Abstract
Due to the numerous advantages of the Learning Management System (LMS), such as the facility to distribute and update the course, their use has become popular not only in the education field but also in business training. In order to improve the efficiency of online courses, previous works adapted LMS to learners preferences based on their learning styles. In the other hand, Game elements had been added to LMS to increase students motivation in achieving a learning goal. In this paper, we are interested in adapting GLMS to student profiles using Q-learning algorithm to attribute an adapted gamified learning path to the user. Our work allows to deal with the users profile as a learner and player at the same time.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Monterrat, B., Lavoué, E., George, S.: Adaptation of gaming features for motivating learners. Simul. Gaming 48, 625–656 (2017)
Felder, R.M., Silverman, L.K.: Learning and teaching styles in engineering education. Eng. Educ. 78, 674–681 (1988)
Goldberg, L.R.: The structure of phenotypic personality traits. Am. Psychol. 48, 26 (1993)
Bartle, R.: Hearts, clubs, diamonds, spades: players who suit muds. J. MUD Res. 1, 19 (1996)
Szabo, M.: Cmi theory and practice: historical roots of learning managment systems. In: E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, pp. 929–936 (2002)
Heeter, C., Lee, Y.-H., Medler, B., Magerko, B.: Beyond player types: gaming achievement goal. In: ACM SIGGRAPH 2011 Game Papers, p. 7. ACM (2011)
Deterding, S., Dixon, D., Khaled, R., Nacke, L.: From game design elements to gamefulness: defining gamification. In: Proceedings of the 15th International Academic MindTrek Conference: Envisioning Future Media Environments, MindTrek, pp. 9–15 (2011)
Richard, F.: Matters of style. ASEE Prism 6, 11 (1996)
Myers, I.B.: The Myers-Briggs type indicator manual, p. 9 (1962)
Kolb, D.A.: The learning style inventory: Technical manual. McBer and Company, Boston, p. 11 (1976)
Dunn, R., Dunn, K.: Learning style as a criterion for placement in alternative programs. Phi Delta Kappan 56, 275–278 (1974)
Kuljis, J., Liu, F.: A comparison of learning style theories on the suitability for elearning. In: Web Technologies, Applications, and Services, pp. 191–197 (2005)
Yee, N.: Motivations for play in online games. CyberPsychol. Behav. 9, 772–775 (2006)
Nacke, L.E., Bateman, C., Mandryk, R.L.: Brainhex a neurobiological gamer typology survey. Entertain. Comput. 5, 55–62 (2014)
Sutton, R.S., Barto, A.G.: Reinforcement Learning: An Introduction. MIT Press, Cambridge (1998)
Rummery, G.A., Niranjan, M.: On-line Q-learning using connectionist systems. University of Cambridge, Department of Engineering Cambridge, England (1994)
Watkins, C.J.C.H., Dayan, P.: Q-learning. Mach. Learn. 8, 279–298 (1992)
Watkins, C.J.C.H.: Learning from Delayed Rewards. Ph.D. thesis, Cambridge University (1989)
Nacke, L.E., Bateman, C., Mandryk, R.L.: BrainHex: preliminary results from a neurobiological gamer typology survey. In: Anacleto, J.C., Fels, S., Graham, N., Kapralos, B., Saif El-Nasr, M., Stanley, K. (eds.) ICEC 2011. LNCS, vol. 6972, pp. 288–293. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-24500-8_31
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Chtouka, E., Guezguez, W., Amor, N.B. (2019). Reinforcement Learning for New Adaptive Gamified LMS. In: Jallouli, R., Bach Tobji, M., Bélisle, D., Mellouli, S., Abdallah, F., Osman, I. (eds) Digital Economy. Emerging Technologies and Business Innovation. ICDEc 2019. Lecture Notes in Business Information Processing, vol 358. Springer, Cham. https://doi.org/10.1007/978-3-030-30874-2_24
Download citation
DOI: https://doi.org/10.1007/978-3-030-30874-2_24
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-30873-5
Online ISBN: 978-3-030-30874-2
eBook Packages: Computer ScienceComputer Science (R0)