I wrote a guest post for the Chronicle’s Prof Hacker section describing our use of video and audio to summarize our research findings. The post was published today and it is available here, but I am reposting it below as well.
Street: First pass – CC licensed image
I use an eclectic assortment of learning resources in my courses. Books, peer-reviewed journal articles, op-eds, white papers, websites, documentaries, lecture videos, podcasts. Readings – especially peer-reviewed journal articles – are integral to my teaching, but I am intentional in my desire to go beyond text, to be inclusive and diverse in my selection of learning resources. In my research, and in my attempts to include multimodal learning resources in my teaching, I discovered that we could do a better job at sharing our scholarship.
One of the ways that I am using to share my scholarship in different ways is through the creation of short video and audio clips that accompany each one of my published papers. I believe these might be helpful to colleagues, students, and broader audiences. Colleagues might use them as a way to introduce, humanize, and explore a topic. Students might access them at times when listening is preferable to reading. For example, I listen to podcasts on bus rides because reading on the bus makes me feel dizzy. Others might be in the same predicament. Some students in our research noted that they watched video lectures when engaging in other activities – such as cooking – as a way to accommodate their studies in their busy lives. Broader audiences, such as the general public or journalists, might find video and audio clips valuable as well, as these clips contain information that usually resides behind journal paywalls.
We have created a dedicated YouTube channel to host these videos. Here is a playlist of some of them:
The audio is hosted on my personal SoundCloud channel. Here’s a playlist:
We follow a simple process to create these. For each published paper, I collaborate with members of my research group to (a) write a script, (b) record an mp3 file, and (c) produce an animated movie. These media are produced by two individuals using off-the-shelf software. One person writes the script and shares it with the other using a shared Dropbox folder. When I narrate the script, I use Audacity to create the audio file. When my colleague Laura Pasquini narrates, she uses GarageBand. We use instrumental music shared under Creative Commons licenses as background. Once the audio file is created, I post it in on my SoundCloud channel and users can stream it or download it from there. Next, we use VideoScribe to create the animation and since the software is cloud-based, we can both review the draft version of the video prior to publication. The final video is then posted on a YouTube account dedicated to these videos.
My research team and I are enjoying exploring the many ways available at our disposal to share our scholarship. We know that creating a video trailer or writing a blog post about a publication isn’t a substitute for high-quality scholarship, but we are enthused at the opportunity to use new technologies to mobilize our research. What are some other ways that you have discovered to share your research with colleagues, students, and the broader public?
Athabasca University Press has just published Emergence and Innovation in Digital Learning, a book I edited that owes its existence to the insightful authors who contributed their chapters on the topic. Like other titles published by AU Press, the book is open access.
Emerging technologies (e.g., social media, serious games, adaptive software) and emerging practices (e.g., openness, user modeling) in particular, have been heralded as providing opportunities to transform education, learning, and teaching. In such conversations it is often suggested that new ideas – whether technologies or practices – will address educational problems (e.g., open textbooks may make college more affordable) or provide opportunities to rethink the ways that education is organized and enacted (e.g., the collection and analysis of big data may enable designers to develop algorithms that provide early and critical feedback to at-risk students). Yet, our understanding of emerging technologies and emerging practices is elusive. In this book, we amalgamate work associated with emergence in digital education to conceptualize, design, critique, enhance, and better understand education.
If you’ve ben following the conversations in the last two years, there will be some themes that you’ll recognize here. To mention a few: defining emerging technologies; not-yetness; data mining; technology integration models; open and social learning; and sociocultural aspects of MOOCs.
In the days that follow, I will summarize each chapter here.
One of our research papers was published in its final form this morning. Since I had yet another conversation about the publishing industry at Congress yesterday and I keep track of dates, below are the behind-the-scenes details for this particular paper.
Submission: Aug 1, 2015
Minor revisions requested: Nov 6, 2015
Revision submitted: Nov 13, 2015
Minor revisions requested: Feb 10, 2016
Revision submitted: Feb 10, 2016
Accepted: Feb 13, 2016
Unedited article (uncorrected proofs) appears online: Feb 15, 2016
In Press version of the article appears online: Feb 23, 2016
Final version of the article – assigned to a journal issue/volume: June 1, 2016
I know (and have experienced) papers taking much longer (and much shorter) to publish. So, four words of caution are probably needed here:
- This n of 1 may or may not to be representative of this journal. I had other papers in this journal published under different time horizons.
