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Optional Finer Granularity in an Open Learner Model

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Artificial Intelligence in Education (AIED 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6738))

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Abstract

Open learner models (OLMs) available independently from specific tutoring or guidance, such as an intelligent tutoring system may provide, can encourage learners to take greater responsibility for learning., Our results suggest that finer grained OLM information, in this context, can support learners in identifying strengths/weaknesses, planning and focussing learning, when different OLM granularities exist. Learners drew regular comparison between OLM and domain information, showing the flexibility of interaction to be important.

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References

  1. Bull, S., Kay, J.: Open Learner Models. In: Advances in Intelligent Tutoring Systems, pp. 318–338. Springer, Heidelberg (2010)

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  2. Zapata-Rivera, D., Hansen, E., Shute, V.J., Underwood, J.S., Bauer, M.: Evidence-based Approach to Interacting with Open Student Models. International Journal of Artificial Intelligence in Education 17(3), 273–303 (2007)

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  3. Mitrovic, A., Martin, B.: Evaluating the Effect of Open Student Models on Self Assessment. International Journal of Artificial Intelligence in Education 17, 121–144 (2007)

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  4. Johnson, M., Bull, S.: Belief Exploration in a Multiple-Media Open Learner Model for Basic Harmony. In: Artificial Intelligence in Education 2009, pp. 299–306. IOS Press, Amsterdam (2009)

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Author information

Authors and Affiliations

  1. Electronic, Electrical and Computer Engineering, University of Birmingham, UK

    Matthew D. Johnson & Susan Bull

Authors
  1. Matthew D. Johnson
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  2. Susan Bull
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Editor information

Editors and Affiliations

  1. EECS Department/ISIS, Vanderbilt University, TN 37235, Nashville, USA

    Gautam Biswas

  2. Electronic, Electrical and Computer Engineering, University of Birmingham, U.K.

    Susan Bull

  3. School of Information Technologies, University of Sydney, 1 Cleveland Street, 2006, Sydney, Australia

    Judy Kay

  4. College of Engineering, Department of Computer Science and Software Engineering, University of Canterbury, Private Bag 4800, 8140, Christchurch, New Zealand

    Antonija Mitrovic

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© 2011 Springer-Verlag Berlin Heidelberg

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Johnson, M.D., Bull, S. (2011). Optional Finer Granularity in an Open Learner Model. In: Biswas, G., Bull, S., Kay, J., Mitrovic, A. (eds) Artificial Intelligence in Education. AIED 2011. Lecture Notes in Computer Science(), vol 6738. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21869-9_75

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  • DOI: https://doi.org/10.1007/978-3-642-21869-9_75

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21868-2

  • Online ISBN: 978-3-642-21869-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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