Study of Introducing Personality Traits and Learning Performance to Advance Career-Fitting by Using ANN Model－University Graduate Student with the Department of Information Management as an Example
| Autor: | PENG, WEN-CHUN, 彭文君 |
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| Rok vydání: | 2019 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 107 Common career test tools include the UCAN University Career and Competency Assessment Network of the Ministry of Education, the nine planet competency tests of the Human Resource Agency, and work temperament test of the Ministry of Labor. Although these test tools have been widely used, the test results of each tool for those who are looking for a job, it is still not possible to use this information effectively to find a suitable career. Based on the above questions, this paper establishes career testing tools, taking into account many typical and atypical factors, and then use Neural Network establishing a predictive model to complete career testing tools. This paper will be divided into two phases, and the key factors will be selected in the first phase. Identify the factors of the adaptation tool and screen them in three ways: expert consensus method, weighted average method, and TOPSIS method. The second stage uses the eight key factors selected in the first stage to collect data. The R language performs Neural Network model calculation to find the best hidden layer to construct the model. The final eight key factor data yields get accuracy of 50%. The test tool of this paper is different from the test of the single factor in the previous career test tool, and narrows the scope of the result recommendation to the suitable career, so that the result can more accurately describe the suitable occupational field of the subject. Those who are interested in the career test field and career counselors can refer to the atypical factors used in this paper as different test methods. For the school, the same method can be used to predict the personality of each department and help students choose the department. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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