Dr. Erin Higgins
In FY 2021, IES competed the Digital Learning Platforms to Enable Efficient Education Research through the Research Network Focused on Critical Problems of Policy and Practice grant program. NCER funded this network to increase the number of digital learning platforms (DLPs) that support research and to provide the infrastructure needed to enable education technology industry leaders and developers, education researchers, and education practitioners to work together to conduct relevant, rigorous, equity-focused research. In FY 2023, IES invited applications for research teams to join the network to conduct research using the network's DLPs.
Purpose: The intent of this network is to leverage existing, widely used digital learning platforms (DLPs) for rigorous education research and replication. Education research is often a slow and costly process. Also difficult is replicating research in a timely and cost-effective way to ensure that findings are meaningful for the wide range of contexts and populations that make up our nation's education system. Conducting research through widely used DLPs may accelerate the research enterprise and make it easier to conduct replications to identify what works for whom under what conditions. As DLPs' role in the provision of education grows, more research is needed to determine how to improve their effectiveness.
The major goals of the network are as follows:
This Network currently includes a network lead, five platform teams, and a research team, as follows:
The SEER Research Network for Digital Learning Platforms
Principal Investigator: Jeremy Roschelle, Digital Promise Global
The Network Lead will help platform developers, researchers, and educators share ideas, build knowledge, and strengthen dissemination.
The ASU Learning at Scale (L@S) Digital Learning Network
Principal Investigator: Danielle McNamara, Arizona State University
This platform team will 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 Canvas+Terracotta LMS-Based Experimental Education Research Platform
Principal Investigator: Benjamin Motz, Indiana University
This platform team will develop Terracotta, a plug-in to Canvas that enables a teacher or researcher to collect informed consent, assign different versions of online learning activities to students, and export deidentified study data.
Efficient Education Research via the OpenStax Learning Platform
Principal Investigator: Richard Baraniuk, Rice University
The platform team will build OpenStax Labs (Labs), a rapid iteration and testing learning environment integrated with OpenStax digital platform designed to conduct research faster and at scale, cultivate an inclusive research community, and deploy insights to improve student outcomes that lead to equitable student success.
MATHia: A Digital Learning Platform Supporting Core and Supplemental Instruction in Middle and High School Mathematics
Principal Investigator: Steven Ritter, Carnegie Learning, Inc.
The platform team will integrate MATHia with UpGrade, an open-source platform that supports fair and rigorous randomized field trials that compare innovative practices with current approaches.
Revisions to the ASSISTments Digital Learning Platform to Expand Its Support for Rigorous Education Research
Principal Investigator: Neil Heffernan III, Worcester Polytechnic Institute
The platform team will build the infrastructure to enable researchers to run studies using open education resources (OER) within the ASSISTments platform.
Now I See It: Supporting Flexible Problem Solving in Mathematics through Perceptual Scaffolding in ASSISTments
Principal Investigator: Avery Closser, Purdue University
The research team will use ASSISTments to explore whether exposure to perceptual cues, referred to as perceptual scaffolding, in mathematics notation (e.g., using color to highlight key terms such as the inverse operators in an expression) may lead learners to pause and notice structural patterns and ultimately practice more flexible and efficient problem solving.
Investigating the Impact of Metacognitive Supports on Students' Mathematics Knowledge and Motivation in MATHia
Principal Investigator: Cristina Zepeda, Vanderbilt University
The research team will use UpGrade/MATHia to explore the effects of evidence-based enhancements implemented during mathematics problem solving on middle school students' metacognitive skills, mathematics knowledge, and motivation.