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An Instructor Learning Analytics Implementation Model
ARTICLE

Online Learning Volume 21, Number 3, ISSN 2472-5749

Abstract

With the widespread use of learning analytics (LA) tools, there is a need to explore how these technologies can be used to enhance teaching and learning. Little research has been conducted on what human processes are necessary to facilitate meaningful adoption of LA. The research problem is that there is a lack of evidence-based guidance on how instructors can effectively implement LA to support students. The goal of the study was to develop and validate a model to guide instructors in the implementation of LA tools. Using design and development research methods, an implementation model was constructed and validated internally. Themes emerged falling into the categories of adoption and caution with six themes falling under adoption including: LA as evidence, reaching out, frequency, early identification/intervention, self-reflection, and align LA with pedagogical intent. Three themes emerged falling under the category of caution including: skepticism, fear of overdependence, and question of usefulness. The model should enhance instructors' use of LA by enabling them to better take advantage of available technologies to support teaching and learning in online and blended learning environments. Researchers can further validate the model by studying its usability (i.e., usefulness, effectiveness, efficiency, and learnability), as well as, how instructors' use of this model to implement LA in their courses affects retention, persistence, and performance.

Citation

McKee, H. (2017). An Instructor Learning Analytics Implementation Model. Online Learning, 21(3), 87-102. Retrieved November 30, 2021 from .

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