The DOI matches its Crossref record; 53 of the 54 references it cites were found in a registry or an index.
Using chatbots to support student goal setting and social presence in fully online activities: learner engagement and perceptions
Open accessAbstract
Although fully online learning is now the 'new normal' in many parts of the world, its implementation is often beset by challenges such as the lack of student self-regulation, and the sense of isolation. In this paper, we explored the use of chatbots to support student goal setting (Study 1) and social presence (Study 2) in online activities. In Study 1, participants in a fully online course were invited to complete a goal setting activity prior to attending class via a goal-setting chatbot. The chatbot engaged participants with five questions developed based on the SMART (specific, measurable, achievable, realistic, and timely) goal setting framework. In Study 2, English-as-Foreign-Language participants in a fully online course were tasked to complete listening practices. The learning buddy chatbot was designed based on the social presence framework (interpersonal communication, open communication, cohesive communication) to guide students through listening exercises. In both Study 1 and 2, we evaluated participants' behavioral engagement by measuring their conversation records with the chatbots, as well as participants' perceived usefulness and ease of use of the chatbots. We also gathered in-depth interview data concerning the participants' perceptions of interacting with the chatbots. Overall, our findings found positive learner experiences with both chatbots with regard to the chatbots' perceived usefulness and perceived ease of use. We also provided suggestions for instructors to apply chatbots in teaching and learning.
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Citations
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“Social presence can be defined as “the ability of participants to project themselves socially and emotionally, as real people” (Garrison et al., 1999, p. 94).”
BackgroundELIZA—a computer program for the study of natural language communication between man and machine
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“The first chatbot, ELIZA, developed in 1966, simulated a psychotherapist’s conversation with humans, where users could communicate with ELIZA by entering text inputs, and the chatbot would respond in kind (Weizenbaum, 1966).”
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“It is therefore suggested that in the long-term use of chatbot, it is important to add variety to sustain the interest in learning with the chatbot (Keller, 1987), by either simplifying or making some changes to the reoccurring sentences.”
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Facilitating student engagement through ChatGPT
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The Involvement of Academic and Emotional Support for Sustainable Use of MOOCs
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“AI in education and conversational agents are also particularly good at forecasting the cognitive demands, outcomes, mental states, and talents of students and then advising the appropriate course of action to take as a result of automated responses (Hew et al., 2023).”
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Adaptive metacognitive prompting in young learners and the role of prior performance
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Shaping the Future of Education: AI ‐Driven Approaches for Primary Schools
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The Application of ChatGPT in Chinese MTI Students’ Autonomous Learning
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Enhancing Self-regulated Learning Through an Emotional Chatbot: A Conceptual Framework
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“Artificial intelligence (AI) has become a potent educational tool by facilitating human-computer interaction as it offers customized and personalized learning experiences (Hew et al., 2022; Jeon, 2022).”
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Li Bai the Youth: An LLM-Powered Virtual Agent for Children's Chinese Poetry Education
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Development of an AI-Powered System for Thesis Advisor Consultations
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“Effective Communication and Engagement: Chat AI facilitates real-time communication, increasing student engagement and providing timely support [55].”
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“The SRL chat assistant by Hew et al. [38] helped students set online learning objectives.”
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Harnessing AI for Sustainable Education: Pathways and Implications
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Enhancing foreign language learning through AI-driven telecollaboration
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BizAssistBot: an artificial intelligence assistant for small business operations
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INTEGRATING AI IN ONLINE LEARNING IN HIGHER EDUCATION: A LITERATURE REVIEW
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“Open-ended questionnaires (Hew et al., 2023; Jefrey, 2020) and semi-structured interviews (Gillissen et al., 2022) have also been used by a few studies to investigate deeper into the research problems.”
Interplay effects of AI feedback and individual differences on learners’ emotional responses
xiangming, L., & Wei, W. (2026) · Education and Information Technologies · doi:10.1007/s10639-026-13937-x · Cited by 4
“Their self-assess - ment, learning interests with AI tools, teacher assessment, and AI’s evaluative comments aligned with each other to some degree (Hew et al., 2023).”
Zhang, Q., & Liang, Y. (2026) · Education and Information Technologies · doi:10.1007/s10639-026-14038-5 · Cited by 5
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Yang, C. H., Li, R. F., & Feng, D. (2026) · The Asia-Pacific Education Researcher · doi:10.1007/s40299-026-01132-y · Cited by 1
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Cheah, Y. H., Hsu, H.-P., Lu, J., & Alsaka, R. (2026) · Journal of Research on Technology in Education · doi:10.1080/15391523.2026.2704778 · Cited by 1
“Better Than Human” in Partnership With AI
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“Their primary function is to act as co-pilots, ensuring that students receive continuous assistance while developing self-regulated learning skills, which in turn enables them to personalise their learning experience in a way that best suits their individual needs [17], [31].”
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Baskara, R. (2023) · The Journal Of English Teaching For Young And Adult Learners · doi:10.21137/jeeyal.2023.2.2.1
“It was observed that chatbots, engineered to respond to students' queries, offer feedback, and stimulate discussions, yielded significant improvements in student engagement (Hew et al., 2022).”
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Muzammil, L., Purnawati, M., Andy, A., & Arifani, F. H. (2024) · Research and Development in Education (RaDEn) · doi:10.22219/raden.v4i1.32919
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Revolutionizing Online Learning: The Role of Chatbots and Virtual Assistants
Almoghrbel, B., Moughrbel, W., & Yavuz, M. (2025) · Özgür Yayınları eBooks · doi:10.58830/ozgur.pub773.c3209
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Metadata
- Authors
- Hew, K. F., Huang, W., Du, J., & Jia, C.
- Affiliations
- University of Hong Kong (HK)
- Zhejiang University (CN)
- Corresponding author
- Hew, Khe Foon
- Venue
- Journal of Computing in Higher Education
- Published
- 2022-09-09
- Volume
- 35
- Issue
- 1
- Pages
- 40-68
- ISSN
- 1042-1726 (ISSN-L)
- 1867-1233
- PMC
- PMC9458299
- OpenAlex
- W4295753326
- Cited by
- 245
- References
- 54
- Citations by year
- 2026: 53 · 2025: 89 · 2024: 59 · 2023: 43 · 2022: 1
- FWCI
- 15.80
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Journal of Computing in Higher Education (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- University of Hong Kong (Teaching Development Grant)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Social Sciences › Education › Online and Blended Learning
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Keywords
- chatbots, student goal setting, social presence, fully online learning, student engagement, student self-regulation, learner isolation, SMART goals, English as a foreign language, listening practices, perceived usefulness, perceived ease of use, learner perceptions
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