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Proceedings of the 2020 ACM Learning@Scale Conference.

Forthcoming

Two stances, three genres, and four intractable dilemmas for the future of learning at scale.

Justin Reich

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 towards 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-, algorithm-, 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 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: the Curse of the Familiar, the EdTech Matthew Effect, the Trap of Routine Assessment, and the Toxic Power of Data and Experimentation. (This paper adapted from the introduction to [38].)

Citations

Reich, J. (2020). Two stances, three genres, and four intractable dilemmas for the future of learning at scale. Proceedings of the 2020 ACM Learning@Scale Conference.

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