Open Access

Author: Lesley S. J. Farmer

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Abstract: Engineering faculty should take advantage of data analytics to improve their curriculum, program, and student success. As such, faculty need to strategically conduct the entire data process: knowing the right questions to ask, determining the relevant data to collection, choosing the appropriate instruments to collect those data, analyzing that data, recommending appropriate actions, implementing them, and evaluating the implementation. Furthermore, students need to learn how to analyze data as part of their professional repertoire of design and development intellectual toolkits. To that end, learning analytics practices are detailed in this paper. Engineering education constitute the contextual focus.

Keywords: learning analytics, data analytics, data, curriculum, instructional design

Cite this paper

Lesley S. J. Farmer. (2017) Learning Analytics For Engineering Education. International Journal of Education and Learning Systems, 2 , 6-11

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Copyright © 2017 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution License 4.0