This analysis compares the performance and feedback accuracy of Gpt-4.0 and Claude-4 in AI-generated educational tools.
This report provides an in-depth comparative analysis of AI-generated portfolio feedback delivered through two leading Large Language Model platforms (LLM): Gpt4.o OpenAI and Claude-sonnet-4 (Anthropic) via Amazon Bedrock. The feedback was analyzed in two distinct stages: preview feedback, which serves as a safety and verification layer for examiners/administrators, and portfolio feedback, which is delivered directly to the students. These systems are integral to Qpercom’s digital assessment tools and support high-stakes clinical assessments such as Objective Structured Clinical Examinations (OSCEs), high-stake recruitment using Multiple Mini Interviews (MMIs), and Video Interviewing and Digital Scoring (VIDS). This evaluation examines how accurately each model reflects students’ actual high-, mid-, and underperformance and whether its feedback provides safe, constructive, and educationally valuable input.
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Kropmans et al. (2025) studied this question.
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