張家凱 專任助理教授

張家凱 專任助理教授
學 歷:國立台灣大學光電工程研究所博士
聯絡電話:(03) 4227151 ext.33415
研 究 室:C2-320
電子郵件:ckchang@ncu.edu.tw
研究領域:數位學習、多模態學習分析、機器學習、生理資料探勘、
實驗室:https://chia-kai-chang.github.io/
教育部計畫 |
1. 基於 IDC 理論與 Learning-Creation Loop 機制之 AI 人機協作式 Python 程式設計教學模式建構與學習成效研究(2026-08-01 ~ 2027-07-31)(教學實踐研究計畫)(計畫主持人)
2. 基於生成式人工智慧的數位鷹架教學法在文學院生成式人工智慧導論課程之學習遷移成效研究(2025-08-01 ~ 2026-07-31)(教學實踐研究計畫)(計畫主持人) 3. 矩陣沉浸式問題導向專案學習法(Problem Oriented Project-Based Learning, POPjBL)在專題實作課程之學習成效研究(2024-08-01 ~ 2025-07-31)(教學實踐研究計畫)(計畫主持人) 4. 自我調節與遷移學習效能研究:以人工智慧適性引導系統為例(2023-12-01 ~ 2025-01-31)(教學實踐研究計畫)(計畫主持人) |
國家科學及技術委員會計畫 |
1. 生理感知語言模型於人機協作學習之多模態歷程分析與資訊教育模型建構(NSTC 115-2410-H-008-028)(2026-08-01 ~ 2027-07-31)(新進人員研究計畫)(計畫主持人)
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期刊論文 |
Li, K.-H., & Chang, C.-K. (2026). Agentic AI as a dual-role lecturer and teaching assistant: Effects on learner autonomy, self-regulated learning, and intrinsic motivation in university-level EFL education. Frontiers in Psychology, 17. https://doi.org/10.3389/fpsyg.2026.1847607
Chang, C.-K., & Li, K.-H. (2026). Chat as learning: Student–AI conversations as discipline-associated cognitive engagement patterns. Computers and Education: Artificial Intelligence, 11, 100644. https://doi.org/10.1016/j.caeai.2026.100644 Li, K.-H., & Chang, C.-K. (in press). Designing and evaluating a Socratic-scaffolded conversational AI assistant for educational tasks: Cross-cohort effectiveness, user perception, and the effort signature. International Journal of Human–Computer Interaction. |
研討會論文 |
Chang, C.-K., & Li, K.-H. (2026). AI teaching assistants at scale: Cross-disciplinary patterns of adoption and cognitive engagement across hundreds of university courses. Proceedings of the Thirteenth ACM Conference on Learning @ Scale (L@S ’26), 46–56. https://doi.org/10.1145/3774398.3811596
Chang, C.-K., & Li, K.-H. (2026). PALM: Scaling physiologically-aware AI tutoring through consumer wearables and large language models. Proceedings of the Thirteenth ACM Conference on Learning @ Scale (L@S ’26), 395–399. https://doi.org/10.1145/3774398.3811576 Chang, C.-K., Li, K.-H., Cheng, C.-L., & Lin, T.-C. (2026). From wearables to classrooms: A person-centered feasibility study of HRV-based physiological monitoring for learning analytics. 2026 IEEE Swiss Conference on Data Science and AI (SDS), 193–196. https://doi.org/10.1109/SDS70563.2026.00035 Chang, Y.-Y., Tsai, M.-C., Chien, Y.-C., Chai, Y.-Z., & Chang, C.-K. (2026). Design of a distributed semantic analysis system for scalable processing of heterogeneous text data. 2026 IEEE 12th International Conference on Big Data Computing Service and Machine Learning Applications (BigDataService), 248–252. https://doi.org/10.1109/BigDataService70481.2026.00049 Yen, C.-C., Chang, Y.-Y., Chai, Y.-Z., Hsieh, P.-T., Li, K.-H., & Chang, C.-K. (2025). Correlation analysis of conversational focus with learning experience in Python courses. 2025 7th International Conference on Modern Educational Technology (ICMET), 258–262. https://doi.org/10.1109/ICMET67594.2025.11451926 Chang, C.