دورية أكاديمية

Artificial multi-verse optimisation for predicting the effect of ideological and political theory course

التفاصيل البيبلوغرافية
العنوان: Artificial multi-verse optimisation for predicting the effect of ideological and political theory course
المؤلفون: Xingzhong Zhuang, Zhaodi Yi, Yuqing Wang, Yi Chen, Sudan Yu
المصدر: Heliyon, Vol 10, Iss 9, Pp e29830- (2024)
بيانات النشر: Elsevier, 2024.
سنة النشر: 2024
المجموعة: LCC:Science (General)
LCC:Social sciences (General)
مصطلحات موضوعية: Teaching sufficiency, Artificial multi-verse optimizer, Classification, Art ideological and political theory course, Science (General), Q1-390, Social sciences (General), H1-99
الوصف: Enhancing teaching sufficiency is crucial because low teaching efficiency has always been a widespread issue in ideological and political theory course. Evaluating data on the course is obtained from a freshmen class of 2022 using questionnaires. The data is organised and condensed for mining and analysis. Subsequently, an intelligent artificial multi-verse optimizer (AMVO) method s developed to predict the effect of ideological and political theory course. The proposed AMVO approach was tested against various cutting-edge algorithms to demonstrate its effectiveness and stability on the benchmark functions. The experimental results indicated that AMVO ranked first among the 23 test functions. Furthermore, the binary AMVO enhanced k-nearest neighbour classifier had excellent performance in the art ideological and political theory course in terms of error rate, accuracy, specificity and sensitivity. This model can predict the overall evaluation attitude of freshmen towards the course based on the dataset. In addition, we can further analyse the potential correlations between factors that enhance the intellectual and political content of the course. This model can further refine the evaluation of ideological and political courses by teachers and students in our school, thereby achieving the fundamental goal of moral cultivation.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2405-8440
العلاقة: http://www.sciencedirect.com/science/article/pii/S2405844024058614Test; https://doaj.org/toc/2405-8440Test
DOI: 10.1016/j.heliyon.2024.e29830
الوصول الحر: https://doaj.org/article/341c1b30f747427b8fdb740fba09de34Test
رقم الانضمام: edsdoj.341c1b30f747427b8fdb740fba09de34
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:24058440
DOI:10.1016/j.heliyon.2024.e29830