Staying up to date on new research findings is an increasingly daunting task for researchers, with scientific literature doubling roughly every 15 to 20 years. Synthesis researchers, too, face growing resource constraints as the size of extant literatures grow. To help mitigate associated challenges, this project will build the foundation and collaborations for using the latest advances in Artificial Intelligence (AI) to transform research synthesis in STEM education. This infrastructure will transform the speed and scale of research syntheses, while also democratizing access to the resources needed to conduct high-quality syntheses and spurring advances in broader researcher ecosystems.
Incubating the Use of Artificial Intelligence for Conducting High-Quality Research Syntheses
Staying up to date on new research findings is an increasingly daunting task for researchers, with scientific literature doubling roughly every 15 to 20 years. Synthesis researchers, too, face growing resource constraints as the size of extant literatures grow. To help mitigate associated challenges, this project will build the foundation and collaborations for using the latest advances in Artificial Intelligence (AI) to transform research synthesis in STEM education. This project tackles a critical bottleneck in how STEM education researchers can build on each other’s work. AI can serve as a powerful assistant to human researchers, helping by automating some of the mundane, repetitive tasks of synthesizing vast amounts of academic literature. Human content experts can then spend more time in interpreting knowledge, while also serving as a vital “human in the loop” to uphold trustworthiness and ethical standards in validating the output of AI-based tools. This infrastructure will transform the speed and scale of research syntheses, while also democratizing access to the resources needed to conduct high-quality syntheses and spurring advances in broader researcher ecosystems.
This Midscale Research Infrastructure Incubator will develop new interdisciplinary collaborations across synthesis methodologists, AI researchers, software developers and engineers, and STEM education researchers. The Incubator team will craft a consensus plan for infrastructure development through a structured process within three working groups: 1) evaluating and comparing existing AI tools, 2) creating open-source technical architectures, and 3) developing applications for STEM education researchers. This project intends to work toward an integrative, community-based, and ethical vision that leverages and significantly expands on related existing efforts that are presently disjointed. The NSF-funded and freely available MetaReviewer platform will serve as the team’s guiding focus for integration. The incubator team will also continue to seek additional partnerships that could benefit through shared open-source code and tools.
Project Materials
Title | Type | Post date Sort ascending |
---|---|---|
No content available. |