Traditionally, education relies on a linear relationship between enrollment and staff; rising enrollment dictates increases to staff with some expertise (such as teaching assistants, TAs) for evaluation. This relationship is expensive, so learning at scale has largely deemphasized expert evaluation and feedback. Two organizations, though, have used different models to scale up class size online while retaining this expert evaluation and feedback. In this paper, we analyze the methods these two organizations have used to increase enrollment while preserving scalability and feedback. We observe an academic program has scaled feedback with traditional TAs by relying on unique characteristics of its student body, while a commercial program has done so with a novel, network-based model. These successes show the potential of learning from experts at scale.
The full paper “Scaling Expert Feedback: Two Case Studies” can be found here.