Chatbot-mediated Learning: Conceptual Framework for the Design of Chatbot Use Cases in Education
Open accessAbstract
While chatbots or conversational agents are already common in many business areas, e.g. for customer support, their use in the education sector is still in its infancy. Chatbots might take over the role of a teacher, tutor, conversational partner, learning analyst, team member, support assistant, or recommender system. Within these different roles, chatbots can enhance learning and inherently address many requirements and success factors for learning. The scalability and adaptiveness of conversational AI allow an individualised learning support for all learners combined with collaboration opportunities and thus more equality in education. In this context, the paper at hand discusses this pedagogical potential of chatbots in different roles and social settings resulting in a conceptual framework for the understanding and design of chatbot use cases in education. Based on success factors for learning derived from established learning theories and reports, core attributes and goals of chatbot learning are deducted within three pedagogical domains of individual, social and analytic chatbot learning. By combining this pedagogical dimension with a technological and content dimension, the presented conceptual framework provides an overview of possibilities of how chatbots in education can be used and designed.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The text we found for this paper looks like another document, so the self-check wasn’t run.
Cites
Self-Efficacy: The Exercise of Control
Bandura, A. (1977) · Oxford University Press eBooks · doi:10.1037/10522-094 · Cited by 57,663 · cited 4× · see citing works
“…theory (Deci & Ryan, 2012) Autonomy experience Social relatedness Competence experience Self-efficacy / social cognitive theory (Bandura, 1997) Self-Mastery; Self-Regulation Role-Modelling; Verbal persuasion Self-Efficacy; Feedback Self-regulation theory (Leventhal et al.,…”
BackgroundMethodInfluentialI.—COMPUTING MACHINERY AND INTELLIGENCE
TURING, A. M. (1950) · Mind · doi:10.1093/mind/lix.236.433 · Cited by 10,290 · cited 1× · see citing works
“From an ultimate technological perspective, the goal of a chatbot and consequently the evaluation focus might be to pass the so-called Turing test (cf. Turing, 1950), meaning that the optimal chatbot cannot be distinguished from humans.”
BackgroundELIZA—a computer program for the study of natural language communication between man and machine
Weizenbaum, J. (1966) · Communications of the ACM · doi:10.1145/365153.365168 · Cited by 4,452 · cited 1× · see citing works
“While the first chatbot named Eliza was already developed over 50 years ago by Weizenbaum (1966), the major developments have happened in recent years.”
BackgroundKremer, J., Moran, A. P., Walker, G., et al. (2012) · doi:10.4135/9781446288702.n14 · Cited by 3,640 · cited 2×
“A corpus of learning-related theories (Bandura, 1997; Deci & Ryan, 2012; Leventhal et al., 1984) and reports (Bransford et al., 2000; Hattie & Yates, 2013; ISTE, 2017) was chosen based on broad acceptance in educational research and related based on its key concepts and constructs for learning…”
BackgroundMethodChatbots: History, technology, and applications
Adamopoulou, E., & Moussiades, L. (2020) · Machine Learning with Applications · doi:10.1016/j.mlwa.2020.100006 · Cited by 1,090 · cited 2× · see citing works
“From a business perspective chatbots mainly allow to improve customer service and to reduce service costs, from a user’s perspective important motivations to use chatbots are productivity, entertainment, social factors and novelty interaction (Adamopoulou & Moussiades, 2020).”
BackgroundChatbots for learning: A review of educational chatbots for the Facebook Messenger
Smutny, P., & Schreiberova, P. (2020) · Computers & Education · doi:10.1016/j.compedu.2020.103862 · Cited by 770 · cited 2× · see citing works
“And in terms of developing a chatbot for learning purposes, Smutny and Schreiberova (2020) offer a list of attributes describing the quality of an educational chatbot within the categories teaching (e.g. set goals and monitor learning progress), humanity (e.g. able to maintain themed discussion),…”
BackgroundUnleashing the Potential of Chatbots in Education: A State-Of-The-Art Analysis
Winkler, R., & Soellner, M. (2018) · Academy of Management Proceedings · doi:10.5465/ambpp.2018.15903abstract · Cited by 581 · cited 7× · see citing works
“…traditional intelligent tutoring systems or pedagogical agents in e-learning scenarios, chatbots do not only give instructions or provide feedback, but can also react to individual intents and create a real personalization and more importantly, a learner-centred approach (Winkler & Söllner, 2018).”
