Abstract
Argument-based machine learning (ABML) knowledge refinement loop offers a powerful knowledge elicitation tool, suitable for obtaining expert knowledge in difficult domains. In this paper, we first use it to conceptualize a difficult, even ill-defined concept: distinguishing between “basic” and “advanced” programming style in python programming language, and then to teach this concept in an interactive learning session between a student and the computer. We demonstrate that by automatically selecting relevant examples and counter examples to be explained by the student, the ABML knowledge refinement loop provides a valuable interactive teaching tool.
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Zapušek, M., Možina, M., Bratko, I., Rugelj, J., Guid, M. (2014). Designing an Interactive Teaching Tool with ABML Knowledge Refinement Loop. In: Trausan-Matu, S., Boyer, K.E., Crosby, M., Panourgia, K. (eds) Intelligent Tutoring Systems. ITS 2014. Lecture Notes in Computer Science, vol 8474. Springer, Cham. https://doi.org/10.1007/978-3-319-07221-0_73
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DOI: https://doi.org/10.1007/978-3-319-07221-0_73
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07220-3
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