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Leveraging Educational Chatbots to Train Future Worker: A Review of Applications, Outcomes, and Challenges.

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Title: Leveraging Educational Chatbots to Train Future Worker: A Review of Applications, Outcomes, and Challenges.
Authors: Ranggana, Alfaza1, Riza, Lala Septem1 lala.s.riza@upi.edu, Abdullah, Ade Gafar1
Source: Journal of Interdisciplinary Studies in Education. 2026, Vol. 15 Issue 5, p321-353. 33p.
Abstract: This study presents a systematic literature review and bibliometric analysis examining how chatbots and virtual agents are used in educational and professional training. Drawing from 52 articles (2021-2025) and a thematic synthesis of ten empirical studies, this review addresses eight research questions concerning chatbot applications, feedback mechanisms, challenges, design features, and effectiveness. The findings show that chatbots are widely deployed as virtual patients, simulated students, and interactive tutors across medicine, teacher education, programming, and risk assessment. Personalized, real-time feedback positively affects learning outcomes, while key challenges include limited empathy, inconsistent responses, and AI overreliance. The review also maps publication trends and emerging themes around LLMs and emotionally responsive interfaces, offering a framework for educators, developers, and policymakers in the design of ethical, sustainable AI-based training interventions. [ABSTRACT FROM AUTHOR]
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Database: Education Research Complete
Description
Abstract:This study presents a systematic literature review and bibliometric analysis examining how chatbots and virtual agents are used in educational and professional training. Drawing from 52 articles (2021-2025) and a thematic synthesis of ten empirical studies, this review addresses eight research questions concerning chatbot applications, feedback mechanisms, challenges, design features, and effectiveness. The findings show that chatbots are widely deployed as virtual patients, simulated students, and interactive tutors across medicine, teacher education, programming, and risk assessment. Personalized, real-time feedback positively affects learning outcomes, while key challenges include limited empathy, inconsistent responses, and AI overreliance. The review also maps publication trends and emerging themes around LLMs and emotionally responsive interfaces, offering a framework for educators, developers, and policymakers in the design of ethical, sustainable AI-based training interventions. [ABSTRACT FROM AUTHOR]
ISSN:21662681
DOI:10.32674/jrw9d811