BackgroundInfluentialA Survey on Dialogue Systems: Recent Advances and New Frontiers
Chen, H., Liu, X., Yin, D., & Tang, J. (2017) · ACM SIGKDD Explorations Newsletter · doi:10.1145/3166054.3166058 · Cited by 579 · cited 1× · see citing works
“While we refer to both categories as chatbots, other researchers with a more technical perspective prefer the umbrella term ‘conversational systems’ and then differentiate between more domain- or task-specific ‘dialog systems’ and generic ‘chatbots’ (cf. Chen et al., 2017).”
BackgroundIllness Representations and Coping With Health Threats
Leventhal, H., Nerenz, D. R., & Steele, D. J. (2020) · Routledge eBooks · doi:10.4324/9781003044307-9 · Cited by 558 · cited 2× · see citing works
“A corpus of learning-related theories (Bandura, 1997; Deci & Ryan, 2012; Leventhal et al., 1984) and reports (Bransford et al., 2000; Hattie & Yates, 2013; ISTE, 2017) was chosen based on broad acceptance in educational research and related based on its key concepts and constructs for learning…”
MethodChatbot learning partners: connecting learning experiences, interest and competence
Fryer, L. K., Nakao, K., & Thompson, A. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2018.12.023 · Cited by 470 · cited 4× · see citing works
“Fryer et al. (2019) summarize that in early research chatbots as language practice tools were shown to be useful for advanced and motivated students, but showed limitations in terms of in- and output quality.”
BackgroundInfluentialViewpoint: Human-in-the-loop Artificial Intelligence
Zanzotto, F. M. (2019) · Journal of Artificial Intelligence Research · doi:10.1613/jair.1.11345 · Cited by 380 · cited 1× · see citing works
“Zanzotto (2019) calls for responsible AI with a "human-in-theloop" and a clear knowledge life cycle to prevent a bias of the AI or the chatbot.”
BackgroundVisible learning and the science of how we learn
Stephenson, J. (2014) · Australian Journal of Learning Difficulties · doi:10.1080/19404158.2014.936332 · Cited by 367 · cited 3× · see citing works
“…(ISTE, 2017) Communication skills; decision making Collaboration skills; creativity; empathy Critical thinking; Use of technology Visible learning (Hattie & Yates, 2013) Feedback; Self-Verbalisation Reciprocal teaching (dialog based) Formative evaluation; Meta-cognitive strategy Table 3:…”
BackgroundMethodBodily, R., & Verbert, K. (2017) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2017.2740172 · Cited by 306 · cited 2× · see citing works
“A future chatbot might also combine and integrate the intelligence of the different student-facing learning analytics systems distinguished by Bodily and Verbert (2017): Learning Analytics Dashboards, Educational Recommender Systems, Educational Data Mining Systems, Intelligent Tutoring Systems.”
BackgroundThe Role of Chatbots in Formal Education
Molnár, G., & Szűts, Z. (2018) · IEEE International Symposium on Intelligent Systems and Informatics (SISY) · doi:10.1109/sisy.2018.8524609 · Cited by 198 · cited 5× · see citing works
“…Webservice (on any device) Social Media (known channel) Embedded in LMS (on any device) Content dimensions Contextual data integration Cf. (Molnar & Szuts, 2018; Winkler & Söllner, 2018) Basic domain knowledge database Basic context data (time, location, user) Personalisation with…”
BackgroundInfluentialThe Evolution of Research on Digital Education
Dillenbourg, P. (2016) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-016-0106-z · Cited by 136 · cited 1× · see citing works
“Since chatbot projects in education, just like innovations in learning technologies, are often driven by a technological direction, it is recommended to combine the pedagogical with the technological perspective at an early stage to develop a shared new vision of learning (Dillenbourg, 2016).”
BackgroundStrategy and Policy Learning for Non-Task-Oriented Conversational Systems
Zhou, Y., Xu, Z., Black, A. W., & Rudnicky, A. I. (2016) · Annual Meeting of the Special Interest Group on Discourse and Dialogue · doi:10.18653/v1/w16-3649 · Cited by 92 · cited 1× · see citing works
“…• Analysis of real dialogs and questions • Creation of bot scripts • Bot training by defining intents • Bot skills development • Testing the chatbot • Optimize in productive use When designing chatbot dialogs, general and education specific design principles can be helpful (cf. Yu et al., 2016).”
