Tag: behaviorism

Theory-informed instructional design tips

In my previous article, I proposed a Taxonomy of Learning Theories to organise a few of the myriad of theories into some semblance of order, and to assist instructional designers in using theory to inform their work.

In this article, I go one step further by listing specific, practical instructional design tips that are informed by those theories.

But beware… You will find empirical evidence reported in the academic literature that supports these tips, and no doubt you can find just as much evidence that refutes them. I don’t purport them to be Gospel, and I certainly consider them highly dependent on context.

Having said that, however, I do vouch for my tips in terms of my own experience in the workplace, where I’ve applied them in various combinations to real-world cases.

I hope you find my list useful too – not so much as a checklist to incorporate every theory into your work – but rather to ensure that you have at least considered what they have to offer.

If you have your own theory-informed design tips, I’d love you to share them with me!

People around a table working with sticky notes.

Behaviourist design

Behaviourist learning theories inform us that stimuli elicit responses, and that one stimulus can be associated with another.

This perspective adopts a “black box” approach to instructional design:

  • Link paired concepts. For example, rolling the mouse over Italy on a map can display “Rome”, while rolling the mouse over Spain can display “Madrid”. Strengthen the association with a short burst of Italian and Spanish music respectively.
  • Incorporate matching pairs into an interactive game that facilitates repetition.
  • Use consistent navigation, symbols and visual design.
  • Provide plenty of questions for practice.
  • Reward correct responses to questions with a visual/verbal reward (eg a big green tick and the message “Well done!”) and perhaps a brief sound (eg a pleasant bing).
  • Flag incorrect responses to questions with a visual/verbal message (eg a small red x and the modest message “Oops, that’s not right”) and perhaps a brief sound (eg a buzz).
  • Avoid exposing the correct answer upon an incorrect response. Instead, allow the learner to re-try (unless of course the assessment is summative).
  • Remember that rote learning is no substitute for deep understanding.

Cognitivist design

Cognitivist learning theories inform us that hierarchically (or otherwise logically) arranged content aligns with the existing network of knowledge in the learner’s mind.

This perspective demands a structured approach to instructional design:

  • Structure your content logically.
  • Start with the learning outcome and work backwards to connect it to prior knowledge. Fill in the gap. If the gap is extensive, consider multiple smaller courses rather than one big one.
  • Use advance organizers to put the upcoming content into context and to pre-organise it. In other words, assist the learner to link the new knowledge to the relevant point in their existing cognitive structure, and to construct high-level cognitive branches within which to fill the detail.
  • Organise your content in increasing order of complexity. Provide an epitome of the domain initially, then elaborate.
  • Apply a minimalist design to reduce extraneous cognitive load.
  • Use plenty of white space.
  • Bold key terms.
  • Modularise some of the text (enclose it in a box) to make it easier to digest.
  • Wrap multiple paragraphs into a single interactive show/hide object.
  • Migrate extensive text into a downloadable document or onto a wiki.
  • Use an infographic to arrange key concepts in a framework.
  • Place the text in the infographic as close as possible to the corresponding point in the picture. Consider an audio overlay.
  • Avoid bright decorations and looped animations that compete with the substantive content for the learner’s attention.
  • Allow the learner to control multimedia and to press “Play” when they’re good and ready, to avoid inducing mild panic.
  • Use consistent navigation, symbols and visual design (as per behaviourism, but according to a different rationale).
  • Include activities that require sequencing and categorisation.
  • Employ real-world examples and scenarios.
  • Summarise the key concepts.
  • Include a formative assessment to enable the learner to test their knowledge, and to modify it or fill in gaps if necessary.
  • Ask higher order questions to confirm deep understanding.
  • Provide rich feedback.
  • Allow time for reflection.
  • Employ a mostly instructivist approach for novices. Reserve problem-based learning (PBL) for experts.

Constructivist design

Constructivist learning theories inform us that the prior knowledge of each learner is different, and thus they have unique needs, goals and contexts.

This perspective demands a learner-centred approach to instructional design:

  • Explain up-front why the learner should bother. What specific problem will it solve?
  • Allow the learner to co-create the learning objectives.
  • Cut to the chase. Content should be relevant, meaningful and practical. Supportive (but unnecessary) content should be made available elsewhere.
  • Avoid forced navigation: instead, allow the learner to explore the content at their discretion. A default linear navigation, however, will assist novices.
  • Ensure the navigation menu is always accessible from anywhere in the course.
  • Would a wiki be a more effective (self-directed) mode of delivery?
  • Avoid using an end-point in the bulk of the course to mark completion: instead, use a summative assessment.
  • If your assessment is robust enough, those who understand the content will pass, while those who don’t will fail.
  • Ask a colleague to bluff their way through your assessment. If they pass, it’s obviously too weak.
  • Ensure the assessment is authentic.
  • Where possible, enable the learner to undertake the learning at their place of practice.
  • Use real photos rather than cartoons or illustrations.
  • Encourage discovery learning.
  • Provide your learners with a forum to ask questions and to learn from one another. The forum may be synchronous or asynchronous, or both.
  • Encourage continual communication among the learners and their colleagues in the wider workplace. Consider a regular “community of practice” meeting if the conversation does not naturally emerge.

