| 摘要(英) |
When companies recruit fresh graduates, in addition to their personal professional abilities, their own soft power is also an ability that they value. In order for students to understand their own interests and competitiveness in the workplace, the Ministry of Education launched the "University and College Employment Function Platform" (UCAN) to provide career interest survey and competency assessment. Competency assessment includes general competency assessment and professional competency assessment. General competencies represent common soft power in the workplace. They are communication, continuous learning, interpersonal interaction, teamwork, problem solving, innovation, job responsibility and discipline, and information technology applications. Quantify these abilities through assessment to understand the individual’s abilities.
The listed general competency items can be judged based on experience that some of them are related to each other. This research uses decision trees to find the rules between student′s course performance and general competencies. Through rule analysis to evaluate whether the items are related and can be merged, so that the total number of items is reduced. And through rules to analyze the distribution of students′ course scores for each general competencies, to assist institutional research in making decisions. According to the results to determine how to improve students′ soft power, so as to enhance students′ competitiveness in the workplace. |
| 參考文獻 |
[1] 李紋霞、符碧真（2017）。全球視野在地化的校務研究：以國立臺灣大學經驗為例。教育科學研究期刊，62（4），1-25。
[2] 劉孟奇（2016）。以校務研究為校務決策之本。評鑑雙月刊，60，10-12。
[3] Quinlan, J. R., “Induction of Decision Trees”, Machine Learning 1: 81-106, Kluwer Academic Publishers, 1986.
[4] Quinlan, J. R., C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers, 1993.
[5] Breiman, Leo; Friedman, J. H., Olshen, R. A., & Stone, C. J., Classification and regression trees, Monterey, CA: Wadsworth & Brooks/Cole Advanced Books & Software, 1984.
[6] C. E. Shannon, “A mathematical theory of communication”, The Bell System Technical Journal, vol. 27, no. 3, pp. 379-423. doi:10.1002/j.15387305.1948.tb01338.x., July 1948.
[7] Quinlan, J. R. “Simplifying decision trees”, International Journal of Man-Machine Studies, 27(3), 221–234. doi:10.1016/s0020-7373(87)80053-6, 1987
[8] Mingers, John., “Expert Systems—Rule Induction with Statistical Data”, The Journal of the Operational Research Society. 38. 10.1057/jors.1987.5., 1987.
[9] BRESLOW, L. A., & AHA, D. W., “Simplifying decision trees: A survey”, The Knowledge Engineering Review, 12(01), 1–40. doi:10.1017/s0269888997000015, 1997.
[10] Breiman, L., “Random Forest”, Machine Learning, 45(1), 5–32. doi:10.1023/a:1010933404324, 2001. |
[Endnote RIS 格式]
[相關文章]
[文章引用]
[完整記錄]
[館藏目錄]
[檢視]
plurk
funp
live
udn
HD
myshare
netvibes
friend
youpush
delicious
baidu
Google bookmarks
del.icio.us
hemidemi
facebook
twitter
google
reddit