This afternoon, I watched a you tube video (below) by Ian Robertson titled “An Introduction to Learning Theories“. While it was a high-level introduction, it carried an underlying message of how I feel about learning theories.
Ian provides a definition or brief explanation for a number of learning theories, backed with examples of when they are most effective. It is this point that I have been trying to communicate through my previous blog posts on the topic of context. There is no learning theory to rule them all. They are all largely valid and meaningful – for a given context.
What I believe to be misguided is the purist approach to learning theory – (ie. theory X is right and theory Y is wrong), or that you have to decide which one you use, and discard the others. In fact after reading a forum post by George Siemens, I believe he has similar perspectives on this. George says:
We use ideas and apply them based not only on their merits, but on the context – where we’re at…where our learners are at…tools available, etc. So, sometimes, sloppiness works. Misapplication still teaches. Our theory is pure in thought, messy in application. And, few things are refuted in their entirety. Many aspects of constructivism, cognitivism have value beyond the language construct we have created to house the ideals. Most ideas are messy, run across domains, and even revolutions bear the characteristics of the system they are attempting to replace.
In Week 4, George Siemens has specifically asked the question “… what are the unique ideas in connectivism?” A very pertinent question. I shall frame my response in terms of which contexts suit the connectivist learning theory, which will in itself, differentiate it from others. Well maybe. 🙂
George said of Constructivism:
Constructivism made sense in that it rode on the cultural trends and philosophical viewpoints of the day … it combined existing ideas into a framework that resonated with the needs and trends of the current era.
Largely, a central tenet of Connectivism is the application of network principles to define both knowledge and the process of learning. Something possible in modern society through our advancements in technology. George asks in his seminal work Connectivism: A Learning Theory for the Digital Age:
Some questions to explore in relation to learning theories and the impact of technology and new sciences (chaos and networks) on learning:
- How are learning theories impacted when knowledge is no longer acquired in the linear manner?
- What adjustments need to made with learning theories when technology performs many of the cognitive operations previously performed by learners (information storage and retrieval).
- How can we continue to stay current in a rapidly evolving information ecology?
- How do learning theories address moments where performance is needed in the absence of complete understanding?
- What is the impact of networks and complexity theories on learning?
- What is the impact of chaos as a complex pattern recognition process on learning?
- With increased recognition of interconnections in differing fields of knowledge, how are systems and ecology theories perceived in light of learning tasks?
Naturally, George positions Connectivism to respond to these modern day sciences and challenges, and herein lay Connectivisms effective context. A response to learning in the era of the 21st century – the information age.
But this context is far from global. What of contexts where such networks are unavailable or difficult to access? There are many developing countries for example where such technological advancement is beyond reach. Even in first-world countries, there is not ubiquitous access to technological services generating the types of challenges and environments questioned by George above. We look at students at our University and many still do not have access to broadband Internet. Our institution has many students who work full-time in the mining sector as another example – many of which are located in remote areas of Australia (ie. Western Queensland, and Western Australia). Try obtaining reliable and affordable broadband Internet in remote areas of Australia, such as Western Queensland. How can they consistently engage in a learning network? Even in urban areas of Australia, there are the haves and have nots for high-speed Internet.
So it would be interesting to see whether Ian considers Connectivism as a learning theory in its own right, and add examples of the appropriate context in which to use it.
This post relates to my study of CCK11.
I found an article I wrote two years ago regarding improving university teaching, learning theories and instructional (curriculum) design while studying instructional design through UManitoba. I thought it was relevant to my current study of CCK11, and so am reposting so that it would be included in the CCK11 daily.
While reposting this article, I’ll also link to a more recent blog post I wrote postulating whether learning theories is too much naval-gazing. In particular, David Jones‘ comments were pertinent to the discussion in my opinion.
Hopefully someone will find this interesting/useful. 🙂
This blog post relates to my study of CCK11 and the study of learning theory.
One of the week 1 readings is a document titled “What is Connectivism?” George Siemens uses Ertmer’s and Newby’s “five definitive questions to distinguish learning theory” framework to produce a table comparing and contrasting Connectivism with 4 other prominent learning theories: Behaviourism, Cognitivism, and Constructivism.
I found this to be quite helpful in making sense of learning theories.
While I have studied, albeit in a very small capacity these other learning theories, it occurs to me that in some ways and in some contexts, each of these learning theories makes sense.
For instance, taking a look at how learning occurs in behaviourism, the idea of learning being a black-box and being focused on observable behaviour makes sense. How do you determine learning without some observable action? Kind of reminds me of the expression “does a bear shit in the woods?” Everyone assumes so, but do we really know for sure? 🙂 Yet, if you look at Constructivism, learning occurs socially and meaning is created by each learner. This too makes sense to me. When I say it makes sense, it is something that resonates with me and fits with my experiences – previous patterns in my life. I’m sure others will have different resonances with this matrix. I’m interested to hear which parts of the matrix matches their life experiences if you are comfortable sharing as a comment?
