When Students Resort to AI First for Homework-Challenges and Countermeasures for the Transformation of Classroom-Teaching Paradigms

DOI: https://doi.org/10.62517/jhve.202616416

Author(s)

Mengyao Zeng

Affiliation(s)

Henan Health Cadre College, Zhengzhou, China

Abstract

As artificial intelligence gains wider application, it has become commonplace for students to turn to AI first when completing homework. This practice exerts substantial pressure on conventional classroom-teaching paradigms. This paper explores practical dilemmas confronting traditional instruction in the AI-driven era and feasible pathways toward renewed teaching frameworks. By analysing behavioural patterns, driving forces and dual-faceted outcomes of students’ “AI-first” learning, this study identifies prominent bottlenecks within knowledge delivery, teacher-role positioning and assessment mechanisms. A transition framework shifting from knowledge transmission toward problem-solving is proposed, covering conceptual renewal, instructional innovation and teacher capacity-building. Findings suggest that AI will not supersede teachers, yet it reshapes existing teaching paradigms. Such transformation demands coordinated progress across four dimensions: educational philosophy, instructional strategies, assessment reform and teacher empowerment. Future research ought to address subject-specific differences, ethical concerns and long-term outcome monitoring.

Keywords

Students’ AI-First Learning Behaviour; Transformation of Classroom-Teaching Paradigms; Knowledge Transmission; Problem-Solving.

References

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