Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.752683
Title: Adaptive exercise selection for an intelligent tutoring system
Author: Okpo, Juliet Airenvbiegbe
ISNI:       0000 0004 7425 8119
Awarding Body: University of Aberdeen
Current Institution: University of Aberdeen
Date of Award: 2018
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Abstract:
Adapting to learner characteristics is essential when selecting exercises for learners in an intelligent tutoring system. This thesis investigates how humans adapt next exercise selection (in particular difficulty level) to learner personality (self-esteem), invested mental effort, and performance to inspire an adaptive exercise selection algorithm. First, we describe the investigations to produce validated materials for the main studies, namely the creation and validation of self-esteem personality stories, mental effort statements, and mathematical exercises with varying levels of difficulty. Next, through empirical studies, we investigate the impact on exercise selection of learner's selfesteem (low versus high self-esteem) and effort (minimal, little, moderate, much, and all possible effort). Three studies investigate this for learners who had different performances on a previous exercise: just passing, just failing, and performed well. Participants considered a fictional learner with a certain performance, self-esteem and effort, and selected the difficulty level of the next mathematical exercise. We found that self-esteem, mental effort, and performance all impacted the difficulty level of the exercises selected for learners. Using the results from the studies, we generated an algorithm that selects exercises with varying difficulty levels adapted to learner characteristics. Finally, through a survey with professional teachers, we evaluated our algorithm and found that the algorithm's adaptations were appropriate in general.
Supervisor: Masthoff, Judith Sponsor: Niger Delta Development Commission
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.752683  DOI: Not available
Keywords: Intelligent tutoring systems ; Computer-assisted instruction
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