Thematic Structure of Pedagogical Agent Studies: LDA Analysis for the Period 2020–2025

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Özet

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.

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dc.contributor.authorTurgut, Yigit Emrah
dc.contributor.authorAktı Aslan, Seda
dc.contributor.authorKopuz, Tuba
dc.contributor.authorAslan, Alper
dc.contributor.authorAllison, Jordan
dc.contributor.authorÖzyurt, Özcan
dc.date.accessioned2026-10-28T14:53:44.008250502Z
dc.date.available2026-10-28T14:53:44.008250502Z
dc.date.issued2026
dc.description.abstractThis 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.
dc.identifier.doi10.1080/10447318.2026.2655931
dc.identifier.eissn1532-7590
dc.identifier.issn1044-7318
dc.identifier.scopus2-s2.0-105036554876
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/munzur/895
dc.identifier.wosWOS:001747288900001
dc.language.isoen
dc.publisherTaylor and Francis Ltd.
dc.relation.ispartofInternational Journal of Human-Computer Interaction
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectbibliometric analysis
dc.subjectlatent Dirichlet allocation
dc.subjectLDA
dc.subjectPedagogical agents
dc.subjecttopic modeling
dc.subject.otherComputer aided instruction
dc.subject.otherE-learning
dc.subject.otherEducation computing
dc.subject.otherIntelligent agents
dc.subject.otherKnowledge based systems
dc.subject.otherLearning systems
dc.subject.otherNatural language processing systems
dc.subject.otherTeaching
dc.subject.otherBibliometrics analysis
dc.subject.otherLatent Dirichlet allocation
dc.subject.otherLDA
dc.subject.otherLearner interaction
dc.subject.otherPedagogical agents
dc.subject.otherResearch gaps
dc.subject.otherStudent centred learning
dc.subject.otherThematic structures
dc.subject.otherTopic Modeling
dc.subject.otherVirtual assistants
dc.subject.otherStudents
dc.titleThematic Structure of Pedagogical Agent Studies: LDA Analysis for the Period 2020–2025
dc.typeArticle
rdl.citation.openalex0
rdl.citation.scopus0
rdl.oa.statusgreen
rdl.oa.statusclosed
rdl.publication.statusinPress
rdl.scopus.quartileQ1
rdl.sdgSDG04
rdl.source.indexSCOPUS
rdl.source.indexWOS