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研究報告

 

研究報告/專書出版

2023 數位經濟六大領域人才需求分析報告封面縮圖
2023 數位經濟六大領域人才需求分析報告

報告產製:資訊工業策進會 - 數位教育研究所
著作權:文件著作權歸屬於數位發展部數位產業署
為能提升臺灣數位科技人才競爭力,本報告聚焦於人工智慧、資料科學、智慧聯網、智慧內容、數位行銷等五大新興領域、以及各行各業皆日益關注之資訊安全領域,2023年持續更新六大領域的發展趨勢、關鍵職務需求及相應職務能力,以因應未來數位科技智慧應用浪潮。

2022 數位經濟六大領域人才需求分析報告封面縮圖
2022 數位經濟六大領域人才需求分析報告

報告產製:資訊工業策進會 - 數位教育研究所
著作權:文件著作權歸屬於數位發展部數位產業署
為能提升臺灣數位科技人才競爭力,以因應未來的數位科技智慧應用浪潮,本報告2022年更新,除聚焦於五大新興領域「人工智慧、資料科學、智慧聯網、智慧內容和數位行銷」,並新增日益受重視的「資訊安全」領域,針對發展趨勢、關鍵職務需求及對應職務能力加以說明。

2021 數位經濟五大領域人才需求分析報告封面縮圖
2021 數位經濟五大領域人才需求分析報告

報告產製:資訊工業策進會 - 數位教育研究所
著作權:文件著作權歸屬於經濟部工業局
為能提升臺灣數位科技人才競爭力,以因應未來的數位科技智慧應用浪潮,本報告2021年更新,聚焦於五大新興領域人工智慧、資料科學、智慧聯網、智慧內容和數位行銷,針對其發展趨勢、關鍵職務需求及對應職務能力加以說明。

2020 數位經濟五大領域人才需求分析報告封面縮圖
2020 數位經濟五大領域人才需求分析報告

報告產製:資訊工業策進會 - 數位教育研究所
著作權:文件著作權歸屬於經濟部工業局
為能提升臺灣數位科技人才競爭力,以因應未來的數位科技智慧應用浪潮,本報告聚焦於五大新興領域人工智慧、資料科學、智慧聯網、智慧內容和數位行銷,針對其發展趨勢、關鍵職務需求及對應職務能力加以說明。

數位轉型跨領域人才培育報告封面縮圖
數位轉型跨領域人才培育

出版作者:資訊工業策進會 - 數位教育研究所
出版日期:2020/06/01
專書定價:12,000元
數位轉型時代,學習應該如何創新 ? 數位教育如何改革進步 ?本書完整收錄「跨領域創新學習模式」、「數位策略設計藍圖」、「數位工具應用秘笈」,讓我們一起來創新學習、學習創新 !

 

研究論文發表

2020
應用區塊鏈技術發展跨域數位人才培育
台灣數位學習發展研討會 (TWELF 2020)
為了改善數位經濟產業人才短缺與學用落差的問題,本研究建立創新培育模式,透過鏈結學界與產業資源培育跨域數位人才。為能有效紀錄與管理學生學習成效與歷程,本研究建立Talent Management System(TMS),並透過區塊鏈技術儲存學生線上課程學習成效、專題成果與結業證書,藉此可提供研習單位、學校與企業快速查詢學生個人履歷,降低管理與徵才成本與確保履歷真實性。

2020
發展數位課程學習地圖以培育跨領域數位人才
台灣數位學習發展研討會 (TWELF 2020)
因應人工智慧時代來臨,培育數位經濟產業的人才已成為現今國際趨勢,為了改善非資訊相關背景之學生難以透過自學成為數位領域人才之問題,本研究建立課程地圖設計模型,發展出適合跨域數位人才之數位課程學習地圖,不僅解決跨域數位人才難以安排學習計畫的困境,並加強學生進行跨域學習之自信,進而加速數位經濟產業的發展。

