|
|
ENQUIRE PROJECT DETAILS BY GENERAL PUBLIC |
| Project Details |
| Funding Scheme : | General Research Fund | ||||||||||||||||||||||||
| Project Number : | 14610522 | ||||||||||||||||||||||||
| Project Title(English) : | School Learning Support and Teacher Digital Competence from a Needs Satisfaction Perspective | ||||||||||||||||||||||||
| Project Title(Chinese) : | 從需求滿足的角度來解釋學校學習支持和教師數碼能力的關係 | ||||||||||||||||||||||||
| Principal Investigator(English) : | Prof Chiu, Kin Fung, Thomas | ||||||||||||||||||||||||
| Principal Investigator(Chinese) : | |||||||||||||||||||||||||
| Department : | Dept of Curriculum & Instruction | ||||||||||||||||||||||||
| Institution : | The Chinese University of Hong Kong | ||||||||||||||||||||||||
| E-mail Address : | tchiu@cuhk.edu.hk | ||||||||||||||||||||||||
| Tel : | |||||||||||||||||||||||||
| Co - Investigator(s) : |
|
||||||||||||||||||||||||
| Panel : | Humanities, Social Sciences | ||||||||||||||||||||||||
| Subject Area : | Education | ||||||||||||||||||||||||
| Exercise Year : | 2022 / 23 | ||||||||||||||||||||||||
| Fund Approved : | 324,000 | ||||||||||||||||||||||||
| Project Status : | Completed | ||||||||||||||||||||||||
| Completion Date : | 30-6-2024 | ||||||||||||||||||||||||
| Project Objectives : |
|
||||||||||||||||||||||||
| Abstract as per original application (English/Chinese): |
COVID-19 和新興科技對未來對數碼技能的需求產生了全球影響。為了在數據和科技驅動的經濟中茁壯成長，我們需要具備數碼能力和自信的教師來提高學生的數碼能力。因此，教師數碼能力 (TDC) 專業發展應識在所有科目進行。 TDC是一個複雜的概念，包括教育學、態度、效能、社會和文化，它被描述在不同的概念框架中，如替代、增強、修改、重新定義框架和技術教學內容知識（TPACK）框架。這樣的框架傾向於強調教學法、技術和程序技能。最近的研究主張涵蓋個人和社會文化方面（例如，道德、安全和安保以及數字判斷）以擴大 TDC。 Falloon 將 TPACK 框架擴展為一個基礎廣泛的 TDC 框架，該框架通過添加兩組新的能力——個人道德和個人專業。實施該框架應該是跨學科的，是所有學校成員的責任。然而，如何在學校成功實施該框架仍不清楚。 學校需要模擬和考慮專業發展活動和政策，以激勵在職教師促進 TDC 發展。教師的動機可以用自決理論 (SDT) 來解釋，它可以提供對影響 TDC 發展的動機過程的理解。最近，SDT 的創始人呼籲對學校領導如何影響教師持續專業學習的動機進行更多研究。 考慮到上述情況，項目的目標是(i) 調查教師需求的滿足感在 學校學習支持與 個人道德和專業能力的關係中發揮的什麼中介作用，以及(ii) 調查為 TDC 提供有效的學校政策和持續的專業發展活動。為了實現這些目標，這項目將提出一個研究模型，實施順序解釋性混合方法研究設計，並通過問卷調查、校本政策文件、專業發展活動以及個人和焦點小組訪談收集數據。參加者將包括來自香港六所不同學業水平的學校的300名教師。 擬議項目將在短期內對研究人員、學校領導和政策制定者產生重大影響，(i) 提高他們對 TDC 發展的理解並提出實施模式； (ii) 通過增加新的 TDC 就中期的教師教育計劃和政策； (iii) 通過提高學生的數字能力，從長遠來看，對整個經濟和社會產生影響。 |
||||||||||||||||||||||||
| Realisation of objectives: | All the research activities were conducted as planned in the proposal. Our team do more than we planned in the original plan, and published more than we expected. There are no deviations from the original plan. See the following The first three objectives are 1. To elucidate how school learning support and teachers’ three psychological needs influence TDC development. 2. To develop evidence-based accounts of implementing needs-based support strategies for the implementation of the TDC framework. 3. To propose an implementation model for sustaining professional TDC development for researchers, policymakers and education officers. To achieve the first four objectives, we conducted the planned study and published journal papers. We conducted a sequential explanatory mixed-method study. First, a quantitative design was adopted to obtain objective statistical findings to examine the research model proposed in the plan. The participants were 370 teachers from nine secondary schools in Hong Kong. We also conducted focus group interviews and collected school-based documents to get the views from school leadership and teachers. In each school, a principal, one vice principal, four panel heads, and four subject teachers were the participants (total of 90 teachers). Purposive sampling was used to include teachers with different subjects to address the interdisciplinary implementation of teacher digital competence. Moreover, Professor Garry Falloon came to Hong Kong and helped with the study as planned. The last and fourth objective is to provide adequate guidelines for schools in designing and delivering professional development activities related to TDC. We do the following • presented the project finding in the following 13 seminars, talks and workshops 1. How to walk with AI, St. Paul's Co-Educational College Primary School, September 17, 2024 (100 participants) 2. AI K-12 education webinar, East China Normal University, September 14, 2024 (50 participants) 3. How can we prepare students, teachers, and schools to embrace AI? , CUHK-ECNU symposium, April 30, 2024 (50 participants) 4. How to Embrace AI in Education, March 26, 2024, St. Paul's Co-educational College (200 participants). 