An intelligent tutoring system incorporating a model of an experienced human tutor

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Abstract

Symbolization is the ability to translate a real world situation into the language of algebra. We believe that symbolization is the single most important skill students learn in high school algebra. We present research on what makes this skill difficult and report the discovery of a “hidden” skill in symbolization. Contrary to past research that has emphasized that symbolization is difficult due to both comprehension difficulties and the abstract nature of variables, we found that symbolization is difficult because it is the articulation in the “foreign” language of “algebra”. We also present Ms. Lindquist, an Intelligent Tutoring System (ITS) designed to carry on a tutorial dialog about symbolization. Ms. Lindquist has a separate tutorial model encoding pedagogical content knowledge in the form of different tutorial strategies, which were partially developed by observing an experienced human tutor. We discuss aspects of this human tutor’s method that can be modeled well by Ms. Lindquist. Finally, we present an early formative showing that students can learn from the dialogs Ms. Lindquist is able to engage student in. Ms. Lindquist has tutored over 600 students at www.AlgebraTutor.org.

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APA

Heffernan, N. T., & Koedinger, K. R. (2002). An intelligent tutoring system incorporating a model of an experienced human tutor. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2363, pp. 596–608). Springer Verlag. https://doi.org/10.1007/3-540-47987-2_61

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