Abstract
The widespread use of chatbots is a reality and their application in higher education is promising. Understanding higher education users’ expectations for the use of chatbots in education is important for the design and development of new solutions. The present investigation documents how higher education users envision the pedagogical uses of chatbots in higher education, and how experts in the domain of education chatbots perceive the potential benefits and challenges related to the use of chatbots in education. A qualitative inquiry was undertaken based on 22 semi-structured interviews with higher-education students and instructors, and experts from the fields of Artificial Intelligence and educational chatbots. Based on our findings, the envisioned pedagogical uses of chatbots can be categorized in terms of chronological integration into the learning process: prospective, on-going, and retrospective. Under each one of those higher-order categories, specific learning domains can be supported (i.e., cognitive, affective), besides administrative tasks. Benefits and challenges foreseen in the use of pedagogical chatbots are presented and discussed. The findings of this study highlight the manner in which higher-education users envision the use of chatbots in education, with potential implications on the creation of specific pedagogical scenarios, accounting also for the learning context, chatbot technology, and pedagogies that are deemed appropriate in each scenario.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Alepis, E., Virvou, M.: Automatic generation of emotions in tutoring agents for affective e-learning in medical education. Expert Syst. Appl. 38(8), 9840–9847 (2011)
Anderson, R.: Reforming science teaching: what research says about inquiry. J. Sci. Teacher Educ. 13(1), 1–12 (2002)
Anderson, L.W., Krathwohl, D.R. (eds.): A Taxonomy for Learning, Teaching, and Assessing: A Revision of ‘s Taxonomy of Educational Objectives. Longman, New York (2001)
Ayedoun, E., Hayashi, Y., Seta, K.: A conversational agent to encourage willingness to communicate in the context of English as a foreign language. Procedia Comput. Sci. 60, 1433–1442 (2015)
Baker, R.S.: Stupid tutoring systems, intelligent humans. Int. J. Artif. Intell. Educ. 26(2), 600–614 (2016)
Beck, J., Woolf, B.P., Beal, C.R.: ADVISOR: a machine learning architecture for intelligent tutor construction. AAAI/IAAI, pp. 552–557 (2000)
Bickmore, T.W., Schulman, D., Sidner, C.: Automated interventions for multiple health behaviors using conversational agents. Patient Educ. Couns. 92(2), 142–148 (2013)
Bii, P.K., Too, J.K., Mukwa, C.W.: Teacher attitude towards use of chatbots in routine teaching. Univ. J. Educ. Res. 6(7), 1586–1597 (2018)
Bloom, B.S., Engelhart, M.D., Furst, E.J., Hill, W.H., Krathwohl, D.R.: Taxonomy of educational objectives: The classification taxonomy of educational goals. In: Handbook 1: Cognitive Domain. David McKay, New York (1956)
Brandtzaeg, P.B., Følstad, A.: Chatbots: changing user needs and motivations. Interactions 25(5), 38–43 (2018)
Colace, F., De Santo, M., Lombardi, M., Pascale, F., Pietrosanto, A., Lemma, S.: Chatbot for e-learning: a case of study. Int. J. Mech. Eng. Robot. Res. 7(5), 528–533 (2018)
Dignum, V.: Ethics in artificial intelligence: introduction to the special issue. Ethics Inf. Technol. 20(1), 1–3 (2018). https://doi.org/10.1007/s10676-018-9450-z
Dutta, D.: Developing an Intelligent Chat-bot Tool to assist high school students for learning general knowledge subjects. Georgia Institute of Technology (2017)
Eisenhardt, K.M.: Building theories from case study research. Acad. Manag. Rev. 14(4), 532–550 (1989)
Feine, J., Morana, S., Gnewuch, U.: Measuring Service Encounter Satisfaction with Customer Service Chatbots using Sentiment Analysis (2019)
Følstad, A., Brandtzæg, P.B.: Chatbots and the new world of HCI. Interactions 24(4), 38–42 (2017)
Fryer, L.K., Ainley, M., Thompson, A., Gibson, A., Sherlock, Z.: Stimulating and sustaining interest in a language course: an experimental comparison of chatbot and human task partners. Comput. Hum. Behav. 75, 461–468 (2017)
Goel, A., Creeden, B., Kumble, M., Salunke, S., Shetty, A., Wiltgen, B.: Using watson for enhancing human-computer co-creativity. In: 2015 AAAI Fall Symposium Series (2015)
