cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Andrian Saputra
Contact Email
andriansaputra@imrecsjournal.com
Phone
+6285371040799
Journal Mail Official
rietm@imrecsjournal.com
Editorial Address
Jalan Soemantri Brojonegoro
Location
Unknown,
Unknown
INDONESIA
Research in Education, Technology, and Multiculture
Published by Institute of Multidisciplinary Research and Community Service
ISSN : -     EISSN : 30256763     DOI : http://doi.org/10.61436/rietm
Core Subject :
Research in Education, Technology, and Multiculture is an open-access, peer-reviewed journal that provides a comprehensive platform for the dissemination of scholarly works across three primary pillars: Technology and Applied Sciences, Technology-Enhanced Education, and Ethnics and Multiculturalism. The journal accommodates a broad spectrum of studies within these fields, encouraging both independent explorations and multidisciplinary approaches. The journal welcomes original research articles, conceptual papers, case studies, and community service reports that contribute to academic development and practical knowledge. Topics of interest comprehensively cover, but are not limited to: • Technology and Applied Sciences: information and communication technology, artificial Intelligence, block chain and digital transformation, STEM disciplines, alongside industrial and practical applications of applied sciences, as well as fundamental and applied research in mathematics and natural sciences. • Technology-Enhanced Education: Digital learning environments, educational technology (EdTech) innovations, and ICT based pedagogical strategies. • Ethnics and Multiculturalism: Multiculturalism in society and educational settings, ethnic relations, immigration and migrant workers’ studies, intercultural communication, cultural heritage, and diversity in social life.
Arjuna Subject : -
Articles 1 Documents
 1 
Search results for "artificial intelligence-based learning and academic achievement" : 1 Documents clear
Artificial Intelligence-Based Learning and Academic Achievement: A Systematic Literature Review of Self-Regulated Learning as a Central Mechanism Saefulah Saefulah; Merry Lapasau; Widodo Widodo; Acep Musliman; Nurjanah Nurjanah
Research in Education, Technology, and Multiculture Vol 5, No 3 (2026): Research in Education, Technology, and Multiculture
Publisher : Institute of Multidisciplinary Research and Community Service

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61436/rietm/v5i3.pp364-378

Abstract

The rapid adoption of artificial intelligence (AI) in education has created new opportunities for personalized learning, adaptive feedback, and academic support. However, existing findings remain fragmented, particularly regarding the mechanisms through which AI contributes to students’ academic achievement. This study systematically synthesizes recent literature on AI-based learning and identifies the technological, psychological, behavioral, and contextual factors that influence academic achievement. A systematic literature review was conducted following the PRISMA 2020 guidelines. Literature was retrieved from the Scopus database on 8 June 2026. From 780 initial records, 59 studies met the eligibility criteria and were included in the final qualitative synthesis. Thematic analysis identified recurring patterns and conceptual relationships across the selected studies. Five main themes were identified: AI literacy and technological readiness, psychological factors, student engagement, self-regulated learning, and contextual and institutional factors. This review interprets self-regulated learning as a key explanatory mechanism in the proposed conceptual framework, based on thematic evidence related to feedback use, goal setting, monitoring, reflection, engagement, motivation, and strategic learning, rather than as an empirically tested mediator across most included studies. Key challenges included academic dishonesty, overdependence on AI, misinformation, cognitive overload, and ethical concerns. AI does not automatically improve academic achievement; rather, its contribution depends on how it supports students’ motivation, engagement, and self-regulated learning within an enabling institutional context. The study proposes an integrated conceptual framework showing that AI literacy and technological readiness strengthen psychological factors, which enhance student engagement, promote self-regulated learning, and ultimately contribute to academic achievement. Keywords: Academic achievement, Self-regulated learning, Student engagement, AI literacy, Generative AI

Page 1 of 1 | Total Record : 1

 1 

Filter by Year

2026 2026


Reset
Filter By Issues
All Issue Vol 5, No 3 (2026): Research in Education, Technology, and Multiculture Vol 5, No 2 (2026): Research in Education, Technology, and Multiculture Vol 5, No 1 (2026): Research in Education, Technology, and Multiculture Vol 3, No 2 (2024): Research in Education, Technology, and Multiculture Vol 3, No 1 (2024): Research in Education, Technology, and Multiculture Vol 2, No 2 (2023): Research in Education, Technology, and Multiculture Vol 2, No 1 (2023): Research in Education, Technology, and Multiculture Vol 1, No 2 (2022): Research in Education, Technology, and Multiculture Vol 1, No 1 (2022): Research in Education, Technology, and Multiculture