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The scope of this theme is broad, combining research in engineering and computing education and assessment with artificial intelligence, machine learning, natural language processing and robotics. We believe that there are synergies that can be realized by bringing these two areas together and that researchers at ¶¶Òõ¶ÌÊÓƵ are well positioned to do so. What’s more, findings could be immediately applied at the university and college to improve courses and practices.

Our team is uniquely poised to both apply existing evidence of proven methods to their teaching practice and to innovate in this space. Many within the college are already deeply involved in engineering education research, computing education research, and the scholarship of teaching and learning. Likewise, the college has great strength in AI, machine learning, and natural language processing. All of which encompass an array of technical challenges found in education research including dialog generation and management, computer vision, multi-modal analysis, and embodiment in robotics. 

The IRT provides a focal point for collaboration within these disciplines in the college and with partners like the School of Education and other disciplinary-based education research (DBER) on campus, as well as industry leaders, through seed grants and teaming activities. This systems level approach matches the college’s strategic vision and goals of providing research with great societal impact while growing our national leadership role in engineering education and artificial intelligence research.

Mission

Our mission in this theme is three-fold. We plan to:

• Develop the theories, technologies, and know-how for advancing: 1) student-centered learning and next generation collaborative learning environments in K-16, graduate, and professional engineering and computing education, and 2) artificial intelligence technologies to support education and learning, most importantly in the areas of natural language understanding, multi-modal dialog management, reinforcement learning and robotics.
• Serve as a national nexus point for empowering stakeholders with diverse identities and interests – researchers, educators, community members, and industry affiliates – to envision, co-create, critique, and apply student-AI teaming technologies in their classrooms and communities.
• Grow a diverse workforce of future researchers, leaders, and practitioners at the convergence of engineering and computing education research and artificial intelligence research.