If I work my way through the list, there seems very little amongst the learning theories that appear untrue and does not connect with my life experiences. Some may take precedence over others, depending on the context, but most seem valid.
Taking a step back, does it make sense to have learning theories, or to state “this is how we learn?” It’s a big call. Beyond the chemical/physical exchanges and reactions that occur within one’s grey matter, is it really definable? Are thoughts, ideas; is learning “real”? I believe context has a vital bearing on how we learn and context, particularly in today’s society is so incredibly diverse, with infinite possibilities. Is there a taxonomy for learning contexts? Perhaps there is, I shall googleith and find out. I’ll make a prediction in saying that if there is a taxonomy, it will be of formally structured learning only, and exclude informal, spontaneous learning. But always happy to be proven wrong – what do I know? 🙂
Are all learning theories both right, and wrong at the same time? I blogged previously about complexity in teaching and my uncertainty about complexity in learning. Perhaps context is what brings about complexity in both teaching and learning?
Can any of these learning theories be proven right, or wrong? I am guessing not otherwise theories would have been proven or disproven by now. This is a social science, and so there are no absolutes. In which case, is all this discussion of learning theories just naval-gazing and meaningless?
Note, this is a real question (not rhetorical) – I don’t know the answer, but I wonder why we try to categorise/frame/conceptualise/organise and all the other verbs when perhaps its just a futile exercise. Or maybe I have just invented the defeatism learning theory. 🙂
Next, my discussion of the big bang theory. 🙂
As part of my studies in Instructional Design with the University of Manitoba, I have been asked to reflect on George Siemen’s blog article entitled Socialization as information objects and comment on the views of the model discussed. This is part 2 of my reflections.
After reading George’s articles, I can see how his learner-centred approach can produce far more effective learning outcomes for students. The students are pursuing what they perceive as important to them. An important aspect, particularly of adult learners is for the learning to have purpose/meaning/relevancy. If a learner can see why what they are learning is important, they are more likely to engage. In this type of design, the learners decide to learn what is most relevant to them, and can focus their efforts to this end.
Rachel has made the following comments on the class forum: “I think the real problem with learners deciding outcomes is the assessment issue. There is a need to know who is competent to do something and how is that going to be measured except through some kind of testing against predetermined objectives?”
While I agree with Rachel, taking a broader view I see the weakness in terms of when it is applied to current (and past) western attitudes and culture. Formal education seeks to evaluate and rank learners quantitatively according to their achievements as one criteria for employers to use to recuit their workforce. A totem pole if you will with the elite at the top. Skills and attributes that employers are looking for and how learners measure up to this criteria is a critical aspect of evaluating potential employees. As such, what employers see as important versus what learners see as important may not always align. Or at the very least, what learners perceive as important may not align with employers. This is where learning outcomes/objectives inform learning designs. The behaviourist heritage – what behaviours do employers seek in their employees. Returning to Rachel’s comments, its not just about how competency is measured, but what competencies according to requirements of the established disciplines.
George made the following comment regarding learner control.
Learner control is not without frustration for the instructor. I recall feeling a bit frustrated that the concept of connectivism that I was trying to communicate – the neural, conceptual, and social/external dimensions of networked learning (expressed in this presentation)- was not resonating with participants. As many theorists in education have stated, what’s important for learning is not what the educator has to share, but the current state of knowledge and interest of the learner. My attempt to move the conversation in one direction was not successful in this instance because participants were not interested in engaging in the concepts I presented. End result: learners took the course in directions that reflected their needs and interests. Not the instructors.
Jenny Mackness highlights the issues around accreditation and the need for a tutor to assess their work. So what if we were to change the topic of the learning to a course around financial auditing. The established standards around auditing dictate what is expected of a professional, and learning outcomes for formal education reflect this (or at least should 🙂 ). It would not be acceptable to the financial auditing establishment for a learner to decide that they were not interested in the procedures of xyz and therefore not engage with it. Perhaps a contrived example, and I’m not a financial professional, but I hope this makes sense.
An extract from the quote above: “what’s important for learning is not what the educator has to share, but the current state of knowledge and interest of the learner.”
I guess it depends on what the educator has to share, and its relevance to established expectations for the field of study. Perhaps that is articulated through the current state of knowledge.
(Update: This post I wrote two years ago when studying instructional (curriculum) design. It seems quite relevant to my current study of CCK11, so I thought I would add this reference so that it may be included in the 2011 MOOC offering.)
