Applying Models to National Surveys of Undergraduate Science Students: What Affects Ratings of Satisfaction?

dc.creator	Anthony Mark Langan
dc.creator	Alan Fielding
dc.creator	Peter Dunleavy
dc.date	2013-05-01T00:00:00Z
dc.date.accessioned	2015-08-12T11:20:07Z
dc.date.available	2015-08-12T11:20:07Z
dc.identifier	10.3390/educsci3020193
dc.identifier	2227-7102
dc.identifier	https://doaj.org/article/952865cdf95949dd8d9304b4969ca992
dc.identifier.uri	http://evidence.thinkportal.org/handle/123456789/28059
dc.description	Many countries use national-level surveys to capture student opinions about their university experiences. It is necessary to interpret survey results in an appropriate context to inform decision-making at many levels. To provide context to national survey outcomes, we describe patterns in the ratings of science and engineering subjects from the UK’s National Student Survey (NSS). New, robust statistical models describe relationships between the Overall Satisfaction’ rating and the preceding 21 core survey questions. Subjects exhibited consistent differences and ratings of “Teaching”, “Organisation” and “Support” were thematic predictors of “Overall Satisfaction” and the best single predictor was “The course was well designed and running smoothly”. General levels of satisfaction with feedback were low, but questions about feedback were ultimately the weakest predictors of “Overall Satisfaction”. The UK’s universities affiliated groupings revealed that more traditional “1994” and “Russell” groups over-performed in a model using the core 21 survey questions to predict “Overall Satisfaction”, in contrast to the under-performing newer universities in the Million+ and Alliance groups. Findings contribute to the debate about “level playing fields” for the interpretation of survey outcomes worldwide in terms of differences between subjects, institutional types and the questionnaire items.
dc.language	English
dc.publisher	Multidisciplinary Digital Publishing Institute
dc.relation	http://www.mdpi.com/2227-7102/3/2/193
dc.relation	https://doaj.org/toc/2227-7102
dc.rights	CC BY
dc.source	Education Sciences, Vol 3, Iss 2, Pp 193-207 (2013)
dc.subject	random forest analysis
dc.subject	data mining
dc.subject	student satisfaction
dc.subject	student surveys
dc.subject	Education (General)
dc.subject	L7-991
dc.subject	Education
dc.subject	L
dc.subject	DOAJ:Education
dc.subject	DOAJ:Social Sciences
dc.subject	Education (General)
dc.subject	L7-991
dc.subject	Education
dc.subject	L
dc.subject	DOAJ:Education
dc.subject	DOAJ:Social Sciences
dc.subject	Education (General)
dc.subject	L7-991
dc.subject	Education
dc.subject	L
dc.subject	Education (General)
dc.subject	L7-991
dc.subject	Education
dc.subject	L
dc.subject	Education (General)
dc.subject	L7-991
dc.subject	Education
dc.subject	L
dc.title	Applying Models to National Surveys of Undergraduate Science Students: What Affects Ratings of Satisfaction?
dc.type	article