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I’ve recently completed a literature review on the topic of Massively Open Online Courses (and, more specifically, whether there is compelling data-based analytics that support the investment in such a platform). What has resulted from my initial review is a curious new learning theory: connectivism, devised by Siemen and Downes, which supports the use of MOOCs from a theoretical standpoint.  Here is an excerpt from my review:

Initial keyword searches of “MOOC” both on the web and within academic journal search engines revealed a consistent theoretical framework behind the MOOC: connectivism. In fact, Clarà and Barberà (2013) revealed that some in the field have begun to classify two types of MOOCs: cMOOC (or connectivist MOOC) and xMOOC (other types). The xMOOC doesn’t necessarily use a particular pedagogical strategy, although Clarà and Barberà found that a behaviorist approach is normal in those “non-connectivist” MOOCs.

Why identify connectivism beyond the three most widely-recognized pedagogical concepts of constructivism, behaviorism, and cognitivism? Siemens and Downes (as cited in Clarà and Barberà) rationalize that traditionally, knowledge is a thing; that is, a representation of what a person can create or appropriate. Web 2.0 and associated technologies create a multiplicity of perspectives and therefore do not mesh with the thingness of knowledge. Siemens and Downes, in response, proposed a new learning theory: connectivism. Connectivism demonstrates the following two key concepts in digital learning (Clarà & Barberà, 2013):

  1. “…Knowledge is subsymbolic, and that representations are just epiphenomena of knowledge, but not its matter.” In other words, knowledge is a representation of the recognition of association of patterns.
  2.  “These neuronal associative patterns are caused by the learner’s recognition of associative patterns between informational entities (named nodes) located outside the learner and organized in a network. In the Web 2.0 environment, the nodes would be people, materials, and tools that the learner connects to.”

Mackness, Mak, and Williams (2010) studied the Connectivism and Connected Knowledge course offered by Siemens and reported the participants’ reactions, especially with regard to the concept of connectivism. They wrote, “…participants [experienced] the principles of connectivism – autonomy, diversity, openness and connectedness in practice. Our findings suggest that these might all be achievable in a complex learning network, but in a course (as opposed to a network), particularly a massive open online course, they can be compromised.” What’s especially relevant about this connectivism study is that it took participant feedback and compared it to successful outcomes in the course itself.

Although the course was specifically tackling the topic of connectivism, because Mackness, Mak and Williams equated connectivism with MOOCs, the results are some of the few and far between evidence-based dialogues on the subject. “It may be true that all learning begins with a connection, but connectivity itself is not a sufficient condition for connectedness or interactivity,” they found.

Clarà and Barberà (2013), meanwhile, dispute the psychological underpinnings of connectivism. They posit that the theory itself is a learning paradox: how does one recognize a pattern if one doesn’t know there is a pattern to be recognized? If one does recognize the pattern, how should he or she know the significance of the pattern? Practically, without leadership and direction, students without the ability to self-regulate at an advanced level feel lost.

Secondly, they propose, the node theory of connecting with another human being is not a binary on-off switch. Rather, building of relationships is a fluid concept that grows (and wanes) as a dynamic process. The authors characterize this fault as underconceptualization of relationships and connections.

Finally, Clara and Barbera claim that connectivism doesn’t explain concept development. As with connecting nodes, learners do not understand concepts as a binary: learning psychology for decades has supported continued growth of the understanding of a concept. A 12-year-old does not understand a concept the same way that he or she did at age four. In the twentieth century, associationism was abandoned for this very reason (in the Vygotskian tradition of cultural psychology).

Even with their critique of connectivism as a theory, Clarà and Barberà don’t call for the abandonment of MOOCs entirely. They urge that a new and adequate pedagogy be developed for xMOOCs.

Connectivism is not without its champions. Rodriguez (2012) characterizes one of the case studies of a cMOOC as a success (although surreptitiously quoting Siemens, the thought-leader behind connectivism, is not terribly convincing). With a lower drop-out rate compared to the Stanford-style courses and a peer model, Rodriguez concludes that though the experience for participants was different, it was still valuable.


Clarà, M., & Barberà, E. (2013). Learning online: Massive open online courses (MOOCs), connectivism, and cultural psychology. Distance Education, 34(1), 129-136. doi:10.1080/01587919.2013.770428

Mackness, J., Mak, S., & Williams, R. (2010). The ideals and reality of participating in a MOOC. Paper presented at the Seventh International Conference on Networked Learning, Aalborg, Denmark. Retrieved from website:

Rodriguez, C. (2012). MOOCs and the AI-Stanford like courses: Two successful and distinct course formats for massive open online courses. European Journal of Open, Distance and E-Learning, 23(1). Retrieved from website:

(This post was originally written in the College of Western Idaho’s Virtual Campus Newsletter, March 2013.  It provides help and resources for online instructors.)

What is a video lecture?

A video lecture is a digital lecture you post on your Blackboard site.  It is different than your standard PowerPoint presentation.  It can include:

  • Video/audio of the instructor with accompanying content (like slides)
  • Instructor demonstrating a process, such as recording a welding technique
  • Presentation that covers multiple subjects with intentional breaks and practice quizzes embedded

There is no “one way” to accomplish this.  It’s a creative process and depends entirely on your subject matter.  For example, a Math lecture may look like this, while a Diesel Mechanic tutorial looks like this.

Why should I use it?

In a word: presence.  Instructor presence is critical to building a connection with your students.  In addition, if you create easy-to-follow multimedia presentations with a comfortable interface, your students will have access to material throughout the semester that they can easily refer back to.

