YANG, L., & Chan, C. K., & Lam, K. S., & Chui, C. K. (2025, June), An Experiential Learning Framework to Harvest Synergy from College and Industry Partnership  Paper presented at 2025 ASEE Annual Conference & Exposition , Montreal, Quebec, Canada . https://peer.asee.org/57615

\bibitem{asee_peer_57615}
  YANG, L., \& Chan, C. K., \& Lam, K. S., \& Chui, C. K. (2025, June), \emph{An Experiential Learning Framework to Harvest Synergy from College and Industry Partnership}
  Paper presented at 2025 ASEE Annual Conference \& Exposition , Montreal, Quebec, Canada .
  https://peer.asee.org/57615

LEI YANG, Chun Kit Chan, Kin Sun Lam, and Chun Kit Chui.  "An Experiential Learning Framework to Harvest Synergy from College and Industry Partnership".  2025 ASEE Annual Conference & Exposition , Montreal, Quebec, Canada , 2025, June.  ASEE Conferences, 2025.  https://peer.asee.org/57615 Internet.  19 Aug, 2025

\bibitem{asee_peer_57615}
  LEI YANG, Chun Kit Chan, Kin Sun Lam, and Chun Kit Chui.
  "An Experiential Learning Framework to Harvest Synergy from College and Industry Partnership".
  \emph{2025 ASEE Annual Conference \& Exposition , Montreal, Quebec, Canada , 2025, June}.
  ASEE Conferences, 2025.
  https://peer.asee.org/57615 Internet.  19 Aug, 2025

@INPROCEEDINGS{asee_peer_57615
author = "LEI YANG, Chun Kit Chan, Kin Sun Lam, and Chun Kit Chui"
title = "An Experiential Learning Framework to Harvest Synergy from College and Industry Partnership"
booktitle = "2025 ASEE Annual Conference \& Exposition "
year = "2025"
month = "June"
address = "Montreal, Quebec, Canada "
publisher = "ASEE Conferences"
note = {https://peer.asee.org/57615}
}

TY  - CPAPER
AB  - The rapid advancement of artificial intelligence (AI) and robotics presents substantial opportunities for innovation across diverse sectors. Industrial enterprises are actively seeking partnership with universities to develop effective testbed scenarios for integrating these emerging technologies into their operations and talent development. On the other hand, college students studying computer science, engineering or relevant fields possess fundamental knowledge of AI and robotics but often lack practical experience and exposure to real-world applications. 
This paper reports on an on-going collaborative initiative between the Tam Wing Fan Innovation Wing at The University of Hong Kong (or HKU InnoWing) and the Workforce Training Center of MTR, a public transport company in Hong Kong. The study identifies the challenges and opportunities in bridging this gap and proposes an experiential learning framework designed to empower college students with practical experience, while simultaneously equipping the staff from the industrial enterprise with insights necessary for successful technology adoption, knowledge transfer, and staff competency development required in workplace. Evaluation based on the self-reflections collected from the first cohort of three HKU InnoWing students and five MTR staff indicates positive outcomes from the experiential learning framework. Additionally, teaching materials as well as the programming codes for robots underscore the achievements of this collaborative initiative. The paper concludes with a discussion and future work to further advance this initiative.
The proposed experiential learning framework consists of several key components designed to foster synergistic collaboration between HKU InnoWing students and MTR staff. On the one hand, HKU InnoWing students organized three progressive workshops to equip MTR staff on how to program a robotic arm serving as the foundations for the testbed scenarios. This hands-on teaching approach not only reinforced the students' understanding of robotic operations programming and improved their interpersonal skills, but also demystify the robot arms for the staff and empowered them with the ability to program robots. In parallel, MTR staff arranged technical visits to familiarize HKU InnoWing students with the industrial work environment in depots, training centers, and frontlines, and outlining potential tasks that the robotic arms could fulfill within their operational framework. A collaborative project was conducted in a scenario-based learning approach, where a robotic system for cleaning CNC machines was developed to evaluate the outcomes of the previous hands-on workshops. 
We observed that this collaboration allowed students to gain insights into real-world applications and operational challenges faced by the public transportation industry while boosting the industrial partner’s confidence in exploring the development of testbed scenarios and equipping the frontline staff with the applications of the technologies. The synergistic partnership between the university and the industrial enterprise enhances both parties' understanding and capabilities in technology integration and deployment, ultimately benefiting students from the educational institution and talents within the industry partner. We also note that this co-training model can be generalized to other industries.

AU  - LEI YANG
AU  - Chun Kit Chan
AU  - Kin Sun Lam
AU  - Chun Kit Chui
CY  - Montreal, Quebec, Canada 
DA  - 2025/06/22
PB  - ASEE Conferences
TI  - An Experiential Learning Framework to Harvest Synergy from College and Industry Partnership
UR  - https://peer.asee.org/57615
ER  -