Public lecture by University of Tartu honorary doctor Joseph S. Krajcik

On Wednesday, 30 November, University of Tartu honorary doctor Joseph S. Krajcik will give a public lecture “How can Artificial Intelligence Support STEM Teaching and Learning?”.

Professor Joseph S. Krajcik from Michigan State University was granted the honorary doctorate in science education for promoting research related to science, technology, engineering and mathematics education and for his effective cooperation with University of Tartu researchers and doctoral students in international projects.

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How can Artificial Intelligence Support STEM Teaching and Learning?

The Science, Technology, Engineering, and Mathematics (STEM) community faces significant challenges in preparing students to solve the most pressing and complex global problems concerning health, security, energy, and sustainability. Knowledge-in-use (i.e., the ability to use STEM knowledge), creativity, and critical thinking are required for future citizens to work together to solve such complex problems. To help students develop these critical competencies, we must make a paradigm shift in how we view STEM classroom environments. Students need to make use of their knowledge to solve complex problems and make sense of compelling and complex phenomena and solve ill-structured problems using scientific knowledge and practices. The vision is for students, no matter their gender, family background, community, and social-economic resources to have an equal opportunity to develop useful scientific knowledge, make sense of phenomena, and solve complex problems. Yet, such environments present challenges to teachers in assessing and providing timely feedback to students.

In this session, Professor Krajcik will present his work on how his team is using artificial intelligence (AI), as a partner to score open-ended explanation tasks and student-drawn models to provide immediate feedback to teachers and students and to suggest next steps that teachers and students can take to improve learning. Using AI can provide immediate, meaningful information on student performance individually and collectively to inform teachers to make timely instructional decisions. Using AI to assess knowledge-in-use performance-based tasks in STEM classrooms will allow teachers to adjust teaching and plan lessons to better support students in developing the competence to use scientific knowledge and practices. Professor Krajcik’s hope is that such classroom resources can help transform STEM classrooms where students take part in meaningful tasks to promote their learning. 

The lecture will start at 16:15 in J. Liivi 2–127.