Instructional Design and the Implications Of Learning Theories

By 20/09/2018 November 20th, 2019 Education, Pedagogy, Technology Enhanced Learning
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In a previous post, entitled “Instructional Design – Learning Models” I looked at the different models that we can use in our curriculum planning, and what aspects of each learning theory was attractive as an instructional designer to plan our learning better.

In today’s post I’m going to look at three specific learning theories and delve a little deeper into learning theory to find out what implications each learning theory will have for our learners if we choose to use them in our planning stages. Today I will be discussing the Behavioural; Cognitive and Social Learning Theories.

For ease of argument, I’ll define what I mean by each one, but please understand that for a fuller understanding of each theory, you will need to dive deep into each of them individually to understand the full nuance of how each learning theory will shape our learning into very different directions, as you’re about to find out.

Behaviorist Learning Theory

behaviourist learning theory

I have to confess, I am quite partial to a bit of Behaviourism. I studied it at Queens University Belfast (specifically Applied Behaviour Analysis, but also known as ABA) at post-graduate level in 2016 and found it matched very well with a lot of my own educational experiences (which would explain why I liked/loathed it in equal measure).  The main aspect of Behaviourism that attracts me to it, is that it works and it’s very logical. Everyone who was educated before the early 1990s, will know what their times tables are. I’m not saying anyone else won’t, but at a certain time in education, learning by rote was the main way of learning. This resonates with behaviourism. Learning to mastery is a key concept within its application to education.


Having already confessed my previous exposure to Behaviourism, I’ll try not to get too geeky or academic about a definition. But it’s helpful to understand the word behaviour using the deadman test: if a deadman can do it, then it’s not a behaviour. Therefore, sitting with your legs crossed in a particular way is a behaviour; handwriting is a behaviour and running is a behaviour.

Behavioural learning theory can be summarised as learning that occurs through the behavioural response to environmentally sourced stimuli (Richey, Klein, & Tracey, 2011). The foundation of this theory is built upon assumptions that “have little regard for the cognitive processing of the learner involved in the task” (Baruqe & Melo, 2003). The assumptions take into account 3 criteria:

  • Τhe instructional task is the focus of a behavioral response,
  • Learning occurs by actively influencing the environmental stimuli, and
  • Learning occurs through the process of repetition or rehearsal of a behaviour.

Furthermore, behavioural learning theory is traditionally divided into 2 separate areas: classical conditioning and operant conditioning.

Classical Conditioning

Ivan Pavlov is best known for his experimentation with dogs. In these studies, Pavlov focused on the natural responses that could be elicited by using unrelated stimuli. In his classical conditioning experiment, Pavlov used a bell (the neutral stimulus) and paired it with food (the unconditioned stimulus) to get the dog to salivate. The idea was that after enough trials (rehearsals), the dog would salivate when the bell was rung. Using the food, the ringing of the bell became a condition that the dog would recognize (over time) and begin to salivate. Over time in the absence of the food, the bell would become less influential and no longer elicit the same response.

Shortcomings to this type of conditioning are similar to the story of the boy that cried wolf. The bell represents the boy that is crying and the food represents the wolf. After using the bell enough times with the absence of the food, the conditioned stimulus becomes ineffective; similarly, the boy that continues to cry wolf for attention becomes unreliable in a sense and help will not come. In the simple example above, the help that comes is symbolic of the response of the dog to salivate.

To summarise this, classical conditioning involves learning to associate an unconditioned stimulus that already brings about a particular response (i.e., a reflex) with a new (conditioned) stimulus, so that the new stimulus brings about the same response.

Operant Conditioning

B. F. Skinner is one of the most influential behaviorists of the 20th century. Similar to Pavlov, Skinner also experimented with animals; however, his primary focus was on the effects that variables had on learning behaviours.

Skinner primarily worked around the idea that reinforcement drives behavioural response. In his classical experiment with animals, Skinner introduced food and water to a deprived animal in an effort to teach how to pull a lever. If the lever was pulled, the animal received a reward; however, as the experiments continued, the animal would only receive the food or water if the lever was pulled with a minimum force.

