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Adaptable Learning and Learning Analytics: A Case Study in a Programming Course

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Adaptive and Adaptable Learning (EC-TEL 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9891))

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Abstract

The focus of this case study is the exploitation of visual learning analytics coupled with the provision of feedback and support provided to the students and their impact in provoking change at student programming habits. To this end, we discuss mechanisms of capturing and analysing the debugging habits and the quality of the design solutions provided by the students in the context of an object-oriented programming course. We instrumented the programming environment use by the students in order to track the student behavior and visualize metrics associated with it, while the students developed programs in Java.

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References

  1. Awasthi, P., Hsaio, I.-H.: INSIGHT: a semantic visual analytics for programming discussion forums. In: Proceedings of the First International Workshop on Visual Aspects of Learning Analytics, vol. 1518, pp. 24–31 (2015)

    Google Scholar 

  2. Edwards, S.H.: Using software testing to move students from trial-and-error to reflection-in-action. ACM SIGCSE Bull. 36(1), 26–30 (2004)

    Article  Google Scholar 

  3. Ferguson, R.: Learning analytics: drivers, developments and challenges. Int. J. Technol. Enhanced Learn. 4(5–6), 304–317 (2012)

    Article  Google Scholar 

  4. Lee, J., Park, O.: Adaptive instructional systems. In: Spector, J.M., Merill, M.D., van Merrienboer, J., Driscoll, M.P. (eds.) Handbook of Research for Educational Communications and Technology, pp. 469–484. Routledge, Taylor & Francis Group, New York (2007)

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  5. Mavroudi, A., Giannakos, M., Krogstie, J.: Insights on the interplay between adaptive learning and learning analytics. In: 16th IEEE International Conference on Advanced Learning Technologies – ICALT 2016, 25–28 July, Austin, Texas, USA (2016, accepted)

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Acknowledgements

The work presented is supported by the European Research Consortium for Informatics and Mathematics (ERCIM). Contract Nr. 2015-07.

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Correspondence to Anna Mavroudi .

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© 2016 Springer International Publishing Switzerland

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Trætteberg, H., Mavroudi, A., Giannakos, M., Krogstie, J. (2016). Adaptable Learning and Learning Analytics: A Case Study in a Programming Course. In: Verbert, K., Sharples, M., Klobučar, T. (eds) Adaptive and Adaptable Learning. EC-TEL 2016. Lecture Notes in Computer Science(), vol 9891. Springer, Cham. https://doi.org/10.1007/978-3-319-45153-4_87

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  • DOI: https://doi.org/10.1007/978-3-319-45153-4_87

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-45152-7

  • Online ISBN: 978-3-319-45153-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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