Twitter, PLEs and PLNs

Thought I would share some bits of my thesis on Twitter, PLN’s and PLE’s  as others might find it useful.

What is a PLN?

For all of the conversation occurring among educators about PLNs, there has been surprisingly little academic research on PLNs (Couros, 2010, p. 123). With many educators using this term to describe their own informal learning habits, it is important for educational researchers to investigate exactly what this concept means to those who are using it as a term to describe a learning activity

A Personal Learning Network (PLN) is a network of people you connect with for the specific purpose of learning (Tobin, 1998). These people may assist you in your learning by acting as a guide, direct you to learning opportunities, and assist you with finding answers to questions (Tobin, 1998).

Digenti (1999) defines a PLN as:

relationships between individuals where the goal is enhancement of mutual learning which is based on reciprocity and a level of trust that each party is actively seeking value-added information for the other (1999, p. 53).

Couros (2010) echoes Digentis notion that a PLN is defined by the relationships among the individuals when he states that:

“a PLN is the sum of all social capital and connections that result in the development and facilitation of a personal learning environment” (2010, p. 125).

In order to fully understand this definition, a distinction needs to be made between the Personal Learning Network (PLN) and the closely related term, the Personal Learning Environment (PLE) as the two terms are often used interchangeably when, in fact, they refer to two separate conceptual models.

A Personal Learning Environment (PLE) can be thought of as the ecosystem that enables a PLN. A PLE represents

“the tools, artefacts, processes, and physical connections that allow learners to control and manage their learning” (Couros, 2010, p. 125).

Using this distinction, Twitter, along with other ICT’s, are tools of the PLE that enables interactions with a PLN. These other ICTs are significant as the PLN is not limited to interactions on Twitter alone and encompass not only other ICTs, but also face-to-face and non-ICT mediated interactions.

The other ICT’s  that are often used alongside Twitter can be divided into three broad categories; technologies used to enhance, extend, view, or manage Twitter data, technologies that are used in conjunction with Twitter, and technologies that are used independent of Twitter.


  1. Technologies used to enhance, extend, view, or manage Twitter data: Twitter extensions are tools that specifically enhance, extend, view, or manage Twitter data. This category can further be divided into three subcategories;
    1. technologies which participants use to view and manage the Twitter data stream (Tweetdeck and HootSuite),
    2. technologies that participants use to repurpose or modify Twitter data (such as, Packrati,The Tweeted Times), and
    3. technologies that are used to search Twitter data.
  2. Technologies used in conjunction with Twitter: Technologies in this category are tools that can be used independent of Twitter, but are often use in conjunction with Twitter, such as  blogs, social bookmarking applications (Delicious and Diigo), and collaborative tools (Google Docs). For example, Twitter itself is not a collaborative platform in that participants do not use it to collaboratively create a tweet. However, Twitter is often used in conjunction with Google Docs, a collaborative document authoring application, to help facilitate the creation of a shared resource among the PLN.
  3. Technologies used independent of Twitter, but may also be used for PLN activities. Other technologies that are used independently of Twitter. Examples are Facebook, LinkedIn, forums and Ning.

This is not an exhaustive list of ICT’s used within a PLE, but a sample based on interviews with thesis participants. PLE = Personal Learning Environment; PLN = Personal Learning Network; Data = Technologies used to enhance, extend, view, or manage Twitter data; Conjunctive = Technologies used in conjunction with Twitter; Independent = Technologies used independent of Twitter, but may also be used for PLN activities


Lalonde, C. (2011). The Twitter experience?: the role of Twitter in the formation and maintenance of personal learning networks. Retrieved September 13, 2011, from

Couros, A. (2010). Developing Personal Learning Networks for Open and Social Learning. Emerging Technologies in Distance Education (pp. 109-127). Edmonton, Canada: AU Press.

