This article is an attempt to address a possible gap in Connectivist thinking, and its expression in cMOOCs. It’s to do with the experience of technology novices, and unconfident learners in cMOOC environments. It comes from a phenomenon, and experience I identified in a recent MOOC I participated in and the experience is best described like this:
To learn in a cMOOC you need to connect.
To connect in a cMOOC you need to learn.

I’m not a Constructivist, Behaviourist, Cognitivist, or Connectivist. This is not a call for a return to an older theory. I’m a pragmatist, like many educators. I flirt outrageously with every theory that will have me. I’m ideologically promiscuous. I go with what works, and I am ruthless in weeding out what doesn’t. I do this because there is no “one size fits all” theory. Because there is no “one size fits all” student. And because students, participants, and learners are the final metric that measures any theory, and experience is the proving ground for theory. Faith to a theory, ideological monogamy, gets in the way of the evidence.

This is the beginning of a conversation with myself and others about where my online practice should go, rather than the end of one.  I want to focus on the novice experience in cMOOCs, and how the theory may badly serve some of its participants.

What we think about who we are, and where we are, tells us how much we are likely to learn. This is key to the gap in Connectivist thought. Central to that gap, at the core of what I think Connectivism might be missing is this idea:
Motivation is the engine of effort, and the sense of self is the ticking heart of motivation. Our sense of self is formed by the experiences we have, the environments we have them in, and the people who design those environments. And that negotiated sense of self can engineer the success or failure of the educational experience. It can also shape our sense of ourselves long after the experience is over.

One of the most important aspects of the learning experience is motivation. And one of the most important aspects of motivation is our sense of our own capability, and our sense that the environment we are learning in will allow us to achieve.

That sense of self, and how educators, participants, and experience converge to engineer it, is the focus of Albert Bandura’s ideas on self-efficacy, which are the ideas around which this article is built. In particular, how technology and learning novices, and their sense of confidence interact with Connectivist theory.

Albert Bandura, Self-efficacy and Motivation
Self-efficacy is one of Bandura’s ideas, and is, he says, the greatest predictor of student success in learning. It’s something Connectivist theory (but not all Connectivist practitioners) largely ignores. Self-efficacy is our belief that a task is achievable by us, and that the environment in which we are working will allow us to achieve that task. It’s that ticking heart that measures out the motivation in us.

High self-efficacy students tend to try harder, for longer. They overcome obstacles, can cope with failure, and continue to strive. They are less easily discouraged. They will be more ambitious, and more likely to achieve those ambitions in their learning.

Low self-efficacy learners tend to try less hard, and for shorter periods of time. They are more likely to blame themselves for lack of success, they are easily discouraged by failure, they strive less hard to overcome obstacles, are less ambitious, and achieve less.

Self-efficacy is, in part, the story students tell themselves: I am going to succeed. I am going to fail. This is beyond, beneath, or within me. But as educators, we help shape that script. We set tasks that are challenging, and achievable, and we create environments that allow achievement to happen.

We provide experiences that enhance students’ self-efficacy, and improve their opportunities for success, enhance their confidence, and improve their long term chances and strategies for success.

What We Know, and What We Can Come to Know
Cognitive load, and Prior Knowledge are key here, at times ignored by Connectivism, and either dismissed or not designed for in both theory and practice. They have a huge determining effect on what we can learn, and how we learn it, and are particular issues for novice learners.

Cognitive load is the amount of information we can take in, process and retain. It’s probably fixed, and not that large (between 3 and 9 pieces of information, depending on who you listen to, and how difficult or new the task is). Complex, new, or difficult tasks have a high load. Simple, known or easy tasks have a low load.

Cognitive load has a relationship to feelings of fear and anxiety, and to mastery experiences. It’s also a critical mechanism for explaining how and why novice learners particularly may have difficulty in unstructured environments.

Too high a Cognitive load decreases a student’s sense of self-efficacy. Too low triggers a boredom threshold that tends to stimulate disengagement. Novices in an area have high cognitive loads, and, typically low Prior Knowledge (the idea that what we already know has a powerful determining effect on what we can learn, and how quickly). This is key. It is variable amongst students generally. And it must be flexibly designed for, or we risk failure.

Cognitive load and Prior Knowledge are why we tend to teach absolute novices using techniques and contexts that are different to the ones we deploy for absolute experts, and why we avoid exposing novices to too much chaos. We start to drive in car parks, not motorways, we learn the names for foods before we deal with negative inversion when learning a language. We learn how to log in to a computer before we learn to code. We are still bundles of brains, experiences, and nervous systems sitting on the other side of a screen. This has not changed. Or been optimised by technology.

This is partially why, when we treat experts like novices, we bore and lose them. If we treat novices like experts we depress and lose them.

In Connectivism, the distributed platforms, the networked nature of learning, the requirements for metacognition, digital literacy, the new tools and techniques add significantly to the novice’s cognitive load. Connectivist theory does not differentiate between novices and experts. And that can be to the disservice of both.

