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14 April 2022 Assisted diagnostic learning based on concept lattice
Xiajiong Shen, Xingchen Li, Daojun Han, Yanfeng Zhang
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Proceedings Volume 12178, International Conference on Signal Processing and Communication Technology (SPCT 2021); 121781Y (2022) https://doi.org/10.1117/12.2631918
Event: International Conference on Signal Processing and Communication Technology (SPCT 2021), 2021, Tianjin, China
Abstract
With the continuous development of education, online education is becoming more and more popular with learners because of its convenience. However, online education has the problem of insufficient interaction with students. Students still need to rely on the students themselves to judge the lack of knowledge in practice tasks, which will greatly affect the learning efficiency. In this paper, we propose a method based on formal concept analysis to analyze the knowledge that may not be mastered, and a method of intensive practice for students. First of all, establishing the formal context of student error test questions, construct the concept lattice to calculate the degree of importance of the knowledge concept that may not be mastered, judge the student’s mastery of the knowledge concept, and give feedback. Secondly, construct the concept lattice of the unpractised test set, and calculate the similarity of the concept extension set that meets the threshold, find similar topics and push them, and realize targeted training for students who have not mastered the knowledge concepts.
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Xiajiong Shen, Xingchen Li, Daojun Han, and Yanfeng Zhang "Assisted diagnostic learning based on concept lattice", Proc. SPIE 12178, International Conference on Signal Processing and Communication Technology (SPCT 2021), 121781Y (14 April 2022); https://doi.org/10.1117/12.2631918
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KEYWORDS
Data mining
Diagnostics
Binary data
Data modeling
Mining
Visualization
Data analysis
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