UNVEILING THE GLOBAL RISE OF CHATBOT-ASSISTED LEARNING A 2020–2025 BIBLIOMETRIC STUDY

Abstract

ABSTRACT Background: Chatbot-Assisted Learning (CbAL) is an innovative educational approach that leverages AI-driven chatbots to deliver personalised, interactive learning experiences. This bibliometric study maps the intellectual landscape and evolutionary trends of CbAL research from 2020 to 2025, a period significantly shaped by advances in generative AI. Methods: Utilising a dataset of 253 peer-reviewed articles from the Dimensions AI database, the analysis employs co-authorship, citation, and bibliographic coupling techniques to examine the field's development. Results: The results reveal a field in rapid expansion, with a 45% surge in citations after 2022 and a publication peak in 2024, directly linked to the influence of models like ChatGPT. Geographically, research is heavily concentrated, with the Asia-Pacific region spearheaded by China (192 articles, 7,773 citations), contributing 76% of the output, highlighting a pronounced global research divide. Thematic analysis reveals robust clusters in Technical Foundations (32%) and Pedagogical Applications (28%), indicating a strong connection between innovation and educational practice. However, the cluster on Emerging and Ethical Considerations remains significantly underdeveloped (5%), indicating a critical gap. Conclusion: The study concludes that while CbAL has achieved remarkable technical maturity, its future trajectory must be consciously steered. Prioritising global collaboration to bridge geographical inequities and embedding interdisciplinary ethical rigour are imperative to ensure the equitable and responsible development of chatbot-assisted learning for diverse educational contexts worldwide. KEYWORDS: Bibliometric Analysis, Chatbot-Assisted Learning, Educational Technology, Generative AI, ChatGPT, Global Collaboration, Research Trends.

Ähnliche Arbeiten