Article,

Some useful tactics to modify, map and mine data from intelligent tutors

, and .
Nat. Lang. Eng., (June 2006)
DOI: 10.1017/S1351324906004153

Abstract

Mining data logged by intelligent tutoring systems has the potential to discover information of value to students, teachers, authors, developers, researchers, and the tutors themselves &ndash; information that could make education dramatically more efficient, effective, and responsive to individual needs. We factor this discovery process into tactics to <i>modify</i> tutors, <i>map</i> heterogeneous event streams into tabular data sets, and <i>mine</i> them. This model and the tactics identified mark out a roadmap for the emerging area of tutorial data mining, and may provide a useful vocabulary and framework for characterizing past, current, and future work in this area. We illustrate this framework using experiments that tested interventions by an automated reading tutor to help children decode words and comprehend stories.

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