Students don’t always learn from simply reading.  They also don’t learn from a 45-minute long video with an instructor talking straight into the camera.  They need the same demonstration and practice opportunities they would receive in a face-to-face lecture.

How do I do it?

We recommend starting small.  You can start by adding audio to your PowerPoint presentations and setting them to auto-run, or giving short introductions recorded on a webcam at the beginning of each new unit.

You can use Camtasia or record your Collaborate sessions, too.  There are a lot of options available!

Francisco Dao writes, “If you listen to the advocates of online learning, MOOCs and Internet-based courses will cure all of our education problems. Just hand out some Android tablets, stream some courses in Python, and sit back and watch as everyone magically becomes a highly productive knowledge worker propelling the United States to new heights of economic prosperity. But this vision of online learning is so ridiculous I’m waiting for Ricardo Montalban to show up in a white suit and welcome these people to Fantasy Island.”

I have no idea what wretched organization he’s referring to, or what e-learning professional would ever recommend handing out toys and expect results. 

I’ve written time and time again the critical need for, at the very least, the ADDIE model when considering any new learning initiative (academic or industry).  There is an incredible level of upfront analysis that Dao seems to have never experienced.  The modality of instruction is merely one of the questions an e-learning practitioner considers when designing and developing instruction – and any practitioner who only sees the bells and whistles of a tablet PC is in the wrong field.

Check out my old friend Dustin Verburg’s piece on Teaching Social Media.  You can find the blog post here.

I’ve very recently moved from private industry instructional design to higher education.  So to give you an idea of what we’re up against, take a look at this fact sheet from Educause Center for Applied Research:

By Kevin Taylor

This is something I have been pondering since I accepted a position at Temple University. As a student, I was never really attuned to Boise State University’s administration. It was always there in the background, helped me register for classes a few times, but for the most part they were the invisible hand behind my academic experience. After being the member of the administration at a nationally ranked university, I can see the wizardry conducted behind the curtain. What I see are a large number of very talented and hardworking people trying adapting to an ever-changing and evolving landscape. There are many struggles facing higher education; increased tuition costs, a dire tax situation, and student loan mechanisms that are commonly seen as broken and misaligned. There are some problems the university can’t fix, but there are other challenges that it can.

Process Design

One of the biggest areas of improvement I can see is process design. Universities are notoriously siloed, and oftentimes what occurs on a functional team doesn’t always align with the goal of a cross functional process. Identifying critical processes around fundraising, admissions, financial aid, housing, and scheduling could help find much-needed efficiencies. The ability to reliably conduct university operations in a manner consistent with Lean, Six Sigma, and TQM best practices could yield tremendous gains and reduced costs for universities with savings that could be used to help expand services, create jobs, and invest in university talent.

Knowledge Management

When processes and procedures change and evolve, there needs to be documentation. “Why do we need to document stuff?” you might hear stakeholders ask, secretly terrified that a loss of transparency in their work may result a loss of control or employment. What I find so funny about this is that it’s typically very difficult to get released from a university. There are ways that this happens, but even poor performance is not usually enough to get you dismissed. However, there is turn over, promotions, and the lucky ones get to retire to a tropical island to enjoy tasty drinks with little umbrellas. This means that all the knowledge they have about their processes, procedures, and where “the bodies are buried” leaves with them, and others must reinvent the wheel. Instilling a culture of knowledge management, providing tools and the training to use them (e.g., in-house wikis, Microsoft OneNote, etc.) and re-enforcing this culture through including knowledge management in job descriptions is critical.

Leadership Development

Process Design and Knowledge Management are business disciplines that require a high degree of leadership to help cut across the silos, agendas, and administrative fiefdoms common higher education. According to Wikipedia, Sayre’s Law states, “In any dispute[,] the intensity of feeling is inversely proportional to the value of the issues at stake.” Wallace Stanley Sayre, former political science professor of Columbia University, also added that, “Academic politics is the most vicious and bitter form of politics because the stakes are so low.” Now, while not all university leaders fall prey to this trap, there are some that do. Personality politics, personal agendas, and other sources of organizational toxicity notwithstanding, there are some truly brilliant leaders in academia that would benefit from leadership development in the form of meeting facilitation skills, project management (in all its various forms), employee engagement, and so on. Without the basic self-awareness, interpersonal skills, and organizational best practices needed to support the first two opportunities, it’s just going to be business as usual.

How Can Instructional & Performance Technologists Help?

The value we can add as Instructional & Performance Technologists is threefold. First, we can help leaders identify opportunities for organizational performance improvement by conducting the qualitative research needed to identify issues at the ground level. We are good at talking, listening, and putting together the puzzle pieces to help identify the current state and help leaders articulate a clear future state. Second, we have the ability to help articulate the Knowledge Management strategy and professional development plans needed by the organization. With Knowledge Management (including the more grass-roots variety), there needs to be a formal training program to support new talent. Finally, we are in a position to build the leadership development programs needed to support these first two components. Pulling these three components together, higher education has the opportunity to excel at what they have done since time immemorial, work to make the world a better place to work, live, and play.

 KeviKevin Taylorn is a Training and Performance Improvement professional in the Philadelphia area.  He can be reached on LinkedIn at

Couldn’t help but share this – visualizing mLearning’s future with a chuckle!

The Future of Mobile Learining


Interesting insight from Workforce, discussing the new Apple iBook Author software. I tend to agree with Mr. Paskoff. While it’s pretty neat that anybody can put together a slick-looking eBook, it’s just another tool to make content look nice. Without solid e-learning practices, I doubt reading a media-rich eBook will cause learning or behavioral change.

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