Abstract
As an educational concept based on learning output, OBE (Outcome-Based Education) is student-centered and emphasizes students' personal progress and learning achievement. Based on BD (big data) analysis, this paper proposes a new talent training mode for the electronic information science and technology specialty. This model employs BD analysis technology to examine the correlation index between social demand and talent cultivation, based on the employment situation of students in the country in previous years. The teaching reform was carried out under the OBE concept, and a new training scheme was formed. Training objectives, graduation requirements, curriculum system, and continuous improvement mechanism were all determined. This paper proposes an algorithm for determining the degree of similarity between the knowledge required by the organization and the knowledge held by its employees. The person with the highest similarity is identified as the training candidate by the algorithm, and the training candidate is then trained according to the knowledge that the organization requires. Talent training in the field of electronic information science and technology has yielded positive results.
Highlights
Computational Intelligence and Neuroscience evaluation method, the lack of scientific evaluation index system, the inefficacy of fairness and authority of evaluation results in practice, and the lack of objectivity of evaluation, which leads to low reliability, insignificant validity, and the difficulty of practical results [6, 7]
As university teaching levels improve, BD analysis is required to scientifically evaluate teaching performance in the practice of the training mode of talents majoring in electronic information science and technology, and how to improve the scientificity and effectiveness of performance evaluation through the digital network platform is the focus of this paper
A new talent training model for electronic information science and technology is proposed in this paper based on BD analysis
Summary
Computational Intelligence and Neuroscience evaluation method, the lack of scientific evaluation index system, the inefficacy of fairness and authority of evaluation results in practice, and the lack of objectivity of evaluation, which leads to low reliability, insignificant validity, and the difficulty of practical results [6, 7]. As university teaching levels improve, BD (big data) analysis is required to scientifically evaluate teaching performance in the practice of the training mode of talents majoring in electronic information science and technology, and how to improve the scientificity and effectiveness of performance evaluation through the digital network platform is the focus of this paper. A new talent training model for electronic information science and technology is proposed in this paper based on BD analysis. E creative point of this research is as follows: this paper adopts the technical platform of big data analysis, based on the theory of constructing the evaluation index system of talent cultivation quality suitable for the collection and analysis of big data evaluation model, and collects and analyzes data through the construction of functional modules, taking a university as an example to get the evaluation results. A relatively perfect big data evaluation model can be formed, which is more widely used in the evaluation of talent cultivation quality in universities
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