Artificial Intelligence Innovations for Multimodal Learning, Interfaces, and Analytics

Abstract

The twenty-first century has brought with it a growing variety of authentic and engaging learning environments. While significant portions of human learning still take place in traditional classrooms, researchers and educators have innovated several learning experiences that are embodied, project-based, inquiry-driven, collaborative, and open-ended. Furthermore, there has been greater acknowledgement of the varying timescales and contexts where meaningful learning takes place, as well as greater attention to previously underappreciated competencies like creativity, self-regulation, and collaboration. This expansion in the types, contexts, and timescales of human learning necessitate novel analytic approaches. This chapter will discuss how artificial intelligence-based tools and technologies can help researchers and practitioners navigate and enact these novel approaches to learning, while also providing a meaningful lens for student reflection and inquiry. Consequently, this chapter includes discussions of (1) technologies that provide learners with a broader set of modalities to showcase their knowledge, (2) tools that offer insights within groups of students using audio/video information, and (3) analytic techniques and interfaces for helping researchers collect and analyze different types of multimodal data across contexts. The chapter will also discuss some of the ethics surrounding these types of data and analytic approaches.