Title: Application of chorus teaching model for pedagogical quality assessment on software engineering skills teaching

Authors: Qidong Kang

Addresses: School of Humanities and Education, Foshan University, Foshan, 528000, China

Abstract: Currently, many software engineering students lack skills at a professional level. To address this issue, a chorus teaching quality evaluation model is constructed and improved to enhance software engineering students' understanding and mastery of relevant knowledge. An adaptive variational genetic algorithm (GA) is proposed to overcome the limitations of traditional GA with fixed variation probability. The improved GA is employed to optimise the BPNN, resulting in the AGA-BP algorithm. The entropy method (EM) is introduced to avoid subjective pedagogy in BPNN, and an EM-AGA-BP-based chorus class pedagogical quality assessment model is constructed. Research results show that the accuracy of the pedagogical quality assessment model utilising EM-AGA-BP algorithm reaches 99.84%, SSE value converges to 0.21, fitness value is 1.20, and AGA-BP model's F1 value is 0.84, all of which outperform other models significantly. The model shows desirable accuracy, thereby enabling software engineering students to gain more and improve their skills.

Keywords: pedagogical quality assessment; GA; BPNN; software engineering; entropy method; EM.

DOI: 10.1504/IJWET.2023.133624

International Journal of Web Engineering and Technology, 2023 Vol.18 No.3, pp.273 - 289

Received: 19 Aug 2022
Received in revised form: 12 Apr 2023
Accepted: 18 Jul 2023
Published online: 25 Sep 2023 *

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