大语言模型能否胜任学校教学?OA

Whether large language models(LLMs)can teach in schools is a pressing practical question in the advancement of educational intelligence.Focusing on LLMs'potential to meet teacher competency requirements,this study first uses GPT-4's perfor-mance on U.S.school assessments across educational levels to identify the knowledge and skills it can plausibly perform in school teaching.These skills are then mapped onto a full-sample teacher job-skill lexicon constructed from U.S.recruitment big data,in or-der to evaluate GPT-4's teaching-capability potential.The results show that skills classified as GPT-4-advantaged achieve an overall coverage rate of 25.2%of the teacher skill lexicon,and the covered skills are disproportionately concentrated in tasks with higher cod-ifiability.In contrast,educational skills that GPT-4 is less able to perform exhibit markedly lower codifiability.Further regression analyses reveal heterogeneous patterns in skill coverage along three dimensions.First,at the subject level,teacher job skills in STEM fields are more likely to be covered by GPT-4,although the coverage gap between STEM and non-STEM teachers is narrowing.Sec-ond,at the educational stage level,higher educational stages are associated with greater coverage;the coverage rates rank from highest to lowest as higher education(including graduate level),high school,middle school,elementary school,and preschool/early childhood.Third,at the task type,broader generalist roles—those requiring a larger number of skills—are more readily covered,whereas more specialized roles—those requiring deeper mastery of specific skills—are less likely to be covered.Overall,the findings suggest that LLMs'aggregate coverage potential delineates a spectrum of teacher skills with codifiability as a shifting boundary.GPT-4's blind spots in expertise-intensive tasks and complex educational practice point to directions for future teacher professional development.Meanwhile,the temporal patterns implied by LLM coverage across educational stages may offer insights for re-examining and adjust-ing the rhythms of schooling.