Chengliang Wang

Chengliang Wang

Collaboration

Collaboration & Routine

Collaborative research connects intelligent learning environments, AI agents, programming learning, public academic service, and method support.

Research NetworkCross-institutional collaborators and mentors
AI AgentsVertical design and implementation
Learning EnvironmentsSpaces, programming learning, and experience
Public ServiceJournal metrics, courses, and method resources

Collaboration

  • I have collaborated extensively with PhD students Yupeng Lin and Haoming Wang from Tsinghua University, as well as Associate Professor Teng Yu from Guangdong Polytechnic Normal University. I also maintain close professional ties with Associate Professor Yuhui Jing of Zhejiang University of Technology, Yuanyuan Li from Shanghai Normal University, and Xiaojiao Chen, an incoming Master’s student at Beijing Normal University. Furthermore, I collaborate with Zihan Xiao from the Pudong Institute of Education Development and Professor Rustam Shadiev from Zhejiang University. Additionally, Jian Dai has been a vital collaborator of mine; though he has transitioned to a direct PhD program in the School of Management, he has recently published several high-quality papers in AJG 3 journals.

  • Our collaboration revolves around intelligent technology-enabled programming learning (instructional foundation), the construction of intelligent learning environments (learning spaces), and the design and implementation of AI Agents. Beyond these areas, I am also interested in the transformative value of technology in language learning—a research direction rooted in my own personal experiences. Additionally, I occasionally contribute to pedagogical methodology; I have recently developed application standards for bibliometric mapping and a user guide for Qualitative Comparative Analysis (QCA), which is currently under external review.

  • In summary, my research begins with the construction of intelligent learning environments and the vertical design of AI Agents. It focuses on three core pillars: learner experience, behavioral modeling, and cognitive development, ultimately exploring how cutting-edge AI can empower teaching, learning, management, and assessment.

  • Our team is also committed to academic public service. We have compiled a set of key metrics for SSCI journals in Education, which can be accessed for free. Additionally, I offer a series of free courses on my Bilibili homepage, covering topics such as Structural Equation Modeling (SEM), Quasi-experimental Design, Systematic Literature Review writing, and Bibliometrics. In the future, I plan to launch a series of methodology courses covering Qualitative Comparative Analysis (QCA) and Artificial Neural Networks (ANN).

  • I maintain an open attitude toward collaboration; however, to ensure high-quality outcomes given my current capacity, I apply certain baseline criteria for new partnerships. Nevertheless, I welcome potential collaborators to reach out via email . I aim to make time for a brief discussion with all inquiries to efficiently explore the possibility of working together.

Routine

  • Feb 19 Arrive in Sydney
  • May 29 - Jun 04 Hong Kong (GCCCE @ CUHK)
  • Jun 30 - Jul 02 Shanghai Visit
  • Jul 02 - Jul 18 Shaoxing for holiday
  • Jul 18 - Jul 23 Shanghai for WAIC (World Artificial Intelligence Conference)
  • Nov 30 - Dec 05, 2026 New Zealand for ICCE 2026
  • Dec 06 - Dec 30, 2026 Travel in New Zealand and Australia (please contact me if interested in joining)
  • Dec 31, 2026 - Feb 15, 2027 Return to China