-K., & Li, K.-H. (2025). Designing an educational omics data lake: A multimodal infrastructure for technology-enhanced learning. 2025 7th International Conference on Modern Educational Technology (ICMET), 284–290. https://doi.org/10.1109/ICMET67594.2025.11452000 Cheng, C.-L., Lin, T.-C., & Chang, C.-K. (2025). Collaborative reasoning framework for edge-deployable EEG sleep staging via local LLM. 2025 IEEE 11th International Conference on Big Data Computing Service and Machine Learning Applications (BigDataService), 108–112. https://doi.org/10.1109/BigDataService65758.2025.00021 E. N. Furqon and C.-K. Chang, “Evaluating Cognitive Performance through Prompt-Based Methods Using LLM in Education,” in 2025 IEEE International Conference on Advanced Learning Technologies (ICALT), Jul. 2025. C.-C. Yen, P.-T. Hsieh, Y.-C. Chen and C.-K. Chang, “Analysis of a Generative AI-Based Graphical Learning Assistance Tool in IPR Courses,” in 2025 IEEE International Conference on Advanced Learning Technologies (ICALT), Jul. 2025. Phay, K. S., & Chang, C.-K. (2025). A Generative Artificial Intelligence-Based Python Learning Assistance System: Assessing Its Impact on Instrument Automation Skills. 2025 IEEE Conference on Education and Training in Optics and Photonics (ETOP), 1–4. https://doi.org/10.1109/ETOP64842.2025.11030677 Chen, Y.-H., Huang, J.-S., Hung, J.-Y., & Chang, C.-K. (2025a). Leveraging Knowledge Graphs and Large Language Models to Track and Analyze Learning Trajectories (No. arXiv:2504.11481). arXiv. https://doi.org/10.48550/arXiv.2504.11481 Chang, C.-K., & Chien, L.-C.-T. (2024). Enhancing Academic Performance with Generative AI-Based Quiz Platform. 2024 IEEE International Conference on Advanced Learning Technologies (ICALT), 193–195. https://doi.org/10.1109/ICALT61570.2024.00062 Chang, C.-K., Chen, P.-C., Chen, Z.-S., & Kuo, T. M. (2023). Developing AI-Based Automated Post-Rating System to Scaffold Interdisciplinary Knowledge-Sharing. 2023 IEEE International Conference on Advanced Learning Technologies (ICALT), 239–241. https://doi.org/10.1109/ICALT58122.2023.00076 Chang, C.-K., Lin, J.-T., You, C., Calderon-Delgado, M., Tjiu, J.-W., & Huang, S.-L. (2019). Skin Cancer Detection using Cellular Resolution Optical Coherence Tomography. 2019 24th Microoptics Conference (MOC), 70–71. https://doi.org/10.23919/MOC46630.2019.8982810 Chang, C.-K., & Huang, S.-L. (2018a). Nucleus and Cytoplasm Segmentation using Full-Field Optical Coherence Tomography. Biophotonics Congress: Biomedical Optics Congress 2018 (Microscopy/Translational/Brain/OTS) (2018), Paper MF3A.2, MF3A.2. https://doi.org/10.1364/MICROSCOPY.2018.MF3A.2 Chang, C.-K., & Huang, S.-L. (2018b). Quantitative Analysis of Keratinocytes in Human Skin Using Full-Field Optical Coherence Tomography. Conference on Lasers and Electro-Optics (2018), Paper JTu2A.100, JTu2A.100. https://doi.org/10.1364/CLEO_AT.2018.JTu2A.100 Li, Y. Y., Soundararajan, R., Chang, C. K., Yang, T. I., Huang, S. L., & Lee, Y. W. (2018). Optical coherence tomography—From micron to nanometer resolution. 