BackgroundExplainable Artificial Intelligence (XAI)
Ridley, M. (2022) · Information Technology and Libraries · doi:10.6017/ital.v41i2.14683 · Cited by 87 · cited 1× · see citing works
“In addition to data protection, there is an important demand for explainable AI (XAI), which is particularly important in the field of education (Gunning, 2017).”
BackgroundBriefing Paper: Chatbots in Education
Brustenga, G. G., Alpiste, M. F. I., & Castells, N. M. (2018) · doi:10.7238/elc.chatbots.2018 · Cited by 64 · cited 6× · see citing works
“Dimensions Characteristics (can be met supplementary) Pedagogical dimensions Chatbot role in individual learning setting Cf. (Garcia Brustenga et al., 2018) Support assistant e.g. research assistant, FAQ, Nerdybot Conversational partner e.g. communication trainer, tutor Recommender system e.g.…”
BackgroundMethodInfluentialHow Are You, Chatbot? Evaluating Chatbots in Educational Settings - Results of a Literature Review
Hobert, S. (2019) · Fachtagung "e-Learning" der Gesellschaft für Informatik · doi:10.18420/delfi2019_289 · Cited by 44 · cited 4× · see citing works
“This leads to complementary but different research procedures and evaluation approaches (Hobert, 2019).”
BackgroundResultInfluentialA Chatbot for a Dialogue-Based Second Language Learning System.
Huang, J.-X., Lee, K.-S., Kwon, O.-W., et al. (2017) · doi:10.14705/rpnet.2017.eurocall2017.705 · Cited by 31 · cited 1×
“Most studies, that have shown successful implementations of chatbot learning scenarios (cf. Dutta, 2017; Goel et al., 2016; Huang et al., 2017), are based on projects with isolated chatbot tasks, e.g. to answer frequently asked questions, to handle forum posts, or to ask questions in language…”
BackgroundChatbots for the Information Acquisition at Universities – A Student’s View on the Application Area
von Wolff, R. M., Nörtemann, J., Hobert, S., & Schümann, M. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-39540-7_16 · Cited by 30 · cited 1× · see citing works
“Previous research on chatbots in education often focuses on designing messenger-like chatbots but there might be a lack on generalizable results (Meyer von Wolff et al., 2020).”
BackgroundLearning analytics im Hochschulkontext
Ifenthaler, D., & Schumacher, C. (2016) · doi:10.15358/0340-1650-2016-4-176 · Cited by 27 · cited 2×
“Future chatbots might include more collaborative learning, analytics (cf. Ifenthaler & Schumacher, 2016) and metacognition functions, use more advanced AI and generative models, and additionally retrieve and process social and context information (maturity level 2-3).”
BackgroundThe cognitive computing turn in education: Prospects and application
Lytras, M. D., Visvizi, A., Damiani, E., et al. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2018.11.011 · Cited by 22 · cited 4×
“Dimensions Characteristics (can be met supplementary) Pedagogical dimensions Chatbot role in individual learning setting Cf. (Garcia Brustenga et al., 2018) Support assistant e.g. research assistant, FAQ, Nerdybot Conversational partner e.g. communication trainer, tutor Recommender system e.g. learning path recommenda…”
BackgroundInfluentialSoziale Roboter im Bildungsbereich
Seufert, S., Guggemos, J., & Sonderegger, S. (2021) · Springer eBooks · doi:10.1007/978-3-658-31114-8_25 · Cited by 5 · see citing works
Self-citationChatbots und mediengestützte Konversation
Spierling, U., & Luderschmidt, J. (2018) · Springer eBooks · doi:10.1007/978-3-658-23297-9_22 · Cited by 2 · cited 3× · see citing works
“Dimensions Characteristics (can be met supplementary) Pedagogical dimensions Chatbot role in individual learning setting Cf. (Garcia Brustenga et al., 2018) Support assistant e.g. research assistant, FAQ, Nerdybot Conversational partner e.g. communication trainer, tutor Recommender system e.g. learning path recommenda…”
Background
Flagged first, then by citations
15 of the 40 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
A systematic literature review of empirical research on ChatGPT in education
Albadarin, Y., Saqr, M., Pope, N., & Tukiainen, M. (2024) · Discover Education · doi:10.1007/s44217-024-00138-2 · Cited by 191 · see citing works
“…chatbots, including ChatGPT, have demonstrated the potential to reshape and revolutionize education, creating new, novel opportunities for enhancing the learning process and outcomes [83], facilitating different learning approaches, and offering a range of pedagogical benefits [19, 43, 72].”