Manufacturing the Sense of Competent Self
Educators encourage or undermine self-efficacy in four ways, typically. Lets look at this in reverse order. Least powerful effect first. (These are taken from the two Bandura articles).

1. Physical and psychological responses.
We reassure students, so that their fears, anxieties and uncertainties are, largely, allayed. Fear and anxiety interfere with a person’s ability to learn, and are, especially for novice learners, an active obstacle to achievement. Novices will tend to feel fear in environments that don’t scaffold for, or support, their needs. This fear lowers their sense of how likely they are to achieve. It also adds to the cognitive load. Novices will give up faster, work less hard and feel less motivated in these contexts.  Connectivist theory does not allow for novice support, from the design and instructor side. It actively encourages us to avoid scaffolding. Students are left to their own devices, whether or not those devices are fit for the purpose. Peers can help to a degree here, with support, encouragement and advice, but, novices who are not supported as such by their instructors and designers are much more likely to fail.

Is Connectivism the theory that sank a thousand learners? Bad classrooms the world over are littered with students who are lost, unsupported, and not learning. There’s oodles of evidence out there that, in general, undirected novices do far worse than directed novices. This is an old lesson waiting to be relearned by Connectivist theory.

2. Encouragement and persuasion.
Good educators provide encouragement, and verbal persuasion, which can increase a student’s self-efficacy. And, the more we are considered to be experts, or authorities, or trustworthy, or prestigious, the more powerful that effect is. Again, individual Connectivist educators can and do provide this. Peers also provide this to a degree. Student success under these circumstances increases their motivation, faith in the process and participants, and their sense of self-efficacy. Failure in the face of this type of encouragement can have the opposite effect. The more we respect those who encourage us, the more failure damages our sense of self. More reason to be careful. More responsibility to shoulder.

Classic Connectivism disregards the theories involved here (constructivism, behaviourism, cognitivism) as outmoded. Educators should be absent, or at most facilitators and not teachers. And peer rewards, or the rewards of social engagement, are not considered to be the primary drivers of motivation.

We cheerlead, and we put students in positions where the cheerleading leads to success, as cheerleading them to failure is carnage. This is part of the responsibility we shoulder when we invite them to participate in experiences we design, and that can have considerable impact on their ongoing sense of themselves. Novices, already in a tough spot where Connectivism is concerned, tend to need this type of support more. The absence of the educator presence, of the cheerleading ethic is a Connectivist design choice. It’s the removal of one more scaffold.

The choice is between serving hundreds an undifferentiated experience that is massively accessible, and personalisation, serving a smaller number an experience that is supported. The difference in cost is measured both in resources, and in lack of success. The challenge is to combine these approaches.

3. Vicarious experience.
Simply put, our sense of our own capability increases when we see people we consider similar to ourselves achieve at a task.

When novices see other novices that they identify with achieve a task, their sense of their own ability to achieve, their self-efficacy — the amount of effort they will deploy, and the length of time they will persist for — tends to increase. There is some evidence to indicate this effect is also present where participants see instructors as similar to themselves.

Conversely, seeing peers succeed and ourselves fail can be highly destructive to self-efficacy, confidence, and, potentially, for learning in that field. Participants who experience failure in contexts where they see people they conceive of as similar to themselves succeed will tend to feel a lowered sense of self-efficacy as a consequence. They can be unwilling to try a similar learning experience subsequently, and may feel themselves to be less capable learners than they had initially thought. Participants may self-blame, feel inadequate, or possibly, in extreme cases, undergo aspects of depression. Placing participants in contexts where they are likely to fail heightens this possibility.

There’s a huge responsibility here. Design for experts, and invite novices, and watch novices get shot out of the sky. The burning wreckage you can see trailing off the back as they quit is self-esteem.

4. Mastery experiences
Mastery experiences provide students with the greatest boost to self-efficacy they will encounter in an educational context. The more students don’t succeed at mastery experiences, the more likely they are to suffer a decrease in self-efficacy. Lower self-efficacy students are more likely to feel this as a consequence than more confident learners.

Good mastery experiences, for novices, are characterised by corrective feedback, achievability, and a cognitive load that presents both a degree of challenge, but also leaves enough space for complex learning. They don’t bore, they engage, they are challenging and attainable, and they track the moving target that is the developing learner as their needs and abilities change.  Mastery experiences need to be clear in terms of the path to achieving them, and to feel achievable to the novice. They also need to include, once mastery is achieved, freedom to play with, and apply the tools and skills learned in self-directed ways. Otherwise the learning and self-efficacy boost can fade. Failure to provide students with achievable mastery experience damages their opportunities to learn, and, possibly, their long term sense of themselves. Connectivist theory, in eschewing almost completely structured, scaffolded experiences like this places many novices in a difficult position.

Prior knowledge makes the learner a moving target. And it’s hugely important, possibly the single most important aspect that determines how effectively we can learn. We teach to what the student knows already. We adapt to them. We shift their targets and move with them. We design for their needs. Failure to take the student’s specific needs into account is a basic error. Students don’t conform to theories. Theories conform to students.