In this context, the behaviours are influenced by the environmental factors that affect the learner. The learner would require some sort of satisfaction in performing a particular behaviour in order to learn it. This could be described as motivation, but in conditioning, it is referred to as the stimulus. While this is similar to classical conditioning, the distinct difference is the behaviour that is being taught. In operant conditioning, the behavior is not automatic (like salivation). This is a task that is to be completed. For those that are new to the world of learning theory, it is important to understand this distinction because of how it applies to education.

Applications In Instructional Design

Influential behaviourists, like Skinner and Pavlov, have ‘blazed the trail’ when it comes to behavioural learning theory as a basis for education. Applications of the theory were presented in the 1950s through Skinner’s teaching machines. These machines comprised of a series of tasks to be completed by the learner—each designed to ensure that the tasks are completed correctly in order to move forward. The machines were inventive and based solely on eliciting a positive response in the form of a behavior.

These machines led to the development of programmed instruction which “follows an empirical approach to analysing and solving problems” (Richey, Klein, & Tracey, 2011). Some view this as the beginning of a systems design approach to education. If we think about how much of our lessons are laid out for students—content, guided tasks, practice, and feedback. This structure helps students learn, but tweaking it will increase their ability to learn and therefore, their success as learners.

Impact On The Field Of Instructional Design

There is no doubt that learning in some instances results in the development of a physical skill; furthermore, the practicing of that skill will result in a response to a stimulus. The focus of behavioral learning theory resides in the use of reinforcement (which can be positive and negative, but all research and academic thought would emphasise the notion that positive reinforcement should be favoured) to drive behavior. Instructional Design can benefit from the use of reinforcement as a means to train learners to complete instructional objectives that are presented to them. The examples of teaching machines and programmed instruction are small contributions to the field but have paved the way Instructional Designers shape the learning environment to result in more effective strategies. It is important to note that many instructional strategies include the use of feedback to the learner as it assists in the development of positive behaviors that result from instruction.

Cognitive Learning Theory


Definition And Characteristics

Cognitivism focuses on the inner activity and mental process of the mind – which would go against the teaching of behaviourism – as there is no internal, ‘mental’ process in behaviourism. According to Richey, Klein, & Tracey, “the ways that learners process and apply information changes one’s thoughts and internal mental structures.” This theory uses the analogy of comparing the human mind to a computer. Check out this link for a simple description of cognitivism.

Cognitivists define learning as “involving the reorganisation of experiences in order to make sense of stimuli from the environment” and also “an internal and active mental process, which develops in a learner, increased mental capacity and skills in order to learn better” (McLeod, 2003).

The primary focus of learning under an understanding of cognitivism, is on the development of knowledge by the creation of schemas. Schemas are like catalogues of information that can be used to identify concepts or experiences through a complex set of relationships that are connected to one another. In short, the catalogs act like a database of knowledge for the learner. Two prominent theories that will be discussed are Gestalt theory and information processing theory; these two have paved the way for cognitivism and its impact on the field of Instructional Design.

Relationship To Behaviorism—Gestalt Theory

“Early movements [providing] alternatives to stimulus-response initiated in Germany” (Richey, R., Klein, J., & Tracey, M., 2011). The leaders of this movement, which is called Gestalt Theory, focused on the individual’s perspective of the relationships that connect various situations and behaviours. To put it another way, Gestalt theory emphasised that “individuals always react in a total, well-organized response to a situation”(Richey, R., Klein, J., & Tracey, M., 2011). While this was one of the early developments in cognitive learning theory, its focus was on the central processing of decisions that are made to result in a specific behavior depending on the situation.

Gestalt theory in a present day example, can be observed through the model of a role-playing game (RPG). Imagine a character that is faced with many situations as he/she moves through the game. Certain decisions have to be made and this results in a behavior that may affect the outcome of the situation. As the player progresses through the game, it becomes clearer that as more information is acquired over time  spent in the game, this may sway decisions later in the game. Take an example, in which a critical piece of information required to make a game-altering decision is not known. This would result in the player making a choice of behavior only relying on experiences that are relevant; and so this could result in a different outcome.

Notice how that in the game example provided, there are decisions that are made based on prior experiences and information that is acquired throughout the game’s progression. In essence, this is representative of how an informed decision is made by the learner to exhibit a behavior that is appropriate for the situation at hand. While this example could be view as a simplified version of reality, it does provides an example that relates to human decision making at the cognitive level and from this, much can be learned.

