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

<p>This paper is oriented to the integrated learning bill for college teachers and integrates blockchain technology to construct a high-security and credibility assessment system for college teachers’ professional competence development. Through similarity calculation and hierarchical clustering to form a dataset related to teachers’ professional competence, the TOPSIS-gray correlation analysis algorithm is used to assess the development of teachers’ professional competence tendencies. The teacher information is then transformed to finally form an information profile panel that can comprehensively characterize the development of college teachers’ professional competence, which is stored in the blockchain in the form of a learning bill. The single feature clustering results indicate that the majority of teachers are either good or above in every professional development evaluation feature, with excellent being above 30%. In the overall clustering, only 17.91% were labeled as excellent. In the teacher professional development assessment indicators, the reaction layer (34.9) and learning layer (33.6) have a greater impact on the professional development of teachers in higher education. The F-values of teachers in different subject areas in the overall test of teacher professional development did not reach a significant level (2.11, 0.24, 0.20, and 0.42, respectively). In the correlation test, blockchain technology was significantly and positively correlated with the quality of teachers’ professional development (p&lt;0.05). The validity of the professional development assessment system for college teachers that incorporates blockchain technology is confirmed by this study.</p>
</abstract>

This paper is oriented to the integrated learning bill for college teachers and integrates blockchain technology to construct a high-security and credibility assessment system for college teachers’ professional competence development. Through similarity calculation and hierarchical clustering to form a dataset related to teachers’ professional competence, the TOPSIS-gray correlation analysis algorithm is used to assess the development of teachers’ professional competence tendencies. The teacher information is then transformed to finally form an information profile panel that can comprehensively characterize the development of college teachers’ professional competence, which is stored in the blockchain in the form of a learning bill. The single feature clustering results indicate that the majority of teachers are either good or above in every professional development evaluation feature, with excellent being above 30%. In the overall clustering, only 17.91% were labeled as excellent. In the teacher professional development assessment indicators, the reaction layer (34.9) and learning layer (33.6) have a greater impact on the professional development of teachers in higher education. The F-values of teachers in different subject areas in the overall test of teacher professional development did not reach a significant level (2.11, 0.24, 0.20, and 0.42, respectively). In the correlation test, blockchain technology was significantly and positively correlated with the quality of teachers’ professional development (p<0.05). The validity of the professional development assessment system for college teachers that incorporates blockchain technology is confirmed by this study.

A Study of Strategies for Integrating Faculty Professional Development and Blockchain Technology in Higher Education

Applied Mathematics and Nonlinear Sciences

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

This paper is oriented to the integrated learning bill for college teachers and integrates blockchain technology to construct a high-security and credibility...

A Study of Strategies for Integrating Faculty Professional Development and Blockchain Technology in Higher Education

Data publikacji: 02 lip 2024

Zakres stron: -

Otrzymano: 29 lut 2024

Przyjęty: 27 maj 2024

DOI: https://doi.org/10.2478/amns-2024-1563

Słowa kluczowe
Blockchain technology, Hierarchical clustering, Gray correlation, Learning bill, Assessment system

© 2024 Xianglong Meng., published by Sciendo

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

A Study of Strategies for Integrating Faculty Professional Development and Blockchain Technology in Higher Education

Data publikacji: 02 lip 2024

Zakres stron: -

Otrzymano: 29 lut 2024

Przyjęty: 27 maj 2024

DOI: https://doi.org/10.2478/amns-2024-1563

Słowa kluczoweBlockchain technology, Hierarchical clustering, Gray correlation, Learning bill, Assessment system

© 2024 Xianglong Meng., published by Sciendo

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

Słowa kluczowe
Blockchain technology, Hierarchical clustering, Gray correlation, Learning bill, Assessment system