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A four-country cross-case analysis of academic staff expectations about learning analytics in higher education
The Internet and Higher Education ( IF 6.4 ) Pub Date : 2020-12-15 , DOI: 10.1016/j.iheduc.2020.100788
Kaire Kollom , Kairit Tammets , Maren Scheffel , Yi-Shan Tsai , Ioana Jivet , Pedro J. Muñoz-Merino , Pedro Manuel Moreno-Marcos , Alexander Whitelock-Wainwright , Adolfo Ruiz Calleja , Dragan Gasevic , Carlos Delgado Kloos , Hendrik Drachsler , Tobias Ley

The purpose of this paper is to explore the expectations of academic staff to learning analytics services from an ideal as well as a realistic perspective. This mixed-method study focused on a cross-case analysis of staff from Higher Education Institutions from four European universities (Spain, Estonia, Netherlands, UK). While there are some differences between the countries as well as between ideal and predicted expectations, the overarching results indicate that academic staff sees learning analytics as a tool to understand the learning activities and possibility to provide feedback for the students and adapt the curriculum to meet learners' needs. However, one of the findings from the study across cases is the generally consistently low expectation and desire for academic staff to be obligated to act based on data that shows students being at risk of failing or under-performing.



中文翻译:

学术人员对高等教育学习分析的期望的四国跨案例分析

本文的目的是从理想和现实的角度探讨学术人员对学习分析服务的期望。这项混合方法研究的重点是对来自四所欧洲大学(西班牙,爱沙尼亚,荷兰,英国)的高等教育机构员工的跨案例分析。尽管各国之间以及理想和预期期望之间存在一些差异,但总体结果表明,教职员工将学习分析视为了解学习活动的工具,并为学生提供反馈并适应课程以满足学习者的可能性的需要。然而,

更新日期:2020-12-15
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