高中数学教师MKT的比较研究:基于认知网络的分析OA

Teachers'knowledge structure is a key factor influencing teaching quality and students'learning outcomes.This study employs Epistemic Network Analysis to code the MKT of eight high school mathematics teachers and constructs epistemic network models to compare differences in knowledge structures across different groups of teachers and lesson types.The findings show that:(1)within the overall cognitive network,SCK occupies a central position and forms a stable structure with CCK,KCS,and KCT,while HCK and KCC are relatively peripheral;(2)expert teachers place greater emphasis on PCK,exhibiting more dense and complex cognitive network structures,whereas novice teachers rely more heavily on SMK,resulting in relatively simpler structures;(3)in new lesson delivery,neither group of teachers forms a stable pattern,but expert teachers demonstrate a higher degree of knowledge integration;in exercise lessons,differences between groups are not significant,while expert teachers show smaller within-group variation and greater instructional stability.The study demonstrates that Epistemic Network Analysis is effective in revealing structural differences in teachers'MKT at different stages of development and provides evidence and implications for teacher professional development and the improvement of mathematics classroom quality.