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Investigating Students’ Reasoning in a Code-Tracing Tutor

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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

Code tracing involves stepping through a program in order to predict its output. In the present study (N = 45), we used the think-aloud protocol to gain insight into students’ cognitive processes as they used a computer tutor to study code-tracing examples and work on code-tracing problems, using either a high-scaffolding or a reduced-scaffolding tutor interface. For the cognitive processes, we included both self-explanation and reading behaviors, relying on a qualitative coding to analyze the transcripts. Our results shed light on how different levels of assistance provided by a computer tutor impact student reasoning during code-tracing activities.

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Notes

  1. 1.

    A between-subjects design was used because the high potential for order effects rendered a within-subject design not suitable.

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Correspondence to Jay Jennings or Kasia Muldner .

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Jennings, J., Muldner, K. (2021). Investigating Students’ Reasoning in a Code-Tracing Tutor. 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_17

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  • DOI: https://doi.org/10.1007/978-3-030-78292-4_17

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