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Getting to Know Your Student in Distance Learning Contexts

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Innovative Approaches for Learning and Knowledge Sharing (EC-TEL 2006)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4227))

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Abstract

Good teachers know their students, and exploit this knowledge to adapt or optimise their instruction. Teachers know their students because they interact with them face-to-face in classroom or one-to-one tutoring sessions. They can build student models, for instance, by exploiting the multi-faceted nature of human-human communication. In distance-learning environments, teacher and student have to cope with the lack of such direct interaction, and this must have detrimental effects for both teacher and student. In this paper, we investigate the need of teachers for tracking student actions in computer-mediated settings. We report on a teacher’s questionnaire that we devised to identify the needs of teachers to make distance learning a less detached experience. Our analysis of the teachers’ responses shows that there is a preference for information that relates to student performance (e.g., success rate in exercises, mastery level for a concept, skill, or method) and analysis of frequent errors or misconceptions. Our teachers judged information with regard to social nets, navigational pattern, and historical usage data less interesting. It shows that current e-learning environments have to improve to satisfy teachers’ needs for tracking students in distance learning contexts.

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References

  1. Cotton, K.: Monitoring student learning in the classroom. Northwest Regional Educational Laboratory, U.S. Department of Education (1988), School Improvement Research Series (SIRS), http://www.nwrel.org/scpd/sirs/2/cu4.html

  2. Goldberg, M.W.: Student participation and progress tracking for web-based courses using webct. In: Proc. 2nd N.A.WEB Conf., Fredericton, NB, Canada (1996)

    Google Scholar 

  3. Greer, J., Zapata-Rivera, J.D., Ong-Scutchings, C., Cooke, J.E.: Visualization of bayesian learner models. In: Proceedings of the workshop Open, Interactive, and other Overt Approaches to Learner Modelling AIED 1999 (1999)

    Google Scholar 

  4. Hardy, J., Antonioletti, M., Bates, S.: e-learner tracking: Tools for discovering learner behavior. In: The IASTED International Conference on Web-base Education, Innsbruk, Austria (2004)

    Google Scholar 

  5. Mazza, R.: Using Information Visualisation to Facilitate Instructors in Web-based Distance Learning. PhD thesis, University of Lugano (2004)

    Google Scholar 

  6. Mazza, R., Dimitrova, V.: Informing the design of a course data visualisator: an empirical study. In: 5th International Conference on New Educational Environments (ICNEE 2003), Lucerne, pp. 215–220 (2003)

    Google Scholar 

  7. Mazza, R., Dimitrova, V.: Generation of graphical representations of student tracking data in course management systems. In: IV 2005: Proceedings of the Ninth International Conference on Information Visualisation (IV 2005), Washington, DC, USA, pp. 253–258 (2005)

    Google Scholar 

  8. Mazza, R., Milani, C.: Gismo: a graphical interactive student monitoring tool for course management systems. In: T.E.L. Technology Enhanced Learning 2004 International Conference, Milan (2004)

    Google Scholar 

  9. Melis, E., Goguadze, G., Homik, M., Libbrecht, P., Ullrich, C., Winterstein, S.: Semantic-aware components and services of activemath. British Journal of Educational Technology 37(3) (2006)

    Google Scholar 

  10. Merceron, A., Yacef, K.: Tada-ed for educational data mining. Interactive Multimedia Electronic Journal of Computer-Enhanced learning 7(1) (2005)

    Google Scholar 

  11. Mostow, J., Aist, G., Burkhead, P., Corbett, A., Cuneo, A., Eitelman, S., Huang, C., Junker, B., Sklar, M.B., Tobin, B.: Evaluation of an automated reading tutor that listens: Comparison to human tutoring and classroom instruction. Journal of Educational Computing Research 29(1), 61–117 (2003)

    Article  Google Scholar 

  12. Mostow, J., Beck, J., Cen, H., Cuneo, A., Gouvea, E., Heiner, C.: An educational data mining tool to browse tutor-student interactions: Time will tell! In: AAAI 2005 Workshop on Educational Data Mining (2005)

    Google Scholar 

  13. Sleeman, D., Brown, S.J. (eds.): Intelligent Tutoring Systems. Computers and People Series. Academic Press, London (1982)

    Google Scholar 

  14. WebCT. WebCT VistaTM 3.0 Designer and Instructor Reference Manual (April 2004), Technical Communications, http://www.webct.com

  15. Zapata-Rivera, J.D., Greer, J.: Externalising learner modelling representations. In: Workshop on External Representations of AIED: Multiple Forms and Multiple Roles. International Conference on Artificial Intelligence in Education AIED 2001, pp. 71–76 (2001)

    Google Scholar 

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© 2006 Springer-Verlag Berlin Heidelberg

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Zinn, C., Scheuer, O. (2006). Getting to Know Your Student in Distance Learning Contexts. In: Nejdl, W., Tochtermann, K. (eds) Innovative Approaches for Learning and Knowledge Sharing. EC-TEL 2006. Lecture Notes in Computer Science, vol 4227. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11876663_34

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  • DOI: https://doi.org/10.1007/11876663_34

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-45777-0

  • Online ISBN: 978-3-540-46234-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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