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Investigation of Generative AI Utilization in Schools

A research team led by Professor Tetsu Nakagawa from the Graduate School of Social Design, part of the Advanced Education Institute in Tokyo, and Professor Norihisa Sakakibara from Joetsu University of Education, has conducted a comprehensive survey to examine the current use of generative AI in elementary and junior high schools in Japan. This pivotal study sheds light on the ‘Browser AI Summary’ tool, revealing essential details about its integration into the educational framework, teaching methods, and the impact on student learning. The findings will be published in the February 2026 issue of the "Monthly Advanced Education," set to be released on December 27, 2025.

Purpose of the Study

The primary objective of this investigation is to explore how students in elementary and junior high schools are utilizing generative AI tools under the GIGA School initiative, which facilitates the integration of information devices. The study particularly focuses on the Browser AI Summary, which automatically presents summarized search results, aiming to document the usage, instructional strategies, and learning effects associated with this technology in education.

Although generative AI has been increasingly seen as a supportive learning tool, there are valid concerns regarding misinformation and a decline in critical thinking skills. The research seeks to understand how educators perceive the utilization of generative AI and its influence on student learning, while also serving as a basis for developing educational approaches that prevent 'shallow learning’.

Survey Overview

• - Investigative Period: Late October to late November 2025
• - Target Areas: Multiple jurisdictions in Kanto, Kinki, and Hokuriku regions (elementary, middle, and compulsory education schools)
• - Response Count: 1,090 teachers in total
• - Methodology: Google Forms with a four-option response plus ‘unknown’ and open comment options (noting that responses were self-reported and not based on access logs).

Main Survey Results

Investigative Learning Data

• - Usage of browser search for inquiry learning: 71.5% of teachers (779 individuals) responded positively.
• - Recommendations for Browser AI Summary: 10.1% (85 teachers) recommended it while 84.3% (657 teachers) did not.
• - Autonomous student use without teacher guidance: 38.5% (300 teachers) indicated that students used it independently, with elementary schools at 33.0% and middle schools at 51.3%.
• - Direct adoption of summarized content by students: 38.6% (301 teachers) observed this behavior.

Dialogical Generative AI Data

• - Recommendations for generative AI summaries: 8.7% (69) endorsed this, while 88.6% (690) opposed it.
• - Independent use by students: 18.2% (142 teachers) reported this, with 11.3% in elementary and 34.7% in middle schools.
• - Copying summarized content: 21.6% (168 teachers) noted this tendency among students.
• - Notably, the rate of autonomous use of Browser AI Summaries was approximately double that of dialogical generative AI.

Discussion and Challenges

• - Many educators express reservations about generative AI use, yet instances of 'shadow use'—where students employ these tools outside of teacher guidance—are becoming prevalent, indicating a significant disconnect between policies and actual classroom practices.
• - The Browser AI Summary tool appears at the top of search results, leading students to often accept it unquestioningly as definitive answers, thereby bypassing critical analysis and synthesis—an alarming trend.
• - Particularly in middle schools, where student autonomy and pressure to submit work converge, there is a heightened risk of passive acceptance of information, posing challenges to deeper learning.

Recommendations for Future Learning Strategies

The research team proposes the following strategies to foster 'deeper learning' while still incorporating generative AI into educational methodologies:
1. Record the processes leading back to primary information sources from AI summaries.
2. Incorporate referenced and comparative perspectives into submitted work.
3. Cultivate an attitude that regards AI outputs as 'one of the references' rather than as concluding statements.

Detailed Findings Release

The complete findings of this research will be featured in the upcoming February 2026 issue of the "Monthly Advanced Education." It is anticipated that this report will serve as an invaluable resource for educators and policymakers as they contemplate the future of AI in learning.

About the Graduate School of Social Design

Established in April 2017 in Takadanobaba, Tokyo, the Graduate School of Social Design focuses on training professionals capable of planning and implementing innovative communication strategies. Students earn a master's degree in Communication Design upon completion. The institution has expanded its offerings, now including a new department dedicated to societal development set to open in April 2024.

For further details about various programs, the latest updates are available on the university's website.