Student Satisfaction Data for Work Based Learners

This paper aims to describe how student satisfaction is measured for work-based learners as these are non-traditional learners, conducting academic learning in the workplace, typically their curricula have a high degree of negotiation, and whose motivations are directly related to their employers- needs, as well as their own career ambitions. We argue that while increasing WBL participation, and use of SSD are both accepted as being of strategic importance to the HE agenda, the use of WBL SSD is rarely examined, and lessons can be learned from the comparison of SSD from a range of WBL programmes, and increased visibility of this type of data will provide insight into ways to improve and develop this type of delivery. The key themes that emerged from the analysis of the interview data were: learners profiles and needs, employers drivers, academic staff drivers, organizational approach, tools for collecting data and visibility of findings. The paper concludes with observations on best practice in the collection, analysis and use of WBL SSD, thus offering recommendations for both academic managers and practitioners.

Authors:

• Rosie Borup
• Hanifa Shah

Keywords:

• Student satisfaction data
• work based learning
• employer engagement
• NSS.

References:

[1] ROWLEY, J. (2003b), "Designing student feedback questionnaires",
Quality Assurance in Education, Vol. 11 No. 3, pp. 142-9.
[2] FISK,P., TEIXEIRA, J., PATRÍCIO, L,, NÓBREGA, L., 2008.
Customer experience modeling: from customer experience to service
design. Journal of Service Management Volume: 23 Issue: 3 2012
[3] DOUGLAS, J.J., 2006. Measuring student satisfaction at a UK
university. Quality assurance in education, 14(3), pp. 251-267.
[4] WANG, Y., 2003. Assessment of learner satisfaction with asynchronous
electronic learning systems. Information & Management, 41(1), pp. 75-
86.
[5] ALDERMAN,B., 2005. The Role of Interaction in Enhancing
Achievement and Student Satisfaction in an Online Course: A Rubric
Analysis. Proceedings of World Conference on E-Learning in Corporate,
Government, Healthcare, and Higher Education 2005 (pp. 214-219).
[6] WURST, C., SMARKOLA, C. and GAFFNEY, M.A., 2008. Ubiquitous
laptop usage in higher education: Effects on student achievement,
student satisfaction, and constructivist measures in honors and
traditional classrooms. Computers & Education, 51(4), pp. 1766-1783.
[7] ESPASA, A.A., 2010. Analysing feedback processes in an online
teaching and learning environment: an exploratory study. Higher
education, 59(3), pp. 277-292.
[8] NAVARRO, M.M.M., 2005. A new management element for
universities: satisfaction with the offered courses. International journal
of educational management, 19(6), pp. 505-526.
[9] LAWSON, A., LEACH, M. and BURROWS, S., 2012. The implications
for learners, teachers and institutions of using student satisfaction as a
measure of success: a review of the literature. Education Journal, (138),
pp. 7-11.
[10] CLARK, D.J., REDMOND, M.V., 1982 Small group instructional
diagnosis: A practical approach to improving teaching AAHE Bulletin
1982, 35
[11] SHERRY, A. C. , FULFORD, C. P. & ZHANG, S . (1998) ÔÇÿAssessing
Distance Learners-
[12] ROBINSON, K. (1995) Using Small Group Instructional Feedback as a
Formative Feedback Strategyfor Audioconference Sources: Practical
Guidelines for Audio Conference Lecturers and Facilitators (ERIC
Document Reproduction Service No. ED 420347).
[13] DIAMOND, M.M.R., 2004. The usefulness of structured mid-term
feedback as a catalyst for change in higher education classes. Active
learning in higher education, 5(3), pp. 217-231.