Inductive and Deductive Learning, Choosing the Right Approach Within Your Virtual Classrooms
Dozens of instructional design theories exist, and selecting which to put in to practice during a particular learning or development initiative within your organization can be a challenging decision. A lot rests in this choice as it can play a large role in projecting the overall success or failure of a particular curriculum. By broadening ones understanding of the unique benefits within these different approaches the more likely one is to employ the format that best stimulates their learners and is most likely to help them achieve their development goals.
Within this post we discuss at a high level two core approaches, inductive and deductive learning, in hopes that this walkthrough will help you and your team make better decisions on which to use within your digital curricula and virtual classrooms.
What is Deductive Thinking?
Deduction is a mental process which all of us participate in every day, and it can be best described using a simple if/then statement example: “if I oversleep and show up late to a 9am meeting, then I will be perceived as being unprepared.” This is because we have been taught that, at least in North America, there is an established social rule that says if you display punctuality it implies forward planning and time management, thus we deduce that by not doing so we will imply the opposite.
Those of us who own cars deduce that if we put diesel in our gasoline engine, then we will encounter significant mechanical issues. This is because at some point we learned, likely from our parents, the important rule that diesel engines process fuel in an entirely different way than their gasoline counterparts do and were encouraged to practice double-checking the label on the fuel pump before placing the nozzle in our car.
Deductive Learning in Application
When thought about in terms of applying this concept in a classroom setting, a deductive environment is one where instructors carry out lessons by introducing rules, discussing adjacent themes and concepts, and ultimately having students complete example tasks or problems to practice the particular rules that have been introduced. Instructors conduct lessons largely in lecture form with minimal dialogue between them and their learners where rules are presented first with examples that then follow.
An example of a deductive approach inside of Adobe Connect might look like a live training session on Photoshop fundamentals where an instructor is teaching their students how to resize images such that their resolution is optimized for a particular screen type and size. The teacher would look to drive home the rule that if they undersize images for a project that is to be optimized around devices with retina displays then they will encounter unsatisfactory levels of pixilation throughout. After presenting this rule to the class the instructor might then further reinforce the concept’s rules by having students individually move through a simulation built with Adobe Captivate inside of the virtual classroom.
Some Common Critiques
While a common critique to the deductive learning approach is that it places too much emphasis on the teacher and not enough on the student there are, however, circumstances in which this format can be highly effective. Deductive methods of instruction are efficient in conveying minimally complex topics and also in establishing the foundation for higher level problem solving. It is important to call out that the operative phrase in the previous sentence of ‘minimally complex’ is highly subjective, and the ways in which an instructor controls for and adjust the aspects of relative complexity amongst learners is where the true power of the deductive learning technique rests.
By using deductive learning either in a straightforward and short curriculum or to introduce a set of topics that will be foundational to more abstract subsequent concepts, instructors can help their learners acquire information rapidly and efficiently.
Of great importance is that instructors consistently ask themselves whether or not their deductive learning environments are maintaining sustainable cognitive load- the amount of information learner’s working memory can process at any one time. Lecture formats can often gloss over the fact that working memory capacity has a set upper bound for the rate at which it can process information, and thus sustainable pacing is central to avoiding overwhelming this cognitive function in learners.
What is Inductive Thinking?
Has an instructor ever presented to you a set of interrelated examples and asked you to infer what underlying rules might bind particular items from the larger set together in to subsets? If you answered yes, then you were being taught through the use of induction.
An example of this would be if a teacher were to provide a list of thirty items found on a farm, (e.g. soil, fertilizer, pesticides, barns, silos, sheds, tractors, propeller planes, trucks), and students were then asked to form a set of categories the terms could be grouped in to. What might emerge are crop growth, storage, and equipment.
Subsequently students might be asked to take the thought process employed in forming these groups a step further so to develop working hypothesis about unknown and upcoming information that might emerge within the lesson. This could look like students engaging in a mental simulation around what particular weather events might imply in terms of the effect they would have on the previous categories of crop growth, storage, and equipment. As the lesson continues to play out students are asked to actively collect more evidence that helps either verify or refine each of their previously formed hypothesis.
Induction can be Overwhelming, Creating Safe Spaces is Key
Inductive instruction is a powerful tool in helping to encourage higher level cognitive processing, but it can also be overwhelming to learners who do not yet have a strong enough knowledge-base to form hypothesizes around the subjects in question. While inductive and deductive formats should in not be thought of as being mutually exclusive, it is essential that learners are provided a sound foundation before one asks them to go through an inductive learning exercise.
There are several ways to accomplish this, but one of the most well regarded is executing on the idea of a ‘flipped classroom’. In this approach students are asked to complete most of what has traditionally been done while inside of an actual classroom before they arrive such as watching a pre-recorded lecture. Students then use the time inside of the class to work through examples or problem-sets either individually or as a group, seeking guidance from the instructor as necessary. By freeing up time within a classroom for inductive learning to take place students are able to more rapidly move from lower order thinking such as memorization to higher order thinking processes like reasoning and analysis.
Another way to help promote inductive learning in a virtual setting is to divide learners in to breakout groups to discuss examples, and to subsequently elect a spokesperson to share with the broader class what hypothesis or rules the group came up with. Reducing the size of the classroom will help foster the sense of there being a safe space for misunderstandings and uncertainties to be discussed and worked through while also fostering further benefits as a result of social learning.
Instructors should always look to avoid approaching their classrooms with a monolithic attitude. Each of these techniques has its own unique characteristics that may make it a better fit for a particular learning objective- remaining highly nimble and iterative in one’s approach to this decision is key. It’s our hope that this post gives you and your team some food for thought on how to delineate between two core approaches, and that it also helps foster more intentional decision making on which to use going forward.