To successfully deliver personalized learning, an eLearning developer needs a clear understanding of what the term means. And that can be a problem, since so many different definitions for personalized learning are floating around. Let’s start with The eLearning Guild’s recent definition of adaptive learning: a teaching approach where the delivery of content and assessment are tailored to each learner’s abilities and needs. That sounds like a good approach to eLearning, but it raises questions for eLearning designers and developers.

In a January 2016 “Best of” Webinar, “The Future of Learning: Where Should We Focus This Year?” Guild Master Nick Floro acknowledged that the trend toward wanting “everything customized to my needs—when I need it, where I need it, how I need it—and I want it to apply to what I am doing” presents a challenge to developers, who are generally creating courses aimed at large, diverse audiences. To meet this challenge, developers need to focus on key aspects of the learning. But, which ones?

Dr. Yong Zhao, a scholar, educator, and expert on educational design, wrote a detailed description of personalization in education: “Outcome vs. Process: Different Incarnations of Personalization.” He divides personalization into two broad categories: personalization of process, which allows learners to make choices about how they learn; and personalization of outcome, which permits learners to define the end results of their learning.

“Corporate training is similar to education in that it has a predefined curriculum, but there is a need that is driving it, whether something is changing in the business, software, whatever, leadership development—there is usually some driving force that says, ‘I need to provide this to my people,’” said Guild Master Jean Marrapodi. This means that, in corporate eLearning settings, the outcome or learning goal is usually defined by someone other than the learner. In other words, only process personalization is likely to be feasible, not outcome personalization.

Slicing, dicing, and reframing the learning process

A traditional learning path has all learners work though a fixed set of modules, in order, before completing an assessment. To personalize the learning process, it’s necessary to leave that narrow one-way path. Zhao defines several elements of the learning process that you can personalize. The ones most relevant to the corporate eLearning environment are: pace, content, and assessment. Each of these raises development challenges.

Pace might be the most natural element to personalize using eLearning. In fact, B.F. Skinner advocated using technology to facilitate self-paced learning in 1954! In a well-designed asynchronous eLearning module, learners can proceed at their own pace and get immediate feedback. This personalization of the pace is baked into the design and the development.

When content is served up in standardized portions, learners waste time and, more significantly, become bored and disengaged, as they are required to cover material they already know. Adding a diagnostic assessment at the beginning of training can provide an individualized picture of what each employee already knows. The eLearning module could then present each learner with (or allow the learner to choose) only the modules he or she needs, allowing learners to skip material they already know. To ensure that all learners complete the training with the needed skill set or knowledge, all learners might take the same final assessment, whether that is in the form of a test, a skills test, or some other means of evaluating their progress and performance. Providing a customized path to that assessment is a first step in personalizing content.

A second step along that path would entail varying the types of content or the medium of presentation, allowing learners to choose their preferred format. Some might choose to read an article, while others watch a video or engage in a simulation. Creating a range of content modules to cover each topic presents its own challenges, of course: budget, time to develop, and technology required to create and present the various types of content.

Assessment might be the element that lends itself least to personalization. If the goal of an eLearning module is for each employee to be able to complete a procedure, then the assessment will be an evaluation of the employee’s performance on that procedure. However, even within the constraint of assessing all learners on the same skill set, some variability is possible. Assessment can, and often is, done using a standard multiple-choice exam. But this is far from the only option. You can test skills using games, simulations, or collaborative projects. The possibilities are limited by the type of knowledge or skill you are testing, the tools and technology available—and the designers’ and developers’ creativity.

Personalizing content is where developers can shine

Much existing eLearning content consists of in-depth course modules of an hour or more. Today’s learners rebel against such time-intensive and inflexible training. In his webinar, Floro used the metaphor of a loaf of bread; to personalize eLearning content, developers must slice the loaf.

The first step is inserting tags and titles and indexing existing content so that learners can find and access smaller slices of it. This lets learners take control over their learning by choosing which sections to access and when.

Once the developers have repackaged long eLearning courses into short, efficient modules, and they’ve indexed and tagged the modules so that each learner can find the relevant ones quickly, is their job done?

Nope. It’s not enough to tag each module as a discrete learning unit. While that increases the learners’ control, it also makes it easy for them to miss important content.

Building connections among the new, short eLearning modules can reinforce skills and encourage learners to build their knowledge while progressing on a path that, ultimately, leads them to that common assessment.  

Developers can build a nonlinear structure that connects modules in logical ways. If skill B requires mastery of skill A, a learner who jumps to skill B can be offered articles or training to refresh skill A. At the completion of a module, suggestions can urge learners along the path to modules that reinforce newly learned skills, provide practice applying those skills, or introduce a new challenge or skill that requires mastery of the newly learned skill. Depending on the content, it might be appropriate to build in feedback or suggestions for additional learning or practice.

In a diverse pool of learners, some will pick and choose discrete modules according to their immediate learning needs and skills gaps. Others will progress through the modules following a more linear path. Some might jump to the end, heading straight to the final assessment. Building in this flexibility increases the likelihood that learners will engage in and complete the training they need—with enhanced performance as the result.