Meng Chen, Mohammad Mohammadi, Siros Izadpanah
Language learning through music on the academic achievement, creative thinking, and self-esteem of the English as a foreign language (EFL) learners
Acta psychologica
background artificial intelligence ai evolving medical education system chatgpt google bard microsoft bing aibased models solve problems medical education however applicability ai create reasoningbased multiplechoice questions mcqs field medical physiology yet explored objective aimed assess compare applicability chatgpt bard bing generating reasoningbased mcqs mbbs bachelor medicine bachelor surgery undergraduate students subject physiology methods national medical commission india developed 11module physiology curriculum various competencies two physiologists independently chose competency module third physiologist prompted three ais generate five mcqs chosen competency two physiologists provided competencies rated mcqs generated ais scale 03 validity difficulty reasoning ability required answer analyzed average two scores using kruskalwallis test compare distribution across total modulewise responses followed posthoc test pairwise comparisons used cohens kappa assess agreement scores two raters expressed data median interquartile range determined statistical significance pvalue 005 results chatgpt bard generated 110 mcqs chosen competencies however bing provided 100 mcqs failed generate two competencies validity mcqs rated 3 33 chatgpt 3 153 bard 3 153 bing showing significant difference p0001 among models difficulty mcqs rated 1 01 chatgpt 1 12 bard 1 12 bing significant difference p0006 required reasoning ability answer mcqs rated 1 12 chatgpt 1 12 bard 1 12 bing significant difference p0235 k 08 three parameters across three ai models conclusion ai still needs evolve generate reasoningbased mcqs medical physiology chatgpt bard bing showed certain limitations bing generated significantly least valid mcqs chatgpt generated significantly least difficult mcqs