Abstract
This chapter discusses the design of a dialog-based intelligent tutoring system for the domain of Business Information Systems education. The system is designed to help students work on group projects, maintain their motivation, and provide subtle hints for self-directed discovery. We analyze the domain of Business Information Systems—which we find to be “ill-defined” in the sense that e.g. multiple conflicting solutions may exist and be acceptable for a given task. Based on an extensive collection of requirements derived from previous work, we propose a solution that helps both groups find solutions and individuals reflect on these solutions. This combination ensures that not only the group’s result is valid, but also that all group members reach the defined learning goals. We show how the complexity of the domain can be captured in a rather simple way via constraint-based engineering and how machine learning can help map student utterances to these constraints. We demonstrate the intended working principles of the system with some example dialogs and some first thoughts about backend implementation principles.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Aleven, V.: Rule-based cognitive modeling for intelligent tutoring systems. In: Nkambou, R., Mizoguchi, R., Bourdeau, J. (eds.) Advances in Intelligent Tutoring Systems, pp. 33–62. Springer Science and Business Media, Berlin, Heidelberg (2010)
Chen, P.P.S.: The entity-relationship model—toward a unified view of data. ACM Trans. Database Syst. (TODS) 1(1), 9–36 (1976)
Chinosi, M., Trombetta, A.: BPMN: an introduction to the standard. Comput. Stand. Interfaces 34(1), 124–134 (2012)
Collins, A., Brown, J.S., Holum, A.: Cognitive apprenticeship: making thinking visible. Am. Educ. 15(3), 6–11 (1991)
Conati, C.: Bayesian student modeling. In: Nkambou, R., Mizoguchi, R., Bourdeau, J. (eds.) Advances in intelligent tutoring systems, pp. 281–299. Springer Science and Business Media, Berlin, Heidelberg (2010)
Davis, E.A.: Scaffolding students’ knowledge integration: prompts for reflection in KIE. Int. J. Sci. Educ. 22(8), 819–837 (2000)
Dennen, V.P.: Cognitive apprenticeship in educational practice: research on scaffolding, modeling, mentoring, and coaching as instructional strategies. Handb. Res. Educ. Commun. Technol. 2(2004), 813–828 (2004)
Di Domenico, S.I., Ryan, R.M.: The emerging neuroscience of intrinsic motivation: a new frontier in self-determination research. Front. Hum. Neurosci. 11, 145 (2017)
Diwanji, P., Hinkelmann, K., Witschel, H.F.: Enhance classroom preparation for flipped classroom using AI and analytics. In: Proceedings of the 20th International Conference on Enterprise Information Systems (ICEIS), pp. 477–483 (2018)
Fournier-Viger, P., Nkambou, R., Nguifo, E.M.: Building intelligent tutoring systems for ill-defined domains. In: Nkambou, R., Mizoguchi, R., Bourdeau, J. (eds.) Advances in Intelligent Tutoring Systems, pp. 81–101. Springer Science and Business Media, Berlin, Heidelberg (2010)
Hmelo-Silver, C.E.: Problem-based learning: what and how do students learn? Educ. Psychol. Rev. 16(3), 235–266 (2004)
Jonassen, D.H., Hung, W.: All problems are not equal: implications for problem-based learning. Essential Readings in Problem-Based Learning, pp. 7–41 (2015)
Kerry, A., Ellis, R., Bull, S.: Conversational agents in E-Learning. In: International Conference on Innovative Techniques and Applications of Artificial Intelligence, pp. 169–182 (2008)
Kimball, R., Ross, M.: The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling. Wiley, New York (2011)
Kusurkar, R.A., Croiset, G., Ten Cate, O.T.J.: Twelve tips to stimulate intrinsic motivation in students through autonomy-supportive classroom teaching derived from self-determination theory. Med. Teach. 33(12), 978–982 (2011)
Lynch, C.F., Ashley, K.D., Aleven, V., Pinkwart, N.: Defining ill-defined domains: a literature survey. In: Intelligent Tutoring Systems (ITS 2006): Workshop on Intelligent Tutoring Systems for Ill-Defined Domains (2006)
Markham, T.: Project based learning a bridge just far enough. Teach. Libr. 39(2), 38 (2011)
Mitrovic, A.: Modeling domains and students with constraint-based modeling. In: Nkambou, R., Mizoguchi, R., Bourdeau, J. (eds.) Advances in Intelligent Tutoring Systems, pp. 63–80. Springer Science and Business Media, Berlin, Heidelberg (2010)
Nkambou, R., Mizoguchi, R., Bourdeau, J. (eds.): Advances in Intelligent Tutoring Systems, vol. 308. Springer Science & Business Media, Berlin, Heidelberg (2010)
Olney, A.M., Graesser, A.C., Person, N.K.: Tutorial dialog in natural language. In: Nkambou, R., Mizoguchi, R., Bourdeau, J. (eds.) Advances in Intelligent Tutoring Systems, pp. 181–206. Springer Science and Business Media, Berlin, Heidelberg (2010)
Reinders, H., et al.: Towards a classroom pedagogy for learner autonomy: a framework of independent language learning skills. Aust. J. Teach. Educ. (Online) 35(5), 40 (2010)
Ryan, R.M., Deci, E.L.: Intrinsic and extrinsic motivations: classic definitions and new directions. Contemp. Educ. Psychol. 25(1), 54–67 (2000)
Ryan, R.M., Deci, E.L.: Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. Am. Psychol. 55(1), 68 (2000)
Stefanou, C., Stolk, J.D., Prince, M., Chen, J.C., Lord, S.M.: Self-regulation and autonomy in problem-and project-based learning environments. Act. Learn. High. Educ. 14(2), 109–122 (2013)
Suraweera, P., Mitrovic, A.: An intelligent tutoring system for entity relationship modelling. Int. J. Artif. Intell. Educ. 14(3, 4), 375–417 (2004)
Trenshaw, K.F., Revelo, R.A., Earl, K.A., Herman, G.L.: Using self-determination theory principles to promote engineering students’ intrinsic motivation to learn. Int. J. Eng. Educ. 32(3), 1194–1207 (2016)
Usher, A., Kober, N.: What Is Motivation and Why Does It Matter? Center on Education Policy (2012)
VanLehn, K., Jordan, P.W., Rosé, C.P., Bhembe, D., Böttner, M., Gaydos, A., Makatchev, M., Pappuswamy, U., Ringenberg, M., Roque, A., et al.: The architecture of Why2-Atlas: a coach for qualitative physics essay writing. In: International Conference on Intelligent Tutoring Systems, pp. 158–167 (2002)
Vygotsky, L.S.: Mind in Society: The Development of Higher Psychological Processes. Harvard University Press, Cambridge, Massachusetts (1980)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Witschel, H.F., Diwanji, P., Hinkelmann, K. (2021). A Dialog-Based Tutoring System for Project-Based Learning in Information Systems Education. In: Dornberger, R. (eds) New Trends in Business Information Systems and Technology. Studies in Systems, Decision and Control, vol 294. Springer, Cham. https://doi.org/10.1007/978-3-030-48332-6_6
Download citation
DOI: https://doi.org/10.1007/978-3-030-48332-6_6
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-48331-9
Online ISBN: 978-3-030-48332-6
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)