Gonda, D.E., Luo, J., Wong, Y.L., Lei, C.U.: Evaluation of developing educational chatbots based on the seven principles for good teaching. In: 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE), pp. 446–453. IEEE (2018)
Gupta, S., Bostrom, R.: Research note—an investigation of the appropriation of technology-mediated training methods incorporating enactive and collaborative learning. Inf. Syst. Res. 24(2), 454–469 (2013)
Gupta, S., Jagannath, K., Aggarwal, N., Sridar, R., Wilde, S., Chen, Y.: Artificially Intelligent (AI) Tutors in the Classroom: A Need Assessment Study of Designing Chatbots to Support Student Learning (2019)
Harley, J.M., et al.: Examining the predictive relationship between personality and emotion traits and students’ agent-directed emotions: towards emotionally-adaptive agent-based learning environments. User Model. User-Adap. Inter. 26(2–3), 177–219 (2016). https://doi.org/10.1007/s11257-016-9169-7
Hone, K.S., El Said, G.R.: Exploring the factors affecting MOOC retention: a survey study. Comput. Educ. 98, 157–168 (2016)
Howlett, N.: How machine learning is developing to get more insight from complex voice-of-customer data. Appl. Mark. Anal. 3(3), 250–254 (2017)
Huang, J.X., Lee, K.S., Kwon, O.W., Kim, Y.K.: A chatbot for a dialogue-based second language learning system. CALL in a climate of change: adapting to turbulent global conditions, 151 (2017)
Jia, J., Chen, W.: Motivate the learners to practice English through playing with Chatbot CSIEC. In: Pan, Z., Zhang, X., El Rhalibi, A., Woo, W., Li, Yi. (eds.) Technologies for E-Learning and Digital Entertainment. Lecture Notes in Computer Science, vol. 5093, pp. 180–191. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-69736-7_20
Keller, C., Cernerud, L.: Students’ perceptions of e-learning in university education. J. Educ. Media 27(1–2), 55–67 (2002)
Kerfoot, B.P., et al.: A multi-institutional randomized control trial of web-based teaching to medical students. Acad. Med. 81(3), 224–230 (2006)
Kerly, A., Ellis, R., Bull, S.: Dialog systems in e-learning. In: Proceedings of AI2008, pp. 169–182 (2008)
Knill, O., Carlsson, J., Chi, A., Lezama, M.: An artificial intelligence experiment in college math education (2004)
Krathwohl, D.R., Bloom, B.S., Masia, B.B.: Taxonomy of educational objectives: the classification of educational goals. In: Handbook II: Affective Domain. David McKay Company, Incorporated (1956)
Kwon, O.W., Lee, K., Kim, Y.K., Lee, Y.: GenieTutor: a computer assisted second-language learning system based on semantic and grammar correctness evaluations. In: Critical CALL–Proceedings of the 2015 EUROCALL Conference, pp. 330–335. Research-publishing, Net (2015)
Lee, T., et al.: Intelligent Career Advisers in Your Pocket? A Need Assessment Study of Chatbots for Student Career Advising (2019)
Lee, Y.C., Fu, W.T.: Supporting peer assessment in education with conversational agents. In: Proceedings of the 24th International Conference on Intelligent User Interfaces: Companion, pp. 7–8 (2019)
Lundqvist, K.O., Pursey, G., Williams, S.: Design and implementation of conversational agents for harvesting feedback in eLearning systems. In: Hernández-Leo, D., Ley, T., Klamma, R., Harrer, A. (eds.) Scaling up Learning for Sustained Impact. Lecture Notes in Computer Science, vol. 8095, pp. 617–618. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-40814-4_79
Ma, W., et al.: TripleNet: Triple Attention Network for Multi-Turn Response Selection in Retrieval-based Chatbots. arXiv preprint arXiv:1909.10666 (2019)
Molnár, G., Szüts, Z.: The role of chatbots in formal education. In: 2018 IEEE 16th International Symposium on Intelligent Systems and Informatics (SISY), pp. 000197–000202. IEEE (2018)
Mimoun, M.S.B., Poncin, I.: A valued agent: how ECAs affect website customers’ satisfaction and behaviors. J. Retail. Consum. Serv. 26, 70–82 (2015)
Novielli, N., de Rosis, F., Mazzotta, I.: User attitude towards an embodied conversational agent: effects of the interaction mode. J. Pragmatics 42(9), 2385–2397 (2010)
Oudeyer, P.Y., Gottlieb, J., Lopes, M.: Intrinsic motivation, curiosity, and learning: theory and applications in educational technologies. In: Progress in Brain Research, vol. 229, pp. 257–284. Elsevier (2016)
