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Preparing K-12 and higher education IT leaders for the exponential era

University of Maryland Opens Center for Ed-Tech Research

The university launched a new center this month aimed at collecting data and developing intentional, research-supported educational tools based on how students and educators are using AI in classrooms.

A person in a white doctor's coat with a stethoscope around their neck holding a blue folder in one hand and extending their other arm with their palm facing up. Floating above their palm is al illustration of a human brain in white.
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As the educational technology sector becomes increasingly saturated with artificial intelligence-powered tools and platforms, the University of Maryland is choosing a more deliberate path.

This month, the university launched the Center for Educational Data Science and Innovation (EDSI) to promote research and collaboration on equitable solutions to educational issues through data science and AI. The center will create and support AI-driven ed-tech tools, but not without a strong research base behind them.

“The fundamental approach we are taking is different from other AI and education institutions or centers,” Jing Liu, assistant professor and director of EDSI, said in a public statement. “We take a step back in terms of focusing on building the infrastructure to enable AI innovation in a responsible and ethical way. We also prioritize high-quality research in this space rather than rushing to produce another AI tool."

For example, EDSI is continuing work on an app called M-Powering Teachers, developed in 2023 to provide math educators with personalized, non-evaluative feedback on classroom recordings. The university's website said the tool uses natural language processing to analyze transcripts of recorded sessions and assess aspects of it that are relevant to the instructor, such as student engagement, question strategies and mathematical discourse. It also provides specific prompts for teacher reflection.
A visual shows feedback on a classroom recording. "Talk Distribution" shows the teacher spoke 84 percent of the time in class while the students spoke 16 percent of the time. "Talk length" shows that, on average, the teacher spoke 34 words continuously and students spoke an average of 5 words continuously.
M-Powering Teachers provides data on classroom recordings, allowing teachers to reflect on communication patterns and instructional choices.
Image credit: University of Maryland
Studies published by the EDSI team before the center's founding demonstrate the effectiveness of automated feedback in improving instructional quality and student outcomes, especially for online learning. Recent papers by Liu and colleagues also show that AI-generated feedback can support teachers in reflecting and making data-informed improvements without the time constraints of traditional person-to-person coaching models. EDSI is also looking into how AI can complement this human feedback.

“It was important to establish a center that would both support AI use in improving teaching and learning and prepare students for an AI-infused future,” Liu said in a public statement. “We wanted a space that would allow us to look at persistent educational challenges, such as declining literacy rates, chronic absenteeism and diverse learning styles, and consider the unprecedented technological possibilities that could address these challenges.”

Another EDSI project is compiling a comprehensive database of classroom transcripts, audio, video, and student demographic and achievement data, alongside human annotations on teaching practices and classroom interactions, to inform better AI tools like M-Powering Teachers with more holistic views of what's happening in class.

To ensure research and innovation includes diverse voices, EDSI has established partnerships with school districts, including Guilford County Schools in North Carolina and San Francisco Unified School District in California, and organizations like the Research Partnership for Professional Learning. The center also serves as a hub for collaboration across the University of Maryland, bringing together experts in computer science, AI and education policy.

“All the stakeholders need to be at the table to do this work really well,” Liu said.
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