Spinning logos, three-dimensional graphics, animated transitions, audience interaction, audio narration, background music, walls of text — at first glance, this may look like a description of a glitzy new Super Bowl commercial or Hollywood’s next major blockbuster movie. However, it is in fact a description of an e-Learning course.
In an effort to engage learners and to maximize their learning experience, e-Learning developers often experiment with various combinations of instructional methods and media. For example, access the first three screens from a sample Web-based lesson located at http://www.clarktraining.com/mtest. After reviewing these screens, grade this small sample on its instructional effectiveness from A to F, and list some reasons for your grade. Use the checklist in Table 1 to identify the instructional treatments that you observe.
Figure 1 Three factors that affect cognitive load
Using the same checklist, consider the e-Learning courses that your organization develops. What instructional methods do these courses typically employ? What combinations of media do you use? How do you currently provide practice and assessment? Do learners complain that the courses are too long? Too boring? What methods have you used to improve the quality of your e-Learning?
This article provides practical, research-based guidelines that you can readily apply to your courses to make them more efficient. Efficient instruction leads to better learning, faster learning, or both. In an age of increased information load and decreased training time, maximum efficiency is more important than ever! To understand how you can make your courses more efficient, we will first look at cognitive load theory and how it relates to human learning.
Then we will examine the three types of cognitive load that instructional materials impose on the learner. Finally, we will review three guidelines that you can use to make your learners’ experience more effective and more efficient.
Cognitive load theory
In 1956, George Miller introduced the magical number 7±2. According to this psychological principle, working memory can only process seven chunks of information at any given time, plus or minus two items. Once a learning task exceeds these cognitive limits, our ability to process and retain information diminishes. As an example, consider which task is more difficult: trying to memorize and recite a seven-digit phone number, or a sixteen-digit credit card number.
Since the introduction of Miller’s 7±2 rule, John Sweller,
Professor in the
Figure 1 illustrates three factors to consider when applying principles derived from cognitive load theory: the learners’ level of expertise, the complexity of your content and, of course, the instructional materials. As part of the analysis phase, you should determine whether your course’s target audience includes learners with no prior knowledge of the subject matter, with some intermediate knowledge, or perhaps even with advanced expertise. In addition, you should analyze your instructional objectives to determine whether they are simple or complex. The guidelines of cognitive load theory must be adapted based on the complexity of the content and on the experience of the learners.
In addition to these factors, one should also consider the media used to deliver the instruction. Two common e-Learning delivery media are asynchronous Web-based training (WBT) courses and synchronous virtual classroom sessions. These delivery media have unique attributes that impose varying levels of cognitive load. For instance, since an instructor facilitates virtual classroom sessions, such sessions reduce the learner’s ability to control the pace of the course, as one might find with a WBT, and therefore impose greater cognitive load. For the same reason, certain types of methods or media such as animations or video may impose more cognitive load on the learner.
Types of cognitive load
Table 2 summarizes the three types of cognitive load: intrinsic, extraneous, and germane. Certain forms of cognitive load are beneficial while others waste limited mental resources. Your goal as an e-Learning developer should be to balance these three forms of cognitive load in your instructional materials to maximize learning efficiency.
Figure 2 Balancing three sources of cognitive load to maximize efficiency
Figure 2 illustrates how an e-Learning course designer can exploit these three types of cognitive load. Intrinsic cognitive load will depend on the complexity of your instructional content. Therefore, your goal as an instructional designer is to manage intrinsic load by segmenting and sequencing your instructional materials to help the learner deal with the complexity of the content. Extraneous cognitive load imposes mental work that does not promote learning. Think of extraneous cognitive load as irrelevant load. There are a number of guidelines for minimizing extraneous load, many involving the appropriate use of visuals, audio, and text in your training environment. In contrast, germane cognitive load is actually beneficial to learning. Therefore, to improve the efficiency of your e-Learning courses, you should maximize the opportunities for germane load.
The three forms of cognitive load are additive. To optimize instructional efficiency you should manage intrinsic cognitive load, minimize extraneous cognitive load, and maximize germane cognitive load. To hear a brief introduction to extraneous and germane cognitive load from Dr. John Sweller, access the video located at http://www.clarktraining.com/mtest/video. When the video screen appears, press the play button to hear the commentary.
Manage intrinsic load: Teach supporting knowledge separate from teaching procedure steps
Compare the two course sequence plans shown in Figures 3 and 4. Which one do you believe imposes more intrinsic load?
Figure 3 Lesson Outline 1
Figure 4 Lesson Outline 2
Many e-Learning courses focus on teaching learners how to perform procedural software tasks, such as the one shown in Figures 3 and 4. You could use a simple table, job aid or even a software simulation to demonstrate how to create a formula in Microsoft ® Excel. One way that you can manage the intrinsic load imposed by this procedural content is to segment supporting knowledge from the actual procedure itself.
For example, in Figure 3, note that background information that supports each respective step is presented concurrently with that step. While a learner needs this supporting knowledge, research by Pollock and colleagues (see References at the end of this article) indicates that novice learners benefit when they learn supporting information separately from complex procedural content. By sequencing supporting facts, concepts, and principles prior to the procedure, as in Figure 4, you can improve the efficiency of your instruction.
