Devi Miftahul Jannah
Universitas Negeri Makassar

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Redefining Social Responsibility Through AI Literacy: The Roles of Digital Literacy and Ethical Awareness in Digital Citizenship Misbahuljannah; Riqqah Dhian Shefira; Devi Miftahul Jannah; Muh. Yusril Anam; Rosidah
Journal of Applied Artificial Intelligence in Education Vol 1, No 2 (2026): January 2026
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/jaaie.v1i2.7

Abstract

The rapid integration of artificial intelligence (AI) into digital learning environments requires higher education students to develop not only technical competence, but also critical, ethical, and socially responsible capacities as digital citizens. This study aims to examine how AI literacy, digital literacy, and ethical awareness influence students’ social responsibility as a key foundation for responsible digital citizenship. A quantitative cross-sectional survey was conducted with 100 undergraduate students in Informatics and Computer Engineering Education, and the hypothesized relationships were tested using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that digital literacy has a positive and significant effect on social responsibility (β = 0.397, p = 0.001) and ethical awareness emerges as the strongest positive predictor (β = 0.615, p < 0.001), while AI literacy exhibits a negative but significant effect (β = −0.151, p = 0.022), suggesting that higher AI literacy may foster more critical or cautious orientations that could reduce socially responsible engagement when not accompanied by strong ethical grounding and citizenship-oriented competencies. The findings imply that higher education curricula should integrate digital literacy, AI literacy, and ethics education in a balanced manner moving beyond purely technical training so that AI literacy translates into constructive social responsibility and strengthened digital citizenship; future studies should extend the sample and adopt longitudinal designs to capture behavioral changes over time.
StudySync Mobile Application Design for Student Academic Activity Management Based on SQLite Database Arsyanda; M. Miftach Fakhri; Pramudya Asoka Syukur; Devi Miftahul Jannah; Elma Nur Jannah; Annajmi Rauf
Journal of Embedded Systems, Security and Intelligent Systems Vol 5, No 3 (2024): November 2024
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v5i3.5042

Abstract

The development of information and communication technology has made significant contributions in various sectors, including education. Mobile applications have become an effective solution in improving time management and reducing academic procrastination among students. This research aims to design and develop a mobile application called StudySync that utilizes SQLite database to assist students in organizing their academic activities. The development method used is the Agile method with three sprint cycles, ensuring incremental improvements and continuous validation of features. The application offers task management features, note-taking, reminders, and a search system to facilitate the management of academic information. SQLite was chosen as the main database due to its self-contained, serverless, zero-configuration, and transactional nature, suitable for mobile applications that require fast and reliable database access. The test results show that the StudySync application successfully meets the needs of users in organizing academic assignments and notes and improving student time management.
Student Resistance to ChatGPT in Indonesia: Extended IRT with PLS-SEM Analysis Andi Muhammad Faiz Iqbal; Nurul Hasmi; Devi Miftahul Jannah; Rizki Wahyu Hunian Putra
Journal of Vocational, Informatics and Computer Education Vol 3, No 2 (2025): December 2025
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/voice.v3i2.264

Abstract

The integration of Artificial Intelligence (AI) in higher education is growing, including the use of ChatGPT as a tool to assist students academically by improving access to information and promoting independent learning. Nonetheless, some students have shown reluctance due to worries about its reliability, academic morals, and changes in conventional learning principles. This research intends to explore how various barriers, such as usage barrier, value barrier, risk barrier, tradition barrier, image barrier, perceived cost barrier, and ethical considerations, contribute to student hesitance regarding ChatGPT. A quantitative method was utilized through Partial Least Squares Structural Equation Modeling (PLS-SEM), gathering data from an online survey of 77 students from Universitas Negeri Makassar. Findings reveal that only the risk barrier (β = 0. 417; p = 0. 006) and the tradition barrier (β = −0. 400; p = 0. 029) have a significant impact on resistance, with the risk barrier being the most influential, while the other factors showed no notable effects. These results suggest that psychological and cultural factors are more significant than practical obstacles in influencing resistance to generative AI and broaden the Innovation Resistance Theory (IRT) by factoring in ethical issues. The study advises creating teaching strategies that find a balance between using technology and maintaining academic honesty, while also promoting further research through multigroup and longitudinal methods.