【作 者】：
张 思， 邓 露， 邓 伟， 夏 丹， 上超望
【关 键 词 】：
网络研修社区； 对话反思； 认知网络分析； 教师工作坊； TPACK
【栏 目】：
网络教育
【中文摘要】：
在网络研修社区的对话反思数据中，蕴含着教师对于整合技术的学科教学知识（TPACK）的丰富、客观和协同的认知。依据TPACK框架，对网络研修社区中教师的对话反思数据进行结构化编码，并应用认知网络分析法（ENA）探索教师的认知框架模式，可以得到教师TPACK特征的最自然的评判。采集网络研修社区“齐心协力工作坊”中的教师对话数据，依据TPACK框架对数据进行编码，探索了教师认知行为的分布特征。再采用认知网络分析，探索了高低分组、不同年龄组、评论和回帖组教师的认知网络结构特征。研究发现教师对话的知识类型主要是学科教学法知识和一般教学法知识。高分组教师的PK-PCK、PK-TPACK、CK-PCK连线系数较高，TPACK更加灵活，低分组教师则更关注技术知识与学科教学法知识的结合。低年龄组教师的PK-PCK、PCK-TPACK连线系数较高，而高年龄组教师的PK-TPACK、CK-PCK、TPK-PCK 连线系数较高。回帖组教师的认知网络中各元素的连线系数均较高。认知网络分析法为大数据支持的学习分析与评价提供了一种新范式。
【英文摘要】：
The data of dialogue and reflection in the network training community contains teachers' rich, objective and collaborative cognition of TPACK. Based on the TPACK framework, the data of teachers' dialogue and reflection in network training community are structured and encoded, and Epistemic Network Analysis (ENA) is applied to explore the cognitive framework model of teachers, so as to obtain the most natural evaluation of the characteristics of teachers' TPACK. The study collects the data of teachers' dialogue in network training community "Faculty Workshop for Working Together ", and then those data are coded according to the TPACK framework so as to explore the distribution tendency of teachers' cognitive behaviors. Furthermore, the ENA is used to explore the structural characteristics of teachers' cognitive network in high and low groups, different age groups, post and reply groups. It is found that the knowledge types of teacher dialogue are mainly subject pedagogical knowledge and general pedagogical knowledge. Teachers in higher-score group have higher connection coefficients of PK-PCK, PK-TPACK and CK-PCK , and their TPACK are more flexible, while teachers in lower-score group pay more attention to the integration of technical knowledge and content-specific pedagogical knowledge. Teachers in lower-age group have higher connection coefficients of PK-PCK and PCK-TPACK, while connection coefficients of PK-TPACK、CK-PCK、TPK-PCK of teachers in higher-age group are higher. The connection coefficient of each element in the cognitive network of teachers in the reply group is higher. ENA provides a new paradigm for learning analytics and evaluation supported by big data.