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IES Grant

Title: The ASU Learning at Scale (L@S) Digital Learning Network
Center: NCER Year: 2021
Principal Investigator: McNamara, Danielle Awardee: Arizona State University
Program: Digital Learning Platforms to Enable Efficient Education Research Network      [Program Details]
Award Period: 5 Years (09/01/2021 – 08/31/2026) Award Amount: $2,000,000
Type: Methodological Innovation Award Number: R305N210041

Co-Principal Investigators: Weigele, Bethany; Anbar, Ariel; Roscoe, Rod

Related Network Teams: This project is part of the Digital Learning Platforms to Enable Efficient Education Research Network (Digital Learning Platforms Network), which aims to leverage existing, widely used digital learning platforms for rigorous education research, and includes the following other projects — The SEER Research Network for Digital Learning Platforms (R305N210034), The Canvas+Terracotta LMS-Based Experimental Education Research Platform (R305N210035), MATHia: A Digital Learning Platform Supporting Core and Supplemental Instruction in Middle and High School Mathematics (R305N210045), Revisions to the ASSISTments Digital Learning Platform to Expand Its Support for Rigorous Education Research (R305N210049), Efficient Education Research via the OpenStax Learning Platform (R305N210064)

Purpose: The purpose of this project is to develop a digital learning network platform with the capacity to connect, access, and examine undergraduate student data and courses within the scope of Arizona State University (ASU) online and digital classrooms (ASU Online). The proposed ASU L@S platform focuses on how students are represented in the system and how those data can be surfaced to the widest range of researchers. The long-term vision is to provide the infrastructure to promote innovation in research, emerging technologies, and community outreach to enhance universal, lifelong learning to students around the world. The ASU L@S project will develop foundational infrastructure and protocols to connect a wide range of data available in the ASU data ecosystem on student achievement, learning, and persistence, make those data accessible to researchers across and beyond ASU in ways that honor institutional and individual privacy so that it can examined through exploratory and experimental methods. Such a platform would leverage diverse types of data from large learner populations and facilitate experimental studies that examine the impact of a wide range of learning tools and approaches to enhance learning. Furthermore, inclusion of demographic data from a highly diverse population of students would empower researchers to advance inclusion and equity-oriented research to benefit all students.

Project Activities: In Year 1, ASU L@S project will produce platform specification documents and prototypes through collaboration with ASU researchers, administration, instructors, and students with guidance from the Advisory Board. Years 2 and 3 of the project will involve continued iterative design of the digital learning platform. Year 2 activities will also include the development of personnel infrastructure and procedures as well as initial small scale usability studies. Year 3 activities include feasibility studies that will inform platform refinement of components and procedures. Beginning in Year 3, the platform will be able to conduct multiple studies that will be used for continued refinement in Year 4. In project Years 4 and 5, the platform will be released for research use. In Year 5, continued collaboration with the Digital Learning Network will be used to continue refining the platform and procedures.

Products: A primary aim of this project is to develop the data and policy infrastructure necessary to enhance features, dashboards, data sets, data-sharing tools, and other system components needed for researchers without access to identified data to conduct collaborative research on ASU Online students and courses. The platform is ultimately envisioned to support multiple types of research including analyses of existing data, efficacy studies, replication studies, rapid A/B testing, and design studies with the overarching objective of contributing to theories of how people learn. ASU L@S will iteratively develop the capacity to collect multiple types of user activity and interaction data (e.g., interaction log data, response accuracy, homework completion, time spent, natural language input), rich demographic and user data (e.g., gender, ethnicity, age, socio-economic status proxies, part-time/full-time status, transfer or other admit type), as well as multiple types of education outcomes (e.g., learning, achievement, persistence, progress in postsecondary education, literacy, retention, performance). The platform infrastructure will be developed in anticipation of new, as-yet-undefined sources providing a flexible framework designed to accommodate emerging prioritized data sources and generating new views into the learning process: pulling, organizing, and connecting data from the student information system, learning management system, student support system as well as learning tools interoperability integrated partner learning tools of research interest. Drawing from the major ASU data sources, the team will conduct several experiments that will lead to a prototype of an aggregated data warehouse specifically for external researchers.