Recently, professor Liu Qingtang 's team has made a series of research results in the field of learning analysis, and many papers have been published in international journals. The article Investigating the relationships among teachers’ motivational beliefs, motivational regulation, and their learning engagement in online professional learning communities was published in Computers & Education, a well-known journal in the field of Education technology (SSCI, 2017 IF=4.538), vol. 134, 2019.The first author is Dr. Si Zhang, who is under the supervision of professor Liu Qingtang and co-corresponding author with professor Liu. This article addresses：https://www.sciencedirect.com/science/article/pii/S0360131519300429
Based on the "project to improve the application ability of information technology for primary and secondary school teachers" jointly implemented by professor Liu Qingtang and the Open University of China, this paper carries out teacher training activities on the network research platform, and discusses the influence of motivational beliefs and motivational regulation on the learning input of in-service teachers. In this paper, a moderated mediation model is established and 520 trainee teachers are selected as research objects by stratified sampling method. In terms of research methods, this paper uses the questionnaire method to collect the motivational beliefs and motivational regulation data of in-service teachers, and creatively uses the learning behavior data as the reference index of learning input. The established research model is shown in figure 1.
figure 1- research model
The results show that the perceived task value of in-service teachers is closely related to their learning input in the network research community. On the path that perceived task value affects learning engagement, motivation regulation of in-service teachers plays a part of intermediary role. In the path of "perceived task value → motivational regulation → learning engagement", the self-efficacy of in-service teachers affects the first half of the path. Finally, the paper puts forward some suggestions on how to improve the learning input of network teachers.
