The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Constructing Human Service Learning in the AI Digital Sphere: China's Case of LivePBL DEEP Method
Abstract
Service learning, a critical pedagogy combining community service with academic goals, fosters civic engagement, practical skill development, and social responsibility. This chapter explores how integrating Gen AI can enhance project-based service learning to address real-world social challenges in higher education (HE). Despite its rapid growth in HE, Gen AI still faces limitations, particularly the lack of a human-centred design method that reflects real-world contexts and the risk of oversimplifying complex tasks, leading to a more automated, less humanised learning process. The DEEP method, structured upon four co-designing phases—direction, education, event, and project—offers a hybrid solution, creating an adaptable and scalable framework for constructing a project with Gen AI for co-designed, social, and personalised learning. The chapter also illustrates the LivePBL project, piloted to train pre-service teachers in China, demonstrating how the method can effectively integrate Gen AI with hands-on co-design to enhance the learning environment and societal exchange.
Related Content
|
Frederic Andres.
© 2027.
14 pages.
|
|
Kalsoom Safdar, Khairul Najmy Abdul Rani, Mohd Aminudin Jamlos, Siti Julia Rosli, Muhammad Usman Younus, Zanab Safdar.
© 2027.
27 pages.
|
|
Bani Adam, Binastya Anggara Sekti, Muhammad Adi Zacky Zahran.
© 2027.
24 pages.
|
|
Swetha Margaret T. A., Renuka Devi D..
© 2027.
31 pages.
|
|
Maurice Saluschke, Michael Schulz.
© 2027.
30 pages.
|
|
Mirjam Sepesy Maučec, Gregor Donaj.
© 2027.
16 pages.
|
|
Jorge A. Ruiz-Vanoye, Ocotlan Diaz-Parra, Ricardo A. Barrera-Cámara, Alejandro Fuentes-Penna, Francisco R. Trejo-Macotela, Jaime Aguilar-Ortiz, Eric Simancas-Acevedo.
© 2027.
21 pages.
|
|
|