The Society for Learning Analytics Research is proud to announce the winner of the first Early Career Research Grant.
The SoLAR ECR Research Grant serves to support promising early career researchers who demonstrate the potential to advance research and practice in learning analytics and increase the educational and socio-economic impacts of learning analytics. Proposed projects should improve our understanding of learning analytics and learning in general, result in positive impacts on education, and align with the topics identified for the current round. It is expected that the ECR grant will help successful applicants develop their career by enabling an initiative that is scalable or has potential to attract further funding.
Winner: Catherine A. Manly
Project: Building an Institutionally Workable Prescriptive Analytics Approach to Support Tutoring Recommendations and Course Redesign
Summary
This project aims at closing the performance gap for students across the full range of dis/ability, whether disclosed or not, even when efforts to anticipate and design for student learning requirements (such as through a Universal Design for Learning (UDL) approach) fall short and students struggle to learn course material. In doing so, this project utilizes an atypical analytics approach, using prescriptive analytics to project predicted potential outcomes for individual students in different simulated worlds, allowing comparison of hypothetical future scenarios in order to make recommendations to students in the present. With additional potential to inform course redesign efforts by identifying places in the course where students are struggling, this project will involve faculty, staff, and students at Bay Path University in action research to collaboratively determine the next steps involved in institutionalizing this approach. Focus group data will inform development of a pilot for integrating prior proof-of-concept work with the data warehouse. The outcome will be a feasibility analysis report regarding potential implementation. Results will provide an example of how prescriptive analytics could be more broadly implemented.
Congratulations Cathy and we look forward to learning more about your project outcomes in the future!
