THE CONSTRUCTION AND VALIDATION OF AN INSTRUCTOR LEARNING ANALYTICS IMPLEMENTATION MODEL TO SUPPORT AT-RISK STUDENTS

Holly McKee

Abstract


With the widespread use of learning analytics tools, there is a need to explore how these technologies can be used to enhance teaching and learning. Little research has been done on what human processes are necessary to facilitate meaningful adoption of learning analytics. The research problem is that there is a lack of evidence-based guidance on how instructors can effectively implement learning analytics in their classroom to support academically at-risk students.

 

The goal of this study is to develop and validate a model to guide instructors in the implementation of learning analytics tools to support academically at-risk students with the purpose of improving learning outcomes. Using design and development research methods, an implementation model will be constructed and validated. The model should enhance the use of learning analytics by instructors by enabling them to better take advantage of available technologies to support teaching and learning in online and blended learning environments.

 

This poster presentation will introduce this work in progress research study. The goal of this presentation is to elicit feedback from peers to include in the stakeholder needs analysis which is an initial step in this study. This will be an excellent opportunity to collaborate in the development of a model to support faculty in implementing learning analytics in the online classroom.


References


Siemens, G., & Long, P. (2011). Penetrating the fog: Analytics in learning and education. EDUCAUSE review, 46(5), 30.

Wise, A. F., Vytasek, J. M., Hausknecht, S., Zhao, Y. (2015). Developing Learning Analytics Design Knowledge in the “Middle Space”: The Student Tuning Model and Align Design Framework for Learning Analytics Use. Manuscript submitted for publication.


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