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Option Tracing: Beyond Correctness Analysis in Knowledge Tracing

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Artificial Intelligence in Education (AIED 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12748))

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Abstract

Knowledge tracing refers to a family of methods that estimate each student’s knowledge component/skill mastery level from their past responses to questions. One key limitation of most existing knowledge tracing methods is that they can only estimate an overall knowledge level of a student per knowledge component/skill since they analyze only the (usually binary-valued) correctness of student responses. Therefore, it is hard to use them to diagnose specific student errors. In this paper, we extend existing knowledge tracing methods beyond correctness prediction to the task of predicting the exact option students select in multiple choice questions. We quantitatively evaluate the performance of our option tracing methods on two large-scale student response datasets. We also qualitatively evaluate their ability in identifying common student errors in the form of clusters of incorrect options across different questions that correspond to the same error.

This work is supported by the National Science Foundation under grant IIS-1917713. We also thank the reviewers for their constructive feedback.

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Notes

  1. 1.

    https://eedi.com/projects/neurips-education-challenge.

  2. 2.

    https://github.com/riiid/ednet.

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Author information

Authors and Affiliations

  1. University of Massachusetts Amherst, Amherst, USA

    Aritra Ghosh & Andrew Lan

  2. Pittsburgh, PA, USA

    Jay Raspat

Authors
  1. Aritra Ghosh
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  2. Jay Raspat
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  3. Andrew Lan
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Corresponding author

Correspondence to Andrew Lan .

Editor information

Editors and Affiliations

  1. Technion – Israel Institute of Technology, Haifa, Israel

    Ido Roll

  2. Arizona State University, Tempe, AZ, USA

    Danielle McNamara

  3. Utrecht University, Utrecht, The Netherlands

    Sergey Sosnovsky

  4. London Knowledge Lab, London, UK

    Rose Luckin

  5. University of Leeds, Leeds, UK

    Vania Dimitrova

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Ghosh, A., Raspat, J., Lan, A. (2021). Option Tracing: Beyond Correctness Analysis in Knowledge Tracing. In: Roll, I., McNamara, D., Sosnovsky, S., Luckin, R., Dimitrova, V. (eds) Artificial Intelligence in Education. AIED 2021. Lecture Notes in Computer Science(), vol 12748. Springer, Cham. https://doi.org/10.1007/978-3-030-78292-4_12

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  • DOI: https://doi.org/10.1007/978-3-030-78292-4_12

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