And, while this may seem like an abstraction to many, course designers are well aware of the limitations or impossibilities proposed by a perpetual motion machine.
Courses and course designs can’t keep moving and improving without considerable effort from learning designers and instructional staff (their energy source).
Online course design, in particular, is intentionally iterative. At TEL Library, our curriculum developers and learning designers begin by creating an initial course outline that is tied to learning outcomes and mastery goals. They then design content, activities, and assessments that are consistent with those outcomes and goals. After creating and reviewing their product, they release it to students.
But this initial release is only the beginning of the online course design process!
As students work through a course, they discover unintended gaps or inconsistencies in the content. Course instructors review student work and find weaknesses in specific information and assignments. Our learning designers recognize learning inefficiencies or areas of possible improvements by collecting data related to student performance related to outcomes.
All of this information is collected and reviewed, and then our learning design team goes back to the drawing board to determine what adjustments they can make to improve the course for the next round of students.
And this is only an example of one iteration.
As every online learning designer knows, a course is never done. There is always room for learning improvement. New technologies and engagement models provide a steady flow of information, activity, and assessment options. Additionally, with online courses, we have a constant stream of quantitative data from different sources that give us insights into student behavior or success.
At TEL Library, this work occurs both at the individual course and curriculum levels. Our team Certified Learning Environment Architects conducts ongoing evaluations of individual courses. At the same time, since we use a common learning environment design across our entire curriculum, the team also reviews our course templates at a macro level, searching for possible redesign opportunities to improve student success.
One example of this macro-level redesign is currently underway on our course modules.
For context, TEL Library courses consist of lessons — each one self-contained learning environment devoted to a single subject/course concept — and modules, which are collections of 4-6 lessons. Since our lessons are designed to function independently as stand-alone learning objects in our free reference library, course scaffolding and summative assessment or mastery work must be designed at the module level.
The challenge for our course designers has been, “What type of activities do we include in our lessons and which ones are more appropriate at the module level?”
Initially, we designed our lessons to function as “mini-courses” that had most components for potential knowledge acquisition and mastery built in. This lesson model contained media and information, engagement activities, research and reflection assignments, discussions, and formative quizzes. These proved effective at the micro-level but had two problems: (1) they required too much time for students to complete as part of a course product, (2) they were too difficult to update and integrate efficiently with other lessons as part of a General Education curriculum.
Faced with that realization and information from current students and instructors, our learning designers have begun working on a revised module design that provides improved support for our different product goals. First, they are revising the amount of non-information content provided in our lessons. This allows our lessons to remain as stand-alone learning objects focused on concept information but remove the bulk of the original learning activities that were included in them. In addition, the team is reimagining our course modules as “hubs” that promote information review and study (in our lessons) that migrates toward knowledge acquisition and understanding.
In this model, we frame learning expectations and mastery requirements at the outset of each module and allow individual learners greater flexibility in how they work through the information content to prepare for demonstrating what they have learned — via discussions, summative quizzes, and mastery-evidence assignments.
Our goal is to begin applying this redesign to come of courses in January. Of course, this will only be the next iteration the ongoing iterative process that is part of the perpetual motion learning design machine.
– Rob Reynolds, Ph.D.