Jul 2026· Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI)· Vol 15· 0 citations
TL;DR
DigiMind, an AI-driven adaptive learning system that integrates digital literacy with mental health support to promote balanced and inclusive learning is proposed, offering a holistic model for sustainable digital education in Indonesia.
Abstract
The rapid advancement of digital technology has significantly transformed education worldwide, including in Indonesia. Artificial intelligence (AI) is increasingly used to create personalized, adaptive, and interactive learning experiences. Despite high exposure to technology, many high school and vocational students still struggle with digital literacy and mental well-being. This study proposes DigiMind, an AI-driven adaptive learning system that integrates digital literacy with mental health support to promote balanced and inclusive learning. Using a mixed-method approach, the study involved 146 students and 10 teachers from two partner schools in Surakarta. Quantitative data were collected through surveys based on the UNESCO Digital Literacy Framework and ICT Watch Indonesia, while qualitative data were obtained from focus group discussions (FGD) with teachers and students. The findings indicate that although 98.6% of students have used AI-based learning tools, many lack awareness of data privacy, digital ethics, and focus management. About half experienced digital fatigue, while most emphasized the need for well-being features such as break reminders, relaxation content, and adaptive materials. Teachers, in contrast, prioritized monitoring, analytics, and early stress detection—revealing a dual orientation between student engagement and teacher support.The resulting DigiMind blueprint combines adaptive learning modules, AI-based mental health analytics, and dual dashboards for students and teachers. Expert validation confirmed its pedagogical, technical, and psychological feasibility. Overall, integrating digital literacy and digital well-being within AI-driven adaptive learning enhances both cognitive performance and emotional resilience, offering a holistic model for sustainable digital education in Indonesia
Artificial intelligence (AI) has transformed higher education by introducing intelligent learning environments that support personalized instruction, adaptive learning, automated assessment, and enhanced student engagement. While AI-supported education offers substantial academic benefits, its implications for students' mental health and psychological well-being remain insufficiently explored. Therefore, this study examined the relationship between AI-supported education and student mental health, This research aimed to identify artificial intelligence-supported education systems and teaching models and the effect that AI-assisted education has on students' psychological well-being and mental state. It focused on health in the field of higher education, balancing the innovations and psychological health of students. A quantitative, cross-sectional study was used. The primary data used were collected by means of a structured questionnaire. The targeted population for this study included both undergraduate and postgraduate students enrolled at public and private universities in Punjab and Sindh, Pakistan, including Bahauddin Zakariya University, The Women University Multan, University of the Punjab, Government College University Faisalabad, Islamia University of Bahawalpur, University of Sindh Jamshoro, Mehran University of Engineering and Technology, NED University of Engineering and Technology Karachi, Foundation university medical college, and the University of Karachi. The specific sample used for this study was convenience sampling. Google Forms were distributed to university mailing lists and academic social media platforms, collecting data from 457 participants. The data were screened using Microsoft Excel. The data were analyzed using IBM SPSS Statistics Version 27. Descriptive statistics and inferential statistics including Cronbach's Alpha, Pearson’s correlation, multiple linear regression, Independent Samples t-test, and One-Way ANOVA were employed for this study. The results showed that AI-supported education positively affected student mental health and psychological well-being, showing distinct demographic patterns for respondents. The results of this study build on established research to show that, when critically applied in the field of higher education, AI innovation may support the enhancement of not only teaching and learning but also the psychological well-being of students. Based on the results, recommendations are made for educators, higher education administrators, and policy makers, as well as instructional designers and education technology entrepreneurs, to aid the development of ethical, student-centered, and psychological support frameworks for the use of AI Learning technologies within the field of higher education.
Batool Butt, Nimra Jamil, Mahira Mirza et al.· Journal of Global Social Tra...· 2 citations
Introduction This study examined the contribution of AI enhanced learning activities to the digital literacy of preservice early childhood education student teachers. Methods A quantitative post-intervention explanatory design was used involving 212 Early Childhood Education students at a university in Jiangxi Province, China, who participated in AI-enhanced learning activities for one semester. Data were collected through a structured questionnaire and analyzed using descriptive statistics, Pearson's correlation, and SEMPLS. Results Students demonstrated a moderate level of digital literacy, with information usage and organization showing the highest scores, while metacognition and problem-solving were relatively lower. Engagement in AI-enhanced learning activities was positively and significantly related to all dimensions of digital literacy. SEM results further showed that AI-enhanced learning activities made a significant positive contribution to overall digital literacy. Discussion These findings suggest that integrating AI enhanced learning activities into pre-service teacher education may support the development of student teachers' digital literacy and better prepare them to integrate AI meaningfully in early childhood settings.
