Category: my research
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.
One of the main arguments that we made in our recent paper on MOOCs, which is also the argument that I continue in this op ed piece published in Inside Higher Ed, is that the field needs to embrace diverse research methods to understand and improve digital learning. The following passage is from our paper, and given that the paper is quite long, I thought that posting it here might be helpful:
By capturing and analyzing digital data, the field of learning analytics promises great value and potential in understanding and improving learning and teaching. The focus on big data, log file analyses, and clickstream analytics in MOOCs is reflective of a broader societal trend towards big data analytics (Eynon, 2013; Selwyn, 2014) and toward greater accountability and measurement of student learning in higher education (Leahy, 2013; Moe, 2014). As technology becomes integrated in all aspects of education, the use of digital data and computational analysis techniques in education research will increase. However, an over-reliance on log file analyses and clickstream data to understand learning leaves many learner activities and experiences invisible to researchers.
While computational analyses are a powerful strategy for making a complex phenomenon tractable to human observation and interpretation, an overwhelming focus on any one methodology will fail to generate a complete understanding of individuals’ experiences, practices, and learning. The apparent over-reliance on MOOC platform clickstream data in the current literature poses a significant problem for understanding learning in and with MOOCs. Critics of big data in particular question what is missing from large data sets and what is privileged in the analyses of big data (e.g., boyd & Crawford, 2012). For instance, contextual factors such as economic forces, historical events, and politics are often excluded from clickstream data and analyses (Carr, 2014; Selwyn 2014). As a result, MOOC research frequently examines learning as an episodic and temporary event that is divorced from the context which surrounds it. While the observation of actions on digital learning environments allows researchers to report activities and behaviors, such reporting also needs an explanation as to why learners participate in MOOCs in the ways that they do. For example, in this research, participants reported that their participation in MOOCs varies according to the daily realities of their life and the context of the course. Learners’ descriptions of how these courses fit into their lives are a powerful reminder of the agency of each individual.
To gain a deeper and more diverse understanding of the MOOC phenomenon, researchers need to use multiple research methods. While clickstream data generates insights on observable behaviors, interpretive research approaches (e.g., ethnography, phenomenology, discourse analysis) add context to them. For example, Guo, Kim, and Rubin (2014), analyzed a large data set of MOOC video-watching behaviors, found that the median length of time spent watching a video is six minutes, and recommended that “instructors should segment videos into short chunks, ideally less than 6 minutes.” While dividing content into chunks aligns with psychological theories of learning (Miller, 1956), this finding does not explain why the median length of time learners spent watching videos is six minutes. Qualitative data and approaches can equip researchers to investigate the reasons why learners engage in video-watching behaviors in the ways that they do. For example, the median watching length of time might be associated with learner attention spans. On the other hand, multiple participants in this study noted that they were fitting the videos in-between other activities in their lives – thus shorter videos might be desirable for practical reasons: because they fit in individuals’ busy lives. Different reasons might be uncovered that explain why learners seem to engage with videos for six minutes, leading to different design inspirations and directions. Because the MOOC phenomenon, and its associated practices, are still at a nascent stage, interpretive approaches are valuable as they allow researchers to generate a refined understanding of meaning and scope of MOOCs. At the same time, it is significant to remember that a wholly interpretive approach to understanding learning in MOOCs will be equally deficient. Combining methods and pursuing an understanding of the MOOC phenomenon from multiple angles, while keeping in mind the strengths and weaknesses of each method, is the most productive avenue for future research.
A computational analysis and data science discourse is increasingly evident in educational technology research. This discourse posits that it is possible to tell a detailed and robust story about learning and teaching by relying on the depth and breadth of clickstream data. However, the findings in our research reveal meaningful learner activities and practices that evade data-capturing platforms and clickstream-based research. Off-platform experiences as described above (e.g., notetaking) call into question claims that can be made about learning that are limited to the activities that are observable on the MOOC platform. Further, the reasons that course content is consumed in the ways that it is exemplifies the opportunity to bring together multiple methodological approaches to researching online learning and participation.
What do learning experiences in MOOCs look like? Amy Collier, Emily Schneider and I have just published a paper that provides some in-depth answers to this question. Here is a copy of the paper in pdf. The paper is part of a special issue published by the British Journal of Educational Technology which can be found here (there are many excellent pieces in that issue, so be sure to read them).
In addition to trying to understand learner experiences, in the paper we describe that we did this study because ”ease of access to large data sets from xMOOCs offered through an increasing number of centralized platforms has shifted the focus of MOOC research primarily to data science and computational methodologies, giving rise to a discourse suggesting that teaching and learning can be fully analyzed, understood and designed for by examining clickstream data”
Our abstract reads:
Researchers describe with increasing confidence what they observe participants doing in massive open online courses (MOOCs). However, our understanding of learner activities in open courses is limited by researchers’ extensive dependence on log file analyses and clickstream data to make inferences about learner behaviors. Further, the field lacks an empirical understanding of how people experience MOOCs andwhy they engage in particular activities in the ways that they do. In this paper, we report three findings derived by interviewing 13 individuals about their experiences in MOOCs. We report on learner interactions in social networks outside of MOOC platforms, notetaking, and the contexts that surround content consumption. The examination and analysis of these practices contribute to a greater understanding of the MOOC phenomenon and to the limitations of clickstream-based research methods. Based on these findings, we conclude by making pragmatic suggestions for pedagogical and technological refinements to enhance open teaching and learning.
