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- MakaleYalnız künye2026Scopus SJRQ1Exploring research themes in the Journal of Librarianship and Information Science: Insights from topic modelings
Aslan, Alper; Özyurt, Özcan
This study aims to explore research interests and trends in the journal by analyzing the entire publication history of the Journal of Library and Information Science (JoLIS) between 1969 and 2023 using Latent Dirichlet Allocation (LDA). A comprehensive topic modeling analysis was conducted on 1437 articles for which titles, abstracts and keywords were available. The research focuses on identifying key thematic shifts in the journal’s publications. The findings highlight that topics such as Information Literacy & Research and Librarian Roles & Skills are growing in importance, while traditional topics such as Cataloging & Classification are declining. The results reveal shifts in the focus of the LIS field, providing critical insights to guide future research. In particular, Information Literacy & Research emerges as a highly accelerating topic, reflecting the need for digital competencies in response to evolving information environments. Meanwhile, declining interest in Cataloging & Classification is in line with the automation of traditional library functions, shifting training priorities toward digital literacy and data management skills. By mapping the evolution of research priorities, this study serves as a valuable resource for LIS researchers and practitioners, helping them to align their work with future developments in the field.
AtıfScopus9WoS7OpenAlex11
İncele - 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).
- MakaleYayıncıda açık erişim2026Scopus SJRQ1Thematic Structure of Pedagogical Agent Studies: LDA Analysis for the Period 2020–2025
Turgut, Yigit Emrah; Aktı Aslan, Seda; Kopuz, Tuba; Aslan, Alper; Allison, Jordan; Özyurt, Özcan
This study examines 2,360 pedagogical agent (PA) articles published between 2020 and 2025 to identify thematic structures, trends, and research gaps through bibliometric analysis and LDA-based topic modeling. The optimal model produced 10 themes (c_v = 0.4767). The dominant themes—Learner Interaction with Virtual Assistants in Education, Student-Centred Learning and Individual Guidance, and NLP Foundations for Pedagogical Agents—account for 51.3% of publications. Trend analyses revealed consistent growth in both Artificial Intelligence and Pedagogical Design in Education and NLP Foundations for Pedagogical Agents, while Learner Interaction with Virtual Assistants in Education reached saturation. Interaction network results showed these themes at the conceptual core of the field, whereas AI-Driven Medical Chatbots, Knowledge-Based Learning Models, and Student Experiences in Intelligent Learning Environments emerged as future research areas. Overall, findings highlight a strong thematic shift toward artificial intelligence, natural language processing, and student-centered learning.