Research On Interactive Behavior Of Popurlar Science Learning Based On Social Media

With the overall goal of improving national scientific quality,science popularization plays an important role in scientific and technological progress and personnel training.With the development of the Internet,social media has a profound impact on people’s learning style because of its open learning environment,diverse learning objects and independent learning methods.People pay more attention to promote the development of science popularization by using social media.The research on science popularization learning based on social media is mostly limited to the aspects of expanding the breadth of science popularization,such as science popularization communication influence and science popularization operation,and there is a lack of research on the process of science popularization learning and exploring the depth of science popularization.Interaction is the core and key of science popularization learning.Based on the theory of connectionism theory and Bandura’s reciprocal determinism,this paper studies the learners’ science popularization learning process from the perspective of interactive behavior.Firstly,using the literature research method,this paper combs the research status of science popularization learning based on social media.Define the core concepts such as science popularization,social media and interactive behavior.Determine the science and technology museum as the main body and Bilibili as the representative of social media,and the social network analysis is studied in detail.Referring to the Connectivist Interaction and Engagement framework based on cognitive participation(CIE framework),this paper constructs a science popularization learning interactive behavior coding framework based on social media.Secondly,using the social network analysis method,based on the relationship between learners’ reply and being replied in the comment data,this paper constructs an interpersonal interaction network based on social media science popularization learning.After analysis,it is found that the interpersonal interaction network of popular science learning is compact and has a low degree of connectivity,showing a "petal shaped" network structure.At the same time,it is found that learners can become core learners through active interaction and publishing high-quality content.There is a phenomenon of unequal interaction in the network,but the network still has development potential.Then,the coding framework is applied to encode the learners’ comment text data,and 10 interaction behavior sequences are obtained.Based on this,the lag sequence analysis is carried out to analyze the interaction structure of path finding interaction level and meaning interaction level,and the transformation relationship between interaction levels is analyzed.It is found that learners are easily influenced by their predecessors in some interactive ways and produce the same interactive behavior;There is a phenomenon of positive emotion aggregation,and learners’ scientific interest attitude and scientific spirit are cultivated;Lack of collective discussion in the learning environment,and learners’ cognitive participation is low;The transformation from low-level interaction to highlevel interaction is gradual,and the transformation from high-level interaction to low-level interaction is gradual and leapfrog.Finally,according to the research conclusion,suggestions are put forward on designing social media popular science content combining the resources in the museum and social hot spots,using positive emotion to improve learners’ scientific cognition and strengthening all-round interaction.