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<p>Classroom teaching mode is an important factor affecting classroom quality and students’ performance. The use of science and technology combined with advanced teaching concepts to rationalize classroom teaching innovation and change has become a research hotspot in the field of education. In this paper, we use the BOPPPS teaching mode on the basis of big data technology to promote teaching innovation in the existing classroom teaching chemical principles. Using a questionnaire survey to study the teaching status of chemical principles in a city university, it is found that the current chemical principle classroom teaching is generally characterized by the problems of solidified teaching mode design, single teaching evaluation method, random design of teaching objectives, etc. The BOPPPS model is applied to the teaching of chemical principles at a city university. The BOPPPS model is applied to the teaching practice of chemical principles in a university, and the student’s classroom performance before and after the change of teaching mode shows obvious differences. After the experiment, 64.17% of the students expressed hope that the BOPPPS teaching model could be promoted in other disciplines. Cluster analysis of students’ performance before and after the experiment using an optimized K-means clustering algorithm shows that the performance of the seven students extracted from the experiment significant improvement after the experiment. The use of the BOPPPS teaching mode makes the students’ score range increase from 60-70 before the test to 80-90 after the test.</p>
</abstract>

Classroom teaching mode is an important factor affecting classroom quality and students’ performance. The use of science and technology combined with advanced teaching concepts to rationalize classroom teaching innovation and change has become a research hotspot in the field of education. In this paper, we use the BOPPPS teaching mode on the basis of big data technology to promote teaching innovation in the existing classroom teaching chemical principles. Using a questionnaire survey to study the teaching status of chemical principles in a city university, it is found that the current chemical principle classroom teaching is generally characterized by the problems of solidified teaching mode design, single teaching evaluation method, random design of teaching objectives, etc. The BOPPPS model is applied to the teaching of chemical principles at a city university. The BOPPPS model is applied to the teaching practice of chemical principles in a university, and the student’s classroom performance before and after the change of teaching mode shows obvious differences. After the experiment, 64.17% of the students expressed hope that the BOPPPS teaching model could be promoted in other disciplines. Cluster analysis of students’ performance before and after the experiment using an optimized K-means clustering algorithm shows that the performance of the seven students extracted from the experiment significant improvement after the experiment. The use of the BOPPPS teaching mode makes the students’ score range increase from 60-70 before the test to 80-90 after the test.

Innovation of classroom teaching of chemical principles based on big data in BOPPPS teaching model

Applied Mathematics and Nonlinear Sciences

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

Classroom teaching mode is an important factor affecting classroom quality and students’ performance. The use of science and technology combined with advanced...

Innovation of classroom teaching of chemical principles based on big data in BOPPPS teaching model

Publicado en línea: 05 ago 2024

Páginas: -

Recibido: 31 mar 2024

Aceptado: 20 jun 2024

DOI: https://doi.org/10.2478/amns-2024-2101

Palabras clave
BOPPPS model, Clustering algorithm, Teaching innovation, Questionnaire survey

© 2024 Guiyun Yi et al., published by Sciendo

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

Innovation of classroom teaching of chemical principles based on big data in BOPPPS teaching model

Publicado en línea: 05 ago 2024

Páginas: -

Recibido: 31 mar 2024

Aceptado: 20 jun 2024

DOI: https://doi.org/10.2478/amns-2024-2101

Palabras claveBOPPPS model, Clustering algorithm, Teaching innovation, Questionnaire survey

© 2024 Guiyun Yi et al., published by Sciendo

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

Palabras clave
BOPPPS model, Clustering algorithm, Teaching innovation, Questionnaire survey