Research Article
Design of Mobile Education Evaluation System for College Students Based on Digital Badge Technology - Taking Legal Education as an Example
@INPROCEEDINGS{10.1007/978-3-031-50552-2_2, author={Yu Zhao and Liang Zhang}, title={Design of Mobile Education Evaluation System for College Students Based on Digital Badge Technology - Taking Legal Education as an Example}, proceedings={Advanced Hybrid Information Processing. 7th EAI International Conference, ADHIP 2023, Harbin, China, September 22-24, 2023, Proceedings, Part IV}, proceedings_a={ADHIP PART 4}, year={2024}, month={3}, keywords={Digital Badge Technology Educational Evaluation Digital Terminal Microprocessor Principal Component Analysis Random Number Badge Vector Cumulative Eigenvector}, doi={10.1007/978-3-031-50552-2_2} }- Yu Zhao
Liang Zhang
Year: 2024
Design of Mobile Education Evaluation System for College Students Based on Digital Badge Technology - Taking Legal Education as an Example
ADHIP PART 4
Springer
DOI: 10.1007/978-3-031-50552-2_2
Abstract
In the process of education evaluation, a lot of analysis and calculation are needed for different parameters. Once the original data is abnormal, the reliability of the evaluation results will be greatly reduced. Therefore, a design of mobile education evaluation system for college students based on digital badge technology is proposed - taking legal education as an example. In hardware design, FK-SK7-M2 is used as the storage device of the system to meet the data management requirements of the system, and STC12C5A60S2 is used as the digital terminal microprocessor of the system to meet the operation requirements of the evaluation system. In the aspect of software design, the digital badges with visual images are designed and classified according to the educational objectives. In the stage of education evaluation, the principal component analysis method is introduced, and with the help of an orthogonal transformation T, the original random digital badge vector whose components are related is transformed into a new random digital badge vector whose components are not related, and the contribution rate of the cumulative eigenvector in the covariance matrix is used to achieve the final teaching evaluation. In this test result, the evaluation result error of the design system for the sample data is stable within 0.15, and the average evaluation accuracy is 98.49%, with high reliability.