Information Processing Theory

Information processing theory further supports cognitive learning theory. It is similar to Gestalt theory, as the focus of learning is on the individual. The processing of information by the learner is similar to the way a computer processes information. The memory system is broken into 3 stages based on this approach:

  • Sensory memory
  • Working memory
  • Long-term memory

Information is constantly being processed by the memory system via sensory memory, but only the more important pieces of memory are sent to the long-term memory. Generally, the working memory is responsible for moving the information into the long-term memory store.

Think about the first math lesson that you had taken to acquire the information that was needed to pass the test. In this scenario, sensory memory picks up and processes the information, filtering out the nonsensical data. Any extraneous information is filtered out while the information that catches the attention of the learner is passed on to the working memory. Generally speaking, the working memory stores the information for a longer period of time; if rehearsed enough times (similar to muscle memory), it will essentially be sent into long-term memory. This would explain why that math lesson was straightforward and simple in the classroom after practicing the concept a couple of times in class. The working memory still kept the important data accessible to you; however, later on at home, the homework seems that much more difficult. Not because it is harder, but because the working memory may require more rehearsal to establish a clear connection to the concept and store it in the long-term memory.

Information processing takes the learning process and compares it to the way that a computer processes information. The more times information needs to be accessed, the quicker the computer will recall the information in future times. While this relationship gives a simple example of how we as individuals process information, how is this information structured?


One of the most widely used and one of the best strategies that can be used could arguably be rehearsal. The expression ‘practice makes perfect’ may seem cliché, and may be used in its corrected form as ‘practice makes better’ but regardless of which you feel more comfortable with, it does fit very well in any discussion around cognition and development.

As one rehearses, the working memory is exercised. Think of a person that starts working out at the gym. In the beginning, the types of workouts may be limited and the amount of weight that could be lifted may be a minimum. But the more a person works out, a system is generally developed to perform a certain number of repetitions to improve muscle strength. In this example, muscle strength is synonymous with long-term memory. The memory repeats the process of working with important information until it has been stored in long-term memory for later access and recall.

Rehearsal is widely used in many applications where learning is necessary, particularly in educational settings. Various courses that require the rehearsal of cognitively complex tasks, like maths, science or computing will all use rehearsal as a means to assist the learners in processing the information to long-term memory. One could argue that once long-term memory stores the information, the information has been ‘learned.’ But what happens if the information is processed to long-term memory, but there seems to be difficulty in the retrieval process? To combat this particular problem, other strategies can be implemented, used and taught to the individual to help improve the organisation and retrieval process.

Chunking And Mnemonics

Sometimes learners will have difficulty in retrieving information, despite it being evident that it has been learned. Instructional strategies that have been developed in the presence of cognitive learning theory are chunking and mnemonics. Chunking is the process of grouping similar pieces of information together into a chunk that can be sent to the working memory for rehearsal and further processing. While working memory has a limit of 7 (plus or minus 2), creating a chunk of information increases the amount that can be worked with. Long strings of numbers may be difficult to remember, but if the information is grouped (the first part, the second part,  the third part) then the working memory can hold the information for long enough to write down the number.

Another strategy used to improve storage and retrieval is the mnemonic. There are certain concepts or critical pieces of information that may need to be easily recalled for a later time; additionally, it may need to be learned in a way that is easy to process. Think of the order of operations from mathematics. The mnemonic “BODMAS” may be recalled as useful way to remember the order in which operations should occur. Start with parentheses, then work with exponents, followed by multiplication and division, and then addition and subtraction. This should occur from left to right. The use of mnemonics is generally designed by organizing the information in a way that can be easily processed and retrieved later on. This strategy has greatly impacted the way that individuals work with new information [1].

Schema Theory

Where information processing theory breaks down the process of taking information and processing it for later storage and retrieval, schema theory explains the organisation of information while it is being constructed and redefined. “Schema theory exists in long-term memory and refers to how [knowledge] is organised in memory” (Richey, R., Klein, J., & Tracey, M., 2011). Schemas then, are constructs of the concepts that are stored in long-term memory. The more organised the schema is, the more efficient the recall of the information is when it is needed later. To give an analogy, schema is the Dewey Decimal System in a library – they present information in an organised fashion and so the more organised this can be, the more understanding will be achieved around the topic being taught.

