Author
Listed:
- Laura Rozman
(International School for Social and Business Studies Celje, Slovenia)
- Valentina Jost Leser
(International School for Social and Business Studies Celje, Slovenia)
- Nada Trunk Sirca
(International School for Social and Business Studies Celje, Slovenia)
- Valerij Dermol
(International School for Social and Business Studies Celje, Slovenia)
- Vesna Skrbinjek
(International School for Social and Business Studies Celje, Slovenia)
Abstract
In this paper, we are discussing a question how to assess students’ workload, which is an important variable in the curriculum and of utmost importance in quality of teaching and learning process in higher education. However, student workload can be influenced by many different factors and at the same time, the measurement of workload faces several methodological challenges. This paper could be considered as a preliminary study, a case study at one higher education institution. Our research question arose when we were evaluating the method that has been used for measuring student workload for a long time; online questionnaire. The need for the evaluation was raised when the gap between the graduate students’ perception of workload and expected workload according to the number of course credits (for specific study subjects) was observed. After preliminary review of the literature, we decided for complementary usage of quantitative method (survey – on line questionnaire) and qualitative method (focus group). The qualitative method helped us to understand “student workload” from different points of view. Findings show that discrepancy was a consequence of students’ previous knowledge and work experiences and also the fact that many students didn’t know how to “count” their workload, since they didn’t know which time to count. Overall, we can conclude that the gap is not as big as we thought, and although, prevailing method for assessing students’ workload is survey, we suggest using a combination of qualitative and quantitative methods in accordance to get data that are more reliable.
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