It has been found in recent years that many students who use intelligent tutoring systems game the system, attempting to succeed in the educational environment by exploiting properties of the system rather than by learning the material and trying to use that knowledge to answer correctly. In this paper, we introduce a system which gives a gaming student supplementary exercises focused on exactly the material the student bypassed by gaming, and which also expresses negative emotion to gaming students through an animated agent. Students using this system engage in less gaming, and students who receive many supplemental exercises have considerably better learning than is associated with gaming in the control condition or prior studies.

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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 – information that could make education dramatically more efficient, effective, and responsive to individual needs. We factor this discovery process into tactics to modify tutors, map heterogeneous event streams into tabular data sets, and mine 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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Abstract. We have constructed a learning agent that models student behavior at a high level of granularity for a mathematics tutor. Rather than focusing on whether the student knows a particular piece of knowledge, the learning agent determines how likely the student is to answer a problem correctly and how long he will take to generate this response. To construct this model, we used traces from previous users of the tutor to train the machine learning agent. This agent used information about the student, the current topic, the problem, and the student's efforts to solve this problem to make its predictions. This model was very accurate at predicting the time students required to generate a response, and was somewhat accurate at predicting the likelihood the student's response was correct. We present two methods for integrating such an agent into an intelligent tutor.

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Various neurodegenerative diseases and psychiatric disorders are marked by alterations in brain cholinergic function and cognitive deficits. Efforts to alleviate such deficits have been limited by a lack of selective M 1 muscarinic agonists. 5-(3-Ethyl-1,2,4-oxadiazol-5-yl)-1,4,5,6-tetrahydropyrimidine hydrochloride (CDD-0102A) is a partial agonist at M 1 muscarinic receptors with limited activity at other muscarinic receptor subtypes. The present studies investigated the effects of CDD-0102A on working memory and strategy shifting in rats. CDD-0102A administered intraperitoneally 30 min before testing at 0.1, 0.3, and 1 mg/kg significantly enhanced delayed spontaneous alternation performance in a four-arm cross maze, suggesting improvement in working memory. In separate experiments, CDD-0102A had potent enhancing effects on learning and switching between a place and visual cue discrimination.Treatment with CDD-0102A did not affect acquisition of either a place or visual cue discrimination. In contrast, CDD-0102A at 0.03 and 0.1 mg/kg significantly enhanced a shift between a place and visual cue discrimination. Analysis of the errors in the shift to the place or shift to the visual cue strategy revealed that in both cases CDD-0102A significantly increased the ability to initially inhibit a previously relevant strategy and maintain a new, relevant strategy once selected. In anesthetized rats, the minimum dose required to induce salivation was approximately 0.3 mg/kg i.p. Salivation increased with dose, and the estimated ED 50 was 2.0 mg/kg. The data suggest that CDD-0102A has unique memory and cognitive enhancing properties that might be useful in the treatment of neurological disorders at doses that do not produce adverse effects such as salivation.

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