Future mathematics teachers’ perception of artificial intelligence integration in assessment in a digital technologies course - Borbón-Alpízar, Alexander (2026)
The integration of generative Artificial Intelligence (AI) in higher education requires understanding student perceptions. This study analyzed the views of pre-service mathematics teachers (N=14) on using ChatGPT as an assessment tool in a university course. Through a mixed-methods approach, their perceptions of the quality of feedback and the validity of AI-generated grades were explored. The findings reveal a fundamental dichotomy: students positively value AI as a formative feedback tool, recognizing its utility for improvement. However, they express significant distrust in its role as a summative assessment agent, perceiving it as incapable of making holistic judgments. The analysis suggests that students view the instructor and AI as agents with complementary strengths, outlining an “augmented assessment” model. The opacity of the AI’s process (the “black box” problem) was identified as a critical barrier. Although a majority (57.1%) prefers human grading, a significant minority (42.9%) leans towards AI, valuing its immediacy and objectivity. It is concluded that the most promising role for AI in assessment is not that of an autonomous judge, but of an assessment copilot that enhances the instructor’s capabilities.