A schema that is defined is never concrete; it can be altered upon being presented with new information. The schema can also be expanded to develop relationships between similar chunks of information. Depending on how a specific learner constructs their cognitive foundation, the schema can improve the acquisition of new memory structures.

Cognitive learning theory has made a considerable impact in the field of education with the formation of learning strategies to enhance the storage and retrieval of data from memory. It is important to note that contributions from all theories centered around cognitive processing have played a role in the formulation of strategies including rehearsal, chunking, and mnemonics to name a few. While these strategies are primarily used as instructional strategies, they could be implemented by Instructional Designers during the development of instructional-based solutions.

Impact On The Field Of Instructional Design

With the integration of cognitive learning theory, Instructional Design has begun the practice of implementing solutions that focus on the learner during the design process. Some Instructional Designers will follow an iterative (or agile) process that makes use of information about the learners as well as the environment to develop instructional solutions (McLeod). The Instructional Designer will then create a list of instructional goals that can then be expanded beyond basic observable behaviour; furthermore, using assessment tools that test the newly acquired knowledge that has been “transferred” to the learner can also be available. As a result of all this, Instructional Design has shifted in the presence of cognitivism and includes a more system-like design approach with a greater focus on the learners.

Social Learning Theory

social learning theory image

Definition And Characteristics

Social learning theory has also made contributions to the field of Instructional Design. Social learning theory focuses on the impact of learning that are based on factors that are related to the social environment. In other words, learning occurs in the environment of a social situation that the learner is placed in or finds themselves in. Variables that are considered within the scope of this theory focus on the surrounding environment and the psychological state of the person. The level of influence that the environment and state of mind have on the learner can be deeply profound. If the learner accepts that a behaviour has an acceptable outcome, then the learner is increasingly more likely to engage in the activity.


There are a wide ranging number of applications that exist as a result of social learning theory. These can, and have had a profound impact on the field of Instructional Design. It is important to note that the applications represented below are just a few of the implications that social learning theory has had on the field itself. These include the use of models and establishing self-efficacy.

Using Models

Models have been used consistently to help deliver information in a manner that can be observed by the learner. Models will typically include a performance or demonstration of an activity that give the learner the opportunity to interpret the observation into useable information for processing and then understanding. Other examples can include graphic pictures, electronic media, or symbolic representation of concepts.


Self-efficacy is the belief that we can be successful at particular tasks. When we think of the expression “perhaps it rubbed off on me”, this has a direct relationship to social learning theory. Self-efficacy can be influenced by the specific construction of lessons in an environemtn that allows learners to view others of similar ability succeeding at instructional tasks. This could be achieved in a number of creative ways, but generally is most effective in collaborative activities where learners work in small groups.

Impact On The Field Of Instructional Design

Social theory has made a considerable impact in the area of instructional tasks by expanding the way that instructional solutions can be developed. With the addition of how the social aspect of environments can influence learning, a world of instructional strategies has generated new opportunities for learning. Collaborative learning groups and the use of peer review are widely used in many settings in which learning occurs. In this way, knowledge is not just transferred to the individual, but by using a set of observable behaviours, the learner can interpret the models in a way that improves their individual understanding.


The world of Instructional Design has evolved over time. Through influences from various learning theory movements like behaviourism, cognitivism, and social learning it has constructed a foundation on which, multiple successful approaches can be securely relied upon. While each theory will include specific theory-specific ideas as to how learning occurs—either by a behavioural response or acquisition of knowledge —they contribute their own unique perspectives on learning as a whole and are responsible for how the field of Instructional Design has changed over time.


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Michael Johnston

About Michael Johnston

I'm a Lecturer in Computing and the Foundation Degree Director in Computing for the Northern Regional College in Northern Ireland. My research interests in the areas of technology enhanced learning, how we interact with technology, blended learning and professional development. Michael currently specialises in the computing areas of web development technologies, cyber security, software development and IoT. Michael has worked in a range of different roles in IT-from teaching roles to running his own web design company, Michael is equally at home working with theory, as he is conducting research, or building a bespoke IT solution. Michael is currently studying a PhD in Cyberpsychology.

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