behavioral intention, in turn, showed a strong positive association with brain rot tendencies (β = 0.817, p < 0.001), explaining 66.7% of the variance (R² = 0.667). Other UTAUT constructs, including performance expectancy and effort expectancy, were not significant predictors. However, given the cross-sectional design, these findings reflect statistical associations rather than causal relationships.Research Implication : Socially driven AI adoption is strongly linked to cognitive passivity, highlighting the need to extend UTAUT with cognitive risk factors and rethink how technology use impacts higher-order thinking.Conclusion – This study indicates that the adoption of AI among preservice teachers is associated with perceptions of declining cognitive abilities. These findings highlight the importance of promoting critical AI literacy and developing assessment approaches that emphasize deep cognitive engagement. Future research is recommended to employ longitudinal designs or incorporate control variables such as digital self-efficacy.
Social Environment and Internet Engagement as Predictors of Cyberbullying in Young People Herawati; Shalsa Nabila; Putri Nirmala; Ummul Khaeri Masna
Indonesian Technology and Education Journal Vol 3 No 2 (2025) : August
Publisher : Sakura Digital Nusantara

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Abstract

Social media has become an important part of young people's lives, not only as a means of communication and entertainment, but also as a space for intense social interaction. The high intensity of internet use brings both positive opportunities and risks, one of which is cyberbullying which has a serious impact on mental health, such as anxiety and depression. This study aims to analyze the effect of internet usage intensity and social environment on cyberbullying tendencies in college students. The research method used a quantitative approach with a cross-sectional design. Data were obtained through a five-point Likert scale online questionnaire filled out by 83 respondents from various generations. Descriptive analysis showed that aspects of social media use were quite high, while direct experience of cyberbullying was relatively lower. Social environment support was moderate, but awareness of cyberbullying prevention was high. The findings indicate that the intensity of internet use potentially increases the risk of cyberbullying, but social environmental factors and digital awareness can serve as important protections. This research provides practical contributions in the form of recommendations for digital literacy, strengthening family support, and social media monitoring to create a safer digital ecosystem for the younger generation.
Application Development for Fasting and Worship Management Ramadan Using the Incremental Method: Kareem Daffa Fakhir; Nabila Al Buqari Jufri; Muh Akhlatul Ihsan; Putri Nirmala; Ummul Khaeri Masna
Indonesian Technology and Education Journal Vol 3 No 2 (2025) : August
Publisher : Sakura Digital Nusantara

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Abstract

The development of Artificial Intelligence (AI) in education, especially in design teaching, offers great potential to improve students' creativity, reflection, and design thinking mindset. This study aims to evaluate the effect of AI integration in design-based learning on students' creative thinking ability, reflection, and design mindset. The study used quantitative methods with a cross-sectional design, involving 82 respondents from various departments in higher education institutions. The research instrument was a questionnaire covering aspects of creativity, reflection, and design mindset. The data analysis technique used descriptive analysis. The results showed that 59.76% of the respondents were 19 years old, and most (85.37%) were 3rd semester students. The use of AI in design-based learning was proven to increase student creativity with an average score of 3.66 on a scale of 5, strengthen reflection skills with an average of 3.63, and improve design thinking mindset with an average of 3.75. However, the results also revealed that AI is more effective as a supporting tool in the learning process rather than replacing direct interaction between students and educators. Therefore, AI can be integrated as a tool that supports creativity, but still requires the role of human guidance.
Extending the Technology Acceptance Model (TAM) to Predict Student Learning Outcomes in GNS3 Based Networking Education Ummul Khaeri Masna; Agus Salim; Fitra Ramadani; Fadhlirrahman Baso
Information Technology Education Journal Vol. 5, No. 1, February (2026)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v5i1.265

Abstract

Purpose – This study investigates the factors influencing network simulator acceptance and its direct impact on learning outcomes within the Department of Informatics and Computer Engineering. It addresses the gap between technology adoption and actual academic success in a technical vocational context. Design/methods/approach – A quantitative approach using the Technology Acceptance Model (TAM) was applied. Data from 187 students were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS 4.0, employing a 5,000-resample bootstrapping procedure. Findings – Results confirm that Perceived Usefulness significantly drives Behavioral Intention (β= 0.774, p < 0.001), while Perceived Ease of Use is non-significant (β = 0.150, p = 0.166). Crucially, Behavioral Intention strongly predicts Learning Outcomes (β = 0.849, p < 0.001). The model exhibits substantial predictive power, explaining 83% of the variance in intention (R2 = 0.830) and 72.1% in learning outcomes (R2 = 0.721). Research implications/limitations – Engineering pedagogy should prioritize demonstrating the industrial utility of simulators over interface simplicity. Limitations include the cross-sectional design and reliance on self-reported data within a single department, which may affect generalizability. Originality/value – This research empirically bridges technology acceptance with tangible academic performance in the Indonesian technical education context. It provides a validated framework for enhancing technical competencies through strategic tool integration.
Co-Authors Agus Salim Arum Putri Rahayu Daffa Fakhir Fadhlirrahman Baso Fitra Ramadani Herawati Muh Akhlatul Ihsan Muh. Yusril Anam Mushaf Nabila Al Buqari Jufri Nurrahmah Agusnaya Putri Nirmala Sakinah Mawaddah Shalsa Nabila Stephen Amukune Udin Sidik Sidin