- This paper is in a non Open Access (NOA) journal.Do no take this n of 1 to mean that Open Access (OA) publishers will necessarily publish a paper faster. I’ve had a paper accepted as is with a reputable OA publisher and the whole process took 2 months. I also have a paper with an OA publisher under review that is taking forever.
- It might be worthwhile to explore what the differences are beyond OA vs NOA. Reviewer turn-around time is a significant variable in this process.
- The paper was published in a journal concerned with education and specifically educational/learning technologies.
Education Scholars’ Evolving Uses of Twitter as a Conference Backchannel and Social Commentary Platform
The scholarly community faces a lack of large-scale research examining how students and professors use social media in authentic contexts and how such use changes over time. Continuing our investigation into how professors and students use social media, Royce Kimmons and I just published a paper in which we used data mining methods to better understand academic Twitter use during, around, and between the 2014 and 2015 American Educational Research Association annual conferences both as a conference backchannel and as a general means of participating online. The first paper we published using similar methods, data, and comparing students and professors’ social media use is here. All of our research on networked scholarship and students’ and faculty members’ use of social media is gathered here.
Descriptive and inferential analysis is used to explore Twitter use for 1,421 academics and the more than 360,000 tweets they posted. Results demonstrate the complicated participation patterns of how Twitter is used “on the ground.” In particular, we show that:
- tweets during conferences differed significantly from tweets outside conferences
- students and professors used the conference backchannel somewhat equally, but students used some hashtags more frequently, while professors used other hashtags more frequently
- academics comprised the minority of participants in these backchannels, but participated at a much higher rate than their non-academic counterparts
- the number of participants in the backchannel increased between 2014 and 2015, but only a small number of authors were present during both years, and the number of tweets declined from year to year.
- various hashtags were used throughout the time period during which this study occurred, and some were ongoing (ie, those which tended to be stable across weeks) while others were event-based (ie, those which spiked in a particular week)
- professors used event-based hashtags more often than students and students used ongoing hashtags more often than professors
- ongoing hashtags tended to exhibit positive sentiment, while event-based hashtags tended to exhibit more ambiguous or conflicting sentiments
These findings suggest that professors and students exhibit similarities and differences in how they use Twitter and backchannels and indicate the need for further research to better understand the ways that social technologies and online networks are integrated in scholars’ lives.
Here’s the full citation and paper:
Kimmons, R. & Veletsianos, G. (2016). Education Scholars’ Evolving Uses of Twitter as a Conference Backchannel and Social Commentary Platform. British Journal of Educational Technology, 47(3), 445—464.
A number of literature reviews have been published on MOOCs. None has focused exclusively on the empirical literature. In a recent paper, we analyzed the empirical literature published on MOOCs in 2013-2015 to make greater sense of who studies what and how. We found that:
- more than 80% of this literature is published by individuals whose home institutions are in North America and Europe,
- a select few papers are widely cited while nearly half of the papers are cited zero times,
- researchers have favored a quantitative if not positivist approach to the conduct of MOOC research,
- researchers have preferred the collection of data via surveys and automated methods
- some interpretive research was conducted on MOOCs in this time period, but it was often basic and it was the minority of studies that were informed by methods traditionally associated with qualitative research (e.g., interviews, observations, and focus groups)
- there is limited research reported on instructor-related topics, and
- even though researchers have attempted to identify and classify learners into various groupings, very little research examines the experiences of learner subpopulations (e.g., those who succeed vs those who don’t; men vs women).
We believe that the implications arising from this study are important for research on educational technology in general and not jut MOOC research. For instance, given the interest on big data and automated collection/analysis of the data trails that learners leave behind on digital learning environments, a broader methodological toolkit is imperative in the study of emerging digital learning environments.