A Systematic Literature Review of Empirical Research on ChatGPT in EducationPreprint
Albadarin, Y., Tukiainen, M., Saqr, M., & Pope, N. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4562771 · Cited by 26 · see citing works
Revolutionising Role-Playing Games with ChatGPT
Stampfl, R., Geyer, B., Deissl-O’Meara, M., et al. (2024) · Advances in Artificial Intelligence and Machine Learning · doi:10.54364/aaiml.2024.42129 · Cited by 21 · see citing works
“In addition, we address the need for better management tools for educators and the creation of personalised learning experiences, as highlighted by Hedderich et al. [32], Sonderegger and Seufert [33], and Gan et al. [34], emphasising the practical aspects of using AI in education.”
BackgroundJaldemark, J., Lundin, J., Säljö, R., Edwards, J., Gegenfurtner, A., Holmes, W., Järvelä, S., de Laat, M. F., Lindberg, Y., Littlejohn, A. H., et al. (2025) · Postdigital Science and Education · doi:10.1007/s42438-025-00602-8 · Cited by 34 · see citing works
“Studies that build on AI-powered tools to support both personalisation and collaboration have the potential to enhance lifelong learning (Sonderegger and Seufert 2022).”
Self-citationSuryanto, T. L. M., Wibawa, A. P., Hariyono, H., & Nafalski, A. (2023) · International Journal of Robotics and Control Systems · doi:10.31763/ijrcs.v3i4.1195 · Cited by 21 · see citing works
An Examination of Studies on the Use of Chatbot Technology in the Field of Education
Durak, H. Y., & Onan, A. (2023) · International Conference on Applied Engineering and Natural Sciences · doi:10.59287/icaens.978 · Cited by 14 · see citing works
“In which areas and how this technology, which is based on technologies such as artificial intelligence, machine learning, natural language processing ([1], [2], [3] , [4], [5] , [6]), is used in education is an issue that needs to be examined.”
BackgroundSchmitz, D., & Becker, B. (2024) · Journal of Multidisciplinary Healthcare · doi:10.2147/jmdh.s424790 · Cited by 10 · see citing works
“8 According to Sonderegger and Seufert (2022), 8 there are three maturity levels of chatbots in education: chatbots for individual chatbot learning based on domain knowledge, chatbots for social or collaborative chatbot learning based on social and contextual knowledge, and chatbots for…”
BackgroundKrushinskaia, K., Elen, J., & Raes, A. (2024) · Communications in computer and information science · doi:10.1007/978-3-031-64312-5_49 · Cited by 15 · see citing works
Inteligencia Artificial en la Educación: Estado del Arte
Sambola, D.-M. (2023) · Wani · doi:10.5377/wani.v39i79.16806 · Cited by 8 · see citing works
“Sin embargo, se proyecta que podrán asumir el papel de profesor, tutor, asistente personal o analista de aprendizaje (Sonderegger & Seufert, 2022).”
Pedagogical Influence of AI-Chatbots on Learning Outcomes: A Systematic Review
Elkot, M. A., Alhalangy, A., AbdAlgane, M., & Ali, R. (2025) · International Journal of Educational Methodology · doi:10.12973/ijem.11.4.527 · Cited by 5 · see citing works
Chatbots in Educational Recommender Systems: A Systematic Literature Review
Pinho, P. C. R., & Primo, T. T. (2023) · IEEE Frontiers in Education Conference (FIE) · doi:10.1109/fie58773.2023.10343248 · Cited by 5 · see citing works
“Study Amount IEEE [3], [4], [5], [6], [7] 5 Scopus [8], [9], [10], [11], [12] [13], [14], [15], [16], [17] [18], [19], [20], [21], [22] [23], [24], [25], [26], [27] 20 ACM [28], [29], [30], [31], [32] [33], [34], [35], [36], [37] [38] 11 Science Direct [39] 1”
Seufert, S., & Meier, C. (2023) · Springer eBooks · doi:10.1007/978-3-658-40079-8_16 · Cited by 2 · see citing works
Self-citationMzwri, K., & Turcsányi-Szabó, M. (2025) · Advances in medical technologies and clinical practice book series · doi:10.4018/979-8-3693-3112-5.ch007 · Cited by 1 · see citing works
Nguyen, H. V., Yen, Y.-C. G., Shakir, O., Huynh, H., Gutierrez, S., Smith, J. A., Jimenez, S., Abdelgelil, S. E., & MacNeil, S. (2025) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3719160.3737636 · Cited by 1 · see citing works
“To explore how novice designers engage with traditional CUIs in a design feedback context, we conducted a formative study.”