I read this article by David Jones some time ago, and have been thinking it over. As an early career curriculum designer, I am trying to find my place in the world of education, and how I can be an effective learning designer.
My understanding is that David in his article argues in order to improve university teaching, we should focus on teacher reflection, rather than learning theories. Reflection is the lowest common denominator in any improvement of learning and teaching practices. Without it, the teacher is destined to make the same mistakes over and over. This is highlighted by Biggs and Tang in their book Teaching for Quality Learning at University 3rd edition, which I am currently (trying to) read, and reflect upon, and is drawn upon in part by David (I believe – it is getting late and I have an assessment due tomorrow :)). Biggs and Tang state:
Wise and effective teaching is not, however, simply a matter of applying general principles of teaching according to rule; they need adapting to each teacher’s own personal strengths and teaching context… Expert teachers continually reflect on how they might teach even better.
Let us imagine that Susan and Robert graduated 20 years ago [as teachers]. Susan now is a teacher with 20 years’ experience; Robert is a teacher with one year’s experience repeated 19 times. Susan is a reflective teacher: each significant experience, particularly of failure, has been a learning experience, so she gets better and better. Robert is a reactive teacher. He goes through the same motions year after year … The kind of thinking displayed by Susan, but not by Robert, is known as ‘reflective practice’.”
It occurs to me that prescribing any particular learning theory (such as constructive alignment) is not the answer, after reading a blog post by Stephen Downes. Stephen critiques a paper by Dicks and Ives that conducted a study into how instructional designers design. In particular, Stephen highlights the following quote from Dicks, and Ives:
Our interviews appear to confirm the findings of Kenny, Zhang, Schwier, and Campbell (2004) that instructional designers do not do their work by following established models, nor by basing actions on theory. Instead, our designers’ tactics suggest they view design as an ‘ill-structured problem’ (Jonassen, 2002; Schon, 1987) or ‘wicked problem’ (Becker, 2007) with many possible solutions, which they pursue with a large repertoire of social and cognitive skills.
Stephen had the following to say about this quote: “Which really forces the question of whether our discipline should continue its ill-founded focus on (this person or that’s) theory. ”
I’ve had the opportunity to talk to quite a few different seasoned instructional designers over the past couple of weeks, and I have seen a common theme emerge that is aligned with the findings of Dicks and Ives above: there is no one ultimate learning theory. All have stated that while they may have a preferred theory, it is rarely implemented solely to a learning design. Choice of theory is informed greatly by the context in which the learning is to occur. No less is the actual teacher of the course a critical factor in deciding which theories are appropriate. If the teacher has been teaching for many years and has a traditional behaviourist approach to their teaching; trying to model their course design around constructivism or connectivism is not going to prove to be an effective learning design. This is unless the teacher was motivated to reflect on their practice and consider alternate ways of doing things.
I have been investigating various learning theories over the past week – hardly a deep analysis, but I always considered religion as an appropriate analogy for learning theories. Everyone has their own view, and they can’t all be right. However, what I am discovering is that learning theories tend to support one another more so than contradict, which was my former view. So its probably not so much about which one is right, but which one is right for the given context.
I am finding learning theory absolutely fascinating, yet I do not have sufficient time to study as deep as I would like. I have decided to remain completely open minded in terms of what tools (theories) I choose to inform my learning designs. Studying many different theories arms me with many tools, and I hope this will mean I am a more rounded designer. The skill will be to use these tools in the right combinations to maximise effectiveness.
As part of my Certificate in Emerging Technologies for Learning, I am studying 4 popular learning theories. The first theory I am discovering is behaviourism.
I have read an article by Melissa Standridge hosted on the Department of Eduational Psychology and Instructional Technology wiki, from the University of Georgia. The article begins with a definition of behaviourism, which was stated as:
Behaviorism is primarily concerned with observable and measurable aspects of human behavior. In defining behavior, behaviorist learning theories emphasize changes in behavior that result from stimulus-response associations made by the learner. Behavior is directed by stimuli. An individual selects one response instead of another because of prior conditioning and psychological drives existing at the moment of the action (Parkay & Hass, 2000).
The article then proceeds with a summary of the work from behaviourism advocates. Much of this work was conducted through experiments on animals. I wasn’t quite sure what to think at this point.
