发现学科差异：整合数据源探究大学英语课程中学生的网络行为

IF 2.1 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

Information Discovery and Delivery Pub Date : 2019-05-20 DOI:10.1108/IDD-10-2018-0053

D. Foung, Julia Chen

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引用次数: 8

摘要

目的本研究旨在探讨学术素养课程中完成混合学习任务的学科差异，以及采用混合学习分析方法探讨学科差异的可行性。设计/方法/方法本研究采用学习分析方法，将学习管理系统和时间表安排的数据融合在一起。研究结果表明，设计专业学生和会计专业学生的网络行为在开始时间和完成率方面存在差异。混合数据源也为我们的学习分析研究提供了一个新的视角。原创性/价值本研究是对该领域的重要贡献，因为对多数据源学习分析的研究很少，大多数学科研究依赖于调查数据;学生的实际行为没有得到充分的探索。

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Discovering disciplinary differences: blending data sources to explore the student online behaviors in a University English course

Purpose This study aims to explore disciplinary differences in completing blended learning tasks in an academic literacy course and the feasibility of adopting a blended learning analytics approach to explore disciplinary differences. Design/methodology/approach Following a learning analytics approach, this study blends data from the learning management system and timetabling arrangements. Findings Results suggest that online behaviors of design students and accounting students are different in terms of starting day and completion rate. Blending data sources also provides a new perspective to our learning analytics study. Originality/value This study is an important contribution to the field because studies on learning analytics with multiple data sources are rare, and most disciplinary studies rely on survey data; students’ actual behaviors are under-explored.

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来源期刊

Information Discovery and Delivery INFORMATION SCIENCE & LIBRARY SCIENCE-

CiteScore

5.40

自引率

4.80%

发文量

期刊介绍： Information Discovery and Delivery covers information discovery and access for digital information researchers. This includes educators, knowledge professionals in education and cultural organisations, knowledge managers in media, health care and government, as well as librarians. The journal publishes research and practice which explores the digital information supply chain ie transport, flows, tracking, exchange and sharing, including within and between libraries. It is also interested in digital information capture, packaging and storage by ‘collectors’ of all kinds. Information is widely defined, including but not limited to: Records, Documents, Learning objects, Visual and sound files, Data and metadata and , User-generated content.