George Veletsianos, PhD

Tag: online learning Page 1 of 4

Recent talks on returning back to “normal”

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On June 28, 2021

In E-learning, flexible learning, future education, my research, online learning, scholarship

Institutions, institutional leaders, faculty, and students face very many challenges in “returning back to normal.”

In our ongoing research – which we are furiously trying to make available as soon as possible – students and faculty in particular tell us that they hope institutions “carry forward” what was learned during the pandemic, while they hope to avoid a return back to “normal.” There’s an important distinction here. Hopes for a “return to normalcy,” aren’t hopes for a return to the pre-pandemic status quo. They want better futures, different futures, futures that are more accommodating, supportive, equitable, and stable, and see this as an appropriate and opportune time for making long-awaited changes.

I gave two talks recently focused on these ideas. Below is the abstract from my keynote at Simon Fraser University’s Symposium on Teaching and Learning. My keynote for the Faculty Summer Institute at Texas State focused on this topic as well, but from the perspective of student voice and resilience, drawing on earlier research.

Online and blended learning in post-pandemic settings
Much of the conversation in higher education at this particular point in time focuses on “building back better.” To engage in such rebuilding means to recognize that various pre-pandemic teaching, learning, and institutional practices were problematic. “Building back better” invites us to ask: What do future online and blended learning environments look like, who do they serve, what are they for, and how do we justly make them available to everyone? How do we make our learning environments more equitable, flexible, accessible, enriching, sustainable, decolonial, and responsive? As we are invited to return back to campus, what aspects of pre-pandemic teaching and learning should we strive to avoid returning back to? In this talk, I draw from a series pan-Canadian studies conducted over the last year with students, faculty, staff, and administrators, and share findings that inform our collective efforts for creating effective, but also engaging and equitable, learning environments.

In education, what can be made more flexible?

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On May 27, 2019

In flexible learning, future education, futures, instructional design, my research, scholarship, sharing

Even though flexibility and flexible learning most usually focus on enabling learners some degree of control and freedom over the location, time, and pace of their online studies (hence the terms “anytime anyplace” learning), flexibility may be applied to a wide range of pedagogical and institutional practices. Here’s some examples:

  • Flexible assessments (e.g., providing learners with “a menu” of assessment options to select from. Dr. Joan Hughes for instance allows students to complete a proportion of pre-determined set of badges in her course. This could also apply to assignment deliverables, wherein some students, for example, may produce essays while others may create videos)
  • Flexible admissions (e.g., providing multiple admission paths. For instance, at Royal Roads University students who do not hold an undergraduate degree may apply for admission under a flexible path that asks them to demonstrate how prior coursework and experience has prepared them for graduate study)
  • Flexible “attendance” (e.g., providing learners to attend class based on their emerging needs. Dr. Valerie Irvine for instance calls this multi-access learning; a situation where a face-to-face classroom is set up in a way that allows learners to choose whether they can attend in f2f or online mode, and to make that decision as needs arise/change).
  • Flexible pacing, not only with respect to activities pertaining to a course, but also with respect to program pacing (e.g., start-end dates).
  • Flexible exit pathways. While flexible admissions refers to an entry pathway, exit pathways refer to how learners choose to finalize their program (e.g., thesis vs. coursework vs. work-integrated learning project options).
  • Flexible coursework options. This is the option where students have some control about the courses they enroll in. Imagining this on a continuum, on the one end students have no option of electives and at the other end students create their own unique interdisciplinary degrees. Typically, students have electives that they select, though that option could be made more flexible through, for example, allowing learners to choose electives from institutions/organizations other than their own.
  • Flexible course duration and flexible course credits. At the typical institution, courses last for X weeks and are worth Y credits (e.g., semester-long and 3-credits, or some variation of the 3-credit system including 1-credit, 6-credits and so on). Flexibility could be applied to this form of structure as well, with course duration and credit dependent on learning needs vis-a-vis a predetermined calendar/schedule. One could imagine for example a 2-credit course, or a 1.5-credit course within a university that typically offers 3-credit courses.

While there’s benefits to flexibility, such as empowering learners through greater agency, I am not arguing for flexibility to embedded in all of these forms. There’s philosophical questions to explore. And practical concerns that need to be overcome: Student information systems for example, might prevent the creation of fractional-credit courses, as I’m certain many of of you know.

What are some other ways that institutions, courses, learning design practices, and education more broadly can be made more flexible?


An important lesson from an external evaluation

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On May 7, 2018

In courses, online learning

Two colleagues and I just finished an external evaluation of a universityʼs online MA in education and MEd programs. The programs are stellar, the students are engaged, and the faculty are thoughtful. Their graduation rates are above 90% and their students do important work, evidenced in part by the number of theses that are subsequently published and the number of projects that seek to make meaningful contributions to practice. The programs do many things right.

