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Enhancing Adaptivity in Moodle: Framework and Evaluation Study

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Interactive Collaborative Learning (ICL 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 545))

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Abstract

The purpose of this paper is to present a framework that can be used to embed an adaptivity mechanism to Moodle so as to achieve better learning results. This mechanism adapts the presentation and the proposed navigation within a course, to students’ different learning preferences as they are expressed by their leaning styles and their educational objectives. An evaluation study was conducted in the context of an introductory programming course in order to examine the effectiveness of the proposed mechanism and students’ feedback on it. Two groups of students were formed, namely the experimental and the control group. The first had access to a Moodle course that exploited the adaptivity mechanism, whereas the second had access to the standard version of a Moodle course. The results were encouraging since they indicated that our extension affected students’ motivation and performance while their feedback about its usability was positive.

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References

  1. Bajraktarevic, N., Hall, W., Fullick, P.: Incorporating learning styles in hypermedia environment: empirical evaluation. In: de Bra, P., Davis, H.C., Kay, J., Schraefel, M. (eds.) Proceedings of the Workshop on Adaptive Hypermedia and Adaptive Web-Based Systems, pp. 41–52. Eindhoven University, Nottingham (2003)

    Google Scholar 

  2. Beck, J., Stern, M., Haugsjaa, E.: Applications of AI in education. ACM Crossroads Stud. Mag. 3(1), 11–15 (1996)

    Article  Google Scholar 

  3. Brusilovsky, P.: Adaptive hypermedia. User Model. User Adap. Interact. 11(1/2), 87–110 (2001)

    Article  MATH  Google Scholar 

  4. Brusilovsky, P., Millán, E.: User models for adaptive hypermedia and adaptive educational systems. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) The Adaptive Web. LNCS, vol. 4321, pp. 3–53. Springer, Heidelberg (2007). doi:10.1007/978-3-540-72079-9_1

    Chapter  Google Scholar 

  5. Capretz, L.: Implications of MBTI in software engineering education. ACM SIGCSE Bull. 34(4), 134–137 (2002)

    Article  Google Scholar 

  6. Carver, C.A., Howard, R.A., Lane, W.D.: Addressing different learning styles through course hypermedia. IEEE Trans. Educ. 42(1), 33–38 (1999)

    Article  Google Scholar 

  7. Felder, R.M., Silverman, L.K.: Learning and teaching styles in engineering education. Eng. Educ. 78(7), 674–681 (1988)

    Google Scholar 

  8. Felder, R.M., Soloman, B.A.: Index of learning styles questionnaire. http://www.engr.ncsu.edu/learningstyles/ilsweb.html

  9. García, P., Amandi, A., Schiaffino, S., Campo, M.: Using Bayesian networks to detect students’ learning styles in a web-based education system. In: 7th Argentine Symposium on Artificial Intelligence (ASAI 2005), Rosario, Argentina, pp. 115–126 (2005)

    Google Scholar 

  10. Graf, S.: Adaptivity in learning management systems focusing on learning styles. Ph.D. dissertation, Vienna University of Technology, Vienna, Austria (2007)

    Google Scholar 

  11. Graf, S., Kinshuk, Ives, C.: A flexible mechanism for providing adaptivity based on learning styles in learning management systems. In: 10th IEEE International Conference on Advanced Learning Technologies (ICALT 2010), Sousse, Tunisia, pp. 30–34 (2010)

    Google Scholar 

  12. Karagiannis, I., Satratzemi, M.: Comparing LMS and AEHS: challenges for improvement with exploitation of data mining. In: 14th IEEE International Conference on Advanced Learning Technologies (ICALT 2014), Athens, Greece, pp. 65–66 (2014)

    Google Scholar 

  13. Kazanidis, I., Satratzemi, M.: Adaptivity in ProPer: an adaptive SCORM compliant LMS. J. Distance Educ. Technol. 7(2), 44–62 (2009)

    Article  Google Scholar 

  14. Kobsa, A., Koenemann, J., Pohl, W.: Personalised hypermedia presentation techniques for improving online customer relationships. Knowl. Eng. Rev. 16(2), 111–155 (2001)

    Article  MATH  Google Scholar 

  15. Popescu, E., Badica, C., Moraret, L.: WELSA: an intelligent and adaptive web-based educational system. In: Papadopoulos, G.A., Badica, C. (eds.) Intelligent Distributed Computing III. SCI, vol. 237, pp. 175–185. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  16. Romero, C., Ventura, S.: Educational data mining: a review of the state of the art. IEEE Trans. Syst. Man Cybern. C 40(6), 601–618 (2010)

    Article  Google Scholar 

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Correspondence to Ioannis Karagiannis .

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Karagiannis, I., Satratzemi, M. (2017). Enhancing Adaptivity in Moodle: Framework and Evaluation Study. In: Auer, M., Guralnick, D., Uhomoibhi, J. (eds) Interactive Collaborative Learning. ICL 2016. Advances in Intelligent Systems and Computing, vol 545. Springer, Cham. https://doi.org/10.1007/978-3-319-50340-0_52

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  • DOI: https://doi.org/10.1007/978-3-319-50340-0_52

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-50339-4

  • Online ISBN: 978-3-319-50340-0

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