Title: Evaluation of interactive teaching effectiveness under social network analysis

Authors: BinBin Yan

Addresses: School of New Generation Information Technology Industry, Shandong Polytechnic, Ji'nan, 250104, China

Abstract: In order to effectively improve the accuracy and comprehensiveness of evaluation results, a method for evaluating the effectiveness of online interactive teaching under social network analysis is proposed. Firstly, collect online interactive teaching data and use Pearson correlation coefficient to calculate the correlation coefficient between the data, filtering out indicators significantly related to teaching effectiveness. Secondly, use information entropy to calculate the weight of evaluation indicators. Finally, construct a social network model, measure the node intimacy function, and identify important nodes in the social network to optimise the social network model and more accurately evaluate teaching effectiveness. The experimental results show that the highest accuracy value of the method proposed in this paper is 95%, the highest precision value is 72%, and the highest recall value is 92%, all of which are better than existing methods, fully demonstrating the effectiveness of its teaching effectiveness evaluation.

Keywords: social network; interactive teaching; effect evaluation; Pearson correlation coefficient; indicators significantly; node intimacy function.

DOI: 10.1504/IJNVO.2025.145366

International Journal of Networking and Virtual Organisations, 2025 Vol.32 No.1/2/3/4, pp.21 - 35

Received: 20 May 2024
Accepted: 27 Aug 2024
Published online: 31 Mar 2025 *

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