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

<p>Under the wave of big data technology development, the traditional experimental teaching methods in colleges and universities are difficult to meet the requirements of the educational objectives of the times, and teaching innovation is the focus of teaching research in many colleges and universities, which has attracted the attention of the majority of educational researchers. This paper focuses on the innovation of the construction of experimental teaching platforms of economic management in colleges and universities based on the background of big data. This paper explains the necessity of innovation of economic management experimental teaching platform, proposes the basic framework of innovation of economic management experimental teaching platform (Kube storage cloud data, front-end design, collaborative filtering algorithm), and researches and discusses the innovation mode and operation mechanism of economic management experimental teaching platform based on experimental teaching construction, based on the similarity between the specified time point and other time points The impact of the time factor on the recommendation results of experimental resources is analyzed. The results of experimental teaching resources recommendation reflect the resource recommendation ability of this platform and compare with H5 technology experimental teaching platform and content analysis method experimental platform to analyze the changing trend of MAE of teaching resources recommendation; analyze the number of concurrent connections and clicks of this platform to verify the performance of this platform. The research results show that this paper platform’s experimental teaching resources recommendation effect with MAE value of 0.51 is better than other platforms. The reason is that this paper platform’s experimental teaching resources recommendation fully takes into account the time factor and co-rated experimental teaching resources, so the accuracy of experimental teaching resources recommendation is significantly improved. This study can improve the quality and teaching efficiency of universities and train more excellent economic management talents for the country, which is of great historical significance to the development of China’s economy and education.</p>
</abstract>

Under the wave of big data technology development, the traditional experimental teaching methods in colleges and universities are difficult to meet the requirements of the educational objectives of the times, and teaching innovation is the focus of teaching research in many colleges and universities, which has attracted the attention of the majority of educational researchers. This paper focuses on the innovation of the construction of experimental teaching platforms of economic management in colleges and universities based on the background of big data. This paper explains the necessity of innovation of economic management experimental teaching platform, proposes the basic framework of innovation of economic management experimental teaching platform (Kube storage cloud data, front-end design, collaborative filtering algorithm), and researches and discusses the innovation mode and operation mechanism of economic management experimental teaching platform based on experimental teaching construction, based on the similarity between the specified time point and other time points The impact of the time factor on the recommendation results of experimental resources is analyzed. The results of experimental teaching resources recommendation reflect the resource recommendation ability of this platform and compare with H5 technology experimental teaching platform and content analysis method experimental platform to analyze the changing trend of MAE of teaching resources recommendation; analyze the number of concurrent connections and clicks of this platform to verify the performance of this platform. The research results show that this paper platform’s experimental teaching resources recommendation effect with MAE value of 0.51 is better than other platforms. The reason is that this paper platform’s experimental teaching resources recommendation fully takes into account the time factor and co-rated experimental teaching resources, so the accuracy of experimental teaching resources recommendation is significantly improved. This study can improve the quality and teaching efficiency of universities and train more excellent economic management talents for the country, which is of great historical significance to the development of China’s economy and education.

Innovative research on the construction of experimental teaching platform of economics and management in colleges and universities based on the background of big data

Applied Mathematics and Nonlinear Sciences

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

Under the wave of big data technology development, the traditional experimental teaching methods in colleges and universities are difficult to meet the...

Innovative research on the construction of experimental teaching platform of economics and management in colleges and universities based on the background of big data

Pubblicato online: 06 giu 2023

Pagine: -

Ricevuto: 31 ago 2022

Accettato: 12 dic 2022

DOI: https://doi.org/10.2478/amns.2023.1.00357

Parole chiave
Big data, University economics and management, Kube storage cloud data, Collaborative filtering algorithm, Experimental teaching platform

© 2023 Jing Li, published by Sciendo

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

Innovative research on the construction of experimental teaching platform of economics and management in colleges and universities based on the background of big data

Pubblicato online: 06 giu 2023

Pagine: -

Ricevuto: 31 ago 2022

Accettato: 12 dic 2022

DOI: https://doi.org/10.2478/amns.2023.1.00357

Parole chiaveBig data, University economics and management, Kube storage cloud data, Collaborative filtering algorithm, Experimental teaching platform

© 2023 Jing Li, published by Sciendo

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

Parole chiave
Big data, University economics and management, Kube storage cloud data, Collaborative filtering algorithm, Experimental teaching platform