“Educational technology seems to be suffering from an identity crisis. Many exciting things are happening in the field, but increasingly we educational technologists find ourselves on the sidelines in our own ballgame. People from other disciplines are taking an interest in educational technology, but they show little interest in our knowledge base (often even little awareness that it exists!) and little interest in our professional organizations and publications. Why is this happening? What can we do about it? To what extent might our mindset be the problem? What new directions do we need to pursue to improve the health and value of our field? These are the central issues which this article discusses.”
This could have been written yesterday, or five years ago. Or, 1989: Reigeluth, C. M. (1989). Educational technology at the crossroads: New mindsets and new directions. Educational Technology Research and Development, 37(1), 67-80.
Here’s what my email spam folder looks like some days:
Predatory open access publishing: “an exploitative open-access publishing business model that involves charging publication fees to authors without providing the editorial and publishing services associated with legitimate journals.”
Jeffrey Beal gathers information on predatory open access publishers and journals. If you are ever unsure, double-check before submitting your paper. Better yet, start with a list of reputable open access journals in your field, such as the one below, which comes from page 33 in Perkins, R., & Lowenthal, P. R. (2016). Open access journals in educational technology: results of a survey of experienced users. Australasian Journal of Educational Technology, 32(3), 1-37.
Australasian Journal of Educational Technology
Canadian Journal of Learning and Technology
Contemporary Issues in Technology and Teacher Education
Educational Technology & Society
Electronic Journal of e-Learning
European Journal of Open and Distance Learning
IEEE Transactions on Learning Technologies*
International Journal of Artificial Intelligence in Education*
International Journal of Designs for Learning
International Journal of Educational Research and Technology
International Review of Research in Open and Distance Learning
Journal of Asynchronous Learning Networks
Journal of Computer-Mediated Communication
Journal of Distance Education
Journal of Information Technology Education
Journal of Online Learning and Teaching
Journal of Technology Education
Online Journal of Distance Learning Administration
Research in Learning Technology (ALT-J)
Turkish Journal of Educational Technology
Turkish Online Journal of Distance Education
What do scholars share on social media? Like the jelly jars below, some topics shared/discussed are familiar. The center jelly nn the top row? I’ve seen many of those. A scholar sharing a link to a paper? I’ve seen many of those, too. Other jellies, and scholarly activities online, are more complex and require a closer look. The bottom right jelly? I’m not quite sure what to make of it. Some scholars disclose challenging professional and personal issues on social media. That’s what Bonnie Stewart and I set out to understand in a our paper Discreet Openness: Scholars’ Selective and Intentional Self-Disclosures Online. Popular literature tends to offer conflicting advice on this topic. Scholars are encouraged to share both personal and professional aspects of their self online, but at the same time they are advised to “watch what they say.” The empirical literature examining scholars’ online self-disclosures and the reasons for making these disclosures remains limited.
DGJ_5184 – Jelly Jars by Dennis Jarvis
Research into emergent forms of scholarship focuses on academics’ use of technology for learning, teaching, and research. Very little attention has been paid in the literature to scholars’ uses of social media to disclose challenging personal and professional issues. This article addresses the identified gap in the literature and presents a qualitative investigation into the types of disclosures that 16 scholars made online and their reasons for doing so. Results identify wide-ranging personal and professional disclosures. Participants disclosed not only about academia-related issues but also about challenges pertaining to family, mental health, physical health, identity, and relationships. Some scholars disclosed as a way to grapple with challenges they faced; others disclosed tactically, sharing information for political rather than personal reasons. Yet others disclosed as a way to welcome care in their lives. In all instances, though, disclosures were selective, intentional, and approached with foresight.
Unlike popular literature that suggests that scholars are “naive users of social media” and must exercise caution, our research shows that people might be thinking deeply about the the ways that the share aspects of their lives.
You can retrieve the paper from here:
Veletsianos, G. & Stewart, B. (2016). Scholars’ open practices: Selective and intentional self-disclosures and the reasons behind them. Social Media + Society, 2(3). doi: 10.1177/2056305116664222
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).
I have a new paper out that sought to identify and describe faculty members’ open and sharing practices at one North American institution. Part of the goal was to juxtapose open practices and sharing practices. The paper highlights individual and environmental influences on open and sharing practices. The paper also suggests that defaults (e.g., the default youtube license) may be exerting pressures on the ways that scholars share their teaching, research, and scholarship. In other words, one way to instigate further change in this domain might be to rethink the default options.
Although the open scholarship movement has successfully captured the attention and interest of higher education stakeholders, researchers currently lack an understanding of the degree to which open scholarship is enacted in institutions that lack institutional support for openness. I help fill this gap in the literature by presenting a descriptive case study that illustrates the variety of open and sharing practices enacted by faculty members at a North American university.
Open and sharing practices enacted at this institution revolve around publishing manuscripts in open ways, participating on social media, creating and using open educational resources, and engaging with open teaching. This examination finds that certain open practices are favored over others. Results also show that even though faculty members often share scholarly materials online for free, they frequently do so without associated open licenses (i.e. without engaging in open practices). These findings suggest that individual motivators may significantly affect the practice of openness, but that environmental factors (e.g., institutional contexts) and technological elements (e.g., YouTube’s default settings) may also shape open practices in unanticipated ways.
The paper, open access and all, is here in pdf, or directly from the source: Veletsianos, G. (2015). A case study of scholars’ open and sharing practices. Open Praxis, 7(3), 199-209. http://openpraxis.org/index.php/OpenPraxis/article/view/206/168
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.
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.