ITU Co-Learning Lab | Artificial Intelligence in Education
“AI in Education: Shaping the Future of Learning Together”
The ITU Co-Learning Lab, held annually, aims to support pedagogical innovations by facilitating the sharing, experimentation, and implementation of new teaching and learning approaches. It has been incorporated into our academic calendar and was organized for the first time in a hybrid format at SDKM on September 25-26, 2024, in collaboration with our Graduate Education Institute and the ITU Center for Excellence in Education (ITU CEE). Detailed information about the event and the extended abstract book can be accessed on the event page.
ITU CEE also aims to organize a series of thematic Co-Learning Labs on topics such as artificial intelligence, gamification, and distance learning. One of the primary objectives of these thematic Co-Learning Labs is to share the outcomes of these thematic events with a broader audience during the annual Co-Learning Lab event. In doing so, short-term Co-Learning Lab cycles will evolve into an integrated annual cycle.
The first thematic Co-Learning Lab focuses on Artificial Intelligence in Education.
The overarching goal is to explore the transformative potential of Artificial Intelligence (AI) in education, share good practices, success stories, and fostering a community-wide capacity for embracing AI in pedagogy. The event will serve as a platform for interdisciplinary collaboration between academics, students, researchers, and alumni from diverse fields related to education and technology.
- Receive Best Practice Presentation Awards
- Publish in a digital proceeding after a peer review process
- Get short-term mobility fund for sharing good practices at international level
- Share good practices with the international academic community at different platforms including also the EELISA European University
- Get support from ITU Centre for Excellence in Education to transform good practices into seasonal schools targeting international learners
General Information and Important Dates
- Date: May 29-30, 2025
- Place: ITU Faculty of Computer and Informatics Engineering, Conference Hall
- Language: Turkish and English
- Format: Hybrid
- Deadline for the submission of abstracts: May 2, 2025
- Deadline for attendee registration: May 23, 2025
- Announcement of accepted abstracts: May 14, 2025
- Announcement of detailed program: May 26, 2025
Objectives
- To explore innovative AI applications that enhance teaching and learning in educational settings.
- To facilitate interdisciplinary discussions among educators, researchers, and students on integrating AI into teaching practices.
- To showcase the role of AI in transforming postgraduate research into impactful educational solutions.
- To build and strengthen collaborations within ITÜ and with international academic networks, including EELISA and other European networks.
Target Audience
- Academics and researchers working in AI, education, and related fields.
- Undergraduate, and postgraduate students.
- Alumni interested in educational innovation and technology.
- Professionals and educators exploring AI-driven educational strategies.
Expected Outcomes
- A comprehensive repository of good practices, case studies, and innovative tools shared during the event.
- Practical research-to-application transformations, enabling educators/researchers to develop AI-based educational tools / implement Al in educational contexts.
- A set of actionable recommendations for integrating AI into ITU’s educational ecosystem.
Section 1: Implementation of AI in Education
This section will:
- Share practical case studies and success stories of AI applications in educational settings.
- Highlight cutting-edge AI-driven tools and methods that improve teaching and learning.
Section 2: From Theses to AI-Enhanced Learning Experiences
This section aims to:
- Facilitate collaborative design sessions where participants prototype AI-enabled learning tools.
- Showcase the conversion of postgraduate research into actionable AI-based educational solutions.
- Provide a platform for students to present their research exploring AI’s role in education.
Section 3: From Interdisciplinary Research to Education
This section will:
- Explore how interdisciplinary research integrates AI in educational innovations.
- Present case studies from researchers applying AI in diverse fields, from cognitive sciences to engineering education.
- Encourage collaboration between research groups and educators to design AI-driven learning experiences.
Key Topics of Interest
Participants will be encouraged to submit abstracts focusing on, but not limited to:
- AI-driven personalized learning and adaptive education, enhancing individualized learning experiences through intelligent systems.
- AI-supported lifelong learning strategies, utilizing AI to facilitate continuous learning and upskilling opportunities.
- The integration of gamification and AI to create immersive, engaging, and interactive learning environments.
- AI-powered assessment, evaluation, and feedback mechanisms, enabling automated and data-driven student performance tracking.
- Enhancing hybrid and online learning models with AI, improving digital classrooms through intelligent tutoring and recommendation systems.
- AI-assisted curriculum design and educational content creation, optimizing instructional methodologies and resource generation.
- AI-driven interdisciplinary research methodologies, fostering innovative approaches to knowledge generation and dissemination.
- Fostering creativity and collaboration using AI-enhanced tools, such as generative AI and collaborative platforms.
- Addressing ethical concerns, data privacy, and fairness in AI-driven educational applications, ensuring responsible and inclusive AI integration in academic settings.
