Abstract—This paper reports data analysis of students’
satisfaction on a graduate course in information technology for
11 consecutive semesters over six years at an Australian
university. We find a negative trend between course satisfaction
and class size and a positive trend between teaching and course
satisfactions, consistent with what reported in literature from
other disciplines. This study also reveals that teaching
satisfaction rate has a negative association with neutral rate but
surprisingly no association with course dissatisfaction rate. This
implies that improvement on student course satisfaction through
good teaching may mainly be resulted from converting those
undecided students from neutrality to satisfaction. Results of
this data analysis support a parallel flow model between course
satisfaction and both neutrality and dissatisfaction, which leads
to a new strategy for achieving a high level of course satisfaction
for other domain-complexity courses in science, technology,
engineering and mathematics (STEM) education. Strategically,
innovative and engaged teaching is still the key to achieve a high
course satisfaction. Tactically, guided by existing and emerging
teaching and learning theories, a number of specified measures
are worth of consideration in course design and delivery for
similar highly technical courses for achieving a high level of
course satisfaction in future.
Index Terms—Course improvement, course satisfaction,
student course evaluation, STEM education, teaching
satisfaction.
William Guo, Wei Li, and Yucang Wang are with School of Engineering
and Technology, Central Queensland University, Rockhampton 4702,
Australia (e-mail: w.guo@cqu.edu.au).
Jun Shen is with School of Information Systems and Technology,
University of Wollongong, Wollongong, NSW 2522, Australia.
Cite: William W. Guo, Wei Li, Yucang Wang, and Jun Shen, "Analysis of Student Course Evaluation Data for an IT Subject: Implications for Improving STEM Education," International Journal of Information and Education Technology vol. 7, no. 9, pp. 635-640, 2017.