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Research Review: The Science of Workplace Instruction


Wed May 12 2021

Research Review: The Science of Workplace Instruction

In the 2021 Annual Review of Organizational Psychology and Organizational Behavior, Kurt Kraiger and J. Kevin Ford address The Science of Workplace Instruction: Learning and Development Applied to Work. This is a relevant summary for L&D professionals, so it’s worth summarizing.

The overall endeavor includes several parts. The first is a proposal for a science of workplace instruction, which leads to 15 empirically supported principles. They also debunk several persistent myths that plague our industry. They conclude with requests for further research. As professionals, there’s serious value in here.


In the article, Kraiger and Ford proceed by defining learning as “the engagement in mental processes resulting in the acquisition and retention of knowledge, skills, and/or affect over time and applied when needed.” They proceed to propose a science of workplace learning. Here, they’re looking to explore the relationships between our instructional interventions and the final outcomes, with a goal to align them.

Core Instructional Principles

The initial part of the article details some principled framing about what learning is, who’s involved, and what appropriate research entails. While of interest to the science, we’re more interested in their prescriptions, which come in the form of a table of core instructional principles that have empirical validity. They’re grouped into categories, which make it easier to discuss, and include descriptions, an example, references, and effect sizes. This categorization itself is worth the effort to read the article and is broken up into these categories:

  • Content. We’re reminded to ensure content is directly related (coherence) and presented in appropriate conjunction in time and space (contiguity) and to ensure there’s appropriate preparatory material (advanced organizers).

  • Sequencing. The learner should be supported in the early stages (scaffolding), the challenge level should adjust to learner performance (adaptive difficulty), and practice should be broken up over different topics (interleaving).

  • Engaging the Learner (Cognitively). This includes helping the learner connect information to their experience (generative effects), supporting the learner’s learning (through prompts and metacognition), and enforcing the necessity of recall (retrieval, which is also known as the testing effect).

  • Effective Practice. The fourth set outlines specific strategies to conduct effective practice. Here the principles include switching contexts (variability of practice), spreading practice out (spaced practice), and a tight link between practice and performance environment (identical elements).

  • Develop Past Initial Mastery. The fifth category includes strategies to ensure that there’s appropriate practice (not just until you get it right). This includes helping the learner understand the outcomes of their actions (knowledge of results), appropriate information about the relation between their actions and the underlying models (feedback and feedforward), and sufficient practice (overlearning).

Closer Look at Delivery and Interaction

This collection of robust results may be well known from other sources already; however, it does represent a solid suite to guide design. There’s additional value in Kraiger and Ford’s work, once moving on from principles to delivery methods, and the interaction with learners.

An important component is what they term as aptitude-treatment interactions. ATIs are proposals that different methods work for different categories of learners. In general, the results haven’t proven valuable. In particular, they use this framework to analyze two persistent and hyped myths. The first is the so-called “meshing-hypothesis,” where you should vary the learning depending on the learner’s learning preferences or measured style. Of course, there’s no evidence that this helps and no meaningful way to measure a learner’s style. A second one is “generations,” where you instruct according to age. Instead, as they suggest, designing learning according to the best learning outcome is the more appropriate approach. Or, as they say, “Well-designed training works for all.”

Call to Action

Their last section calls for further research. They suggest that research supports that properly designed training works, but there’s room to continue to explore the best way to design and deliver training. They also ask for greater investigations into self-directed learning, pointing out that learners aren’t necessarily effective at their learning, and there’s room for improvement. A third suggestion is to further explore the application of these principles to technology-mediated environments: simulations, games, and virtual reality. All are apropos.


The call for the application of learning science to workplace learning is valid. There is much undertaken under workplace learning that doesn’t reflect what’s known. The remedy is greater awareness and application of the results of research. This paper, written in academese and with much philosophical framing, may be hard to wade through, but points in the right direction and provides solid guidance. As such, it’s recommended.

If you’re interested for a deeper dive into many of the core instructional principles and delivery methods discussed in this research review and more, check out Learning Science for Instructional Designers.

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