Content and Program
ITU Co-Learning Lab AI is designed as a two-day activity. The first day unfolds in Section 1, Section 2 and Section 3.
Day 1 – May 29, 2025
Section 1: Implementation of AI in Education
Target group: ITU Academics and all members of the ITU Community
Aim: Highlight cutting-edge AI-driven tools and methods that improve teaching and learning. Share practical case studies and success stories of AI applications in educational settings.
Method:
- Submission of extended abstracts
- Selection of good practices through peer review
- Presentation for each accepted extended abstract
- Q&A / discussion session following each presentation
Section 2: From Theses to AI-Enhanced Learning Experiences
Target group: ITU Academics and all members of the ITU Community
Aim: Showcase the conversion of postgraduate research into actionable AI-based educational solutions. Provide a platform for students to present their research exploring AI’s role in education. Facilitate collaborative design sessions where participants prototype AI-enabled learning tools.
Method:
- Submission of extended abstracts
- Selection of thesis-based learning proposals through peer review
- Presentation for each accepted extended abstract
- Q&A / discussion session following each presentation
Section 3: From Interdisciplinary Research to Education
Target group: ITU Academics and all members of the ITU Community
Aim: Explore how interdisciplinary research integrates AI in educational innovations. Present case studies from researchers applying AI in diverse fields, from cognitive sciences to engineering education. Encourage collaboration between research groups and educators to design AI-driven learning experiences.
Method:
- Submission of extended abstracts
- Selection of thesis-based learning proposals through peer review
- Presentation for each accepted extended abstract
- Q&A / discussion session following each presentation
Day 2 – May 30, 2025
LEARNING STATION MODEL – How to design innovative learning experiences through co-learning?
Target Group: Authors of Extended Abstracts from day 1
- Training of Trainers on Learning Station model
- Q&A / discussion session
- Kick-off session on Learning Station design
Detailed program will be announced soon.
Scientific Committee
| Name Surname | Institution |
|---|---|
| Görkem Külah | Department of Chemical Engineering (Middle East Technical University) |
| Hatice Köse | Department of Artificial Intelligence and Data Engineering (Istanbul Technical University) |
| Loredana Maria Manasia | Department of Teacher Education and Social Sciences (National University for Science and Technology Politechnica Bucharest – UNSTPB) |
| Suncem Koçer | Department of Media and Visual Arts (Koç University) |
| Şule Gündüz Öğüdücü | Artificial Intelligence and Data Science Application and Research Center (Istanbul Technical University |
| Yılmaz Akkaya | Department of Civil Engineering (Istanbul Technical University) |
| Yuki Kaneko | Foundations Development Directorate, (Sabancı University) |
| Zuhal Zeybekoğlu | Director, Office of Learning and Teaching (Koç University – KOLT) |
| + | Scientific committe will be updated |
Organization Committee
| Name Surname | Institution |
|---|---|
| Emrah Acar | Department of Architecture Director, ITU Centre for Excellence in Education (Istanbul Technical University) Board Member, European Society for Engieneting Education – SEFI) |
| Semra Ahmetolan | Department of Mathematics Vice Director, ITU Centre for Excellence in Education (Istanbul Technical University) |
| Merve Çalımlı Akgün | ITU Centre for Excellence in Education (Istanbul Technical University) |
| Emine Görgül | Department of Interior Architecture (Istanbul Technical University) |
| İskender Gökalp | Faculty of Aeronautics and Astronautics (Istanbul Technical University) |
| Hale İlkçakın | ITU Centre for Excellence in Education (Istanbul Technical University) |
| Hazal Taşdemir | ITU Centre for Excellence in Education (Istanbul Technical University) |
| Mehmet Aksu | ITU Centre for Excellence in Education (Istanbul Technical University) |
| Gülşen Cebiroğlu Eryiğit | Department of Artificial Intelligence and Data Engineering (Istanbul Technical University) |
| Faik Boray Tek | Department of Artificial Intelligence and Data Engineering (Istanbul Technical University) |
| Fatma Seniha Güner | Department of Chemical Engineering Dean, ITU Graduate School (Istanbul Technical University) |
| Onur Ferhanoğlu | Department of Electronics and Communication Engineering Vice Dean, ITU Graduate School (Istanbul Technical University) |
| Burçak Karagüzel Kayaoğlu | Department of Textile Engineering Vice Dean, ITU Graduate School (Istanbul Technical University) |
| Sema Erentürk | Department of Nuclear Researches Vice Dean, ITU Graduate School (Istanbul Technical University) |
| Hikmet Gültekin | ITU AI Student Club (Istanbul Technical University) |