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A local think tank has found that Hong Kong primary and secondary schools are struggling with isolated "data silos" due to the fragmented use of multiple artificial intelligence tools without unified standards, making it difficult to evaluate teaching effectiveness.
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The Hong Kong Future Economy Institute surveyed more than 80 schools and analyzed over 200,000 student learning records covering areas such as essay grading and language learning.
The findings show that while many schools utilize a wide range of AI tools—with some adopting more than a dozen different platforms—very few have established data-tracking or analytics mechanisms to evaluate the effectiveness of these technologies or to guide future teaching strategies.
As a result, student learning data remains scattered. This fragmentation makes it difficult for teachers, parents, and school administrators to gain a comprehensive picture of student progress or assess the real impact of AI on education.
To address these challenges, the think tank recommended that schools develop school-based data governance frameworks and enhance teachers’ data literacy.
It urged school sponsoring bodies and the government to collaborate on standard contracts and common data governance requirements to unify rules on data use and information security.
Additionally, the institute called for a cross-sector AI product evaluation and certification system to help establish industry-wide standards.
