Abstract
Online learning communities have changed the “silo” learning structure of traditional online learning and provided an effective support environment for wisdom sharing and collaborative knowledge building. The construction of a good online learning community has become a core issue in the field of online learning research. The study abstracts the construction of online learning community as a constrained clustering problem and proposes an intelligent construction method for online learning community based on constrained clustering. In particular, the three principles include the combination of limited freedom of choice and continuous iterative improvement, the combination of openness and standardization of the sharing platform, and the combination of public welfare and paid attributes of data resources. This paper discusses how to share valuable basic statistical data and social survey data in the field of college students’ ideological and political education (IPE) and make them public to the whole society by building a data resource sharing platform, so as to improve the utilization of data on the one hand and support comparative research topics in related fields through statistical analysis among survey data on the other hand. The experimental results show that the proportion of low-level posts (KC1 and KC2) of the two groups of students is relatively high (79.4% and 76.5%, respectively), indicating that the students in the learning community have carried out a lot of knowledge sharing and discussed and compared them to a certain extent. The proportion of high-level posts by students in both groups is very small (20.8% and 23.5%, respectively), but the number of high-level (KC3, KC4) posts by the students in the experimental group is significantly higher than that of the students in the control group, indicating that the students in the experimental group have good exchanges and discussions have resulted in meaningful negotiation and testing on some issues.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
