在线教师培训中的群体社会认知网络特征分析

Analysis of Social and Epistemic Network Signatures in Online Teacher Training

在线教师培训对教师专业发展具有重要意义。深入动态地分析教师学习者在线培训过程有助于提升教师参训效果,同时也充满挑战。社会认知网络特征分析方法综合运用了社会网络分析与认知网络分析的优势,能够对学习过程进行动态表征和分析。本研究采用社会认知网络特征分析方法分析教师在线评论和交互文本,探究了不同成绩教师学习者的社会认知网络特征及演变情况。研究发现,高分组与低分组的教师学习者的社会交互情况差异显著,社会网络特征的演变情况不同;认知主题存在差异,认知网络特征演变的趋势相似而程度不同;社会交互与认知演变存在内部一致性,但受个人特征与教学组织影响显著。对在线教师培训中的教师学习者群体进行社会认知网络特征分析,有助于精准把控教师学习者的学习情况,从而促进有效反馈和提升培训质量。

Online teacher training is an important part of teacher professional development. Dynamic and procedural analysis of the learning process of teacher learners can help improve the effect of online teacher training, but is also full of challenges. Social and Epistemic Network Signatures(SENS) analysis method comprehensively considers the advantages of social network analysis and epistemic network analysis, and can dynamically represent and analyze the learning process. This study adopted the SENS analysis method to deeply analyze teacher learners’ online interactive texts, and explored the situation and migration of social and epistemic signatures of teacher learners with different grades(high and low group). The results showed that there were significant differences in social interaction between high and low group, and the migration of social network signatures was different. There were differences in epistemic topics and similar trends but different degrees of epistemic network signature migration. There was internal consistency between the migration of social and epistemic network signatures, but it was obviously influenced by individual characteristics and teaching organization. The use of the SENS method is helpful to accurately control the learning of teacher learners, so as to promote effective feedback and improve the quality of online teacher training.