Practically and productively analysing Course Experience Questionnaire student comment data

Palmer, Stuart and Campbell, Malcolm 2013, Practically and productively analysing Course Experience Questionnaire student comment data, in AAEE 2013 : Proceedings of the 24th 2013 Australasian Association for Engineering Education Conference, Griffith School of Engineering, Griffith University, Brisbane, Qld..

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Title Practically and productively analysing Course Experience Questionnaire student comment data
Author(s) Palmer, Stuart
Campbell, Malcolm
Conference name Australasian Association for Engineering Education. Conference : (24th : 2013 : Gold Coast, Qld)
Conference location Gold Coast, Queensland
Conference dates 8-11 Dec. 2013
Title of proceedings AAEE 2013 : Proceedings of the 24th 2013 Australasian Association for Engineering Education Conference
Editor(s) [Unknown]
Publication date 2013
Conference series Australasian Association for Engineering Education Conference
Total pages 9
Publisher Griffith School of Engineering, Griffith University
Place of publication Brisbane, Qld.
Keyword(s) course experience questionnaire
CEQuery
student comment analysis
Summary Australia national survey of graduates from 1993 onward. In addition to quantitative items, the CEQ also includes an invitation to respondents to write open-ended comments on the best aspects (BA) of their university course experience and those most needing improvement (NI). These responses provide a rich source additional information that can help in understanding what students had in mind when agreeing or disagreeing with the CEQ response items. Based on more than 160,000 comments from students graduating from 14 Australian universities over the period 2001-2004, Scott (2006) developed a five domain model (Outcomes, Staff, Course design, Assessment and Support) for the classification of CEQ comments, as well as a software package (CEQuery) to automate the analysis of CEQ BA and NI comment data. While computer automated comment analysis is convenient, there are a number of known limitations to this approach, and where the number of student comments is not large, manual coding/classification is a viable, and arguably superior, approach.
ISBN 9780992409913
Language eng
Field of Research 130212 Science, Technology and Engineering Curriculum and Pedagogy
130303 Education Assessment and Evaluation
Socio Economic Objective 930502 Management of Education and Training Systems
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2013, AAEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30060776

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