Chen, Woolcott, and Sweller (2017) provided suggestions to structure Massive Open Online Courses (MOOCs) using instructional design principles that are based on Cognitive Load Theory (CLT):
1) Goal-free effect: Use goal-free instead of goal-specific problems
Goal-free problems (e.g., find the value for as many angles) reduces extraneous load as they help students to focus on solving the problem in a stepwise manner. In contrast, goal-specific problems (e.g., find the value for angle x) require students to consider a sequence of related angles that leads to the final goal, and hence, increases element interactivity.
2) Worked example and problem completion effects: Use effectively structured work-examples for students to study
Providing students with well-structured and effective worked examples help students to learn better in comparison to having students solve problems by randomly generating solutions and checking if they have the correct solution in the absence of worked examples. However, it is important to note that providing poorly structured worked examples and providing worked examples to students who do not need them can lead to negative effects. Therefore, instead of providing full solutions in the worked examples, instructors can also consider partial worked examples in the form of completion problems.
3) Multimedia design principles: split-attention, redundancy, and modality effects
When designing multimedia presentation, instructors should consider the relations between multiple sources of information presented in the form of text, diagrams, and narration. To avoid split attention effect, instructors can consider integrating text and diagrams that cannot be understood in isolation. To avoid redundancy effect, instructors can consider whether the information presented is necessary for learning. The modality effect concerns the presentation of information in both auditory and visual formats. Instructors should consider how best to present information in both formats without both making the information redundant.
4) Expertise reversal effect: adapt instructions according to students’ levels of knowledge
Necessary information for novices is perhaps redundant information for experts. Given that students in MOOCs are highly diverse, to cater to the different levels of expertise, instructors can consider assessing students and providing instructions that are appropriate for students’ level of knowledge.
While these effects have been found to be fairly robust in online learning environments, they need to be systematically examined in MOOCs to know how well each of the effects can be generalized to learning in MOOCs. Nonetheless, applying designing principles according to CLT in MOOCs seems like a promising direction for improving design of MOOCs.