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An Epistemic Model-Based Tutor for Imperative Programming

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Artificial Intelligence in Education (AIED 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12749))

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Abstract

We developed a tutor for imperative programming in C++. It covers algorithm formulation, program design and coding – all three stages involved in writing a program to solve a problem. The design of the tutor is epistemic, i.e., true to real-life programming practice. The student works through all the three stages of programming in interleaved fashion, and within the context of a single code canvas. The student has the sole agency to compose the program and write the code. The tutor uses goals and plans as prompts to scaffold the student through the programming process designed by an expert. It provides drill-down immediate feedback at the abstract, concrete and bottom-out levels at each step. So, by the end of the session, the student is guaranteed to write the complete and correct program for a given problem. We used model-based architecture to implement the tutor because of the ease with which it facilitates adding problems to the tutor. In a preliminary study, we found that practicing with the tutor helped students solve problems with fewer erroneous actions and less time.

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Acknowledgments

Partial support for this work was provided by the National Science Foundation under grant DUE-1432190.

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Authors and Affiliations

  1. Ramapo College of New Jersey, Mahwah, NJ, 07430, USA

    Amruth N. Kumar

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  1. Amruth N. Kumar
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Correspondence to Amruth N. Kumar .

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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Kumar, A.N. (2021). An Epistemic Model-Based Tutor for Imperative Programming. In: Roll, I., McNamara, D., Sosnovsky, S., Luckin, R., Dimitrova, V. (eds) Artificial Intelligence in Education. AIED 2021. Lecture Notes in Computer Science(), vol 12749. Springer, Cham. https://doi.org/10.1007/978-3-030-78270-2_38

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  • DOI: https://doi.org/10.1007/978-3-030-78270-2_38

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-78269-6

  • Online ISBN: 978-3-030-78270-2

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