Acting on Actionable Intelligence

Full name:  BIGDATA: IA: Acting on Actionable Intelligence: A Learning Analytics Methodology for Student Success Efficacy Studies. Principle Investigator: Rich LevineCo-PIs: Bernard Dodge and Juanjuan Fan. Funding agency: National Science Foundation. Funding period: 2016-2020.

How can instructors, administrators, and education researchers take advantage of rich institutional student information system (SIS), learning management system (LMS), and non-LMS performance data to characterize at-risk students that will most benefit from pedagogical innovations and intervention strategies?  An SDSU interdisciplinary team from statistics and data science, institutional research, and instructional technology have secured NSF funding to develop a learning analytics methodology to automate the tasks of data collection and processing, data visualizations and summaries, data analysis, and scientific reporting in student success efficacy studies.  As part of this development, the concept of individualized treatment effects will be introduced as a method to assess the effectiveness of interventions and/or instructional regimes and provide personalized feedback to students.