Gül, F. Ö. (2025) · Journal of Educational Technology and Online Learning · doi:10.31681/jetol.1781815 · Cited by 1 · see citing works
How Can I Help You? Didactic Alignment for RAG Chatbots in Education
Lauber, A.-M., Martin, S., & Pampel, B. (2025) · International Conference on Education Technology and Computer · doi:10.1109/icetc66579.2025.11387412 · Cited by 1 · see citing works
“A N A BSOLUTE P RECONDITION : D IDACTIC E MBEDDING Initial attempts have been made to categorize standard LLM-based chatbots according to the roles they can take on in teaching and learning contexts [3], [11], [18].”
Цифрові інструменти розвитку емоційного інтелекту в умовах «Індустрії 4.0»
Федорова, Ю., Момот, Д., & Стешкін, С. (2024) · Adaptive Management Theory and Practice Economics · doi:10.33296/2707-0654-18(36)-19 · Cited by 1 · see citing works
Answering Student Queries with a Supervised Memory Conversational Agent
Baud, F., & Aussem, A. (2023) · Proceedings of the ... International Florida Artificial Intelligence Research Society Conference · doi:10.32473/flairs.36.133195
“(Sonderegger and Seufert 2022) propose a framework and address several limitations regarding data privacy and dependence on big technology suppliers.”
Backgroundتطوير بوت المحادثة (Chatboot) في بيئات التعلم الإلكترونية في ضوء تجربة المستخدم
المدهوني, ف. ع. م. (2024) · Tuknūlūǧyā Al-Taʿlīm wa Al-Taʿalum Al-Raqamī · doi:10.21608/jetdl.2024.267785.1097
Іваненко, В. (2024) · Наука і техніка сьогодні · doi:10.52058/2786-6025-2024-7(35)-698-709
Emotional Intelligence Training Tools in Entrepreneurship Education
Fedorova, Y. V., Pilková, A., Kovalenko, D., Mikuš, J., & Бондаренко, Т. (2024) · Lecture notes in networks and systems · doi:10.1007/978-3-031-72430-5_17
Lobus Frontalis und ChatGPT – Chatbots als Lernassistenz für Studierende
Großauer, B., Hörmann, C., & Sabitzer, B. (2024) · Zeitschrift für Hochschulentwicklung · doi:10.21240/zfhe/19-4/04
Case Study on Providing AI Chabot-Based Support Services in E-Learning Platforms
Baneș, V., & Ravariu, C. (2025) · Lecture notes in networks and systems · doi:10.1007/978-3-031-83520-9_56
Künstliche Intelligenz trifft Sexuelle Bildung. Eine Analyse des FragLovis Chatbots
Holzenkamp, S. (2025) · Zeitschrift für Sexualforschung · doi:10.1055/a-2673-6412
Widyananda, R., Maylinda, & Lie, Y. (2025) · International Conference on Cybernetics and Intelligent System (ICORIS) · doi:10.1109/icoris67789.2025.11296018
“Perceived security and trust not only affect credibility but also influence positive attitudes and adoption decisions [15].”
Rao, S. P. R., Li, L., Haddad, H., & He, S. (2026) · Journal of Information Systems Applied Research and Analytics · doi:10.62273/xqbk2345
Designing a Conversational AI Application Along Bloom’s Taxonomy for Higher Education
Lange, T. C., Schlimbach, R., Wagner, F., & Benz, N. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-29596-5_31
- Authors
- Sonderegger, S., & Seufert, S.
- Affiliations
- University of St.Gallen (CH)
- ORCID
- Seufert, Sabine
- Venue
- Proceedings of the 14th International Conference on Computer Supported Education
- Published
- 2022
- Pages
- 207-215
- OpenAlex
- W4285195611
- Cited by
- 29
- References
- 40
- Citations by year
- 2026: 2 · 2025: 10 · 2024: 9 · 2023: 8
- FWCI
- 3.73
- Type
- conference paper
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by-nc-nd
- Locations
- International Conference on Computer Supported Education (publishedVersion, cc-by-nc-nd)
- Alexandria (UniSG) (University of St.Gallen) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Keywords
- chatbots, educational chatbots, conceptual framework, personalized learning support, social learning, learning analytics
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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review