<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>According to the internal and external constraints of higher education model innovation and development as well as the innovation power, this paper proposes the higher education model development path based on the quadratic planning algorithm and neural network. Using the establishment of a quadratic planning algorithm and neural network model, the EM-AGA-BP algorithm is selected to construct the quality prediction model of higher education model innovation path of deep neural network based on the establishment of the quality evaluation system. The proposed algorithmic path is analyzed for development prediction, and the algorithm is recommended for 2020-level learners, which are classified into different types based on their learning and the relationship between the achievement of course objectives and the similarity of educational paths is explored separately for different types of learners. In type 4 learners, in addition to the similarity of 20%-40%, the total course goal attainment decreases by 0.0085. For the same type of learners, the more similar the educational path is to the recommended path, the better the total course goal attainment is.</p>
</abstract>

According to the internal and external constraints of higher education model innovation and development as well as the innovation power, this paper proposes the higher education model development path based on the quadratic planning algorithm and neural network. Using the establishment of a quadratic planning algorithm and neural network model, the EM-AGA-BP algorithm is selected to construct the quality prediction model of higher education model innovation path of deep neural network based on the establishment of the quality evaluation system. The proposed algorithmic path is analyzed for development prediction, and the algorithm is recommended for 2020-level learners, which are classified into different types based on their learning and the relationship between the achievement of course objectives and the similarity of educational paths is explored separately for different types of learners. In type 4 learners, in addition to the similarity of 20%-40%, the total course goal attainment decreases by 0.0085. For the same type of learners, the more similar the educational path is to the recommended path, the better the total course goal attainment is.

Research on the development path of higher education model innovation based on quadratic planning algorithm

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

According to the internal and external constraints of higher education model innovation and development as well as the innovation power, this paper proposes...

Research on the development path of higher education model innovation based on quadratic planning algorithm

Publicado en línea: 11 nov 2023

Páginas: -

Recibido: 28 dic 2022

Aceptado: 22 may 2023

DOI: https://doi.org/10.2478/amns.2023.2.01100

Palabras clave
Quadratic programming algorithm, Neural network, EM-AGA-BP algorithm, Predictive modeling, Educational model innovation

© 2023 Rongjuan Chen, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on the development path of higher education model innovation based on quadratic planning algorithm

Publicado en línea: 11 nov 2023

Páginas: -

Recibido: 28 dic 2022

Aceptado: 22 may 2023

DOI: https://doi.org/10.2478/amns.2023.2.01100

Palabras claveQuadratic programming algorithm, Neural network, EM-AGA-BP algorithm, Predictive modeling, Educational model innovation

© 2023 Rongjuan Chen, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Palabras clave
Quadratic programming algorithm, Neural network, EM-AGA-BP algorithm, Predictive modeling, Educational model innovation