Adapting exercise selection to performance, effort and self-esteem

Juliet A. Okpo*, Judith Masthoff (Corresponding Author), Matt Dennis, Nigel Beacham

*Corresponding author for this work

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Adapting to learner characteristics is essential when selecting exercises for learners in an intelligent tutoring system. This paper investigates how humans adapt next exercise selection (in particular difficulty level) to learner personality, invested mental effort, and performance to inspire an adaptive exercise selection algorithm. First, the paper describes 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 self-esteem (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. Finally, using the results from the studies, we propose an algorithm that selects exercises with varying difficulty levels adapted to learner characteristics.

Original languageEnglish
Pages (from-to)193-227
Number of pages35
JournalNew Review of Hypermedia and Multimedia
Volume24
Issue number3
Early online date21 Jun 2018
DOIs
Publication statusPublished - 31 Jul 2018

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Keywords

  • adaptation
  • cognitive efficiency
  • Exercise selection
  • mental effort
  • performance
  • personality
  • self-esteem

ASJC Scopus subject areas

  • Information Systems
  • Media Technology
  • Computer Science Applications

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