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

Fielding, Alan H.; Dunleavy, Peter J.; Langan, A. Mark

doi:10.1080/0309877x.2010.484054

Cited by 40 publications

(54 citation statements)

References 24 publications

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“…All analyses used percentage satisfaction scores returned (i.e., percentage of students answering 4 or 5 on the 5 point Likert scale, often referred to as the "percentage agree"; see [4]) and each used responses for the core survey questions (Q1 to Q21 are ratings of the learner's experience; with all years and all subjects included) to hierarchically predict "Overall Satisfaction" (the explicit measure of satisfaction; Q22). Three RFA models' outcomes were calculated using data that combined all three annual surveys, subjects and university grouping.…”

Section: Data Extraction and Analysismentioning

confidence: 99%

“…Previous analyses have highlighted subject differences, in particular how different types of feedback were valued differently by students in different subject disciplines. This work pointed to a need for greater depth of analysis, with more robust techniques to explore what best predicts overall satisfaction of respondents [4].…”

Section: Introductionmentioning

confidence: 99%

“…The survey excludes already students that have left the course before their third undergraduate year and there are potential biases in the survey participants, for example females are more likely to respond [2]. Student surveys have been criticised as being tools with insufficient practical value [3] and there remains a need for greater context of the results to draw value from the results [4]. Previous analyses have highlighted subject differences, in particular how different types of feedback were valued differently by students in different subject disciplines.…”

Section: Introductionmentioning

confidence: 99%

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

2013

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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.

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Section: Data Extraction and Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

2013

Self Cite

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“…The importance of feedback is recognized by practitioners in higher education who spend a great deal of time and effort producing feedback for assignments. It seems, however, that a lot of this effort is wasted: on the one hand, student surveys such as the National Student Survey (NSS) suggest that students are not satisfied with the feedback they get, with particularly low satisfaction in the category "Feedback helped me clarify things I did not understand" (Fielding et al 2010). On the other hand, many students do not collect their feedback (Jollands et al 2009) or if they do, they fail to read or to act upon it (Buswell & Matthews 2004).…”

Section: Introductionmentioning

confidence: 99%

Audio Feedback – Better Feedback?

Voelkel

Mello

2014

Bioscience Education

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National Student Survey (NSS) results show that many students are dissatisfied with the amount and quality of feedback they get for their work. This study reports on two case studies in which we tried to address these issues by introducing audio feedback to one undergraduate (UG) and one postgraduate (PG) class, respectively. In case study one audio feedback was given to half of the UG class whereas the other half received written feedback for a low stake (10%) exam style essay. In case study two audio feedback only was given to the PG class for a purely formative assignment which formed the basis for a final, summative piece of work. In both studies, audio feedback was received favourably as students found it clear, detailed and personal. A comparison between audio and written feedback (case study one) indicated that audio feedback left students more satisfied and provided more explanatory as well as motivational comments than written feedback. Generating audio feedback proved to be significantly more time consuming (by five minutes per script) than written feedback, but was more efficient in the sense that it produced nearly 10 times as much and higher quality feedback per unit of time. However, neither form of feedback led to an increase in students' subsequent performance in a final, summative exam essay. We conclude that audio feedback is better feedback in terms of student experience but it is still unclear if audio feedback can lead to higher attainment than other forms of feedback.

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“…separating all but the top universities, and hence small changes in weighting for the component elements of a survey can greatly influence the results, leading to significant influences on future student recruitment and financial sustainability of institutions, (Denson et al, 2010;Hou et al, 2012;Fielding et al, 2010).…”

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confidence: 99%

Student Surveys — ‘You Don't Think about the Good Things’

Sutcliffe

Linfield

Geldart

2014

Research in Education

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League tables are often used to compare universities and are increasingly becoming the focus for the selection of universities by national and international students. Yet, there can be little separating all but the top universities, and hence small changes in weighting for the component elements of a survey can greatly influence the results, leading to significant influences on future student recruitment and financial sustainability of institutions, (Denson et al., 2010; Hou et al., 2012; Fielding et al., 2010). The National Student Survey (NSS), which is a major source of data for UK league tables, is completed by students in their final year of study at all publically funded Higher Education Institutions in England, Wales, Northern Ireland and the majority in Scotland. It asks for twenty-two statements to be considered. An apparent lack of definition of words within statements, however, led to the pilot study which is the focus for this Short Notice. An opportunity sample of thirty final-year students on a Bachelor of Arts Primary Education course were invited for interview to explore how they had interpreted key words within statements from the NSS and how they allocated the levels of agreement such as 'mostly agree' and 'disagree'. Following transcription two key themes emerged: The different interpretations students had of words within the survey statements. The disproportionate impact that critical incidents can have on a survey which requires responses spanning 'a course as a whole'.

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

Cited by 40 publications

References 24 publications

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

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

Audio Feedback – Better Feedback?

Student Surveys — ‘You Don't Think about the Good Things’

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