Sürdürülebilir Kalkınma Amaçları
Yayınlar
- MakaleAçık Erişim2026Scopus SJRQ1Technology Acceptance in Sustainable Distance Education
Akti Aslan, Seda; Çekmez, Erdem; Ayaz, Ahmet; Özyurt, Özcan; Aslan, Alper
This study aims to examine the thematic structure and temporal evolution of the literature on technology acceptance in distance education using the Structural Topic Modeling method. Peer-reviewed articles indexed in the Scopus database between 2016 and 2025 were included in the analysis, yielding 18 consistent thematic clusters. Technology Acceptance Model (TAM) Core Constructs and Structural Equation Modeling (SEM)/Partial Least Squares (PLS) Methodology emerged as the most prevalent themes, reflecting the field’s sustained reliance on quantitative model-testing approaches. Trend analyses revealed a pronounced decline in TAM Core Constructs, while Unified Theory of Acceptance and Use of Technology (UTAUT) and Extensions, Hybrid and Emergency Remote Teaching, and Mobile and AI Applications demonstrated significant upward trends. The period comparison showed that pandemic-related themes became markedly prominent in the 2021–2025 period. Topic correlation analysis indicated the presence of competing temporal niches within the literature. Taken together, the findings suggest that research on technology acceptance in distance education is undergoing a structural transition from single-framework TAM dominance toward a multi-model, context-sensitive research paradigm. These findings carry important implications for the sustainable development of technology-enhanced distance education ecosystems and offer evidence-based guidance for researchers and policymakers committed to building inclusive and adaptive educational systems.
- MakaleAçık Erişim2026Scopus SJRQ1Generative Artificial Intelligence in Education: Conceptual Dimensions, Trends, and Research Directions
Akti Aslan, Seda; Ayaz, Ahmet; Ozyurt, Ozcan; Aslan, Alper
Research into generative artificial intelligence (GenAI) in the field of education has been growing rapidly in recent years. The rapid expansion of the literature has necessitated a systematic examination of the field. In this study, the thematic structure of GenAI research in the field of education during the 2023–2025 period was examined. Given the need to work with a large-scale dataset comprising 15,036 studies, a Latent Dirichlet Allocation (LDA)-based topic modelling analysis was selected. A search conducted on Scopus resulted in the inclusion of 15,036 studies in the analysis. The LDA analysis identified 12 prominent topics based on consistency scores. Descriptively, these prominent topics were grouped under four broad thematic areas. Among these axes, the technical axis holds the largest share (25%). It was observed that whilst technical topics were on the rise during the 2023–2025 period, topics such as ethics and chatbots showed a relative downward trend. The observed trends suggest that scholarly attention is increasingly directed towards technically oriented research. The findings also indicate a need for theoretical frameworks to ensure pedagogical depth. It is anticipated that the study’s findings will serve as an important reference point for future research. © The Author(s) 2026. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
