From Intelligent Tutoring Systems to Generative AI: Changing Educational Priorities in Research Involving Asian-Affiliated Scholars

Abstract

This study examines how educational priorities have changed in artificial intelligence (AI) research involving scholars affiliated with institutions in 34 Asian countries and territories. It analyses 1,585 English-language Scopus journal articles published between 2010 and 2026, with partial coverage for 2026 up to 23 May. Biblioshiny was used to map keyword co-occurrence, thematic positioning, and thematic evolution across three periods: 2010–2016, 2017–2020, and 2021–2026. TALL was applied to a random sample of 792 abstracts to elaborate on the educational meanings embedded in the bibliometric structures. The findings indicate a reorientation from computer-aided instruction, intelligent tutoring systems, and learning systems towards generative AI, ChatGPT, technology adoption, and emerging human–AI discourses. Higher education and students provide the field’s principal educational focus, although students are frequently positioned as technology users or as adopters. Pedagogical mechanisms, teacher agency, assessment redesign, and responsible-use competencies remain less integrated. AI literacy, academic integrity, ethics, and critical thinking are visible but remain embedded within the broader technology and adoption structure. Abstract-level patterns further revealed benefit-oriented framing around support, enhancement, and future potential, which should not be interpreted as evidence of educational effectiveness. The study contributes an education-centred account of how technological expansion has outpaced the conceptual integration of pedagogy, human agency, assessment, and responsible institutional conditions.