理解学生参与的国际基准:从计算机科学的角度认识、研究校准和响应

Michael Morgan, M. Butler, J. Sinclair, G. Cross, Janet Fraser, J. Jacková, Neena Thota
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引用次数: 32

摘要

越来越多的人使用国家基准来衡量学生的参与度,比如美国和加拿大的北美国家学生参与度调查(NSSE),澳大利亚和新西兰的学生体验调查(SES)(以前称为大学体验调查UES),以及英国的学生参与度调查(SES)。不幸的是,在这些调查中,即使与相关的STEM学科相比,计算机科学(CS)在许多指标上的排名也相当低。最初的研究表明,这种糟糕表现的原因可能包括计算机科学学者对这些工具和他们所基于的学生参与措施缺乏认识,以及这些工具与计算机教育者的研究重点之间的不一致,导致研究和教学实践中的错误努力。在这个工作组中,我们对国际学生参与度工具进行了深入分析,以促进对国际基准以及它们衡量学生参与度的哪些方面的认识。工作组还审查了当前计算机教育研究的重点及其与这些工具所依据的学生参与措施的一致性。有了这些知识,计算机教育界可以就如何最好地应对这些措施做出明智的决定,并考虑如何提高我们与其他学科的表现。特别重要的是要理解为什么这些工具中内置了某些学生参与的衡量标准,这些标准如何与我们当前的研究实践相一致,甚至从CS的角度向这些工具的设计者提供反馈。
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Understanding International Benchmarks on Student Engagement: Awareness, Research Alignment and Response from a Computer Science Perspective
There is an increasing trend to use national benchmarks to measure student engagement, with instruments such as North American National Survey of Student Engagement (NSSE) in the USA and Canada, Student Experience Survey (SES) in Australia and NZ (previously known as the University Experience Survey UES), and Student Engagement Survey (SES) in the UK. Unfortunately, Computer Science (CS) rates fairly poorly on a number of measures in these surveys, even when compared to related STEM disciplines. Initial research suggests reasons for this poor performance may include a lack of awareness by CS academics of these instruments and the student engagement measures they are based on, and a misalignment between these instruments and the research focus of computing educators, leading to misdirected efforts in research and teaching practice. In this working group we carry out an in-depth analysis of international student engagement instruments to facilitate a greater awareness of the international benchmarks and what aspects of student engagement they measure. The working group also examine the focus of current computing education research and its alignment to student engagement measures on which these instruments are based. Armed with this knowledge, the computing education community can make informed decisions on how best to respond to these measures and consider ways to improve our performance in relation to other disciplines. In particular it is important to understand why certain measures of student engagement are built into these instruments, how these align to our current research practice or even to provide feedback to the designers of these instruments from a CS perspective.
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