January 19, 2022 | By Jeremy Roschelle
To do so, the Learning Sciences Research team is engaging in a new strategy: creating or participating in hubs that connect researchers, educators, and software developers. Hubs can combine the expertise and perspectives required to connect research to meaningful improvement of teaching and learning at scale. We are already partnering in three research hubs* and are excited about the potential for other early stage partnerships to grow into future hubs.
The Center for Integrative Research in Computing and Learning Sciences (CIRCLS) is a community-based hub that connects over 150 National Science Foundation research projects. The projects explore emerging technologies, combining the research expertise of computer scientists and learning scientists. Our recent convening, attended by 300 participants, focused squarely on how to remake “broadening”—that is, how can this community more strongly engage themes of participatory design, equity, and scale? By working together in a hub, we hope to propel hundreds of individual projects toward broader impacts.
The SEERNet research hub brings together five large-scale digital learning platforms, each of which serves over 100,000 students per year. With funding from the U.S. Department of Education’s Institute of Education Sciences, the aim of this program is to open up these platforms so that third-party researchers can accelerate the pace of improvement within them. For example, researchers can join forces to improve supports, tutorials, and hints for students who are solving math problems in ASSISTments—a no-cost platform that already serves 500,000 mathematics students. Our prior research found that ASSISTments is effective and particularly advantageous for students who struggle in mathematics. However, we need more than one research study to improve mathematics homework and effectively support students with disabilities, students who are learning English, and students who have experienced trauma. SEERNet will open up ASSISTments and four other platforms to more researchers, so we can strengthen involvement for those conducting useful research at scale.
The AI Institute for Engaged Learning is a newly awarded National Science Foundation institute ith $20 million in funding over five years. The Engage AI Institute is a coalition of four universities—North Carolina State University, Indiana University, the University of North Carolina at Chapel Hill, Vanderbilt University—and Digital Promise. Together, we will investigate the potential for AI-enhanced, narrative-centered learning environments to engage students in science learning through customized stories, plots, and characters, while deepening their understanding of foundational science concepts. Digital Promise is creating the nexus or hub of activity and communication for the Institute. The premise of our nexus is that large-scale success of this effort depends on our ability to involve many more people in the intellectual challenges as well as the attendant questions of ethics, equity, and effectiveness of the emerging approaches to story-based learning.
In partnership with OpenSciEd and a large science education research community, we are also running a hub-like project to stimulate more research about open science education. Our partnerships with other teams in Digital Promise also may lead to hubs. For example, we partner with the League of Innovative Schools, which serves 125 districts in 35 states serving more than 3.8 million students. With the League, we have been developing a research hub around inclusive computational thinking pathways that districts can implement in their schools.
By adopting strategies like research hubs and researcher-practitioner partnerships, we hope to better address the magnitude of the challenges facing education today, tomorrow, and in the years to come.
To learn more about the three research hubs, visit their websites:
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*This material is based upon work supported by the National Science Foundation under Grant No. 2021159 (CIRCLS) and Cooperative Agreement DRL-2112635 (Engage AI Insitute) and by the Institute of Education Sciences, U.S. Department of Education Grant No. R305N210034 (SEERNet). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation, the Institute of Education Sciences, or the U.S. Department of Education.
