In my previous blog, I discussed the ways in which Benjamin Bloom’s revised Taxonomy of Educational Objectives can be leveraged to define effective and meaningful objectives for an eLearning course at the outset of its development. Thanks to Bloom, we’re armed with an active vocabulary of verbs to help us articulate our learner’s desired outcomes, as well as a solid hierarchical structure of cumulative learning processes, with lower-order thinking skills undergirding more complex, higher-order ones.
So now what? We have the words, we have the layout, and we have a firm grasp of what we want our learners to be able to do at the end of their training. How do we put it all together into the writing of coherent objectives? To start with, it may be helpful to shift our focus from the learning processes Bloom outlines to the results we expect to see from our instruction. Robert Mager provided a roadmap for doing just that with his book Preparing Objectives for Programmed Instruction.
Mager and Performance-Based Learning Objectives
Like Bloom, Mager was concerned with learning that could be measured and observed in order to gauge comprehension (and therefore the success of the lesson or training). He defined these outcomes even more precisely than Bloom by breaking them down into three separate components:
- the performance of an action by the learner;
- the conditions under which the action is to be performed;
- and the criteria that define whether the learner’s performance is acceptable as a measure of success.
The Three Components of Learning Success
We’re already familiar with performance verbs that demonstrate comprehension from my previous blog on Bloom. The other components of Mager’s model are a little more nuanced.
In a nutshell, Mager’s conditions set the parameters within which the learner will need to perform the action that proves their comprehension. Often these conditions are the impetus for the performance of an action, or the “givens” or limitations placed upon it. Examples might include having a learner solve a series of equations without the use of a calculator, or setting up a specific scenario for them to respond to, such as processing a merchandise return for a customer.
Mager’s criteria establish measures of success to gauge your learner’s comprehension: for example, answering nine out of ten answers correctly or completing an exercise within a specific amount of time.
Test your understanding of Mager’s performance-based learning objectives by matching the performances, conditions, and criteria below to their correct component in his formula:
Applying the Mager Methodology to eLearning
The clarity of purpose and intent provided by Mager’s performance-based learning objectives benefits both the learner and the instructional designer because it clearly defines the scope of the instruction itself. Strong learning objectives establish both what the learner will need to demonstrate, and to what degree they will need to do so. It’s important to note that Mager acknowledged that including both criteria and conditions in your objectives may not always be practical, depending on the material at hand; use them at your own discretion.
eLearning is a terrific medium for the application of Mager’s theory because it allows the developer to build the tools necessary for the learner to achieve success directly into the framework of the lesson or training. These tools can include interactive elements such as drag-and-drop or fill-in-the-blank activities, periodic skills assessments, and so forth. Mager’s theories can also be applied at every level of eLearning course design, which addresses one more nuance of objective-writing: terminal versus enabling objectives.
Terminal vs. Enabling Objectives
Often, the objectives you define at the outset of your eLearning don’t apply to every stage of the learning process. Bloom’s revised taxonomy taught us that a learner has to build upon prior knowledge to attain higher levels of learning; similarly, the objectives you set for your learner will probably build upon one another to allow the learner to achieve success.
Terminal objectives describe the learner’s expected performance by the end of the course or training, while enabling objectives define the skills, knowledge, or behaviors learners must learn in order to fulfill those terminal objectives.
It’s important to establish at the outset of your eLearning what kind of objective you’re defining. You can make this distinction by figuring out how much your learner’s performance at the end of their training will depend on prior knowledge or training. Fortunately, Mager’s formula can be applied equally effectively to both kinds of objectives— after all, you want your expectations to be clear to your user no matter where they are in the learning process!
Use this job aid I created, to put Mager’s theory into practice in writing your own eLearning objectives.
This blog post from Convergence Training provides an excellent overview of Mager’s approach to writing performance-based learning objectives. If you’re interested in taking a deeper dive into his methodology, it’s more than worth your while to check out a copy of his original book, Preparing Instructional Objectives: A Critical Tool in the Development of Effective Instruction, 3rd Edition (Center for Effective Performance, 1997).