Makatchev, M. & VanLehn, K. (2005). Analyzing completeness and correctness of utterances using an ATMS. In G. McCalla & C. K. Looi (Eds.), Artificial Intelligence in Education (pp. 403-410). Amsterdam, Netherlands: IOS Press.

Analyzing coverage of a student’s utterance or essay (completeness) and diagnosing errors (correctness) can be treated as a diagnosis problem and solved using a well-known technique for model-based diagnosis: an assumption-based truth maintenance system (ATMS). The function-free first-order predicate logic (FOPL) representation of the essay is matched with nodes of the ATMS that are then analyzed for being within the sound part of the closure or relying on a particular misconception. If the matched nodes are sound they are analyzed for representing a particular required physics statement. If they do not represent the required statement, a neighborhood (antecedent and consequent nodes within N inference steps) of these nodes can be analyzed for matching the statement, to give a measure of how far the student utterance is, in terms of a number of inferences, from the desired one.

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