We reported 3 main findings:
1. Interactions in social networks outside of the MOOC platform
A number of learners alluded to interactions they have had with individuals who are part of their social networks. These include digital connections with other participants in a MOOC, face-toface interactions with friends and family, and face-to-face interactions with new connections in a MOOC.
Despite the fact that none of the popular MOOC platforms support integrated notetaking at the time of writing this paper, nearly all interviewees reported taking notes while watching lecture videos. Only one interviewee never took notes. However, the tools used to take notes and the subsequent use of notes varied substantially by learner.
3. Consuming content
All individuals participating in this study discussed factors that shaped the ways they consumed MOOC content, shedding light on the context surrounding their participation. Scholars in the learning sciences have long highlighted the critical role of the environment, arguing that learning must be understood as a sociocultural phenomenon situated in context and culture (Brown, Collins & Duguid, 1989). Patterns of MOOC content consumption can be examined by clickstream data, but these contextual factors help explain why learners exhibit particular patterns of participation.
Veletsianos, G., Collier, A., & Schneider, E. (2015). Digging Deeper into Learners’ Experiences in MOOCs: Participation in social networks outside of MOOCs, Notetaking, and contexts surrounding content consumption. British Journal of Educational Technology 46(3), 570-587.
I am editing, revising, and re-writing various parts of my book, Networked Scholars. I still like the name, but I mentioned the other day on Twitter that I should rename the book to “Yes, but…” because of the complexities and intricacies inherent in the use of social media for scholarship (as in “yes scholars network, but privilige permeates networks”). Or because I now know that trying to synthesize research my colleagues and I did over the last 6 years isn’t an easy feat (as in “Yes, I’ll write this book, but I am looking forward to turning my attention to other activities”).
Today I was writing about crowdsourcing and networks as places of knowledge sharing, creation, and dissemination. Here’s a relevant piece:
While Tufecki (2014) convincingly argues that practices may differ from one social media platform to another, and big data analyses focusing on one platform may not transfer to others, one common element in the use of social media for knowledge production and dissemination is the concept of crowdsourcing. Crowdsourcing refers to the process of gathering contributions from large groups of individuals in order to solve a common problem or tackle a challenge. Though readers may be familiar with modern crowdsourcing examples that are mediated by technology (e.g., wikipedia as a content crowdsourcing platform), the practice has long existed before the rise of social media. For instance, the design of the Sydney Opera House was crowdsourced. It was based on a 1955 international design competition that received 233 entries. Crowdsourcing content and ideas characterizes social media use, and scholars have capitalized on this practice to gather readings for their syllabi, activities for their courses, resources for their research, and other input – including effort – intended to solve scholarly problems.[Not included in the book: A fun but could-have-held-my-iphone-more-horizontally picture of the lovely Sydney opera house I took a while back]
I am editing, revising, and re-writing various parts of my book, Networked Scholars. I can’t write any more today, so here’s a visual update:
Update (May 13): As a result of your amazing response to this invitation, we are not currently seeking to interview any more people. We are deeply humbled by everyone’s desire to contribute and will be sharing our results in due course. Thank you!
We are inviting PhD students/candidates and academics to participate in a research study that we are conducting entitled “Academics’ use of social media: care and vulnerability.”
While the research community has studied the use of social media for teaching/research, we don’t know much about how social media are used by academics to share the challenges they face, express their vulnerabilities, and experience care online.
If you have disclosed a professional challenge that you have faced on social media (e.g. blogged eponymously or anonymously about: being denied tenure, a dissertation committee conflict, or underemployment or adjunct challenges), we invite you to participate in this study.
If you know of any colleagues who have disclosed such challenges on social media, please feel free to share this call with them.
We believe that these experiences are significant to share and discuss and we would love the opportunity to interview you to learn and write about your experiences.
If you are interested in participating in this study, please visit the following page to read the consent form that provides more details about this project: http://survey.royalroads.ca/index.php?sid=44151
We understand that this topic is very personal and discussing it with us may be difficult. If you have any questions or concerns regarding this study, please don’t hesitate to contact us. We would love to talk to you more about it.
George & Bonnie
Dr. George Veletsianos
Canada Research Chair and Associate Professor
Royal Roads University
Dr. Bonnie Stewart
Royal Roads University/University of Prince Edward Island
If it wasn’t abundantly clear by now, George Siemens and Stephen Downes are two individuals that are making significant contributions to the field. I respect them both and I enjoy engaging with their work. They have been having a conversation regarding the research and academic diversity in MOOCs, (here and here and here) as a result of a report that George and colleagues released on the history and current state of blended, distance, and online education.
I am writing to add to that conversation because my colleagues and I analyzed some parts of the literature published on MOOCs, and have some results that are relevant and interesting. The paper is under review but the editor gave me permission to share our findings.
