Category: my research
Over the last year or so, we’ve interviewed more than 200 individuals who have participated in a number of open courses. We are working on a project in which we are using learner narratives and vignettes from these interviews to help administrators, faculty, researchers, and learning designers understand learners and improve their learning experience. Though there are many ways that are used to understand learners (e.g., dashboards) we believe that in-depth vignettes of typical experiences may allow for greater sensitivity of the learners’ lifeworld and realities. We will be using these stories to problematize various aspects of digital learning. Each story will be followed by a longer analysis of the issues raised in the story. For now, below is one such (DRAFT!) story. What do you think? Is there anything else that you’d like to see in this narrative? Is it interesting? If you are an administrator, faculty, researcher, or learning designer, does this story add anything valuable?
Title: Why not?
Theme: Open learning opportunities are oftentimes costless and relatively risk-free.
Mary and her demanding Pomeranian, Kylie, live deep in the heart of Texas. “I have a passion for the law!” the thirty-year-old exclaimed when we called her on her landline. She had seriously considered going to law school and had even passed her LSATS, the law school entrance exams used for US Universities. But having just finished four intense years of a bachelor’s degree, she decided to wait a bit. “Law school just didn’t seem like a good choice at the time,” she reflected. Five years later, Mary has settled into her work as a business consultant. Her interest in the law is still keen, and she’s never completely given up the dream of law school, but it’s been tempered with a bit of realism. “I don’t know if I can afford to spend another three years in the classroom,” she confided to us, “I don’t know if I still have the same passion for the legal industry as I did five years ago.”
During an afternoon enjoying frozen mango margaritas with a friend, trying to cope with the scorching sun, Mary learned about MOOCs. Shortly thereafter, she signed up for a number of courses, dabbling in some and promptly forgetting about others. One day, ContractsX, a course on contract law taught by a Harvard professor, popped up on her screen and she decided to “give it a shot”. What had she got to lose? “It’s a free class, taught at one of the more well-respected institutions. Why not?!” she laughed.
The course was flexible and fit into her busy life. On Saturday mornings she would sit in her office, with Kylie by her side and a warm cup of dark roast coffee in her hand, and use her trusted iPad to watch Harvard Law lectures. These weren’t just any lectures. Professor Fried was a masterful storyteller, a king of his trade. It was through these short, interesting, and memorable stories that Professor Fried taught concepts relating to contract law. “I can’t believe that I’m sitting here, I’m learning this material from Harvard law!” The fast pace and cramped content made the course challenging, Mary acknowledged, and she didn’t always do as well as she would have liked on the course tests. But, as she was able to go back to review the answers and re-watch the videos, this didn’t stress her too much, and she ended up passing the course with flying colours. Proud of her certificate of accomplishment, Mary enthused, “It makes me want to keep coming back for more!”
Even though it was a personal interest in the law that led her to sign up for this course, Mary has found what she learned in ContractsX helpful when she has to deal with contracts in her own job. She has enthusiastically recommended the course to co-workers and friends. She’s currently taking a number of other open courses and is anxiously awaiting the second version of the Contracts course. While Mary’s dream of attending law school, may not have changed, her confidence in herself has: “I never thought of applying to Harvard. There was no way I would be getting in. But then, five years later, I’m taking a course from Harvard. I wouldn’t say that I’m a Harvard law student, but at least now I could sit across from a Harvard law student and have a clear conversation with them. It’s very rewarding to know that.”
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.
Scholars are often encouraged to be public intellectuals – to ‘go online’ and engage with diverse audiences. Yet, scholars’ online activities appear to be rife with tensions, dilemmas, and conundrums. In a presentation that I gave last week at AERA, I discuss some tensions and challenges scholars face when engaging networked publics and highlight some uncomfortable realities of being a public scholar. Evangelizing public and networked scholarship without acknowledging the existence of tensions is detrimental to the field and misleading to the scholars who may be considering greater public engagement- becoming more networked, more public, and more “digital.” Individual scholars and institutions need to evaluate the purposes and functions of scholarship and take part in devising systems that reflect and safeguard the values of scholarly inquiry.