Here’s a copy of the paper:
Veletsianos, G. & Shepherdson, P. (2016). A Systematic Analysis And Synthesis of the Empirical MOOC Literature Published in 2013-2015. The International Review of Research in Open and Distributed Learning, 17(2).
One. An article in Inside Higher Ed last week noted that for some academics, Reddit is becoming a “credible platform to discuss academic interests with people whom they otherwise would not have had a chance to debate.”
Owens (2014) provides more history into this phenomenon and describes in more detail into how “ Reddit created the world’s largest dialogue between scientists and the general public.” The argument goes something like this: Social media (like Reddit) allow scholars to network with diverse audiences – a valued activity, considering that knowledge generated in universities can have significant benefits for society.
Reddit is a popular content aggregator. Various communities within the site are called subreddits. One subreddit is called IAmA, which stands for “I am A.” In this community, users post “Ask Me Anything” or “Ask me Almost/Absolutely Anything” threads, inviting others to ask questions of them. This community is one of the most popular on the site, and it features more than 8 million subscribers. “Ask me Anything” threads appear in other subreddits as well (e.g., in the Science subreddit).
A number of scholars have initiated threads and have sought to share their knowledge with this community. Such scholars included Tina Seelig (a professor of innovation and creativity at Stanford), Steven D. Munger (a researcher of tastes and odours at the University of Florida), Peggy Mason (a Professor of Neurobiology at the University of Chicago who studies empathy in rats), David Kimhy (a professor of psychiatry at the University of Columbia who discussed the results of his latest research study), and Mae Jemison (former NASA astronaut who discussed the teaching and learning of science).
Two. It’s not all rosy.
Reddit’s creators impose little restrictions and take a hands-off approach to user-contributed content. Thus, while Reddit features some shining examples of networked scholarship and knowledge exchange, it has often – and rightly so – been critiqued for being a festering ground for communities promoting misogyny, racism, and homophobia.
We need critical accounts of networked scholarship – because even though Reddit, any “Reddit” allows people to come together and network, the technology is not as democratizing as anticipated.
Multidisciplinary, interdisciplinary, and crossdisciplinary research represent promising approaches for studying digital learning. Prior research however, discovered that research efforts directed at digital learning via MOOCs were dominated by individuals affiliated with education (Gašević, Kovanović, Joksimović, and Siemens, 2014). In their assessment of proposals submitted for funding under the MOOC research initiative (MRI), Gašević and colleagues show that more than 50% of the authors in all phases of the MRI grants were from the field of education. This result was interesting because a common perception in the field is that the MOOC phenomenon is “driven by computer scientists” (p. 166).
We were curious to understand whether this was the case with research conducted on MOOCs (as opposed to grant proposals) and used a dataset of author affiliations publishing MOOC research in 2013-2015 to examine the following questions:
RQ 1: What are the disciplinary backgrounds of the authors who published empirical MOOC research in 2013-2015?
RQ 2: How does the disciplinary distribution of the authors who published MOOC research in 2013-2015 compare to that of the submissions to the MRI reported by Gašević et al. (2014)?
RQ 3: Is the 2013-2015 empirical research on MOOCs more or less interdisciplinary than was previously the case?
Results from our paper (published in IRRODL last week) show the following:
– In 2013-2015, Education and Computer Science (CS) were by far the most common affiliations for researchers writing about MOOCs to possess
– During this time period, the field appears to be far from monolithic, as more than 40% of papers written on MOOCs are from authors not affiliated with Education/CS.
– The corpus of papers that we examined (empirical MOOC papers published in 2013-2015) was less dominated by authors from the field of education than were the submissions to the MOOC Research Initiative.
– A comparison of affiliations with past published papers shows that recent MOOC research appears to be more interdisciplinary than was the case in research published in 2008–2012.
We draw 2 implications from these results:
1. Current research on MOOCs appears to be more interdisciplinary than in the past, suggesting that the scientific complexity of the field is being tackled by a greater diversity of researchers. This suggests that even though xMOOCs are often disparaged for their teacher-centric and cognitivist-behaviorist approach, empirical research on xMOOCs may be more interdisciplinary than research on cMOOCs.
