For more information, visit: https://learningatscale.asu.edu/

Research Questions

L@S provides a platform to promote innovation in research, analytical methods, and collaboration to enhance universal lifelong learning. When researchers have the ability to examine student data using exploratory and experimental methods, it can result in the advancement of equity-oriented research, benefiting all students.

User Population

L@S features data from ASU students (undergraduate, graduate, immersion, and online) and ASU courses.

Learn more about some of the work of the EdPlus team at ASU here. 

Pre-Registration/Vetting

The ASU L@S team, in coordination with the ASU Provost’s Office and IRB, will vet potential research studies. 

To support independent and custom data requests, L@S has designed a comprehensive intake process with steps to guide researchers. As researchers move through each step, the L@S team will collaborate with you to: 

• Scope the lift 
• Determine expected turnaround 
• Communicate research and publication expectations (the expectation that researchers will publish and share results associated with L@S data)
• Collect required documentation

IRB requirements

IRB documentation is required to ensure any proposed study complies with IRB standards and data security guidelines. All prospective researchers are required to obtain IRB approval from their home institution prior to final study approval. However, researchers may complete the initial interest forms without existing IRB approval.

Recruitment (Students)

No recruitment of subjects necessary for historic, aggregated data. Per course/per survey studies with interventions would require navigating the appropriate buy-in and consent procedures.

Randomization

Interventions can be randomized at different levels: university-wide, class-level, individual level, etc.

Intervention

Future platform development will include features to support multiple types of research including A/B testing, efficacy and replication studies, and design studies including ability to evaluate and maximize EdTech Tools in play, ex: InScribe, YellowDig

Prior achievement/demographic data 

Our team identified and prioritized five foundational tables that provide a comprehensive understanding of the ASU student learning experience. Integrating these datasets enables impactful and embedded research at ASU that enhance student outcomes and contribute to theories of how people learn.

L@S Foundational Tables:

• Student Profile – includes academic performance and demographic information

• Student Trajectory – includes academic participation and performance data

• Course Profile – characteristics of ASU courses (for example, pass/fail rates)

• Discussion Boards – text data from discussion board posts and replies (for NLP analysis)

• Written Assignments – text data from written assignment submissions (for NLP analysis)

Outcome Measures

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

Analysis

The ASU Learning@Scale (L@S) project develops the foundational infrastructure and protocols that connect a wide range of student data to researchers across and beyond ASU. We provide researchers with access to data on student achievement, learning, persistence, courses and more, while maintaining individual and institutional privacy.