The application of multivariate data chain network in the design of innovation and entrepreneurship teaching and learning in colleges and universities

At present, although colleges and universities are actively exploring the construction of innovative and entrepreneurial teaching classrooms, they do not have the expected effect in practice. In this paper, based on the compressed perception technology, the complex data in the multivariate data chai...

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Main Authors: Yan Lijuan, Wang Yanlei
Format: Article
Language:English
Published: Sciendo 2024-01-01
Series:Applied Mathematics and Nonlinear Sciences
Subjects:
Online Access:https://doi.org/10.2478/amns-2024-0168
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author Yan Lijuan
Wang Yanlei
author_facet Yan Lijuan
Wang Yanlei
author_sort Yan Lijuan
collection DOAJ
description At present, although colleges and universities are actively exploring the construction of innovative and entrepreneurial teaching classrooms, they do not have the expected effect in practice. In this paper, based on the compressed perception technology, the complex data in the multivariate data chain network is sparsely represented, and multiple linear subsets in the data matrix are calculated by similarity. Statistical inference is used to generate the recommendation module after describing the encoding of innovation and entrepreneurship information packages in the data. Acquire the characteristics of students’ interest in innovation and entrepreneurial learning, create an interest graph module, and integrate the multi-perspective attention network to overcome the issue of recommendation bias. The analysis of teachers’ competence and students’ learning effectiveness involves the use of empirical testing methods. The results showed that among the 20 teachers, the teacher numbered 11 had a good performance with a competency of 0.8632 on entrepreneurship resources. The students’ 4 dimensions of innovation and entrepreneurship competence improved by more than 2 points, and the standard deviation was within the acceptable range. In the effect of the teaching model application, the mean value of students’ scores after improvement is more than 28. Teachers’ competence and students’ innovation and entrepreneurship ability are improved according to the model constructed in this paper.
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spelling doaj.art-9acce76f7bff47ddb2d52e02feaf9b542024-02-19T09:03:35ZengSciendoApplied Mathematics and Nonlinear Sciences2444-86562024-01-019110.2478/amns-2024-0168The application of multivariate data chain network in the design of innovation and entrepreneurship teaching and learning in colleges and universitiesYan Lijuan0Wang Yanlei11Guangzhou Sport University, Guangzhou, Guangdong, 510500, China.2Harbin Sport University, Harbin, Heilongjiang, 150006, China.At present, although colleges and universities are actively exploring the construction of innovative and entrepreneurial teaching classrooms, they do not have the expected effect in practice. In this paper, based on the compressed perception technology, the complex data in the multivariate data chain network is sparsely represented, and multiple linear subsets in the data matrix are calculated by similarity. Statistical inference is used to generate the recommendation module after describing the encoding of innovation and entrepreneurship information packages in the data. Acquire the characteristics of students’ interest in innovation and entrepreneurial learning, create an interest graph module, and integrate the multi-perspective attention network to overcome the issue of recommendation bias. The analysis of teachers’ competence and students’ learning effectiveness involves the use of empirical testing methods. The results showed that among the 20 teachers, the teacher numbered 11 had a good performance with a competency of 0.8632 on entrepreneurship resources. The students’ 4 dimensions of innovation and entrepreneurship competence improved by more than 2 points, and the standard deviation was within the acceptable range. In the effect of the teaching model application, the mean value of students’ scores after improvement is more than 28. Teachers’ competence and students’ innovation and entrepreneurship ability are improved according to the model constructed in this paper.https://doi.org/10.2478/amns-2024-0168multivariate data chain networksimilarity calculationmulti-perspective attentioninterest mapinnovative entrepreneurship teaching05c82
spellingShingle Yan Lijuan
Wang Yanlei
The application of multivariate data chain network in the design of innovation and entrepreneurship teaching and learning in colleges and universities
Applied Mathematics and Nonlinear Sciences
multivariate data chain network
similarity calculation
multi-perspective attention
interest map
innovative entrepreneurship teaching
05c82
title The application of multivariate data chain network in the design of innovation and entrepreneurship teaching and learning in colleges and universities
title_full The application of multivariate data chain network in the design of innovation and entrepreneurship teaching and learning in colleges and universities
title_fullStr The application of multivariate data chain network in the design of innovation and entrepreneurship teaching and learning in colleges and universities
title_full_unstemmed The application of multivariate data chain network in the design of innovation and entrepreneurship teaching and learning in colleges and universities
title_short The application of multivariate data chain network in the design of innovation and entrepreneurship teaching and learning in colleges and universities
title_sort application of multivariate data chain network in the design of innovation and entrepreneurship teaching and learning in colleges and universities
topic multivariate data chain network
similarity calculation
multi-perspective attention
interest map
innovative entrepreneurship teaching
05c82
url https://doi.org/10.2478/amns-2024-0168
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