2020
Innovative Training Model of Cross-Domain Digital ICT Talent Development for Training Application of Data Analysis in Medical Field
2020 IEEE An International Conference on Engineering, Technology, and Education(TALE)
In response to the increasing demand for cross-domain digital talent, the researchers in this study designed and tested cross-domain digital courses for medical students. These Artificial Intelligence (AI) courses were made available throughout the semester via an innovative blended learning model. Fourteen students took part in a one-credit, an 18-week online and offline blended learning model course entitled Application of Data Science in Medical Fields. The instructors for the physical courses comprised both academics and industry professionals. The final presentation, students put what they learnt into practice in a contemporary medical environment. The course not only helped students develop problem-solving skills but also strengthened the connections between academic subjects and AI-related technology. As a result of this research, medical university students achieved significant academic improvement after participating in the course. Students’ rated their satisfaction levels for course contents and materials an average of four out of five.

2019
Applying an Innovative Blended Model to Develop Cross-Domain ICT Talent for University Courses
2019 IEEE 49th Frontiers in Education (FIE)
This study designed an an online course Application of Data Science in the Realm of Medicine in which 33 students of medical university and the staff of a medical university hospital enrolled. and Artificial Intelligence and Law of Technology course in which 59 national university students enrolled. A massive open online course platform was used with the online class mentor diversification course operation method and teaching strategy to provide solutions to problems existing in the industry and to encourage a spirit of teamwork in the physical class. Through diverse cross-domain channels, students learned how to use the technology that was integrated with artificial intelligence and relevant to their department. Students cultivated the cross-domain ability required in the contemporary digital economy. The results of this study revealed that after medical university students and general university students received this cultivation-model training, the students who did not study information and communications technology (ICT) significantly outperformed the students who studied ICT. Moreover, no significant differences were found between the learning performance of male and female students. This cultivation model proved to be effective for cross-domain learners. The model also reduced the achievement gap in science learning asssociated with gender differences. In the after-class survey, average score of satisfaction reached 7 and higher in the total of 9 points.

2019
Applying Blockchain Technology to Develop Cross-Domain Digital Talent
2019 IEEE 11th International Conference on Engineering Education (ICEED)
To decrease the talent shortage in the digital economy industry and fill the gap between academics and industry, this study establishes an innovative model to cultivate interdisciplinary talent that links the resources in the academic and industrial fields. To monitor and manage the learning performance and training history throughout the process, this study creates a Talent Management System (TMS), which uses blockchain technology to record 698 interns’ data on their online learning history, project outcomes, and certification of completion. With TMS, research institutions, schools, and corporations can access the digital resumes of interns more efficiently, thus reducing the cost of management and recruiting and ensuring the authentication of resumes.

2019
Developing a Curriculum Learning Map for Cultivating Cross-domain Digital Talent
2019 IEEE 11th International Conference on Engineering Education (ICEED)
Cultivating digital talent for the digital economy industry has become a current international trend because the artificial intelligence era has arrived. To ameliorate the problem that students who do not come from information-related backgrounds cannot become digital talent through self-learning, this research creates a design pattern for curriculum maps. A Curriculum Learning Map for cross-domain digital talent is developed by identifying learners’ starting points, learning paths, course levels, and learning evaluation. This not only solves cross-domain digital talent’s problems scheduling learning plans but also develops students’ confidence on cross-domain learning, which expedites the digital economy’s development.

2018
An Innovative Hybrid Model for Developing Cross Domain ICT Talent in Digital Economy
2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE)
Taiwan currently faces a severe talent shortage. According to ManpowerGroup Talent Shortage Survey 2016, 73% of employers in Taiwan experience difficulty in recruiting talents, which is the second highest rate of talent shortage in the world. Human capital is the critical key to well-being and economic growth; therefore, the talent shortage has become an urgent issue for the government to solve. In the age of digital transformation, the ability to use a fast and effective model for developing digital talent is of the utmost importance to Taiwan's future. Hence, this study developed Innovative Hybrid Model for Developing Cross-Domain ICT Talent in Digital Economy to cultivate future talents needed. The program had already produced many of outstanding outcomes and created significantly impacted upon Taiwan's talent development including received the ATD (Association for Talent Development) award of Innovation in Talent Development.