Digenti, D. (1999). Collaborative learning: A core capability for organizations in the new economy. Reflections, 1(2), 45-57. doi:10.1162/152417399570160

Tobin, D. R. (1998). Personal Learning Network. Retrieved October 4, 2009, from


3 research studies on potential advantages of using Twitter in the classroom

Three academic studies are cited in this article about Twitter, and how it can increase student engagement, enhance social presence, and help develop peer support models among students through the formation of personal learning networks.

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A small but impressive study of students at Lockhaven University in Pennsylvania found that those who used Twitter to continue class discussions and complete assignments were more engaged in their classwork than students who did not.

Four sections (70 students) were given assignments and discussions that incorporated Twitter, such as tweeting about their experiences on a job shadow day or commenting on class readings. Three sections (55 students) did the same assignments and had access to the same information, but didn’t use Twitter.

In addition to showing more than twice the improvement in engagement than the control group, the students who used Twitter also achieved on average a .5 point increase in their overall GPA for the semester.

An earlier study [pdf] by Joanna C. Dunlap and Patrick R. Lowenthal from the University of Colorado at Denver found that Twitter was able to “enhance social presence” and produce other instructional benefits in an online course.

Another experiment into the use of social media at the University of Leicester found that tweeting helps to develop peer support among students and personal learning networks and can be used as a data collection tool. Read a more detailed description of the experiment here. [via Faculty Focus]



On social software & student ownership of their own tools

Two points from this article. First, social software enables learning conversations to occur outside of the classroom, not only between students, but also between students and the larger community. Second, when students taking ownership of their own tools, they are set up to become lifelong learners. My take is that this requires flexibility on the part of educators in that they have to be willing to go where the learners are and let the learner decide where they want these conversations to occur.

Amplify’d from

But, most importantly, their learning experiences often involve a conversation, a process, and this conversation can include teachers and others with knowledge in their field. The skills students gain in the process are those they need to join a wider community and succeed in today’s economy.

Colleges and universities need to do more to incorporate social software into their courses and methodologies. I hear from faculty and administrators regularly about transformations of entire programs to the social/conversational/active learning paradigm of today.

This extension of the learning conversation online (with blogs, wikis, e-mail, texting, chat, conferencing systems, portfolios, and so on), helps students develop online literacy skills. Though it is dependent on technology, it represents a return to the roots of human learning. Learning has always involved conversation. In fact, knowledge results from, or increasingly is, consensus-building through conversation.

To the extent that students are engaged in that conversation using their own–literally their own–Web and Internet applications, some of them have a chance to become independent, life-long learners and enjoy a better chance to develop their own expertise





I’ve signed up for Personal Learning Environments Networks & Knowledge, a Massively Open Online Course (MOOC) from Stephen Downes, George Siemens, Rita Kop and Dave Cormier. I am not sure how much I will be able to participate, considering I am already in the throes of a thesis, but the topic is so perfectly aligned with my thesis research on PLN’s, informal learning and the role of microblogging that I couldn’t pass up the opportunity to participate at some level.

Conceptually, there is a pretty clear distinction in my head between PLE’s and PLN’s. In very broad terms, I think of PLE’s as the technology, with the PLN being the people. The PLE enables me to build a PLN. Not that everyone who is part of my PLN requires technology to connect with, but technology has made my PLN much richer, more diverse, and instantly available.

Personally, I am more interested in the PLN than the PLE. Considering I am primarily a technologist in my day job, this is probably a bit off-kilter, but while I use a PLE (built primarily in Netvibes and good ol fashioned, still alive and kicking butt in my little world RSS) and find it invaluable to my learning, I realize I am not a typical user. I do wonder how viable the idea of learners constructing their own environments really is within the context of higher education, which is one of the things I hope this course will help me come to terms with.

But the PLN – I am much more interested in the PLN as a learning construct, both formally and informally, and how it is similar or different to other learning constructs, such as networks of practice and communities of practice.

