My research agenda brings together teacher education, artificial intelligence (AI), and argumentation in STEM education. Learning to facilitate argumentation that leads to productive mathematics and science learning is difficult. Teachers make many complex decisions when facilitating argumentation, such as what questions to ask, when to probe ideas, and even how to display and keep track of students’ ideas. From my experience as a teacher educator and researcher, I have witnessed teachers develop their expertise in facilitating collective argumentation from long-term professional development situated in their practice.
Challenges to replicating this professional development model are the time and resource intensive needs to support teachers within their context. To alleviate some of these obstacles, I seek to develop AI-based tools with natural language processing and computer vision technologies that are able to provide teachers with data, feedback, and reflective prompts regarding the argumentation in their classroom. For example, teachers could be provided a simple metric of percentage of warrants explicitly provided by students during argumentation episodes. The feedback from the AI-based tools would be part of an augmented intelligence loop that will assist teachers in making decisions about how to productively facilitate argumentation. Questions that I am thinking about include:
facilitation of argumentation in mathematics and science lessons and their students’ understanding of critical concepts in mathematics and science?
ability to address issues of access and equity when facilitating argumentation?