Connectivist design

Connectivist learning theory informs us that the learner can’t possibly take in all knowledge, and it changes too quickly anyway.

This perspective demands a realistic approach to instructional design that doesn’t rely on memory:

  • Supplement your content with further learning resources, not only to assist the learner to broaden and deepen their knowledge, but also to keep it up to date.
  • Avoid merely listing hyperlinks: instead, provide explanations to help the learner recognise meaningful patterns among them.
  • Create a social bookmarking account.
  • Encourage social networking (both online and face-to-face).
  • Develop an ILE to centralise all the resources.
  • Encourage the learner to integrate the ILE into a broader PLE.

Do you have any instructional design tips to share?

Taxonomy of Learning Theories

Academia is teeming with learning theories.

Some of them are old, some of them are new. Some are flash-in-the-pan, others stand the test of time and remain applicable to this very day. Some of them are controversial, while others have assumed the aura of conventional wisdom. Some of them are simple, while others are incomprehensible to mere mortals.

It can be quite a challenge for the modern learning professional to identify an appropriate learning theory, draw practical ideas from it, and apply it to their daily work.

Where do you start? Which theory do you choose? What is its central premise? How does it relate to other theories?
Frustrated man with post-it notes stuck to his face.

Taxonomy

To clear some of the obfuscation that surrounds learning theory, I have developed the following Taxonomy of Learning Theories.

Tracey's Taxonomy of Learning Theories

This taxonomy identifies key theories that apply to workplace learning, categorises them according to common properties, and illustrates the relationships among them.

I hope that this taxonomy, along with the corresponding notes below, will assist you in using learning theory to inform your instructional design decisions.

Close up of The Thinker by Rodin

Overarching themes

Almost all learning theory is derived from one or more of the following psychological schools of thought:

  • Behaviourism
  • Cognitivism
  • Constructivism
  • Connectivism

These four psychologies form the overarching themes of my taxonomy.

Cartoon of one dog dog saying to another 'Watch what I can make Pavlov do. As soon as I drool, he'll smile and write in his little book' while Pavlov looks on.

Behaviourism

Classical conditioning maintains that a neutral stimulus can be associated with another stimulus that elicits a particular response. This concept was demonstrated in the early 1900s by Ivan Pavlov, who reported that after a period of conditioning, a dog will associate the sound of a beating metronome (neutral stimulus) with food, and respond to it in the same manner (salivate).

Operant conditioning maintains that behaviour is controlled by its consequences: behaviours that are rewarded are likely to be repeated, while behaviours that are punished are unlikely to be repeated. This concept was demonstrated by Edward Thorndike, who placed a cat in a “puzzle box”. The cat discovered that by pulling a ring, a side door fell open which allowed it to escape. So when Thorndike put the cat back in the box, it pulled the ring again.

Social Learning Theory is another theory that has its roots in behaviourism. I somewhat amateurishly consider it operant conditioning by proxy, whereby the learner (especially a child) observes the rewarded actions of someone else, and thus behaves similarly. It’s important to note that Social Learning Theory now extends beyond the behaviourist domain to encompass cognition, particularly through the work of Julian Rotter and Albert Bandura.

Stylised x-ray of a brain in a skull.

Cognitivism

Since behaviourism focuses on external behaviour, it considers the mind a black box. In contrast, cognitivism peers inside the box to explain the inner structures and processes of learning.

Models of memory

Numerous cognitivist learning theories derive from the Modal Model of Memory developed by Richard Atkinson and Richard Shiffrin since 1968. They proposed that human memory comprises three components: (1) Sensory memory, which perceives the information that is collected by our senses, such as visual information (eg a drawing) and auditory information (eg a bell toll); (2) Short-term memory, which processes the information that has been supplied by the sensory memory; and (3) Long-term memory, our more-or-less permanent knowledge storage area.

The original Atkinson-Shiffrin memory model, lacking the sensory memory stage which was devised later, showing incoming information going to short-term memory storage then to long-term memory storage.

Atkinson & Shiffrin’s concept of short-term memory was superseded in 1974 by Alan Baddeley and Graham Hitch’s concept of working memory, which comprises the central executive and three slave systems: (1) The phonological loop, which processes verbal information; (2) The visuospatial sketchpad, which processes visual imagery and spatial information; and (3) an integrative component called the episodic buffer.

Baddeley's model of working memory in which the phonological loop, the visuospatial sketchpad and the episodic buffer connect to the central executive.

In 1956, George Miller reported that the “span of immediate memory” is limited to the magical number 7±2 items. From this, he deduced that the amount of information that could be processed at any one time could be increased by “chunking” it.

