Click go the students, click-click-click: the efficacy of a student response system for engaging students to improve feedback and performance

Mula, Joseph M. and Kavanagh, Marie (2009) Click go the students, click-click-click: the efficacy of a student response system for engaging students to improve feedback and performance. e-Journal of Business Education and Scholarship of Teaching, 3 (1). pp. 1-17. ISSN 1835-9132

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Abstract

This paper uses an action research approach to examine the impact of phase two of a dynamic education project involving SRS technology on student learning outcomes. We examine the use of clickers or student response systems (SRS) as an educational tool in accounting. Both quantitative and qualitative methods are used to compare outcomes for students over three semesters in first year accounting classes. Results support an increase in the participation level of students in class, improved understanding of the course content and a positive learning experience. No correlation between in-class responses and overall assessment performance was found, but there was a decrease in the failure rate in the semester in which SRS technology was used. Overall, the study provides preliminary evidence of the efficacy of this technology to enhance student engagement and learning outcomes.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Deposited in accordance with the copyright policy of the publisher (blanket permssion granted by Editor 23/6/2009).
Depositing User: Dr Joseph M. Mula
Faculty / Department / School: Historic - Faculty of Business - School of Accounting, Economics and Finance
Date Deposited: 27 Oct 2009 04:40
Last Modified: 01 Sep 2014 01:52
Uncontrolled Keywords: student response system; pedagogy; education technology; student engagement; feedback; action research
Fields of Research (FOR2008): 13 Education > 1303 Specialist Studies in Education > 130306 Educational Technology and Computing
08 Information and Computing Sciences > 0807 Library and Information Studies > 080703 Human Information Behaviour
17 Psychology and Cognitive Sciences > 1702 Cognitive Sciences > 170203 Knowledge Representation and Machine Learning
URI: http://eprints.usq.edu.au/id/eprint/5859

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