STEP | TEA Lab research scientists Emma Anderson, Christina Bosch, and Grace Lin were featured on the Silver Lining for Learning podcast Episode 221, where they shared insights and thoughts on AI education and AI for Education.
To watch or listen to the podcast, click here.
From the Silver Lining for Learning website:
In this episode, we will hear from the MIT STEP Lab on two of their AI initiatives: Collaborative Artificial Intelligence for Learning (CAIL) and RAICA (Responsible AI for Computational Action). Collaborative Artificial Intelligence for Learning (CAIL) is a research and design project at the MIT Step Lab focused on integrating innovative AI tools in the classroom to support learning in collaborative groups. RAICA (Responsible AI for Computational Action) designs curriculum focusing on computational action with artificial intelligence for late primary, middle, and secondary students.
Collaborative Artificial Intelligence for Learning (CAIL) is a research and design project focused on integrating innovative AI tools in the classroom to support learning in collaborative groups. Students interact with AI-powered conversational agents in group work and discussions. The agent is envisioned as a peer who would promote deeper thinking on the topics instead of an efficiency tool. We also aim to provide real-time information to teachers and students to support teachers’ formative assessment and students’ self reflection. As part of the project, we are building out CAILA (Collaborative Artificial Intelligence for Learning and Analysis) to process the real-time data while keeping with human- and child-centered design principles and keeping humans in the loop. To date, we have created conversational agents to work with high school students in PBL data science workshops and investigated potential roles the agents could play in team-building exercises. Our lines of inquiry span from the personas and roles of the agents to analytic tool development to formative and reflective assessments for learning.
The goal of the RAICA curriculum is computational action with artificial intelligence for late primary, middle and secondary students. In order for students to take computational action with AI, RAICA has designed lessons that provide opportunities for students to apply computational thinking and responsible design while growing their AI fluency. We approach all of our work with a constructionist pedagogy, a belief that students learn best by constructing their own knowledge and being creative. We use Universal Design for Learning (UDL) and the Technological, Pedagogical, and Content Knowledge (TPACK) frameworks to guide the design of RAICA’s materials to support student and teacher learning.
