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Comparing AI-Generated Preview and Portfolio Feedback: Gpt 4.o vs. Claude 4

Author

Listed:
  • Thomas Kropmans

    (Qpercom Ltd Platform 94 Mervue Business Park Galway, Ireland)

  • Oleh Bilokrylyi

    (Qpercom Ltd Platform 94 Mervue Business Park Galway, Ireland)

  • Dmytro Predchyshyn

    (InventorSoft, Ukraine)

  • David Cunningham

    (Qpercom Ltd Platform 94 Mervue Business Park Galway, Ireland)

  • Edward Melvin

    (Marino_Software, DCU Alpha, Dublin)

  • Gabia Neverauskaité

    (Qpercom Ltd Platform 94 Mervue Business Park Galway, Ireland)

Abstract

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.

Suggested Citation

Handle: RePEc:epw:ejai00:v:4:y:2025:i:5:id:1082
DOI: 10.24018/ejai.2025.4.5.82
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