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

机译：解释英国自然学生（满意度）调查数据的上下文

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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.View full textDownload full textKeywordsstudent perceptions, satisfaction measures, factor analysisRelated var addthis_config = { ui_cobrand: "Taylor & Francis Online", services_compact: "citeulike,netvibes,twitter,technorati,delicious,linkedin,facebook,stumbleupon,digg,google,more", pubid: "ra-4dff56cd6bb1830b" }; Add to shortlist Link Permalink http://dx.doi.org/10.1080/0309877X.2010.484054
机译：大学会收集并利用学生的反馈意见来改善学生的学习体验，但是如何在地方和机构级别使用来自国家规模调查的信息呢？作者使用满意或非常满意的学生百分比，探索了与科学和工程计划相关的英国国家学生（满意度）调查（NSS）数据。为简洁起见，探索了一个NSS国家数据集，但发现的模式在第二年是一致的。简单的探索性数据分析技术强调了在解释NSS输出时需要注意的事项，从而证实了以前对其国际先驱物的研究。因素分析支持了调查内部高度一致性的说法。受试者分组显示出一致的反应差异，一些受试者始终表现出较高的满意度。这降低了NSS用于比较大学内不同学科分组的有用性。大学提供不同的学科构成，因此机构之间的直接比较并不简单。应仅将主题分组与相似的主题进行比较，然后应格外小心以了解满意度的复杂性。需要对此类国家调查表进行进一步分析，以根据其输出结果进行背景分析。例如，在所有学科中，都有一种国家对评估反馈的满意度低的趋势，但是反馈满意度和总体满意度之间的关系很复杂。学科之间存在明显的差异，在科学学科中，这些学科可能与数学内容有关。有未来的“整体满意度”价值的说明和使用不满措施的余地。 services_compact：“ citeulike，netvibes，twitter，technorati，美味，linkedin，facebook，stumbleupon，digg，google，更多”，发布：“ ra-4dff56cd6bb1830b”};添加到候选列表链接永久链接http://dx.doi.org/10.1080/0309877X.2010.484054

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