Research topic mining and evolution analysis of digital literacy within higher education based on BERTopic
DOI:
https://doi.org/10.47989/ir31iConf64189Keywords:
Digital literacy, Higher education, BERTopic, Topic modeling, Topic evolutionAbstract
Introduction. Digital literacy is becoming increasingly central to higher education in the context of rapid digitalisation and the adoption of AI. Accordingly, it is necessary to analyse the research topics and evolutionary trends of digital literacy in higher education.
Method. This study applies BERTopic to analyse 2,605 bibliographic records from the Web of Science Core Collection, using SBERT embeddings, MDS reduction, K-means clustering, and LLR weighting.
Results. Seven key topics were identified, including Teacher digital literacy and professional training, social media, mental health, and digital inequality, digital transformation in nursing and medical education, Artificial intelligence and educational innovation, digital health literacy, Student digital citizenship and information literacy, and digital learning environments and student outcomes. Temporal analysis across five periods (1997–2025) reveals how digital health and AI research surged during the pandemic, while responsible digital practices gained prominence in recent years.
Conclusions. The findings map the field’s evolving knowledge structure and provide evidence-based insights for policymakers and educators to inform the design of curriculum, instructional reform, and digital competence development.
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Copyright (c) 2026 Shuangling Cheng, Shubin Zhou
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