2. These results however, also lead us to wonder whether the trend toward greater interdisciplinarity of recent research might reflect (a) the structure and pedagogical model used in xMOOCs, (b) the greater interest in the field of online learning, and (c) the hype and popularity of MOOCs. Could it be that academics’ familiarity with the xMOOC pedagogical model make it a more accessible venue in which researchers from varying disciplines can conduct studies? Or, is increased interdisciplinary attention to digital education the result of media attention, popularity, and funding afforded to the MOOC phenomenon?
We conclude by arguing that “The burgeoning interest in digital learning, learning at scale, online learning, and other associated innovations presents researchers with the exceptional opportunity to convene scholars from a variety of disciplines to improve the scholarly understanding and practice of digital learning broadly understood. To do so however, researchers need to engage in collaborations that value their respective expertise and recognize the lessons learned from past efforts at technology-enhanced learning. Education and digital learning researchers may need to (a) take on a more active role in educating colleagues from other disciplines about what education researchers do and do not know about digital learning from the research that exists in the field and, (b) remain open to the perspectives that academic “immigrants” can bring to this field (cf. Nissani, 1997).”
For more on this, here’s our paper.
I joined Audrey Watters, Philipp Schmidt, Stephen Downes, and Jeremy Friedberg in Toronto last week, to give a talk at Digital Learning Reimagined, an event hosted and organized by Ryerson University’s Chang School. I presented some of our latest research, and tried to highlight research findings and big ideas in 15 minutes. Below are my slides and a draft of my talk.
Welcome everyone! It’s a pleasure and an honor to be here. Even though I’m the person giving this talk, I’d like to acknowledge my collaborators. A lot of the work that I am going to present is collaborative and it wouldn’t have been possible without such amazing colleagues. These are: Royce Kimmons from the University of Idaho, Amy Collier and Emily Schneider from Stanford University, and Peter Shepherdson from the University of Zurich. The Canada Research Chairs program, the National Science Foundation and Royal Roads University have funded this work.
I want to start my talk by telling a story.
This castle that you see here is one of the most recognizable parts of Royal Roads University (RRU). But, don’t let the castle fool you. RRU was created in 1985. It’s purpose was to serve the needs of a changing society by serving working professionals through graduate digital education and multidisciplinary degrees. It has grown since 1985. It has matured, developed a social learning model that is now infused in all courses, developed new areas of focus, forged global partnerships, and continues to explore how to improve what it does through pedagogical and technological approaches.
Why am I sharing this short story about RRU?
Because this story, minus the specific details, is a common story. It’s also a Ryerson story, a story that is played out at the University of Southern New Hampshire, a story that Open Universities around that world have gone through. It is a story that repeats itself over and over for years and years.
What is the essence of the story?
It is often assumed that universities have been static, unchanging since the dawn of time. The short story I shared illustrates that universities are, and have always been, part of the society that houses them, and as societies change, universities change to reflect those societies. The economic, sociocultural, and technological pressures that universities are facing are sizable, and for better or for worse, usually for both, there’s a continuous re-imagination of education throughout time. Throughout time. Universities have always been changing.
As universities are changing and exploring different ways to offer education, faculty, researchers, and administrators engage in a number of practices that I like to describe as emerging. Emerging practices & emerging technologies are those that are not necessarily new, not yet fully researched, but appear promising.
Online learning and openness are example of emerging practices.
Online learning has a long history. But it also has a new history, with the development of multimedia platforms, media that can be embedded across platforms, syndication technologies that enable learners to use their own platforms for learning and so on. So, even though some of the problems that online learners are facing in contenmporary situations are not new (eg dropout), learners abilities’ to congregate in online communities is expanded through newer technologies and that poses different sorts of challenges and opportunities.
