AI can be useful in specific cases for formative feedback, which focuses on continuous assessment to support student growth. It can quickly grade quizzes and identify patterns in performance, allowing students to see their mistakes almost immediately. This is particularly valuable in subjects like math, science, or foreign languages, where answers can be objectively evaluated, helping reinforce foundational skills.
AI can also be effective for summative feedback such as grading a final exam if the answers are relatively straightforward, meaning that the variety in responses should be minimal. However, in more complex areas requiring critical thinking, creativity, or analysis, AI falls short. Human teachers can evaluate reasoning, creativity, and the learning process itself—elements that AI cannot fully understand. AI struggles to deliver comprehensive summative feedback that addresses aspects of personal development such as student engagement, work habits, and interpersonal skills. More specifically, AI is constrained by predefined algorithms and is unable to interpret aspects beyond academics.
Formative and summative feedback are most effective when personalized. Unlike AI, teachers can observe subtle signs of misunderstanding or frustration then provide an appropriate approach to support the student. In creative disciplines, providing feedback also necessitates an understanding of context, intent, and personal growth, areas where AI may lack awareness. AI’s responses tend to be rigid and limited to quantifiable data which misses the emotional and intellectual nuances a teacher can address.
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