“Smart” Practices: Machine Intelligence for Transforming Pedagogy and Learning

Advances in machine intelligence (MI) have coincided with recent shifts in education, across all levels and contexts, towards constructivism. As a pedagogical tool, MI promises new opportunities for adaptive learning that may help to fully actualize constructivist learning theory, transforming how learners interact with teachers, other learners, content and (technology) tools. Richer multi-modal environments for interaction, adaptive information aggregation and curatorial support, and personalized learning through analytics-informed responsive instruction, are among the possibilities, with teachers positioned in more strategic pedagogical roles vis-a-vis these teaching machine partners. So far, however, MI implementation in education has failed to live up to its promise. This failure has little to do with technological possibilities, and rather stems from limitations in how learning theory, pedagogy and imagination have informed the application of MI within education contexts. As Russell (The no significant difference phenomenon: As reported in 355 research reports, summaries and papers. Raleigh, NC, North Carolina State University, 1999) contends: Pedagogy, not technology, makes a “significant difference”. As education transitions to become a lifelong learning process within the twenty-first century’s “information age” context, outcomes must focus on domain knowledge as well as adaptive process skills, such as communication, critical thinking, self-direction and collaboration. In this chapter, the authors consider how MI implementation and pedagogical reform may address 21st learning goals. These will advance simultaneously with broader systemic changes, and shifts in institutional mandates towards digital resiliency. Purposeful and strategic implementation of MI at a societal scale will require careful long-term planning and new objectives, including education that supports development of MI user skills throughout the workforce and general population.