There’s a need for bridging the gap between potential and practical implementation for educational research. Shouldn’t we be doing more of that with what we already know about how humans learn?

In the meantime, explore The LEARN Lab from NorthEastern University.

The LEARN Lab is a hub for use-inspired research that leverages AI and technology to transform teaching and learning across educational contexts. As an innovation incubator and research hub, we connect faculty, students, researchers, practitioners, and external partners to explore and document effective approaches to AI-enhanced teaching, learning, and research. Through structured inquiry and rigorous documentation, we help bridge the gap between AI’s potential and its practical implementation in education.

Some of their projects include (I really like the idea of the first one):

RAG-based Analysis Solutions

Analysis LEARN Lab is designing and prototyping a RAG (Retrieval-Augmented Generation) solution to enable comprehensive research and analysis of large text-based datasets, with particular focus on transcripts generated by AI interviewer agents and AI-based simulations used in assessing skills. The team of doctoral and masters students at CPS aims to develop and test a centralized platform that can process, chunk, and provide analytical support for faculty and student researchers.

Self-Assessment Tools for AI-Assisted Research & Inquiry  

LEARN Lab is developing a self-assessment framework designed to guide student reachers in the ethical and effective integration of AI technologies to support research processes. This research project addresses a critical need for frameworks that help emerging scholars navigate AI’s role in academic inquiry while maintaining the highest standards of scholarly rigor and integrity. The tool positions AI as a research assistant that enhances, rather than replaces, the critical judgment and methodological expertise essential to doctoral-level research. Through this initiative, we are investigating how structured self-reflection can support students in preserving their scholarly voice while leveraging AI’s capabilities responsibly, contributing to broader understanding of how graduate education can adapt to technological advances without compromising academic standards. This tool will be made available to other researchers and schools to adapt and modify as they see fit, once completed. 

AI Literacy Organizational Learning Strategies

CPS is using voice-based AI technology to interview faculty and staff about their current AI literacy levels and integration needs. The CPS LEARN Lab is analyzing these transcribed interviews to inform a comprehensive strategy supporting the College’s AI integration efforts across the organization. We are inviting doctoral researchers to join this analysis and visioning process because combining academic rigor with use-inspired research creates valuable experiential learning opportunities while giving students a meaningful voice in shaping the future of workplace AI education.

Voice-based AI for Teaching, Learning and Research

In partnership with SchoolJoy, the LEARN Lab is developing and implementing voice-based AI technology to document learner experiences across diverse educational settings, using structured conversational assessments to support student reflection on experiential learning activities in K12 and higher education contexts. This technology has potential to provide instructors with rich, just-in-time insights into individual student experiences and challenges while generating broader insights about what makes experiential learning more or less impactful for learners across K12, higher education, and workforce settings. We invite doctoral researchers to participate in this development and evaluation process because integrating academic research with innovative educational technology creates powerful experiential learning opportunities while enabling students to contribute directly to advancing how we understand and support learner growth in real educational contexts.