5. How does AI transform school education? March 8, 2024, Quality Education Fund (700 participants) 6. Empowering educators with essential competencies for thriving in the AI era, March 5, 2024, Kwun Tong Maryknoll College (80 participants) 7. Empowering educators with essential competencies for thriving in the AI era, December 1, 2023, Three schools’ joints event (250 participants) 8. Future of K-12 and Higher Education Powered by Generative AI, Chinese University of Hong Kong, November 3, 2023 (100 participants). 9. AI for all teachers, Munsang College, November 1, 2023 (60 participants). 10. AI for all teachers, Fanling Rhenish Church Secondary School, October 3, 2023 (60 participants). 11. AI competence for all teachers, Office of School Partnership and Community Engagement, Chinese University of Hong Kong, June, 16, 2023 (100 participants) 12. Should we use AI in classrooms? , Concordia Lutheran School, June 7, 2023 (80 participants) 13. AI for All teachers, Cognition College (Kowloon), May 19, 2023 (100 participants) • shared the findings in the USA Computer Research Association's Expanding the Pipeline: An Ecosystem for the Integration of AI in Education. Computing Research Association. January, 2025. https://cra.org/crn/2025/01/expanding-the-pipeline-an-ecosystem-for-the-integration-of-ai-in-education/ • sent the papers to the officers in the technology education committee. • Shared the findings with technology education officers in a meeting • published five papers related to this proposal, see the following papers. Since ChatGPT was introduced just before the project started, we include AI in the research. Chiu, T. K. F., Falloon, G., Song, Y.J., Wong, V. W. L., Zhao, Li, & Ismailov, M., A (2024a) A self-determination theory approach to teacher digital competence development, Computers & Education, 24, 105017. https://doi.org/10.1016/j.compedu.2024.105017 Chiu, T. K. F. (2024a). The impact of Generative AI (GenAI) on practices, policies and research direction in education: A case of ChatGPT and Midjourney, Interactive Learning Environments, 32(10), 6187-6203. https://doi.org/10.1080/10494820.2023.2253861 Chiu, T. K. F. (2024b). A classification tool to foster self-regulated learning with generative artificial intelligence by applying self-determination theory: a case of ChatGPT, Educational Technology Research & Development, 72, 2401–2416. https://doi.org/10.1007/s11423-024-10366-w Chiu, T. K. F., Ahmand, Z., Ismail, M., & Sanusi, I. T. (2024b). What are artificial Intelligence literacy and competency? A comprehensive framework to support them, Computers & Education Open, 6, 100171. https://doi.org/10.1016/j.caeo.2024.100171 Chiu, T. K. F. Ahmand, Z., & Çoban, M (2024c). Development and validation of teacher Artificial Intelligence (AI) competence self-efficacy (TAICS) scale. Education and Information Technologies, 30, 6667–6685. https://doi.org/10.1007/s10639-024-13094-z | ||||||||||||||||||||||||
| Summary of objectives addressed: |
|
||||||||||||||||||||||||
| Research Outcome | |||||||||||||||||||||||||
| Major findings and research outcome: | Empirical Implications 1. School Learning Support & Teacher Needs Satisfaction: School learning support significantly enhances teachers' satisfaction of autonomy, competence, and relatedness. When these psychological needs are met, teachers engage more effectively in Teacher Digital /AI Competence (TDC) development. (Chiu et al. 2024a; Chiu, 2024a). 2. School Learning Support & TDC Development: Direct correlations exist between school support and three TDC domains: TPACK (Technological Pedagogical Content Knowledge), personal-ethical, and personal-professional competencies. Schools fostering a supportive culture enhance teachers' ability to use digital tools responsibly (Chiu et al. 2024a, 2024b, 2024c). 3. Mediating Role of Teachers’ Needs Satisfaction: Needs satisfaction mediates the relationship between school support and personal-ethical/professional competencies. Autonomy, competence, and relatedness indirectly predict TDC growth (Chiu et al, 2024a). 4. Needs-Supportive Strategies for TDC: Twelve strategies were identified to foster TDC, including sharing opportunities, financial support, decision-making involvement, accessible learning resources, and recognition of achievements. (Chiu et al, 2024a). Theoretical Contributions 1. SDT and TDC Integration: We extend SDT to digital education, emphasizing school policies' role in TDC development (Chiu et al, 2024a, 2024b; Chiu, 2024a) 2. TPACK as a Core Competency: We position TPACK as an innate teaching need under SDT. TPACK serves as foundational knowledge for digital teaching, aligning with recommendations for teacher training programs (Chiu et al, 2024a, 2024c). 