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Basic sequence analysis techniques for use with audit trail data
Article

, , The University of Melbourne, Australia

Journal of Educational Multimedia and Hypermedia Volume 17, Number 3, ISSN 1055-8896 Publisher: Association for the Advancement of Computing in Education (AACE), Waynesville, NC USA

Abstract

Audit trail analysis can provide valuable insights to researchers and evaluators interested in comparing and contrasting designers' expectations of use and students' actual patterns of use of educational technology environments (ETEs). Sequence analysis techniques are particularly effective but have been neglected to some extent because of real and perceived difficulties associated with their implementation and interpretation. This paper describes two simple sequence analysis techniques that are readily applied to audit trail data - a new sequence characterisation technique and a modification of an existing sequence comparison technique. The utility of these techniques are demonstrated through the analysis of audit trail data collected from two contrasting ETEs that were used by students in naturalistic settings. The first of these investigations examined the sequence in which students completed a single drag and drop task; the second examined the order in which students accessed the full complement of tasks within a modular ETE. The results of these analyses revealed that the order in which students completed the drag and drop task closely matched the tasks supporting narrative and that the order in which students accessed the various tasks in the modular ETE was strongly influenced by their physical location within on-screen menus. The concurrences of these findings with the various designers' expectations of use of the two ETEs are discussed.

Citation

Judd, T. & Kennedy, G. (2008). Basic sequence analysis techniques for use with audit trail data. Journal of Educational Multimedia and Hypermedia, 17(3), 285-306. Waynesville, NC USA: Association for the Advancement of Computing in Education (AACE). Retrieved November 30, 2021 from .

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