Accuracy and reliability of large language models in assessing learning outcomes achievement across cognitive domains
Swapna Haresh Teckwani, Amanda Huee‐Ping Wong, W. A. N. V. Luke, Ivan Cherh Chiet Low
Abstract
The advent of large language models (LLMs) such as ChatGPT and Gemini has offered new learning and assessment opportunities to integrate artificial intelligence (AI) with education. This study evaluated the accuracy of LLMs in assessing an assignment from a course on sports physiology. Concordance and correlation between human graders and LLMs were mostly moderate to poor. The findings suggest AI's potential to complement human expertise in educational assessment alongside the need for adaptive learning by educators.
Topics & Concepts
Reliability (semiconductor)CognitionPsychologyCognitive psychologyComputer scienceNeurosciencePower (physics)Quantum mechanicsPhysicsIntelligent Tutoring Systems and Adaptive LearningOnline Learning and AnalyticsTopic Modeling