Weiping Zhu, Panjanat Vorawattanachai· Frontiers in Psychology· 0 citations
To overcome obstacles like inadequate infrastructure and a lack of prepared teachers, data-driven optimization of AI-driven educational technologies is necessary to improve personalized learning under Kenya's Competency-Based Curriculum (CBC), which has been in place since 2017 to place an emphasis on skill-based and learner-centered education. Research has indicated that teachers have a moderate level of faith in AI and that there needs to be an ethical component to information and communication technology (ICT) education. New initiatives, like Kenya's National AI Strategy 2025–2030, aim to close the skills gap among the country's young population (median age: 19). This study examines survey responses from 30 stakeholders at Jogoo and Kiamabundu DOK Primary Schools (33.33% teachers, 20% children) in order to develop artificial intelligence tools that enhance results in neglected areas. Factors identified by multivariate statistical analysis, including Principal Component Analysis (PCA), include a moderate level of computer literacy (73.33%), a lack of experience with artificial intelligence (60%), and a strong endorsement of teacher training (50% deem it essential/significant). In line with initiatives such as digital literacy programs and AI-powered teacher support tools, such as chatbots for lesson preparation and grading, these findings point out the value of capacity building and the challenges to adoption. With 53.34% of respondents noting a significant or moderate impact on learning outcomes, optimization modeling prioritizes AI platform features such as interactive content (36.67%), personalized learning paths (33.33%), and real-time feedback (26.67%). This guarantees the optimization of CBC's learner-centric objectives. To promote inclusive education, these mathematical models provide a scalable framework for low-infrastructure solutions like virtual tutors and platforms based on short message service (SMS). Policymakers and EdTech developers in Kenya can use the findings as a guide to include AI in CBC that addresses the needs of everyone involved, reduces dependence on infrastructure, and supports fair, modern education.
Bulinda Vincent, Cynthia Mwau· American Journal of Robotics...· 0 citations
This study examined the relationships among artificial intelligence literacy, digital competence and academic engagement among Generation Z students enrolled in higher education institutions. A mixed-method research design was employed to obtain a comprehensive understanding of students’ preparedness for AI-supported learning. Quantitative data were collected through a structured questionnaire administered to undergraduate and postgraduate students from public and private universities. Qualitative data were obtained through semi-structured interviews with students and university faculty members to explore experiences, perceptions, and challenges associated with AI integration in higher education. Quantitative data were analysed using descriptive and inferential statistical techniques, while qualitative data were examined through thematic analysis. The integrated findings indicated that Generation Z students demonstrated varying levels of AI literacy and digital competence, which were significantly associated with their academic engagement. Students with stronger AI literacy and digital skills reported greater participation in learning activities, improved collaboration, enhanced problem-solving abilities and increased confidence in technology-supported learning environments. Qualitative findings further revealed that institutional support, faculty guidance, ethical awareness, and access to digital resources played critical roles in fostering meaningful academic engagement. Participants also emphasized the importance of responsible AI use, digital ethics and continuous skill development for effective learning in higher education. The study contributes to the growing body of knowledge on AI integration in education by providing empirical evidence that can inform curriculum development, institutional policy and professional practices aimed at preparing Generation Z learners for technology-rich academic environments.
Saira Saeed, Omar J. Alkhatib, Uzma et al.· TAMSAAL· 0 citations
Background and Aim: The COVID-19 pandemic accelerated the integration of mobile applications and artificial intelligence (AI) into language education, transforming traditional learning environments. This study introduces the Integrative Language Acquisition and Learning Model (ILALM) as a framework for promoting learner autonomy, ethical digital engagement, and cultural responsiveness in Philippine higher education.
Methods: A qualitative phenomenological approach was employed to examine the lived experiences of students and educators using AI and mobile technologies in language learning. Data were collected through interviews, focus group discussions, classroom observations, and document analysis involving ten participants.
Results: Findings revealed that SmartSpeak enhanced students’ oral fluency, pronunciation, and confidence through AI-supported real-time feedback, while LinguaLitBoost improved reading comprehension and writing proficiency through adaptive literacy activities. Thematic analysis identified increased motivation, learner autonomy, personalized learning, immediate feedback, and cultural responsiveness as significant outcomes. However, challenges such as digital inequity, limited internet access, and cultural misalignment of content were also observed.
Conclusion: The study demonstrates the transformative potential of AI and mobile technologies in post-pandemic language education. The implementation of SmartSpeak and LinguaLitBoost highlights the capacity of ILALM to support inclusive, context-sensitive, and learner-centered instruction. Sustainable integration of these technologies requires strengthened digital infrastructure, localized content, equitable access, and continuous teacher training to ensure effective and ethical classroom application.
Edgar R. Eslit· Journal of Education and Lea...· 0 citations
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