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Case Study

Summary

Kaplan is a worldwide, highly diversified education and training provider with a million-plus enrollment. Kaplan’s goal is to be a “learning engineering” company, distinctive in its application of learning science and learning measurement at scale. As part of this effort, Kaplan wants to establish company-wide quality in the learning environments and resources it produces, consistent with principles of evidence-based learning science. To accomplish this, Kaplan has created a training program for Kaplan “learning architects” — those who apply learning science at scale to design learning environments — and a formal learning audit program. Both the 40-plus-hour asynchronous training program and the audit program are structured around the Kaplan Way Checklist, a 12-item list of guidelines for instructional design grounded in learning science. (The first unit of the training program, focused on using the checklist, is publicly available.) After Kaplan learning architects complete the training and begin designing courses, they also pair up to review courses from other business units against criteria in the Checklist.

Evidence for the Design

The Kaplan Way Checklist is based on a large body of empirical results and principles drawn from learning science results, including Clark & Mayer (2011), Pashler et al. (2007), and Koedinger et al. (2010).

Context of Application

The training and learning-audit programs are being applied company-wide at Kaplan. They are applied to a wide array of learning environments targeted to a variety of learners – students in secondary schools receiving tutoring and college exam prep; higher education degrees including associate’s, bachelor’s, master’s, and even some PhDs; corporate training learners; and English language learners worldwide. The Checklist is also available to the public, and so it may be finding even broader use.

Datasets

A rich array of instructional design quality data is being accumulated on dozens of learning environments in a wide array of settings, including examples of best practices as they are identified.

Results

The process of pairing Kaplan instructional designers to evaluate each others’ work helps cement the principles more deeply, as the designers work creatively with each other to suggest improvements that fit within each others’ contexts. The data itself allows the organization to review progress, and prioritize where the next investments in learning quality should go. Each learning context has different learning challenges and priorities, but the consistency afforded by this approach allows the whole organization to learn from a wide variety of different learning contexts.

Broader Applications

This approach would arguably be helpful across a variety of other educational contexts — in higher education, K-12 education, or corporate training &emdash; where instructional designers need to be trained in designing evidence-based online learning environments.

Lessons learned / considerations for future

Using a consistent framework to improve “learning engineering” across a wide variety of learning environments requires a mix of flexibility and consistency. Each learning environment has different challenges to meet, so each calls for different priorities. Yet, since minds learn in consistent ways laying out evidence-based opportunities in a consistent way (and updating the framework with new best practices) allows for maximum creativity across boundaries of learning. The intent is that, as each learning environment moves forward on its priorities and generates data, these data can be understood rapidly by others thanks to shared language and ideas embodied in the framework.

Learn More

• Kaplan Way Checklist