The L@S data warehouse will allow researchers to conduct several types of exploratory analysis and future designs may allow experimental interventions.
Post-secondary online ASU students. Potential in the future to expand the user population.
The ASU Provost’s Office and IRB, along with ASU L@S team members, will coordinate vetting of potential research studies.
ASU IRB, researchers use own IRB
No recruitment of subjects necessary for historic, aggregated data. Per course/per survey studies with interventions would require navigating the appropriate buy-in and consents.
Interventions can be randomized at different levels: university-wide, class-level, individual level, etc.
Focus on features to support multiple types of research including A/B testing, analyses of existing data, efficacy and replication studies, and design studies. Evaluate and maximize EdTech Tools in play, ex: InScribe, YellowDig
Pre-Alpha build includes Course Profile table, Course Outcomes table, and Common Student Characteristics Table. ASU will utilize NLP to evaluate written assignments and discussion board postings.
For initial proof of concept, L@S will build student profile model and a course profile model to analyze what outcome measures are essential to improve student outcomes and integral to future iterations of the L@S platform
L@S will connect a wide range of available data in the ASU ecosystem and make it accessible to researchers in ways that honor institutional and individual privacy.