以人工智慧技術建構職業訓練課程推介模型研究

A Study on AI Technology Application for the Establishment of the National Vocational Training Program

黃春長(Chun-Chang Huang)；徐雅媛(Ya-Yuan Hsu)；黃維平(Wei-Ping Huang)；蔡禮宇(Li-Yu Tsai)；周鴻文(Hung-Wen Chou)

職業訓練 ； 人工智慧 ； 機器學習 ； 就業 ； Vocational training ； Artificial intelligence ； Machine learning ； Employment

勞動及職業安全衛生研究季刊

27卷2期（2019 / 06 / 15）

149 - 164

繁體中文

本研究係以勞動部所屬機關之公務資料為基礎，規劃以大數據分析及人工智慧建置職業訓練課程推介模型，提供有效資訊並同時最佳化訓練課程效益。基於研、訓、檢、用的核心理念，改善訓及用之間的落差，引進人工慧技術分析過去職業訓練課程參與者特質及其訓後就業情形，並進一步根據職訓課程參與者特質及其訓後就業情形進行分組分類，使用演算法進行計算，建立課程推介模型。本研究將勞保資料及職業訓練資訊系統資料進行串聯、整理過後以機器學習演算法根據勞工是否參與職業訓練進行分類分群，找出影響勞工參與職業訓練的特徵值，再根據定義之就業成效指標計算參訓勞工之訓後就業成效，根據相關結果以人工智慧建置職業訓練課程推介模型。職業訓練課程推介模型以資料為基礎，目的在於建構可針對不同勞工特性推介適合的職業訓練課程模型。本研究主要應用決策樹演算法建立職業訓練課程受訓者分類模型及職業訓練課程受訓者就業成效預測模型。

Based on the data owned by the agencies of the Ministry of Labor, this research plans to use the big data analysis and artificial intelligence to build a vocational training curriculum promotion model to provide effective information and optimize the effectiveness of the training curriculum. Based on the core concepts of research, training, inspection and use, improve the gap between training and use, introduce artificial intelligence technology to analyze the characteristics of past vocational training course participants and their post-training employment situation, and further establish a classification model based on the vocational training curriculum. The traits and their post-training employment situation are grouped into categories, and then the algorithm is used for calculation to establish a curriculum recommendation model. In this study, we serialized and organized the labor insurance data and the vocational training information system data, and then used the machine learning algorithm to classify and group according to whether the workers participated in vocational training, and found out the characteristic values that affect the labor participation in vocational training. The defined employment effectiveness indicators are used to calculate the post-training employment effectiveness of the participating laborers. Based on the relevant results, the vocational training curriculum promotion model is built with artificial intelligence. The vocational training curriculum promotion model is based on information and aims to create a model that can be used to recommend suitable vocational training courses for different workers based on their characteristics. In this study, the decision tree algorithm is applied to establish the classification model of the trainees of the vocational training courses and the prediction model of the employment performance of the trainees of the vocational training courses.

1. 吳瓊治(2006)。訓練成效的評鑑。品質月刊，42(10)，44-48。
   連結：
2. 孫仲山,李德純(2007)。職業訓練學員學習成效的影響因素─學員屬性的周密化分析。高雄師大學報：教育與社會科學類，23，29-50。
   連結：
3. Andersson, P,Hellgren, M,Köpsén, S(2018).Factors influencing the value of CPD activities among VET teachers.International Journal for Research in Vocational Education and Training,5,140-164.
4. Ebenehi, AS,Rashid, AM,Bakar, AR(2016).Predictors of career adaptability skill among higher education students in Nigeria.International Journal for Research in Vocational Education and Training (IJRVET),3,212-229.
5. Feifei, T.(2015).The Demand Analysis of Vocational Education in BaZhou Employment Structure Evolution.Intelligent Transportation, Big Data and Smart City (ICITBS) 2015. International Conference on IEEE
6. Fernández-Henarejos, ADCT,Hernández-Prados, MÁ(2017).The Dual Vocational Training. Program of Labor Health in the Company.Procedia-Social and Behavioral Sciences,237,1026-1031.
7. Guoqiang, R,Yuhui, L(2010).Notice of Retraction The research on rural labors' training status and its impact to employment behavior based on Tianjin 2008 survey data.Information Management and Engineering (ICIME) 2010; The 2nd IEEE International Conference on IEEE
8. Kruppe, T,Lang, J(2014).IAB-Discussion PaperIAB-Discussion Paper,未出版
9. Ngai, SSY,Cheung, CK,Yuan, R(2016).Effects of vocational training on unemployed youths' work motivation and work engagement: Mediating roles of training adequacy and self-actualization.Children and Youth Services Review,63,93-100.
10. Popescu, ME,Roman, M(2018).Vocationl training and employability: Evaluation evidence from Romania.Evaluation and program planning,67,38-46.
11. Qianqian, Y,Hongju, Z,Yan, X(2011).From Concerning the Employment Rate to the Quality of Employment.Knowledge Acquisition and Modeling (KAM) 2011; Fourth International Symposium on IEEE
12. Sella, L(2014).Enhancing vocational training effectiveness through active labour market policies.Procedia-Social and Behavioral Sciences,141,1140-1144.
13. 王家蓁(2015)。逢甲大學金融碩士在職專班。
14. 李秀鳳(2014)。中國科技大學企業管理研究所。
15. 李健鴻,張景旭,陳月娥(2004)。,職業訓練局。
16. 李誠,辛炳隆(2005)。,行政院經濟建設委員會。
17. 李誠,辛炳隆(2003)。,經濟建設委員會。
18. 李德純(2010)。高雄師範大學。
19. 辛炳隆,李健鴻(2008)。,職業訓練局。
20. 林昭吟(2007)。,行政院經濟建設委員會。
21. 林昭吟,徐美,辛炳隆,劉宜君(2007)。,經濟建設委員會。
22. 林柏威(2009)。中國文化大學。
23. 林瑞鑫(2007)。中華大學。
24. 洪木生(2010)。長榮大學經營管理研究所。
25. 袁罡,肖濤(2017)。基於機器學習的電力培訓滿意度研究。江西電力職業技術學院學報，4，017。
26. 袁淑玲(2014)。銘傳大學觀光事業學系碩士在職專班。
27. 張育肇(2012)。國立高雄師範大學。
28. 張育蓉(2012)。中興大學圖書資訊學研究所。
29. 張雅嵐(2010)。,未出版
30. 陳翰(2018)。淡江大學運輸管理學系。
31. 彭若婷(2015)。屏東科技大學技職教育研究所。
32. 楊淑美(2012)。臺北大學會計學系。
33. 溫玲玉(2005)。彰化師範大學商教育系。
34. 翟玉雰(2015)。中興大學國家政策與公共事務研究所。
35. 劉侑學(2010)。政治大學。
36. 職業訓練局(2018).勞動力發展辭典.職業訓練局.