2018 7th International Symposium on Next Generation Electronics (ISNE), 1–2. https://doi.org/10.1109/ISNE.2018.8394691 Chang, C., Tsai, C.-C., Chien, M.-T., M.d, Y.-I. L., M.d, C.-T. S., & Huang, S.-L. (2015). Web-based 3D digital pathology framework for large-mapping data scanned by FF-OCT. Medical Imaging 2015: PACS and Imaging Informatics: Next Generation and Innovations, 9418, 94180H. https://doi.org/10.1117/12.2081587 Tsai, C.-C., Chang, C.-K., Hsu, K.-Y., Ho, T.-S., Wang, Y.-T., Lin, M.-Y., Tjiu, J.-W., & Huang, S.-L. (2014). In vivo 3-D cellular level imaging using Mirau-based full-field optical coherence tomography on skin tissue. Biomedical Optics 2014 (2014), Paper BW4A.2, BW4A.2. https://doi.org/10.1364/BIOMED.2014.BW4A.2 Tsai, C.-C., Ho, T.-S., Chang, C.-K., Hsu, K.-Y., Lin, M.-Y., Tjiu, J.-W., Huang, S.-L., & Huang, S.-L. (2014). Cellular-resolution optical coherence tomography. Latin America Optics and Photonics Conference (2014), Paper LTh3D.3, LTh3D.3. https://doi.org/10.1364/LAOP.2014.LTh3D.3 |
已發表、出版中 |
Furqon, E. N., & Chang, C.-K. (2026). Did you lose them? Predicting the exact moment of disengagement via multimodal VLM classroom orchestration in education. 2026 IEEE International Conference on Advanced Learning Technologies (ICALT). (in press)
Chien, Y.-C., Yen, C.-C., & Chang, C.-K. (2026). Validation of natural language-based educational digital twins through embedding geometry in Python courses. 2026 IEEE International Conference on Advanced Learning Technologies (ICALT). (in press) Chang, Y.-Y., Chai, Y.-Z., & Chang, C.-K. (2026). Temporal lag effects in multimodal learning analytics: Physiological–behavioral characterization. 2026 IEEE International Conference on Advanced Learning Technologies (ICALT). (in press) Cheng, C.-L., Lin, T.-C., & Chang, C.-K. (2026). C-GRASP: Clinically-grounded reasoning for affective signal processing. 2026 IEEE Engineering in Medicine and Biology Society Conference (EMBC). (in press) Chang, C.-K., & Li, K.-H. (2026). Uedu: A six-dimensional educational omics platform bridging AI, physiological sensing, and classroom practice. European Conference on Technology Enhanced Learning (EC-TEL 2026), Springer LNCS. (in press) Chang, C.-K., & Li, K.-H. (2026). Uedu: Layered learner agency for mindful personalization without surveillance. European Conference on Technology Enhanced Learning (EC-TEL 2026), Springer LNCS. (in press) |
學歷 |
國立台灣大學光電工程學博士(2018) |
現職 |
通識教育中心專任助理教授(2021~)
人工智慧國際碩士學位學程專任助理教授 AI輔助教學推動委員會,技術研發組組長 |
經歷 |
1.資訊工業策進會數位教育研究所資深工程師(2019-2021) 2.工業技術研究院材料與化工研究所研究員(2018-2019) 3.國家儀器科技研究中心助理研究員(2004-2008) |
學術榮譽 |
1.2025 IEEE International Conference on Advanced Learning Technologies (ICALT)最佳短論文獎 2. 2023 Garmin Health 高峰會年度大獎賽入圍 3. 2026 ACM Conference on Learning @ Scale (L@S) 最佳論文提名(全會議 4 篇入圍之一) 4. 2026 eLearning Forum Asia (eLFA) Technology Innovation Award 銅牌 5. 2026 European Conference on Technology Enhanced Learning (EC-TEL) 最佳展示論文提名 |