Work conducted by Skinner involved an approach known as operant conditioning. Melissa writes:
His model was based on the premise that satisfying responses are conditioned, while unsatisfying ones are not. Operant conditioning is the rewarding of part of a desired behavior or a random act that approaches it. Skinner remarked that “the things we call pleasant have an energizing or strengthening effect on our behavior” (Skinner, 1972, p. 74). Through Skinner’s research on animals, he concluded that both animals and humans would repeat acts that led to favorable outcomes, and suppress those that produced unfavorable results (Shaffer, 2000). If a rat presses a bar and receives a food pellet, he will be likely to press it again. Skinner defined the bar-pressing response as operant, and the food pellet as a reinforcer. Punishers, on the other hand, are consequences that suppress a response and decrease the likelihood that it will occur in the future. If the rat had been shocked every time it pressed the bar that behavior would cease.
While it seemed briefly amusing to think of students as experimental rats in a lab (classroom), the final sentence of this paragraph got me thinking: “Skinner [B. F. (1904-1990)] believed the habits that each of us develops result from our unique operant learning experiences (Shaffer, 2000).” I am currently reading Biggs’ Teaching for Quality Learning at University and so I am immersed in learning theories around constructivism. Biggs’ (2007) states: “All [forms of constructivism] emphasise that the learners construct knowledge with their own activities, building on what they already know. Teaching is not a matter of transmitting but of engaging students in active learning, building their knowledge in terms of what they already understand.” I wonder if these two learning theories compliment each other in some small way. I’m not quite sure how to define or articulate the link at this point – its just getting too late. Will need to give this further thought.
Reflecting on my own prior teaching activities, I have employed behaviourist tactics in my classes without even realising it. One of the key aspects of success with behavourism is to understand your learners desires and to select highly attractive and valuable reinforcers. As Melissa puts it: “They change behaviors to satisfy the desires they have learned to value.”
Some of the behaviourist designs I have employed include:
When I was teaching network security, there was a particular module of learning that students found difficult to remain engaged in. Without the opportunity to make changes to the design of this learning module, instead I attempted to improve engagement in the material and the class activities through small rewards of the confectionery type. The class activity was question and answer sessions where I would go around the room soliciting solutions from students. Those who got the answers correct would receive a chocolate reward.
It was mildly effective. In subsequent offerings, I redesigned the learning activity which proved more effective.
1Gb Memory sticks
Similar to the situation of the chocolate bars, I made a competition of the question and answer time and kept a tally of correct answers for students. The top two students received a free 1Gb memory stick. At the time, 1Gb was quite large, and being IT students, it was an attractive item. This was more effective than the chocolates. Seems it was a better reinforcer than the confectionery.
Access to a desirable learning activity
When I was teaching data communications, I included an activity that was popular with students. The activity was for students to be hands-on with creating their own network cables using Cat 5e UTP cable, connectors and a cable crimper. I organised for network engineers and support staff from the university’s networking team to volunteer their time in my class, and assist with the learning activity. I split students into groups, and then assigned them a mentor from the volunteers. Each would then guide the students through the process of connectorising their computer cables. On completion, the students would then attach their cable to a tester and determine if the cable was connectorised correctly.
The first time I ran this activity, students were unable to recall the order in which the individual wires were to be connected, despite setting it as homework. This delayed the activity and quite a few students resulted in faulty cables.
To improve on this situation, the next time I ran this activity, I set the homework to rote memorise the order of the wires. They are colour coded. The students were told that they would have to recite the order of the coloured wires from memory before they were permitted into the activity room.
On the day, I went around the room asking students the order – those who had it correct from memory were permitted into the adjacent room to commence the activity. Those who couldn’t remember, would have time to revise, and after cycling through the class, I would return to them. Three quarters of the group had it correct first time round. The activity ran to schedule and there was only 1 faulty cable at the end.
Similar results were repeated in the following offering of the course. This proved to be an effective design. Also on reflection, with the inclusion of the volunteer mentors, it was a form of cognitive apprenticeship. 🙂
Desire to win
It had been suggested to me that nothing will bring out the inner fire of a geek more than a little healthy competition. This was in response to queries about how to improve engagement from the students.
When I was teaching System Administration, I was looking for a way for students to develop problem solving skills, and at the same time, gain a deeper understanding of how the UNIX shell parses and executes commands. So I set a challenge and divided the class into two groups. As teams, they were required to write a UNIX shell command that would perform a specified set of actions with the greatest efficiency, and the minimum exec system calls. My apologies for the non-geek reader. 🙂
There was no prize but the glory of being the winner. Boy were they right. The students engaged with gusto, searching through documentation, man pages, howtos (even espionage) to come up with the ideal solution. The winners had bragging rights for weeks to come. It was also encouraging to see that the score difference between the two groups was by only 1 point, and the winning team’s score was only 1 point short of my own model solution.
It seems to me that behaviourism is not the trendy learning theory of the day, yet in certain circumstances, I believe they can be quite effective. It is not something however I would use to underpin an entire course design.