Modified Flipped Learning as an Approach to Mitigate the Adverse Effects of Generative Artificial Intelligence on Education
Abdulmalik Ahmad Lawan, Basheer Ridwan Muhammad, Ahmad Muhammad Tahir, Kamaluddeen Ibrahim Yarima, Abubakar Zakari, Aliyu Hassan Abdullahi, Adamu Hussaini, Hafizu Ibrahim Kademi, Abdullahi Aliyu Danlami, Mustapha Abdulkadir Sani, Alhassan Bala, Safiya Lawan
Abstract
Generative Artificial Intelligence (GAI) systems such as ChatGPT, which create new educational content based on their training data, have led to debates on the systems’ impact on educational practice and the question of whether academia should embrace or reject these tools. Flipped learning is a pedagogical approach that reverses the traditional order of teaching and learning. Instead of receiving direct instruction in the classroom, students are introduced to the learning material before class. This study explores the potential of modified flipped learning as an approach to mitigate the effects of GAI on education. The study highlights the relevance and importance of flipped learning and GAI in the 21st-century educational landscape and proposes a modified flipped learning model that combines the individualized and active learning aspects of flipped learning with the adaptive capabilities of GAI. The study also addressed concerns related to the responsible use of GAI, ethical considerations, and the role of educators in guiding students’ interactions with intelligent systems. In conclusion, the proposed modified flipped learning model would empower students to actively engage in the learning process and take ownership of their education by replacing the traditional role of the teacher with the use of GAI systems for pre-class activities and content creation. However, further research is needed to explore the effectiveness of flipped learning in this context and identify the best ways to implement this approach in the classroom.