In the 1970s, John Anderson started to develop ACT-R, which maintains that long-term memory comprises declarative memory which is explicitly stored and retrieved (eg crashing your bike into a tree on your birthday when you were a child) and procedural memory which is unconsciously stored and retrieved (eg the motor skills required for riding a bike generally).

Stylised neurons

Schema theories

Models of memory provide the foundation for subsequent cognitivist theories that (arguably) have more direct implications for instructional design.

In 1977, Richard Anderson extended the work of earlier theorists such as Frederic Bartlett and Jean Piaget. His Schema Theory of Learning maintains that within long-term memory (or more specifically, declarative memory), knowledge is arranged in a hierarchical network of constructs called “schemas”.

Similarly, David Ausubel’s Subsumption Theory proposes that learning involves the linking of new information to relevant points in the learner’s existing cognitive structure. During the learning process, new information is subsumed under more general information in the hierarchical arrangement of the learner’s prior knowledge.

Charles Reigeluth’s Elaboration Theory complements Ausubel’s principle of ideational scaffolding. Reigeluth maintains that instruction should be organised in increasing order of complexity. In particular, the simplest (or epitomised) version of the domain should be provided initially, and elaborated upon subsequently. This approach develops a broad, meaningful context into which the learner can assimilate the narrow, detailed information.

A woman studying.

Cognitive load

In 1988, John Sweller synthesised key principles of memory and schema under a new proposal called Cognitive Load Theory.

Cognitive Load Theory maintains that the mental effort required for learning imposes a cognitive load on working memory. The total cognitive load consists of three components: (1) Intrinsic cognitive load, which is imposed by the intrinsic characteristics of the content that is to be learned; (2) Germane cognitive load, which refers to the mental effort required to organise the elements of the content into a schema, integrate it into long-term memory, and automate its processing; and (3) Extraneous cognitive load, which does not contribute to the learning process (eg the mental effort required to block out loud music).

If the total cognitive load of the learning task exceeds the processing capacity of working memory, learning fails. This suggests that instruction should be designed with a view to reduce cognitive load and thereby avoid overload.

Two workers on a construction site.

Constructivism

Constructivism has a rich history. Numerous theorists have contributed to its development over the last century (eg Jean Piaget, Lev Vygotsky, Jerome Bruner, Ernst von Glaserfeld), and several brands are recognised in the domain (eg cognitive constructivism, social constructivism, radical constructivism).

Regardless of the theorist or the brand, however, constructivism essentially maintains that people learn by constructing their own knowledge on the basis of their experiences. Constructivist learning theories recognise that everyone’s framework of prior knowledge is unique, thus they have their own needs, goals and contexts.

A baby playing with books.

Adaptation

In his study of child development, Jean Piaget posited that every learner has a mental representation of the world which he or she constructs through their experiences.

When a person experiences cognitive conflict (a discrepancy between their mental representation and what they are currently experiencing), they undergo a process of adaptation. If the new experience aligns with their mental representation, the learner assimilates it in the form of new knowledge into their existing schema. If, however, the new experience does not align with their mental representation, the learner must rearrange their existing schema to accommodate the new knowledge.

Clearly, adaptation is complementary to Schema Theory; however, the constructivist perspective emphasises the learner centredness of the activity.

A blacksmith hammering a piece of metal while his colleague supervises.

Situated Learning Theory

A valuable means by which a learner can close the gaps in their existing schema, and broaden and deepen their knowledge, is to engage with other people, ask questions, debate ideas, and share experiences.

Situated Learning Theory focuses on this social, practice-based approach to learning. The theory views learning in terms of participation in a community of practice, and considers knowledge to be highly dependent on its context.

A standing businessman facilitating a training session with a group of colleagues seated in a semi circle.

Andragogy

Andragogy focuses on adult learning, and it adopts a strong constructivist perspective.

It boils down to 5 assumptions about adult learners as articulated by Malcolm Knowles: (1) Adult learners are self directed; (2) Adults bring experience with them to the learning environment; (3) Adults are ready to learn to perform their role in society; (4) Adults are problem oriented, and they seek immediate application of their new knowledge; and (5) Adults are motivated to learn by internal factors.

I have stated previously that I believe Knowles’ 5 assumptions generally hold true – but not for all adults, and certainly not all of the time. An andragogical approach is appropriate for adults who are intellectually mature, self directed and intrinsically motivated, with time to learn and their heads in the right space.

A humanoid figure with networked nodes extended from its head.

Connectivism

While cognitivism focuses on knowledge inside the mind, connectivism focuses on knowledge outside the mind.

George Siemens describes connectivism as “a learning theory for the digital age”. He maintains that in today’s world, there’s simply too much knowledge to take in – and it changes too quickly anyway.

So forget about trying to know everything; instead, exploit technology to extend your knowledge beyond your own brain. Build a network of knowledge sources which you can access as the need arises.

Recognising meaningful patterns among distributed sets of information, rather than storing it all in your head, re-defines what it means to “learn”.