Connectivism, as a theory, generally does not provide support for, or recognition of, prior knowledge, cognitive load, or novice issues, or recognise particular novice needs,  even though individual connectivists sometimes do, or try to. It fails to structure experiences to follow that moving target. Its lens does not focus. Difference is blurred, and opportunity is lost. People fail.

Helping Your Novices to Fail to Succeed
If you want a low self-efficacy learner, or novice to fail, here’s four surefire ways to grease the pole. Each reminds me of something I’ve seen in a MOOC, or read in the literature. Each reminds me of something in theory. Each is something I’ve seen.

  • Watch your peers succeed, while you don’t. “All of my peers are nodes! Look at them connect! Everyone else seems to be succeeding! Why am I not?”
  • Too high cognitive load, and no assurance, or anxiety relieving measures. “New to Connectivism and social media? Here’s 300 tweets, 700 Google+ posts in your inbox, 70 blog posts, and a Java-enabled seminar software environment you’ll need to calibrate your laptop to access (on a MAC we call that an adventure!), using totally unfamiliar software! Say hello to the LMS too! First task due yesterday, create a digital artefact using a piece of software you’ve never encountered!”
  • Decentralise the learning process to a degree where clarity and structure require skills you don’t have to access the information you need. “Four different platforms! The information is out there! Somewhere! Choose your own path to it! In Connectivism, no one can hear you scream! (If you don’t tweet it with #helpImdrowninginthefreedom)”
  • Tasks that are too complex with no guidance in how to achieve them. “Everyones a node! Connect to learn! Setup your blog, crosspost to Google+ and socially curate to Diigo while using Audacity to post a podcast to Tumblr! That’s updated on Twitter! I’ve done my bit. Now learn!”

All Nodes are Equal, but Some Nodes are More Equal than Others
Some people aren’t actually nodes. If I type a 140-character message into Twitter and don’t know how to use a hashtag, can anyone really hear me tweet?

Not everyone knows how to be a node. Not everyone is comfortable with the type of chaos Connectivism asserts. Not everyone is a part of the network. Not everyone is a self-directed learner with advanced metacognition. Not everyone is already sufficiently an expert to thrive in a free-form environment. Not everyone thinks well enough of their ability to thrive in an environment where you need to think well of your ability to thrive.

Learning to be a node in a cMOOC environment is hyper-demanding. Learning the tech tools, while conforming to a new pedagogy, navigating multiple platforms, and fielding hundreds of messages about unfamiliar ideas from people you don’t know with patterns you may not recognise. Connectivism’s assumptions — we are all digitally literate nodes, knowledge is in the network, we are all motivated, have good learning strategies, and information sifting abilities, and can cope with multi-platform information streams, in an environment where instruction is at most facilitative, but probably absent — mean that the sensitive design of experience that engages prior knowledge, motivation, confidence level, and student need is absent, and not possible.

Technology does not represent a psychological year zero. And if we unlearn the hard fought lessons of the past we fail our learners. We will design for predictable failure.

It’s not difficult to design for novices. It’s not difficult to give people the tools they need to catch up. It’s not difficult to connect if a sensitive, careful and thoughtful design is there to connect you to the help you need.

Designing for Failure
MOOCs are littered with the drowned, who want to participate, but see their sense of possibility get sucked under by an experience designed to, in part, ensure they sink. Connectivism’s mistakes have already been made. We have a  history of knowledge and experience to draw on. Technology and ideological elation do not relieve us of our responsibility to apply the hard won past to the overly optimistic present. Learners dictate the shape of theory, and this, as much as in person as online, is the driving force behind what we do, how we design, what experiences we put our participants through.

cMOOC organisers are no less designers than their xMOOC counterparts, and no less responsible for the experiences their participants have. It may not be ideal, perfect, or particularly desirable, but the reality is, we exert significant control, potentially, over an important sense of how students conceive of themselves as a consequence of how we design.

Many of Connectivism’s finest practitioners seem to know and intuit this. They model and cheerlead. They scaffold and support. It’s inspiring when a great, and involved educator puts that part of themselves into a MOOC experience. I’d put Alec Couros in this category, for example, and his presence, participation, persona, and educator’s intuition in etmooc. I’d put Alison Seaman in the same category. I’d put aspects of ds106 and the infectious enthusiasm of Alan Levine in here.

But more needs to be done. And I guess, in part, my point boils down to this. The theory needs to catch up with its best practitioners, and its most challenged learners.

Additional Resources:
Stephen Downes, “Connectivism and Connective Knowledge
Stephen Downes, “Creating the Connectivist Course
Paul A. Kirschner, John Sweller, & Richard E. Clark, “Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based experiential and inquiry-based teaching
Rita Kop, “The challenges to connectivist learning on open online networks: Learning experiences during a massive open online course
Rita Kop, Helene Fournier, & John Sui Fai Mak, “A pedagogy of abundance or a pedagogy to support human beings? Participant support on massive open online courses
George Siemens, “Connectivism: A Learning Theory for the Digital Age

And a full bibliography for this article with annotations.

[Photo by nickwheeleroz]