Another emerging practice is openness. Openness refers to liberal policies for the use, re-use, adaptation, and redistribution of content. Openness is also a value: It refers to adopting an ethos of transparency with regards to access to information. And this ethos ranges from academics publishing their work in open formats, to teaching open courses, to creating open textbooks. And it doesn’t stop at individual academics or institutions. In 2014 the Premiers of Alberta, British Columbia, and Saskatchewan signed a Memorandum of Understanding to facilitate creation, sharing, and use of Open Educational Resources. In the same year, SSHRC, NSERC, and CIHR have drafted a tri-agency open access policy to improve access to and dissemination of research results (NSERC, 2014);
There is a growing interest in and exploration of online learning and openness, practices which are still emerging. Next, I will share four recent results from our research into these practices that I believe are interesting to consider because they reveal the tensions that exist when dealing with emerging topics.
First, research into online learning is becoming more interdisciplinary
Interdisciplinary research into online learning means that individuals from a diverse range of disciplines, not just education, are interested in making sense of online learning. It is hoped that more research into online learning and more research from multidisciplinary groups will help us learn more about online learning and about learning in general.
We have evidence to show that research into online learning is becoming more interdisciplinary. I won’t bore you with the statistics, but we measure diversity in published research using a nifty measure and found that the period 2013-2014 can be described as more interdisciplinary than the period 2008-2012.
This is a positive trend, but before I explain its significance, let me explain to you how I view technology.
My perspective on online learning centers around the idea that technology is socially shaped . That means that technology always embeds its developers’ worldviews, beliefs, and assumptions into its design and the activities it supports and encourages.
What does this mean for interdisciplinarity? This means that we have both an opportunity and a challenge.
Our opportunity: to use our respective expertise to improve education.
Our challenge: to actually do interdisciplinary thinking and to go into the study and design of future educational systems with an open mind and the realization that our own personal experiences of education may not be generalizable. A lot of educational technology is produced by people of privilege and to develop educational technology that matters and makes societal difference, we need diversity in thinking and experience.
Our second finding refers to the increasing desire to collect, mine, and analyze data trails to make inferences about human behavior and learning. This practice is often referred to as learning analytics and educational data mining. This practice is a reflection of a larger societal trend toward big data analytics. The idea is that by looking at what people do online one can understand how to improve education.
A couple of things that researchers discovered for example are:
Data trails. Nearly everything that learners do online is tracked. Can we understand learners and improve learning by analyzing their data trails?
While these approaches can help us explain what people do, they often don’t tell us why they do they things they do nor how they actually experience online education.
My colleagues and I are interviewing MOOC students to learn about their experiences in MOOCs.
I am now going to tell you about our third result. We find that learners schedule their learning, use of resources, and participation to fit their daily life. This is in stark contrast to the idea of undergraduate education situated at a university and happening at particular time periods.
One retired individual in Panama that we interviewed works on his class early in the morning every day. Why does he do that? He does that because at that time his daughter is asleep. She is homeschooled and once she wakes up she needs access to the 1 computer that they have in the household to do her own schoolwork. In this case a lack of resources necessitates this scheduling.
One individual that we interviewed moved from the UK to the USA to be with her partner. She is currently waiting for her work permit, driver’s license, and so on, and she was enrolled in multiple MOOCs at the same time. She would work on her courses on Monday because she just “wanted them out of the way,” and so she would work on these courses straight throughout the day.
The fourth and final finding that I have for you today, is that MOOC platforms to date have not offered learners the ability to keep notes, so that particular activity, by virtue of being unsupported by the platform goes undetected when researchers only look at data trails.
Unsurprisingly, learners keep notes. A number of students that we talked to described that they keep notes on paper, frequently keeping a notebook for particular courses and returning to them during exams or during times that they needed them. Learners of course also keep notes in digital format. Usually in word documents, but again documents are dedicated to particular courses, but sometimes they are dedicated to particular topics across courses.
To give you an example, of how we believe this activity could be supported in the future and how we believe innovations can contribute to learning, we recommend designers support this practice by pedagogical innovations such as scaffolding notetaking, but also by technological innovations, by developing online systems for notetaking. What is important here is that such systems should support learning by being interoperable, by allow learners full and unrestricted access to their notes, supporting them to be able to import & export their notes between platforms. Such a design is in line with emerging ideas in the field which call for learners to own their data.
Thank you for being a great audience. I am really excited to hear the speakers that follow me, as I am sure you are!
A visualization of my talk, created by Giulia Forsythe