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<p>The rapid development of information and artificial intelligence technology has brought new opportunities for innovation and transformation in higher education, leading to innovative applications of data-driven-assisted teaching decisions. This paper analyzes the equilibrium point in predicting students’ performance using nonlinear differential equations, solves the expected value of students’ performance, and constructs a prediction model for students’ innovation and entrepreneurship performance. Student achievement data and characteristics are preprocessed to improve the accuracy of the prediction model. Based on Pearson’s coefficient, students’ innovation and entrepreneurship achievement are significantly correlated with teaching ability (P&lt;0.05). The results show that, after implementing innovation and entrepreneurship teaching based on this prediction model, the predicted achievement of students in the intervention group is significantly higher than that of students in the control group (P&lt;0.05). In the actual achievement test, the average total grade for the innovative entrepreneurship course of students in the intervention group was about 4.68-8.78 points higher than that of students in the control group. The achievement prediction model developed in this paper, along with the proposed optimization path for building innovation and entrepreneurship teaching capacity, offers significant guidance for the teaching research department in implementing effective teaching interventions and in the development of innovation and entrepreneurship education.</p>
</abstract>

The rapid development of information and artificial intelligence technology has brought new opportunities for innovation and transformation in higher education, leading to innovative applications of data-driven-assisted teaching decisions. This paper analyzes the equilibrium point in predicting students’ performance using nonlinear differential equations, solves the expected value of students’ performance, and constructs a prediction model for students’ innovation and entrepreneurship performance. Student achievement data and characteristics are preprocessed to improve the accuracy of the prediction model. Based on Pearson’s coefficient, students’ innovation and entrepreneurship achievement are significantly correlated with teaching ability (P<0.05). The results show that, after implementing innovation and entrepreneurship teaching based on this prediction model, the predicted achievement of students in the intervention group is significantly higher than that of students in the control group (P<0.05). In the actual achievement test, the average total grade for the innovative entrepreneurship course of students in the intervention group was about 4.68-8.78 points higher than that of students in the control group. The achievement prediction model developed in this paper, along with the proposed optimization path for building innovation and entrepreneurship teaching capacity, offers significant guidance for the teaching research department in implementing effective teaching interventions and in the development of innovation and entrepreneurship education.

Construction of innovation and entrepreneurship teaching capacity in colleges and universities and its optimization path based on differential equation modeling

Applied Mathematics and Nonlinear Sciences

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

The rapid development of information and artificial intelligence technology has brought new opportunities for innovation and transformation in higher...

Construction of innovation and entrepreneurship teaching capacity in colleges and universities and its optimization path based on differential equation modeling

Online veröffentlicht: 05. Aug. 2024

Seitenbereich: -

Eingereicht: 02. Apr. 2024

Akzeptiert: 19. Juni 2024

DOI: https://doi.org/10.2478/amns-2024-1929

Schlüsselwörter
Difference equation, Pearson correlation coefficient, Feature selection, Achievement prediction, Innovative entrepreneurship teaching

© 2024 Fangfang Lian et al., published by Sciendo

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

Construction of innovation and entrepreneurship teaching capacity in colleges and universities and its optimization path based on differential equation modeling

Online veröffentlicht: 05. Aug. 2024

Seitenbereich: -

Eingereicht: 02. Apr. 2024

Akzeptiert: 19. Juni 2024

DOI: https://doi.org/10.2478/amns-2024-1929

SchlüsselwörterDifference equation, Pearson correlation coefficient, Feature selection, Achievement prediction, Innovative entrepreneurship teaching

© 2024 Fangfang Lian et al., published by Sciendo

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

Schlüsselwörter
Difference equation, Pearson correlation coefficient, Feature selection, Achievement prediction, Innovative entrepreneurship teaching