Abstract
The purpose of this study is to use machine learning and exploratory data analysis to interrogate patterns of metrics from a national-level student survey. Analysis of over 1.8 million returns detected long-term stability of the predictors of student satisfaction, with survey items relating to course management and teaching being consistently most influential. All metric outputs increased over the survey period; however, the rates of increase of several dimensions including Overall Satisfaction decreased markedly in the most recent years to a point of levelling off. There was also a growing similarity in an institution of outcomes at a national level. This study contributes new insights into the influential survey instrument, through rigorous determination of the most influential survey items, descriptions of the changes in variability between institutions, and exploration of the importance of patterns of outliers at the extremes of the metric outputs. We also identify a rapidly growing spike in total satisfaction at a broad course level and highlight how this is inconsistent with a customer satisfaction model. We conclude by considering the challenges of the use of national-level student surveys for the management of student satisfaction in higher education.
Highlights
The sustained, growing impetus worldwide to measure performance in higher education (HE) using comparative metrics has been driven by economic pressures and consumer agendas (Hazelkorn 2015)
We found that institution-level data shows an increase in levels of agreement with all survey dimensions from 2006 to 2015 (Fig. 1) and survey items that started with lowest values gained most in the 10-year period
We found that metrics relating to aspects organisation and teaching were the main predictors of Overall Satisfaction metric (Q22), which is consistent with previous studies (Burgess et al, 2018; Langan et al 2013; Fielding et al, 2010)
Summary
The sustained, growing impetus worldwide to measure performance in higher education (HE) using comparative metrics has been driven by economic pressures and consumer agendas (Hazelkorn 2015). This has led to increased public accountability and intensified the emphasis placed on measures of institutional performance, founded on consideration of students as customers, or consumers, of education (see Molesworth et al 2009). These factors are thought to have contributed to an international trend in using student satisfaction ratings as surrogate measures of educational quality, despite considerable debate surrounding their value and validity in comparing higher education institutions (Ball 2017; Hazelkorn 2015). Evidence suggests that surveys of selected aspects of the student experience have had limited impact in improving levels of satisfaction at a large scale (Shah 2012)
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