The Impact of GenAI on Chinese HSS Students' Academic Development

This large-scale survey of humanities and social sciences (HSS) students in China examines how Generative AI reshapes academic development across four dimensions: usage patterns, effects on learning processes and performance, challenges, and preferred curricular integration approaches. Over half of respondents reported enhanced learning motivation, independent thinking, and creativity, though a substantial minority saw little change or decline. A larger majority reported academic performance gains, though the authors caution these may partly reflect limitations in conventional Assessment practices.

Key Findings

Usage patterns: HSS students use GenAI primarily for writing assistance, information synthesis, and idea generation — tasks that align closely with HSS learning outcomes expressed through written and interpretive forms. Variations emerged by discipline and duration of GenAI experience, with modest gender differences.

Learning processes: More than half of students perceived enhanced motivation, independent thinking, and creativity. However, a substantial minority reported little change or even decline, suggesting that Personalized Learning approaches to GenAI integration may be necessary.

Academic performance: A notably larger majority reported academic gains, though these may partly reflect assessment practices ill-equipped to distinguish AI-assisted from independent work — a challenge related to Academic Integrity.

Challenges: Limited accuracy and Over Reliance emerged as the most pressing concerns. While an overwhelming majority valued ethical considerations, only slightly more than half were satisfied with Privacy protections. Students favored partial or optional GenAI integration into curricula.

Implications

The study highlights the need for Higher Ed institutions to develop nuanced policies that balance GenAI's potential benefits against risks of over-reliance and assessment validity. Disciplinary differences suggest that Faculty Development programs should tailor guidance to specific fields rather than adopting one-size-fits-all approaches.

Connected Concepts

Generative AI

Assessment

Personalized Learning

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Citation

Fan, L., & Liu, F. (2026). The impact of generative artificial intelligence on academic development of Chinese students in humanities and social sciences. arXiv:2606.24104.