Team-based Learning with Artificial Intelligence Integration in Mathematics

Most students with a mathematical background may not possess good social skills in comparison with other graduates from different disciplines. Because of the mathematical nature, lectures are often instructor-led, i.e., lectures are often structured as an introduction of concepts, workings of examples, and reinforcement of key points. With this teaching structure, weak students may not be able to follow through while strong students find it tedious. With previous grants, the MA department has established an e-Help Center, which has several components: a WeBWorK e-system for students to do practice questions, a collection of more than 130 tutorial videos that cover most of the main fundamental mathematical concepts, consultation timeslot reservations for one-to-one tutorial and discussion boards. Statistics revealed the following: the videos have been viewed and downloaded more than 4,380 times, more than 500 consultation timeslots were reserved by students over each semester, and over 200 threads on discussion boards. It is evident that students are making good use of the additional resources, however, the above are more passive learning than active learning.    Active learning is often preferred over passive learning. Through Team-Based Learning (TBL), active learning can be achieved as students are provided opportunities to involve theoretical knowledge in solving either real-life problems or practice problems that require higher-order thinking skills through collaboration with their peers. Through the TBL approach, autonomy, peer learning, communication, and social bonding are provided, which are essential elements to increase motivation (Lysne et al., 2023). In the long run, students can foster and improve communication and interpersonal skills (Allen., R.E. et al, 2013), which is important for whole person development. As TBL is a teaching pedagogy, artificial intelligence (AI) should be used as a delivery tool.    In this proposal, we will specifically discuss the use of Generative AI (GenAI), Virtual Reality (VR), and Augmented Reality (AR) under the umbrella of AI. Previous literature supported that AI tools can be used as a facilitator to promote active learning such as engagement, flexibility, interaction (Allen., R.E. et al., 2013), and the “autonomy to learn (Ryan & Deci, 2000)”. This aligns with the TBL approach. With the use of TBL and AI tools, students’ inherent learning behavior, such as “achievement, satisfaction, attitude, critical thinking, self-learning abilities, and problem-solving skills,” will be improved (Allen., R.E. et al, 2013). In order to achieve the above learning outcomes, the TBL approach with AI tools as facilitators must be intricately designed and carried out. Therefore, the aim of this proposal is to provide a detailed outline of the TBL approach with AI as a facilitator tool to promote active learning, which includes helping weak students’ academic performance, encouraging strong students to achieve the above and beyond, and increasing students’ inherent learning behaviors such as motivation and interest.