About a year ago, I wrote about my casual search on trying to historically define the term Personal Learning Network, and came across a 1999 article by Dori Digenti called Collaborative Learning: A Core Capability for Organizations in the New Economy (pdf) in which she noted that reciprocity and trust are two crucial elements in constructing a PLN. I have thought about, and referred to, this article a lot in the past year, specifically when speaking about the idea of reciprocity and how it manifests itself in a network enabled PLN. The more I have thought about it, and the more I examine my own use of a PLN, the more I realize that the reciprocity in a PLN is not so much between myself and individuals within the PLN, but between myself and the PLN itself. I find myself both answering and asking questions to a relatively anonymous group of people whom I have weak ties with, with whom I have developed a certain level of trust with, based primarily on the ambient exposure I have to them and their ideas as a result of them being open and transparent on the web. How did I get to trust these people? Why do I think they know something that will help me? And what are the expectations of me of the people who choose to include me in their PLN? What are my responsibilities? Or are there even any responsibilities?  Oh, the questions.

The other point on PLN’s that I am interested in is a bit more grounded, and that is whether people who use PLN’s use them as a general tool, or segment them to professional development. In my view, a PLN is a general learning tool regardless of what I want to learn, yet I often see PLN’s used primarily as tools for professional development. But I realize that I only get a small glimpse into other people’s PLN’s based on who I am and the role they believe I play in their PLN, so this is probably not the case.

Okay, I need to wrap this up. Hopefully I’ll be able to articulate some of this more clearly in the coming weeks, and be able to contribute to your PLN’s in a meaningful way. At the very least, I am happy to be along for this PLENK2010 ride.


Adaptive learning, disputes, and breaking out of echo chambers

I have just installed a FireFox addon called Dispute Finder. Dispute Finder is an addon developed by Intel Research and UC Berkley that highlights disputed information on a web page and displays alternatives to that disputed claim. It uses both crowdsourcing and curated resources to try to expose you to alternative views about what you are reading.

As my Masters has progressed, I find myself becoming increasingly interested in adaptive learning systems and the role that technologies could play in shaping a users personal learning environment. Now, I am no computer scientist and when I hear words like ontologies being thrown around I have to admit my head begins to ache slightly. The depth of my knowledge of semantic web technologies doesn’t go far beyond a high level flyby of FoaF and RDF . Nonetheless, I remain interested in advancements in recommendation systems, both technical (semantic) and human (folksonomies) and the implications they could have for learning and constructing knowledge.

More and more on the web we are seeing personalized recommendations pop up for us to explore, often based on our past behaviours or, increasingly, recommendations provided to us by our social networks. Amazon recommends books to me not only based on what I have bought or browsed before, but also what other people who have bought or browsed similar titles to me have found interesting. Facebook will recommend friends to me based on who is already in my network, and adjust the information I see about that network based on my viewing habits (and some other variables, I am sure).  When Facebook introduced a real time stream a few versions ago, it did so with a News view and a Live view. At the time I wasn’t sure what the differences were, but after using it for awhile the advantage of the News feed becomes clear. The News feed is content that the system deems to be more relevant to me – it is a filter to help control the tidal wave of network information (I have Clay Shirky in my head saying “it’s not information overload – it’s filter failure“). And most of the time, it is right.

I am intrigued by what it means for learning if some of the construction of these connections is being done by technology, and how educators can assist learners in setting up environments that are conducive to this kind of semi-organic discovery. On one hand, these types of recommendations help to bring order to the chaos and may open up paths for exploration that may not always be obvious. On the other hand, they also set up the possibility of developing echo chambers. If the only information I am being exposed to is information congruent with my own views, then how can I be expected to become a critical thinker? After all, being critical often means being able to discern between two opposing points of view. How can you do this if you are only being presented one point of view?

Which brings me back to Dispute Finder and why I find this project interesting. Dispute Finder seems to depart from the general trend of recommendation engines on the web. Instead of recommending things it thinks I will like, it shows me information that may not be aligned with my own views, which opens up a possibility for me to learn.

via interview with Rob Ennals on Spark