3. New TDC Frameworks: We introduce and validate personal-ethical and personal-professional competencies as key TDC components, relevant for emerging technologies like AI and the metaverse (Chiu et al, 2024a, 2024c). Practical Recommendations 1. For School Leaders: We adopt needs-supportive policies using the 12 strategies to enhance TDC. Governments should integrate these into national digital competence frameworks. (Chiu et al, 2024a) 2. For Teacher Educators: We design programs prioritizing TPACK as a prerequisite before advancing to ethical/professional competencies, and suggest the programs must align teacher frameworks with AI competency levels (Chiu et al, 2024a, 2024c) 3. For Leadership Programs: We focus on TPACK, AI, and metaverse risks/benefits, forming partnerships with tech firms and policymakers for industry-academic alignment (Chiu et al, 2024a; Chiu, 2024a). 4. Implementation Challenges: Mandating TDC in policy alone is insufficient; institutional support and mindset changes are critical (Chiu, et al., 2024a). Conclusion This project bridges SDT and TDC, demonstrating how needs-supportive school environments enhance digital /AI teaching competencies. It offers actionable strategies while acknowledging the complexity of implementing TDC in traditional education systems. | ||||||||||||||||||||||||
| Potential for further development of the research and the proposed course of action: |
This project highlights limitations that pave the way for further research, particularly in the context of Teacher AI Competency, an emerging subset of TDC. Future studies should: (1)Empirically Test Needs-Supportive Strategies–12 proposed strategies should be quantitatively tested through experimental or Delphi studies to determine their effectiveness in fostering AI competency among teachers, (2)Cross-Cultural Comparisons–Given potential East-West differences in teacher perceptions, comparative studies should examine how societal reputation and institutional culture influence AI adoption in education, (3)Incorporate Objective Measures–Since self-reported TDC may not reflect actual competency, future research should use AI-driven assessments, classroom observations to validate teacher proficiency in AI-integrated teaching, (4)SDT Implementation in Diverse School Contexts–Further empirical research is needed to assess how SDT-based policies function in high-stakes, standardized, or under-resourced schools, where AI integration may face resistance, (5)AI Competency–We should explore TDC frameworks for university educators, focusing on ethical AI use, digital pedagogy, and continuous upskilling. In sum, a proposed course of action includes developing AI-specific TDC frameworks for teachers, integrating them into teacher training programs, and fostering school-university to align AI advancements with classroom needs. Policymakers should support longitudinal studies to track teacher AI competency development over time. | ||||||||||||||||||||||||
| Layman's Summary of Completion Report: | This research project investigates how schools can better support teachers in developing their digital competencies, especially as technology like AI becomes more important in education. We find that when teachers feel supported, confident, and connected at work, they are more likely to use technology effectively and responsibly in the classroom. The big idea is that teacher digital competency is not just about knowing how to use tech— it is about using it in a way that is safe, ethical, productive, and helpful for students. We also suggest 12 practical strategies schools can use, like giving teachers training, encouraging teamwork, and recognizing their efforts. Why does this matter? Because AI and digital tools are changing education fast, and teachers need the right skills to keep up. If schools create a positive environment where teachers feel empowered, they will be better prepared for future classrooms—whether that means using AI responsibly, protecting student privacy, or designing engaging digital lessons. The value of this project is that it gives school leaders, policymakers, and teachers clear steps to improve digital education. Instead of just telling teachers to use more technology, it shows how schools can actually help them succeed. | ||||||||||||||||||||||||
| Research Output | |||||||||||||||||||||||||
| Peer-reviewed journal publication(s) arising directly from this research project : (* denotes the corresponding author) |
|
||||||||||||||||||||||||
| Recognized international conference(s) in which paper(s) related to this research project was/were delivered : |
|
||||||||||||||||||||||||
| Other impact (e.g. award of patents or prizes, collaboration with other research institutions, technology transfer, etc.): |
|||||||||||||||||||||||||
| SCREEN ID: SCRRM00542 |