Two Stances, Three Genres, and Four Intractable Dilemmas for the Future of Learning at Scale

Abstract

The late 2000s and 2010s saw the full arc of a dramatic hype cycle in learning at scale, where charismatic technologists made bold and ultimately unfounded predictions about how technologies would disrupt schooling systems. Looking toward the 2020s, a more productive approach to learning at scale is the tinkerer's stance, one that emphasizes incremental improvements on the long history of learning at scale. This article offers two organizational constructs for navigating and building on that history. Classifying learning-at-scale technologies into three genres-instructor-guided, algorithm-guided, and peer-guided approaches-helps identify how emerging technologies build on prior efforts and throws into relief that which is genuinely new. Four as-yet intractable dilemmas-the curse of the familiar, the edtech Matthew effect, the trap of routine assessment, and the toxic power of data and experiments-offer a set of grand challenges that learning-at-scale tinkerers will need to tackle in order to see more dramatic improvements in school systems.