Evaluation of ERST - An external representation selection tutor

Research output: Chapter in Book/Report/Conference proceedingConference proceeding

30 Citations (Scopus)

Abstract

This paper describes the evaluation of ERST, an adaptive system which is designed to improve its users' external representation (ER) selection accuracy on a range of database query tasks. The design of the system was informed by the results of experimental studies. Those studies examined the interactions between the participants' background knowledge-of-external representations, their preferences for selecting particular information display forms, and their performance across a range of tasks involving database queries. The paper describes how ERST's adaptation is based on predicting users' ER-to-task matching skills and performance at reasoning with ERs, via a Bayesian user model. The model drives ERST's adaptive interventions in two ways - by 1. hinting to the user that particular representations be used, and/or 2. by removing from the user the opportunity to select display forms which have been associated with prior poor performance for that user. The results show that ERST does improve an individual's ER reasoning performance. The system is able to successfully predict users' ER-to-task matching skills and their ER reasoning performance via its Bayesian user model.

Original languageEnglish
Title of host publicationDiagrammatic Representation and Inference - 4th International Conference, Diagrams 2006, Proceedings
PublisherSpringer-Verlag Italia
Pages154-167
Number of pages14
ISBN (Electronic)9783540356240
ISBN (Print)3540356231, 9783540356233
DOIs
Publication statusPublished - 1 Jan 2006
Externally publishedYes
Event4th International Conference on Diagrammatic Representation and Inference, Diagrams 2006 - Stanford, United States
Duration: 28 Jun 200630 Jun 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4045 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference4th International Conference on Diagrammatic Representation and Inference, Diagrams 2006
CountryUnited States
CityStanford
Period28/06/0630/06/06

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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