Year: 2025
Type: conference-paper
Abstract: As we usher in the Industry 4.0 age, artificial intelligence (AI) is seeing increasing impact on education. Educational practitioners often follow the first principles of instruction (FPIs), such as problem-centered teaching, activation, demonstration, application, and integration, when designing intelligent computer-assisted language learning (ICALL) environments. Against this backdrop, generative inquiry learning (GIL), a new model of education, offers new solutions to the challenges that education faces currently as AI penetrates every aspect of our lives and incurs “technological alienation” in the domain of education. Thus, in the present work, a teacher-student-machine collaborative framework based on the 4C/ID model is put forth, and the adoption of AI in instructional design and student inquiry is discussed. Moreover, a case study on the module “Python Programming” was performed to investigate how the reconstruction of traditional teaching processes could improve the student's critical thinking, creativity, and self-motivation in learning. It was found that GIL could reduce the students’ cognitive load and improve the teachers’ teaching efficiency, providing strong support for educational reform to cultivate talent better suited to the needs of the development of Industry 4.0.
Authors: Gang Zhou, Jiawei Huang
Institution: Naval University of Engineering
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: gold
OpenAlex ID: W4413986550