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).
Royce Kimmons and I have been exploring the use of large-scale data in a number of recent studies. We just published a paper that tries to make sense of students’ and professors’ social media participation on a large scale. We are continuing our qualitative investigations to understand “why, in what ways, and how” scholars (students & professors) are using social media, but this is our first data mining study making use of Twitter data. It’s also the first study using large-scale Twitter data to make sense of how professors and students of education are using Twitter.
Here’s a high-level summary of three of our findings:
- There is significant variation in how scholars participate on Twitter. The platform may not be the democratizing tool it is often purported to be: The most popular 1% scholars have an average follower base nearly 100 times that of scholars in the lower 99% and 700 times those in the bottom 50%.
- Civil rights and advocacy seem to be an important activity of social media participation – this is rarely captured in research to date, which most often focuses on how social media are used in teaching & research. Scholars’ participation on Twitter extends well beyond traditional notions of scholarship.
We found that those scholars who follow more users, have tweeted more, signal themselves as professors, and have been on Twitter longer will have more followers. This model predicts 83% of the variation on follower counts. This finding raises questions as to the meaning of follower counts and its use as a metric in conversations pertaining to scholarly quality/reach.
Veletsianos, G., & Kimmons, R. (2016). Scholars in an Increasingly Digital and Open World: How do Education Professors and Students use Twitter? The Internet and Higher Education, 30, 1-10.
The British Journal of Educational Technology and BERA approached us to create an infographic for the article we (Amy Collier, Emily Schneider, and myself) published last year: Digging Deeper into Learners’ Experiences in MOOCs: Participation in social networks outside of MOOCs, Notetaking, and contexts surrounding content consumption
Below is the outcome (and a pdf version is here):
Martin Weller sent me a photo of my book a couple of weeks ago. I was away from the office, and that was the first time I saw a photo of the physical book. I saw the physical one a week later when I returned to my office. There it was. In print. And published.
I wanted to write a book about the complicated realities of the use of technology in education. I wanted to write about us. About the people who use technology as part of their day-to-day professional life – and about the times that professional and personal life are intertwined. I am tired of the recycled unsubstantiated claims regarding the potential of new solutions and new technologies. So, I wrote a book about scholars and social media. A book about what scholars – professors and doctoral students – do on social media and why the use them. A book about those times that the potential is realized, those times that new technologies are put into familiar uses, and those times that the issues become a tad more complex. No surprises there – I’ve been working on this area for a few years now.
If you would like me to talk to your colleagues or students about this area, I would be happy to do so. I hope the short blurb below describes the essence of the argument:
Social media and online social networks are expected to transform academia and the scholarly process. However, intense emotions permeate scholars’ online practices and an increasing number of academics are finding themselves in trouble in networked spaces. In reality, the evidence describing scholars’ experiences in online social networks and social media is fragmented. As a result, the ways that social media are used and experienced by scholars are not well understood. Social Media in Academia examines the day-to-day realities of social media and online networks for scholarship and illuminates the opportunities, tensions, conflicts, and inequities that exist in these spaces. The book concludes with suggestions for institutions, individual scholars, and doctoral students regarding online participation, social media, networked practice, and public scholarship.
“Personalized learning” is that one area of research and practice that brings to the forefront many of the debates and issues that the field is engaging with right now. If one wanted to walk people through the field, and wanted to do so through *one* specific topic, that topic would be personalized learning.
Personalized cans? (CC-licensed image from Flickr)
Here’s are some of the questions that personalized learning raises:
- We have a problem with labels and meaning in this field. Heck, we have a problem with what to call ourselves: Learning Technologies or Educational Technology? Or perhaps instructional design? Learning Design? Learning, Design, and Technology? Or is it Learning Science? Reiser asks: What field did you say you were in? The same is true for personalized learning. Audrey Watters and Mike Caulfield ask what does “personalized learning” mean and what is the term’s history? Does it mean different pathways for each learner, one pathway with varied pacing for each learner, or something else?