We studied the disciplinary distribution of the authors who published MOOC research in 2013-2015 and compared it to the submissions to the MOOC Research Initiative (MRI) reported in Gašević et al., (2014). Our tests showed that the MOOC literature published in 2013-2015 differed significantly from the MRI submissions: our corpus had a greater representation of authors from Computer Science and the Gašević et al., corpus had a greater representation of authors from Education and Industry. In other words, our corpus was less dominated by authors from the field of education than were the MRI submissions. One of Downes criticisms is the following: “the studies are conducted by people without a background in education.” This finding lends some support to his claim, though a lot of the research on MOOCs is from people affiliated with education, but to support that claim further one could examine the content of this papers and identify whether an educational theory is guiding their investigations.
We also compared author affiliation information in our papers with the papers used in Liyanagunawardena et al.’s (2013) review of the 2008-2012 MOOC literature. We found that the two samples differed significantly. For example, the Liyanagunawardena et al. corpus was relatively over-represented in the Independent Researcher category. This result suggests that the bodies of literature published in 2008-2012 and 2013-2015 differ in significant ways. This may or may not hold true for the writing that has occurred in blogs, unpublished reports etc. We don’t know and we haven’t studied that.
Finally, and most significantly, we found that the disciplinary makeup of the literature is changing over time: there’s greater interdisciplinary activity in MOOC research now than in the past. This result is very interesting and its implications are worth examining. Suffice to say that this provides opportunities (can we capitalize on the expertise of one another to improve education?) and challenges (are newcomers to the field capitalizing on what we now about the science of learning?). The move to greater inter- and cross- disciplinarity in the field is evident in other initiatives. See for example, the Digital Learning Research Network.
Keep in mind that this research faces some of the same limitations raised by Downes (i.e. like Siemens, our inclusion criteria mean that some research is included while other is excluded). However, it also addresses some of those criticisms. For example, we tried to verify whether some of our results could have arisen by chance by running 10,000 computer simulations on the samples. The computer is confident that they could not have arisen by chance.
I’m hoping this paper will be out of peer-review soon so that I can share, but I’m thankful to the editor that allowed us to share our findings.
The couches of strangers, and three perspectives on the relationship between social media and scholarship
The thought of spending a night on a stranger’s couch many elicit apprehension and concern. The thought of spending time online may elicit many trepidation for scholars. Scholars are worried about the time commitment of such activities when universities may not value them. Scholars may also be concerned about personal-professional boundaries. Both couchsurfing and networked scholarship offer opportunities for growth as well: couchsurfing may allow people from different cultures to get to know one another; networked scholarship might allow scholars from disparate disciplines to meet and collaborate. Alternatively, both activities may have relatively mundane outcomes: sleeping on a stranger’s couch does not necessarily mean that one will have a life-changing experience, in the same way that going online does not mean that one will find a welcoming and supportive scholarly community. And engagement with couchsurfing or networked scholarship may require certain literacies for successful participation.
The practice of networked scholarship isn’t without perils. While advocacy for open, social, and digital scholarship features prominently in the literature (Kimmons, 2014), the reality on the ground is that scholars’ activities on social media are both exceptional and mundane, and their experiences are inspiring and harrowing – but above all, such experiences are neither universal nor pre-determined.
Siemens and Matheos (201X) argued that educational institutions reflect the societies which house them: as societies change, so do their educational institutions and the scholarly practices that they support and encourage. As social media and openness become increasingly popular, sharing economies gain hold, and online networks permeate every aspect of life, the scholarly enterprise and the work that educators and researchers do is experiencing social, cultural, and technological tensions to change. However, we should be careful in our attribution of causality. Academics may have always wanted to share more freely, connect in better ways, and social media simply supported that desire.
At the same time, we should be weary of the perspective that technologies are neutral tools that merely respond to the needs of users. Technologies have assumptions and worldviews embedded in their design that shape the experiences and behaviours of their users. The algorithms used by Facebook to deliver tailored timelines and the recommender systems used by Amazon are representative examples of the ways that technologies are influenced by their developers worldviews.
Thus, the relationship between academic practices and technologies is negotiated and complex. It can be seen via three perspectives.
The first perspective suggests that social media (and their design and affordances) shape scholarship and participation. This is the technological deterministic perspective that is often revealed in narratives pertaining to social media having an impact on scholarship. Institutional encouragement to use social media to increase scholarly reach and citations falls under this perspective.
The second suggests that teaching and scholarship (and the structures, rewards, practices of academia) shape how social media are used. This perspective reflects a social shaping of technology approach. This perspective recognizes that networked scholarly practices are shaped by social, cultural, economic, and political factors, rejecting the notion that technologies (and practices) are deterministic.
The third perspective is an extension of the second and anticipate that academics adapt and appropriate social media to fulfill personal and professional desires and values. This perspective holds that, with adequate information and evidence, learners, instructors, and researchers have the agency to accept or reject any particular technology or to find alternative uses for it that will better serve their needs. Such agency is recognized in scholars’ strategic uses of technology in scholarship broadly, and in teaching and research in particular.
These three perspectives are often unstated, but permeate the literature and conversation pertaining to social media use in education and scholarship.