Social network analysis (SNA) can be used in many different ways in the study of learning. Some examples of these are:
Learning design – finding ways to design courses which don’t follow the instructor-led model but which allow students to ask and answer questions with each other. Involving the students in this way leads to higher levels of engagement with and understanding of the course material. The paper by Lockyer and colleagues gives more detail about this use of SNA.
Sense of community – identifying students who may not feel like they are part of the community of learners in a course, and coming up with ways to improve their sense of community. SNA based on online discussion forums can be used instead of questionnaires to identify these students. See the paper by Dawson for more information about this approach.
Creative potential – trying to identify the network brokers i.e. the students who are the link between communities with the network, as they are often the students with the greatest creative potential. This is due to them being exposed to information and ideas from multiple networks, so they have the chance to put all the information together in new and creative ways. For an example of this, see the paper by Burt and colleagues.
Academic performance – there is a link between network position and a student’s location within a network. If there are cross-class networks i.e. the same students enrol in the same subjects, then the performance of these students in higher than those who take classes separately. Students who were at the centre of the network typically performed better. Gasevic and colleagues have written a paper on this topic.
Social presence – students who are able to present themselves and their personality are said to have social presence. The online interactions of students can be investigated to try and identify the level of social presence that each student has. This allows instructors to develop and implement strategies to encourage those students with a low social presence to improve it. See the paper by Kovanovic for an explanation of this use of SNA.
MOOCs – identifying the effectiveness of connectivist MOOCS (cMOOCs) i.e. those which encouraged students to acquire knowledge for themselves rather than be led by an instructor. SNA can be used to see if the information flows and community formation within the cMOOC reflect the goal of moving the responsibility for learning from the instructor to the students. Skrypnyk and colleagues have written a paper on this use of SNA in learning.
Before taking this MOOC, I wasn’t aware of the wide range of potential uses of learning analytics. I thought that they were designed for identifying students currently at risk or trying to predict those students who might fall into this category later in their studies. However, after seeing the case studies for this week, I now realise how powerful a tool they are and that they can be used in many different settings.
The Data, Analytics and Learning MOOC (DALMOOC) that I’m taking via edX is structured a little differently to the MOOCs that I’ve completed previously. Rather than relying solely on the MOOC platform for providing content and submitting assessment tasks, DALMOOC also provides an option for using other tools and social media to complete the course. It did take me a while to get my head around the distributed nature of the course, but I think I’ve got a handle on it now.
I’m mostly following the “traditional” pathway through the course, with the occasional detour down the “social” pathway. This means that edX is the main platform that I’m using to access the course content – videos, exercises, and assessment tasks. However, some of my fellow students are using a platform called ProSolo to do this. ProSolo is a social learning tool which lets you select a competency that you would like to complete, and provides you with a list of tasks that you need to complete in order to meet that competency. You can upload completed tasks and link to blog posts you write which provide evidence that you’ve met the requirements of each competency. It’s also possible to receive and provide feedback from your peers on your work, which is the “social” aspect of learning. I dip into ProSolo now and then, but I’m not a heavy user of it.
Peer feedback is also possible via the discussion forums on edX; these also allow further discussion with fellow students and course instructors. There’s also a Facebook page and Twitter hashtag (#dalmooc) to facilitate discussion, too. A tool which I used for the first time as part of DALMOOC was Google Hangouts. There are weekly Hangouts scheduled with the course instructors, where they share their thoughts about the content for the week, as well as provide feedback on the previous week. Luckily, some of them are held at a time which is convenient for those of us in Australia – most webinar-type activities from the US are usually at a very early hour in the morning for us. All the Hangouts are recorded, so we can still access the ones that are on too early.
I appreciate the effort that the DALMOOC instructors have put into providing different options for learning to suit the varied preferred learning styles of the participants. It’s certainly an interesting course to be part of.
Last week I started the Data, Analytics, and Learning MOOC (DALMOOC) through edX. I signed up for this course because I’m a bit of a data nerd, but have never really got into it in any depth. This course seemed to be a good way to get a basic understanding of what learning analytics are, and the sorts of tools which can be used to analyse and visualise the data.
The content from the first week was, as I expected, an introduction to the concept of learning analytics, and the tools which we’ll be using later in the course. It was all fairly straightforward, and it was presented through a mix of recorded videos and Google Hangouts. DALMOOC is structured a little differently to the other MOOCs which I’ve taken. Rather than being driven by an instructor who releases content each week with corresponding assessment tasks, DALMOOC includes a social learning pathway as well. It uses a tool called ProSolo to facilitate this, and I’ll admit I was a bit wary of using it. I’m not used to having my peers assess my work, so I might use ProSolo to track how I’m progressing but submit my assignments through edX. The distributed nature of the course content has confused a few people (myself included), but I think it’s becoming a bit clearer now.
I’m looking forward to getting some hands-on experience with using these tools over the next few weeks, and seeing if I get inspired to use learning analytics within the library.
It’s been seven years since the original 23 Things Learning 2.0 program was created by Helene Blowers for the staff of the Public Library of Charlotte and Mecklenburg County library system. The program was used by hundreds of libraries from around the world to allow their staff to learn about the new web 2.o tools which were being developed. At my workplace we delivered a web 2.0 training program to staff in 2010, but only focused on four tools (blogs, wikis, IM, and RSS feeds). Michael Stephens and Warren Cheetham undertook a study in 2012 to investigate “The Impact and Effect of Learning 2.0 Programs in Australian Public Libraries“.
In the last few days, the newest version of 23 things has been launched, and it looks at mobile technologies that library staff need to be familiar with. It’s called 23mobilethings, and is based on a Danish program created by Jan Holmquist. Jan is working with Mylee Joseph and Kathryn Berwick from the State Library of New South Wales to develop the English-language version. The “things” include Twitter, Dropbox, curating tools such as tumblr, and photo apps such as Instagram.
I don’t know if I’ll have time to do all 23 things, but there are a couple that I might have a look at. I think I’ll share this course with the training and development staff at work, and see if we could run another cut-down version for our staff.