- The Chan-Zuckerberg initiative and the Bill and Melinda Gates Foundation endorse personalized learning. What is the role of philanthropy in education in general and educational technology in particular? Should educators and researchers “beware of big donors” or should they enthusiastically welcome the support in the current climate of declining public monies?
- Where is the locus of control? Is personalization controlled by the learner? Is the control left to the software? What of shared control? Obsolete views of personalization and adaptive learning focus on how the system can control both the content and the learning process ignoring, for the most part, the learner, even though learner control appears to be an important determinant of success in e-learning (see Singhanayok & Hooper, 1998). The important question in my mind is the following: How do we balance system and learner control? Such shared control should empower students and enable technology to support and enhance the process. Downes distinguishes between personalized learning and personal learning. I think that locus of control is the distinguishing aspect, and that the role of shared control remains an open conceptual and empirical question. Debates about xMOOCx vs cMOOCs fall in here as well as the debate regarding the value of guided vs discovery learning.
- How do big data and learning analytics improve learning and participation? What are the limitations of depending on trace data? Personalized learning often appears to depend on the creation of learner profiles. For example, if you fit a particular profile you might receive a particular worked-out example or semi-completed problem, and problems might vary as one progresses through a pathway. Or, you might get an email from Coursera about “recommended courses” (see my point above regarding definitions and meanings). Either way, the role that large datasets, analytics, and educational data science – as well as the limitations and assumptions of these approaches, as we show in our research – is central to personalization and new approaches to education.
- What assumptions do authors of personalized learning algorithms make? We can’t answer this question unless we look at the algorithms. Such algorithms are rarely transparent. They often come in “black box” form, which means that what we have no insight into the processes of how inputs are transformed to outputs. We don’t know the inner workings of the algorithms that Facebook, Twitter, and Google Scholar use, and we likely won’t know how the algorithms that EdTechCompany uses work to deliver particular content to particular groups of students. If independent researchers can’t evaluate the inner workings of personalized learning software, how can we be sure that such algorithms so what they are supposed to do without being prejudicial? Perhaps the authors of education technology algorithms need a code of conduct, and a course on social justice?
- Knewton touts its personalization engine. Does it actually work? Connecting this to broader conversations in the field: What evidence do we have about the claims made by the EdTech industry? Is there empirical evidence to support these claims? See for example, this analysis by Phil Hill on the relationship between LMS use and retention/performance and this paper by Royce Kimmons on the impact of LMS adoption on outcomes. If you’ve been in the position of making a technology purchasing in K-12/HigherEd, you have likely experienced the unending claims regarding the positive impact of technology on outcomes and retention.
- And speaking of data and outcomes, what of student privacy in this context? How long should software companies keep student data? Who has access to the data? Should the data follow students from one system (e.g., K-12) to another (e.g., Higher Ed)? Is there uniformity in place (e.g., consistent learner profiles) for this to happen? How does local legislation relate to educational technology companies’ use of student data? For example, see this analysis by BCCampus describing how British Columbia’s Freedom of Information and Protection of Privacy Act (FIPPA) impacts the use of US-based cloud services. The more one looks into personalization and its dependence on student data, the more one has to explore questions pertaining to privacy, surveillance and ethics.
- Finally, what is the role of openness is personalized learning? Advocates for open frequently argue that openness and open practices enable democratization, transparency, and empowerment. For instance, open textbooks allow instructors to revise them. But, what happens when the product that publishing companies sell isn’t content? What happens, when the product is personalized learning software that uses OER? Are the goals of the open movement met when publishers use OER bundles with personalized learning software that restricts the freedoms associated with OER? What becomes of the open agenda to empower instructors, students, and institutions?
There’s lots to contemplate here, but the point is this: Personalized learning is ground zero for the field and its debates.