Patton, M.Q.: Qualitative Research and Methods: Integrating Theory and Practice. SAGE Publications, Thousand Oaks (2015)
Picciano, A.G.: Educational Leadership and Planning for Technology, 2nd edn. Prentice-Hall Inc., USA (1998)
Popovici, A., Mironov, C.: Students’ perception on using eLearning technologies. Procedia-Soc. Behav. Sci. 180, 1514–1519 (2015)
Savery, J.R., Duffy, T.M.: Problem based learning: an instructional model and its constructivist framework. Educ. Technol. 35(5), 31–38 (1995)
Serban, I.V., et al.: A deep reinforcement learning chatbot. arXiv preprint arXiv:1709.02349 (2017)
Shawar, B.A., Atwell, E.: Chatbots: are they really useful? Ldv forum 22, 29–49 (2007)
Sheikh, S.A., Tiwari, V., Singhal, S.: Generative model chatbot for human resource using deep learning. In: 2019 International Conference on Data Science and Engineering (ICDSE), pp. 126–132. IEEE (2019)
Smutny, P., Schreiberova, P.: Chatbots for learning: a review of educational chatbots for the Facebook Messenger. Comput. Educ. 151, 103862 (2020)
Söllner, M., Bitzer, P., Janson, A., Leimeister, J.M.: Process is king: evaluating the performance of technology-mediated learning in vocational software training. J. Inf. Technol. 33(3), 233–253 (2018)
Stathakarou, N., et al.: Students’ perceptions on chatbots’ potential and design characteristics in healthcare education. Stud. Health Technol. Inform. 272, 209–212 (2020)
Strauss, A., Corbin, J.: Grounded theory methodology. Handbook Qual. Res. 17, 273–285 (1994)
Strauss, A., Corbin, J.: Basics of qualitative research: Techniques and procedures for developing grounded theory, 2nd edn. Sage, Thousan Oaks (1998)
Thai, M.T.T., Chong, L.C., Agrawal, N.M.: Straussian grounded theory method: an illustration. Qual. Rep. 17(5), 1–55 (2012)
Thies, I.M., Menon, N., Magapu, S., Subramony, M., O’Neill, J.: How do you want your chatbot? An exploratory Wizard-of-Oz study with young, urban Indians. In: Bernhaupt, R., Dalvi, G., Joshi, A., Balkrishan, D.K., O’Neill, J., Winckler, M. (eds.) Human-Computer Interaction – INTERACT 2017. Lecture Notes in Computer Science, vol. 10513, pp. 441–459. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-67744-6_28
Tsivitanidou, O., Ioannou, A.: Users' needs assessment for chatbots’ use in Higher Education. In: Proceedings of the Central European Conference on Information and Intelligent Systems, pp. 55–62 (2021). Faculty of Organization and Informatics, University of Zagreb. ISSN 1848–2295 (Online)
Winkler, R., Söllner, M.: Unleashing the potential of chatbots in education: a state-of-the-art analysis (2018)
van der Meij, H., van der Meij, J., Harmsen, R.: Animated pedagogical agents effects on enhancing student motivation and learning in a science inquiry learning environment. Educ. Tech. Res. Dev. 63(3), 381–403 (2015). https://doi.org/10.1007/s11423-015-9378-5
Yan, M., Castro, P., Cheng, P., Ishakian, V.: Building a chatbot with serverless computing. In: Proceedings of the 1st International Workshop on Mashups of Things and APIs, pp. 1–4 (2016)
Zemčík, M.T.: A brief history of chatbots. In: DEStech Transactions on Computer Science and Engineering. AICAE (2019)
Acknowledgments
This work is part of the project EDUBOTS, which is funded under the scheme Erasmus + KA2: Cooperation for innovation and the exchange of good practices - Knowledge Alliances (grant agreement no: 612446), and from the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement No 739578 and the Government of the Republic of Cyprus through the Directorate General for European Programmes, Coordination, and Development.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Tsivitanidou, O., Ioannou, A. (2021). Envisioned Pedagogical Uses of Chatbots in Higher Education and Perceived Benefits and Challenges. In: Zaphiris, P., Ioannou, A. (eds) Learning and Collaboration Technologies: Games and Virtual Environments for Learning. HCII 2021. Lecture Notes in Computer Science(), vol 12785. Springer, Cham. https://doi.org/10.1007/978-3-030-77943-6_15
Download citation
DOI: https://doi.org/10.1007/978-3-030-77943-6_15
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-77942-9
Online ISBN: 978-3-030-77943-6
eBook Packages: Computer ScienceComputer Science (R0)