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

机译:在全国大学生理科学生调查中应用模型:哪些因素会影响满意度?

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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.
机译:许多国家/地区使用国家级调查来收集学生对其大学经历的看法。有必要在适当的背景下解释调查结果,以在许多层面上为决策提供依据。为了提供国家调查结果的背景信息,我们描述了英国国家学生调查(NSS)对科学和工程学科评级的模式。新的,强大的统计模型描述了总体满意度评级与之前的21个核心调查问题之间的关系。受试者表现出一致的差异,“教学”,“组织”和“支持”的评分是“总体满意度”的主题预测指标,最佳的单个预测指标是“课程设计合理且运行平稳”。对反馈的总体满意度较低,但有关反馈的问题最终是“总体满意度”的最弱预测指标。英国的大学附属团体发现,较传统的“ 1994”和“ Russell”团体在使用21个核心调查问题预测“总体满意度”的模型中表现出色,而在Million +和Alliance中表现较差的较新大学则相反组。研究结果有助于就“公平竞争环境”进行辩论,以便根据主题,机构类型和问卷项目之间的差异来解释全球范围内的调查结果。

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