Promoting academically productive talk with conversational agent interventions in collaborative learning settings
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Chatbot interventions could effectively stimulate group discussions and help students utter their thoughts.
“Chatbot interventions could effectively stimulate group discussions and help students utter their thoughts [55].”
From A Meta-Analysis and Systematic Review of the Effect of Chatbot Technology Use in Sustainable Education (2023) · cites this paper as [55]
Cites
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Corbin, J. M., & Strauss, A. (1990) · Qualitative Sociology · doi:10.1007/bf00988593 · Cited by 11,133 · see citing works
Mediation Analysis in Social Psychology: Current Practices and New Recommendations
Rucker, D. D., Preacher, K. J., Tormala, Z. L., & Petty, R. E. (2011) · Social and Personality Psychology Compass · doi:10.1111/j.1751-9004.2011.00355.x · Cited by 2,430 · see citing works
A Normalized Levenshtein Distance Metric
Yujian, L., & Bo, L. (2007) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2007.1078 · Cited by 986 · see citing works
Towards an Agile Approach to Adapting Dynamic Collaboration Support to Student Needs
Adamson, D., Dyke, G., Jang, H., & Rosé, C. P. (2014) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-013-0012-6 · Cited by 156 · see citing works
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Interacting with educational chatbots: A systematic review
Kuhail, M. A., Alturki, N., Alramlawi, S., & Alhejori, K. (2023) · Education and Information Technologies · doi:10.1007/s10639-022-11177-3 · Cited by 841 · see citing works
The impact of ChatGPT on higher education
Dempere, J., Modugu, K., Hesham, A., & Ramasamy, L. K. (2023) · Frontiers in Education · doi:10.3389/feduc.2023.1206936 · Cited by 519 · see citing works
“Tegos et al. (2015) analyzed the effects of chatbots in collaborative learning experiences among college students, finding that tech increases various knowledge acquisition measures.”
BackgroundDeng, X., & Yu, Z. (2023) · Sustainability · doi:10.3390/su15042940 · Cited by 298 · see citing works
“, [44,55]) have attempted to mitigate the novelty effect by introducing and familiarizing students with chatbot technology prior to intervention.”
BackgroundMetatla, O., Oldfield, A., Ahmed, T., Vafeas, A., & Miglani, S. (2019) · Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3290605.3300608 · Cited by 112 · see citing works
Yusuf, H., Money, A., & Daylamani-Zad, D. (2025) · Educational technology research and development · doi:10.1007/s11423-025-10447-4 · Cited by 112 · see citing works
Ouyang, F., Guo, M., Zhang, N., Bai, X., & Jiao, P. (2024) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2024.3486749 · Cited by 39 · see citing works
Desai, S., & Chin, J. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3581507 · Cited by 38 · see citing works
“While some studies use chatbots and intelligent tutoring systems in pedagogy [82, 95, 104], there is limited literature discussing VUIs for informal self-regulated learning.”
BackgroundXie, T., Liu, R., Chen, Y., & Liu, G. (2021) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2021.3129800 · Cited by 32 · see citing works
Multimodal modeling of collaborative problem-solving facets in triads
Stewart, A. E. B., Keirn, Z., & D’Mello, S. K. (2021) · User Modeling and User-Adapted Interaction · doi:10.1007/s11257-021-09290-y · Cited by 30 · see citing works
Breideband, T., Bush, J. B., Reitman, J. G., Rose, S., Weatherley, J., Penuel, W. R., & D’Mello, S. K. (2025) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-025-00509-2 · Cited by 5 · see citing works
“…(Adamson, Ashe, et al. 2014; Adamson, Dyke, et al., 2014a, 2014b; Dyke et al., 2013; Kumar & Rose, 2010) and others (Tegos & Demetriadis, 2017; Tegos et al., 2015) have illustrated the viability of using computer agents to engage students in collaborative discourse (Michaels & O’Connor, 2015).”
Liu, W., & Cui, X. (2024) · 2024 4th International Conference on Educational Technology (ICET) · doi:10.1109/icet62460.2024.10868171 · Cited by 4 · see citing works
- Authors
- Tegos, S., Demetriadis, S., & Karakostas, A.
- Affiliations
- Aristotle University of Thessaloniki (GR)
- Corresponding author
- Tegos, Stergios
- Venue
- Computers & Education
- Publisher
- Elsevier BV
- Published
- 2015-09
- Volume
- 87
- Pages
- 309-325
- ISSN
- 0360-1315 (ISSN-L)
- OpenAlex
- W1418763296
- Cited by
- 90
- References
- 4
- Citations by year
- 2026: 7 · 2025: 12 · 2024: 19 · 2023: 9 · 2022: 10 · 2021: 14 · 2020: 6 · 2019: 5 · 2018: 3 · 2017: 1 · 2016: 4
- FWCI
- 2.62
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Computers & Education (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Visual and Cognitive Learning Processes
- Keywords
- chatbots, educational agents, computer-supported collaborative learning, dialogue support, explicit reasoning, argumentation, knowledge acquisition, multimedia learning, higher education, small group collaboration
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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