| Abstrakt: |
With the changing trends in ideological and political teaching methodologies in colleges and higher institutes, the previous political and ideological teaching mode of blackboard and power point-enabled face-to-face instruction is in danger of being phased out. As a result, college counselors' work in political and ideological education is an essential component of college-level instruction. The reform's focal points, i.e., integral platforms, are wireless communication and big data video streaming. These platforms provide a sense of situation, immersion, and involvement that traditional ideological and political education lacks. Using big data concepts for wireless-enabled video streaming, this paper assesses the effectiveness of college counselors' ideological and moral instructions. We provide data-driven insights to improve the efficacy of education by analyzing a large quantity of video data, which include teaching content, student behavior, and interaction status. We present a big data-enabled evaluation approach that blends ideological and moral education aspects, employing least squares fitting analysis for indicator distribution control, fuzzy support vector machine and fuzzy clustering models for assessment. The study conducts quantitative analysis, dynamic monitoring, and feature extraction of efficacy indicators by assessing college counselors' advice based on parameters and benefits. The experiment shows that the proposed method has a high degree of confidence in evaluating the effectiveness of college counselors' ideological and moral education and can dynamically adjust their approach to improve data interaction ability and analysis. [ABSTRACT FROM AUTHOR] |
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