The integration of Artificial Intelligence (AI) into education presents unprecedented opportunities for innovation, alongside complex challenges that require rigorous, evidence-based exploration. This year, an International Summer School focusing on Artificial Intelligence in Education will be held at East China Normal University. The aim is to foster an in-depth examination of empirical research on AI’s application across diverse educational domains. Through interactive sessions, participants will engage empirical methodologies and insights into AI’s impact in education, guided by leading experts and researchers in the field.
The Summer School will provide young researchers an opportunity to present their work, receive feedback from leading experts in the field, and refine their ideas through collaborative dialogue. It’s a chance to build academic connections, and spark new ideas forfuture research.
The Summer School is organized by the Institute of Education, National Research University Higher School of Economics (Russia). The institution is at the forefront of cutting-edge interdisciplinary studies, exploring the intersection of AI and education, paving the way for innovative practices and policies that address the challenges and opportunities of AI.
Key features of the SummerSchool:
Discussionon your research ideas with leading experts in the field;
A strong emphasis on empirical strategies;
Multidisciplinarity approaches;
Cross-national perspectives (faculty and participants from different parts of the world);
A friendly and supportive environmentthat fosters fruitful academic discussions.
Main tracks:
AI and Skills
This track explores how AI is reshaping the skills required in today’s world and how education systems must adapt. It focuses on AI-driven changes in skill structures, curriculum design, and their implications across general, higher, and vocational education, highlighting economic, pedagogical, and technological perspectives.
AI and Assessment (Psychometric)
This track explores the integration of artificial intelligence (AI) into educational and psychological assessment, focusing on its transformative potential and methodological innovations.Topics include:
The application of AI, such as Artificial Neural Networks (ANNs), to enhance the data analysis.
The adaption oftraditional assessment models, such as Item Response Theory (IRT) and Factor Analysis (FA) into ANNs with the potential to advance these models beyond traditional formats (e.g., multiple-choice)by incorporating process data, speech, and images,thereby broadening the scope of measurable constructs.
Participants will gain hands-on experience in constructing AI-driven assessments, analyzing real-world data, and interpreting key parameters. Discussions will address the ethical and practical implications of AI in education, highlighting its role in transforming assessment practices and advancing computational behavioral science.
Prerequisites for this track:
A solid grounding in statistical modelscommonly usedin the social sciences (e.g., linear and logistic regressions, Factor Analysis, IRT, path analysis).
A laptop with Python installed, ready for coding exercises.
AI and Pedagogy
This track examines how AI transforms teaching and learning processes, including personalized content delivery, AI-based feedback, simulations for experiential learning, and AI-driven skills assessments. Participants will explore empirical research on the effectiveness of these tools and the challenges of integrating them into educational practice.
AI, Regulation andImplementation inUniversities
This track of the Summer School will focus on how different actors within universities are adapting to the use of generative AI in their activities and what rules are being established at the university level. Discussions will also explore comparative perspectives on generative AI policies in different countries and universities, highlighting how different contexts shape regulatory approaches. Participants will present their research, empirical findings, case studies and theoretical approaches to the adaptation and governance of generative AI in universities.
Keynote speakers
Evgeniy Terentev
PhD in Sociology, Dean, Institute of Education, National Research University Higher School of Economics
Denis Federiakin
Department of Business and Economics Education, Johannes Gutenberg University Mainz, Germany, Department of Educational Psychology, Goethe University Frankfurt, Germany
Mik Fanguy
Assistant Professor, Department of English Language Education, The Education University of Hong Kong
Vera Maltseva
PhD in Economics, Director of the Centre for Skills Development and Vocational Education,National Research University Higher School of Economics, Russia
Chanjin Zheng
PhD in Educational Psychology, Shanghai Institute of Artificial Intelligence for Education, East China Normal University, China
Okan Bulut
Professor, Measurement, Evaluation, and Data Science, Centre for Research in Applied Measurement and Evaluation, University of Alberta, Canada
Ling Li
Associate Researcher, Shanghai Institute of Artificial Intelligence for Education, East China Normal University, China
Isak Frumin
PhD in Education, Head of Observatory of Higher Education Innovations
School of Business, Social & Decision Sciences, Constructor University, Germany
Jing Leng
Associate Professor, Department of Education Information Technology, East China Normal University, China
Andrei Ternikov
PhD in Economics, Senior Lecturer at HSE Campus in St. Petersburg
Format and Activities
The Summer Institute will combine lectures, workshops, and collaborative sessions. Each track will feature presentations from prominent researchers and educators, interactive discussions, and hands-on labs to deepen participants’ understanding of empirical research techniques in the context of AI applications. Participants will also present their research proposals submitted during the application process, receiving valuable feedback from both lecturers and peers. Additionally, cross-track panels and networking events will provide opportunities for interdisciplinary insights and discussions, fostering a dynamic exchange of ideas.
Eligibility
The call is open for MA and PhD students and early-career researchers with up to 5 years of experience after completion of PhD. Applicants are invited to submit extended research proposals, CV and a motivation letter. Applications are evaluated by a panel of reviewers.
Submission information
Prepare Submission
Proposals should describe your own empirical study and must not exceed 2,500 words (approximately four single-spaced pages). References, tables, and figures are not included in the word limit. The structure of proposals should include the following elements: Purpose of the paper, Design/methodology, Findings, Research limitations, Social and Practical implications, Significance of paper, 3-4 keywords, References.
In addition to proposals applicants are to submit a CV and a motivation letter. Motivation letters must not exceed 700 words (approximately one single-spaced page).
All the papers submitted should be in English.
Submit Application
Submit the application by sending the document tocontact@cs.ecnu.edu.cn
The deadline for submission is April, 6, 2025.
Selection Participants
The Summer Institute Committee will select participants and confirm acceptance in the beginning of May
Location and Date
East China Normal University (Shanghai), 07-12 July 2025
Participation fee
International Summer School has a participation fee of $350, which includes meals during the school sessions, participant package, cultural day programme, welcome and closing buffets. Participants will cover their own travel costs and accommodation. Visa support will be provided if necessary. The Organizing committee will provide assistance with accommodation.
Should you have any questions regarding the Summer School, please contact us at: contact@cs.ecnu.edu.cn
关闭窗口