Investigating the Relationship between Spatial Ability and Feedback Style in ITSs

Nancy Milik, Antonija Mitrovic, Michael Grimley

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

3 Citations (Scopus)

Abstract

Rapid and widespread development of computerised learning tools have proven the need for further exploration of the learners' personal characteristics in order to maximise the use of the current technology. In particular, this paper looks at the potential of accounting for spatial ability in ERM-Tutor; a constraint-based tutor that teaches logical database design. Our evaluation study shows no conclusive results to support a difference in effectiveness of the textual versus multimedia feedback presentation modes with respect to the students' spatial ability. However, we observed a number of trends indicating that matching the instruction presentation mode towards the students' spatial ability influences their perception of the system and motivation to use it, more than their learning gain.

Original languageEnglish
Title of host publicationIntelligent Tutoring Systems - 9th International Conference, ITS 2008, Proceedings
Pages281-290
Number of pages10
DOIs
Publication statusPublished - 1 Dec 2008
Externally publishedYes
Event9th International Conference on Intelligent Tutoring Systems, ITS 2008 - Montreal, QC, Canada
Duration: 23 Jun 200827 Jun 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5091 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference9th International Conference on Intelligent Tutoring Systems, ITS 2008
CountryCanada
CityMontreal, QC
Period23/06/0827/06/08

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    Milik, N., Mitrovic, A., & Grimley, M. (2008). Investigating the Relationship between Spatial Ability and Feedback Style in ITSs. In Intelligent Tutoring Systems - 9th International Conference, ITS 2008, Proceedings (pp. 281-290). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5091 LNCS). https://doi.org/10.1007/978-3-540-69132-7-32