Interpreting context to the UK’s National Student (Satisfaction) Survey data for science subjects

Abstract

Universities capture and use student feedback to improve the student experience, but how should information from national scale surveys be used at local and institutional levels? The authors explored the UK’s National Student (Satisfaction) Survey (NSS) data relevant to science and engineering programmes using percentages of students who were satisfied or very satisfied. For brevity, one NSS national dataset was explored, but the patterns found were consistent for the following year. Simple exploratory data analysis techniques underlined the care that is needed when interpreting NSS outputs, corroborating previous research into its international precursors. Factor analysis supported claims of a high internal consistency of the survey. Subject groupings showed consistent differences in responses, with some subjects consistently recording higher satisfaction. This reduces the usefulness of the NSS for comparing different subject groupings within a university. Universities provide different subject compositions, so direct comparisons between institutions are not straightforward. Subject groupings should be compared only against similar subjects, and then with due care to understand the complexity of satisfaction. Further analysis of national questionnaires like this is required to contextualise its outputs. For example, there is a national trend of low satisfaction with assessment feedback in all subjects, but the relationship between feedback satisfaction and overall satisfaction is complex. There are marked differences between subjects which may, in science subjects, be associated with mathematical content. There is scope for future elucidations of the ‘overall satisfaction’ value and for use of the measures of dissatisfaction.

Keywords:

• student perceptions
• satisfaction measures
• factor analysis