The Academic Analytics Tool: Workflow and Use Cases
To meet the demand for timely analysis and revision of online courses, educators need ongoing, unfettered access to data about how students interact with courses and online resources. Currently available tools for exploring student data provide some impor
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Athabasca University, Canada {tross, cindyi; nancyp; andrewh; sabineg}@athabascau.ca 2 Beijing Normal University, China [email protected]
Abstract.To meet the demand for timely analysis and revision of online courses, educators need ongoing, unfettered access to data about how students interact with courses and online resources. Currently available tools for exploring student data provide some important insights, but are typically focused on automated data mining, visualizations, or displaying pre-set reports. These tools also often require either high technical skills and/or installation of specialized software, making them inaccessible to most educators and learning designers. In this paper, we introduce the Academic Analytics Tool (AAT) and provide some hands-on examples on how the tool can be used. AAT is designed to allow people (e.g., educators, learning designers, etc.) without technical expertise to extract and analyse data from learning management systems (LMSs). AAT offers high usabilityand permits full exploration of LMSs’ data on any computer with internet access to foster responsive analysis and improvement of online courses. Keywords:academic analytics · data extraction and analysis · online learning
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Introduction
Online learning is still a rather new educational option, and there is much to be learned about the best teaching methods and course designs for this format. The multi-year course revision process is simply not conducive to meeting the evolving demands of online students, or rapid changes in the online educational marketplace. To ease the burden on IT departments and ensure courses are monitored and revised frequently and appropriately, educators and learning designers should be empowered with direct access to data about student behaviour in online courses [1].
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The authors acknowledge the support of Athabasca University and NSERC.
© Springer Science+Business Media Singapore 2017 E. Popescu et al. (eds.), Innovations in Smart Learning, Lecture Notes in Educational Technology, DOI 10.1007/978-981-10-2419-1_32
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Learning management systems (LMSs) store vast quantities of data about student activities in their courses, including forum activities, access of online books and resources, grades on quizzes and exams, assignment submissions, and communications with instructors [2]. By analysing this information, educators can learn a great deal about what students are doing in their courses, and what factors affect student success. A number of tools exist to extract student behaviour data, but these typically come with limitations that make them difficult for educators to use or they limit the data educators are able to investigate. There is a need for tools designed for educators that allow for a full range of queries on all available data in an LMS, and that work with a wide range of LMSs and database formats [3,4]. The Academic Analytics Tool (AAT) [5] is a software tool designed to allow educators, learning designers and school administrators to perform th
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