Application Opens for 2026 LearnLab Summer School

March 17, 2026

The Breakdown 

• Applications are now open for the 2026 CMU LearnLab Summer School.
• Four parallel learning tracks will cover online courses, intelligent tutoring systems, educational data mining and computer science education. 
• The week-long event concludes with research presentations on Friday. Learn more and apply at LearnLab.org. 

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The application is now open for the 2026 LearnLab Summer School at Carnegie Mellon University. This intensive, one-week program gives participants hands-on experience building advanced educational technologies and tutoring systems to solve real-world learning challenges.

Unlike many other summertime programs, this event is not for high school students. This professional initiative is designed for researchers, educators, graduate students and technology developers who want to bridge the gap between the science of learning and practical classroom technology. 

The 2026 Summer School will be held Monday, July 27 through Friday, July 31, at the CMU campus in Pittsburgh, Pennsylvania. Each day includes lectures, discussion sessions and hands-on sessions. 

“The Summer School has always had a great combination of project-based learning by doing and fundamental skill development,” said Ken Koedinger, Hillman University Professor of Computer Science. “Our participants often work in pairs to complete a research and development (R&D) project over the course of the week. We match them with the support of two skilled mentors – typically one who is research-oriented and one who is more technical.”

Participants apply to one of four parallel tracks to direct their learning experience for the week. Summer 2026 tracks include:  

• Building online courses with OLI (BOLI) - create interactive, technology-enhanced course materials.
• Intelligent Tutor Systems development (ITS) - build software that provides personalized, step-by-step tutoring.
• Educational Data Mining (EDM) - analyze big data from students to find patterns in how people learn.
• Computer Science Education Research (CER) - focus on how to teach and learn computer science.

One subject area becoming increasingly relevant across all tracks is how to use generative artificial intelligence (AI). Attendees will receive guided instruction and hands-on experience using generative AI in their prototypes and experiments to aid instructional development, AI tutor development, data analysis, or learning modeling.

A Staple in the Learning Sciences Community 

The LearnLab Summer School started 25 years ago with about 10 participants and a primary focus on intelligent tutoring systems. 

Since then, it has since expanded greatly, both in the number of attendees and in the subject areas covered in the tracks. 

“It is amazing to me that we have maintained the Summer School for so long – this will be the 26th summer,” said Koedinger, who has attended all of the events so far. “I am proud that we have reached and continue to support so many others in doing cutting-edge learning sciences and engineering.” 

Organizers estimate that more than 1,000 learners have completed the program. 

“The Summer School has trained students, faculty and industry in the artificial intelligence for education (AIED) and educational data mining (EDM) communities for decades,” said John Stamper, associate professor. “Many of today’s top researchers got a taste of this level of research at the Summer School, including myself. I took the ITS track as a Ph.D. student from UNC Charlotte in 2007.”

Feedback from Previous Attendees 

Summer 2025 attendees frequently described the week as “transformative” and “energizing.” Participants mentioned the benefits of working with real DataShop data and building actual courses using tools like OLI and Torus. 

They also enjoyed the Friday poster session to see the tangible results of their peers’ learning during the week. 

“Judged by the work that participants present during the final-day poster session, and the enthusiasm with which they present it, the Summer School very effectively supports learning-by-doing,” said Professor Vincent Aleven. 

Jennifer Noble, assistant dean of the School of Applied Technology at Alfred State, is one of several 2025 attendees who commented on the positive energy of the week. 

“Being surrounded by such a diverse group of creative, growth-minded, and research-driven educators, innovators, and thought leaders was incredibly energizing,” said Noble. “The collective passion, experience, and curiosity in the room sparked new ideas constantly. I left each day with a head full of insights I could hardly get down on paper fast enough. LearnLab created the perfect environment to fuel collaboration, innovation, and forward-thinking educational research.”

Returning attendee Angela Thering, Instructional Consultant for AI/Technology-Enabled Pedagogy at University at Buffalo, was grateful to the facilitators and community for creating such a vibrant space for collaboration.  

“Spending the week at LearnLab at Carnegie Mellon, and diving into learning science, AI, and human-computer interaction was an incredible experience. As a returning Data Science for Education (DS4EDU) mentor, I was excited to support this year’s fellows while continuing to grow in AI-enhanced instructional design, ethical ed tech, and data-informed teaching innovation,” said Thering. 

Summer School Expands to Zürich  

Thomas Schmalfeldt, a professor at Zürich University of Teacher Education (PH Zürich), was inspired to start a similar event after attending the Pittsburgh program.  

The “Zürich Workshops on Learning in a Digitalized World,” will take place Monday, August 3 to Friday, August 7, 2026.

Now entering its fourth year, the Zürich event is expanding its scope. Attendees can choose from three tracks in 2026: Intelligent Tutoring Systems, Adaptivity, or Process Data Analysis.

Several members of the CMU community, including Aleven, Octav Popescu and Jonathan Sewall, will support the ITS track as mentors.

The Zürich Summer School is a cooperative effort between the Zürich University of Teacher Education, ETH Zürich, Carnegie Mellon University, University of Potsdam and University of Tübingen.