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Extending the AAT Tool with a User-Friendly and Powerful Mechanism to Retrieve Complex Information from Educational Log Data

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Human-Computer Interaction and Knowledge Discovery in Complex, Unstructured, Big Data (HCI-KDD 2013)

Abstract

In online learning, educators and course designers traditionally have difficulty understanding how educational material is being utilized by learners in a learning management system (LMS). However, LMSs collect a great deal of data about how learners interact with the system and with learning materials/activities. Extracting this data manually requires skills that are outside the domain of educators and course designers, hence there is a need for specialized tools which provide easy access to these data. The Academic Analytics Tool (AAT) is designed to allow users to investigate elements of effective course designs and teaching strategies across courses by extracting and analysing data stored in the database of an LMS. In this paper, we present an extension to AAT, namely a user-friendly and powerful mechanism to retrieve complex information without requiring users to have background in computer science. This mechanism allows educators and learning designers to get answers to complex questions in an easy understandable format.

The authors acknowledge the support of Athabasca University and NSERC.

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Kladich, S., Ives, C., Parker, N., Graf, S. (2013). Extending the AAT Tool with a User-Friendly and Powerful Mechanism to Retrieve Complex Information from Educational Log Data. In: Holzinger, A., Pasi, G. (eds) Human-Computer Interaction and Knowledge Discovery in Complex, Unstructured, Big Data. HCI-KDD 2013. Lecture Notes in Computer Science, vol 7947. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39146-0_31

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  • DOI: https://doi.org/10.1007/978-3-642-39146-0_31

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39145-3

  • Online ISBN: 978-3-642-39146-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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