You have to look inside to get a clear view of what is happening
The photo is of Georgetown University, and has no relationship to the program evaluated

 

Their outcomes contradict the opinion that online learning is solitary and lacks inclusion. Rather – and despite the fact that these programs are thriving – they face institutional obstacles that prevent them from doing better, that preclude them from further expanding equity and quality. We have a few recommendations for improvement, including suggestions for course design, evaluation, assessment, and enrolment, and Iʼm looking forward to following their work in the future. Being able to examine degree programs in depth and interview faculty, staff, administrators, and students is a worthwhile experience in its own right.

This program is a single case, and by no means an accurate reflection of online programs in general. However, the more I do these evaluations the more I see online learning curtailed not just by forces external to the institution, but also by recurring internal barriers that staff, faculty, and administrators can address.

Thinking out loud about coding bootcamps, nanodegrees, & alternative credentials

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On June 29, 2017

In scholarship

“The CanCode program will invest $50 million over two years, starting in 2017-18, to support initiatives providing educational opportunities for coding and digital skills development to Canadian youth from kindergarten to grade 12 (K-12).

The program aims to equip youth, including traditionally underrepresented groups, with the skills and study incentives they need to be prepared for the jobs of today and the future. Canada’s success in the digital economy depends on leveraging our diverse talent and providing opportunity for all to participate—investing in digital skills development will help to achieve this.”

The CanCode program is a new funding opportunity in Canada. Similar initiatives have occurred globally. The investment in coding to prepare youth and adults for the jobs of the future is an interesting phenomenon. In a past project for example, we worked with over fifty high schools and developed a dual enrolment course focused on computational thinking and the presence of computing in daily life. The ability to read, write, and tinker with code is one aspect of this course. Our course was about introducing students to computer science – and though coding is an aspect of it, computer science is not coding.

But, coding is a central feature of an ever-expanding market of emerging credentials. Badges. Nanodegrees. Certs. And so on. Providers offer these in many different ways, both in terms of modality (e.g.,  online courses vs. face-to-face coding bootcamps) and pacing (e.g., self-paced vs. cohort-based). Some highlight experiential components (e.g., industry partnerships) while others highlight the flexibility of adjusting to learner’s life circumstances.

In short, providers make a case that their credentials promise employment opportunities in a rapidly changing global economy where coding is in demand. This space seems to be an example of what certain aspects of unbundling may look like. The space configures alternative credentials, digital learning, for-profit education, skills training, and re-training in unique ways. I have a lot of questions around this space

  • What are learners’ experiences with coding bootcamps and nanodegrees?
  • Who enrols? Who succeeds?
    • To what extent do these programs broaden participation in computing?
    • To what degree and in what ways do these programs democratize learning and participation? Do they?
  • What do learners expect from these offerings and how do they judge the quality of their experience and credential?
  • What are the dominant pedagogical practices (within and across providers) in teaching people how to code?
  • What is the role of technology in these programs?
  • What do outcomes look like, and how do those align with providers’ promises? For instance, what proportion of participants find gainful employment and what does that employment look like?
  • What are instructors’ roles in these offerings? Who are they? What is their pedagogical background? Is this their main employment? Are there connections to the gig economy and precarious employment here?
  • How diverse are these offerings in terms of gender and race with respect to students (who enrols?), instructors (who teaches?) and content (are minorities represented in curricular materials? in what ways?)

I’ve been looking for some answers to my questions, but I’m not finding much.

Additional reading

http://hackeducation.com/2015/11/23/bootcamps-the-new-for-profit-higher-ed

https://www.wired.com/2017/02/programming-is-the-new-blue-collar-job

https://www.nytimes.com/2017/04/04/education/edlife/where-non-techies-computer-programming-coding.html

https://www.geekwire.com/2015/dear-geekwire-a-coding-bootcamp-is-not-a-replacement-for-a-computer-science-degree/

https://news.slashdot.org/story/16/08/22/0521230/four-code-bootcamps-are-now-eligible-for-government-financial-aid

http://www.chronicle.com/article/Coding-Boot-Camps-Come-Into/239673?cid=cp21

http://hackeducation.com/2011/10/28/codecademy-and-the-future-of-not-learning-to-code

Industry report: https://www.coursereport.com/reports/2016-coding-bootcamp-job-placement-demographics-report

A large-scale study of Twitter Use in MOOCs

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On February 1, 2017

In moocs, my research, online learning, open, papers

Researchers have proposed that social media might offer many benefits to Massive Open Online Courses. Yet such claims are supported by little empirical evidence. The existing research exploring the use of social media in MOOCs has been conducted with individual courses and convenience samples, making it difficult to know to what extent research results are generalizable. In this mixed methods research, I used data mining techniques to retrieve a large-scale Twitter data set from 116 MOOCs with course-dedicated hashtags. Using quantitative and qualitative methods, I then examined users’ participation patterns, the types of users posting to those hashtags, the types of tweets that were posted, and the variation in types of posted tweets across users. I found little evidence to support the claims that Twitter as an adjunct to MOOCs is used much/effectively. Results show that learners make up only about 45% of users and contribute only about 35% of tweets. The majority of users contribute minimally, and an active minority of users contributes the preponderance of messages.

Brand new tennis ball with bright fluorescent green felt and white rubber band, surrounded by eight other used balls with duller, more washed out colors, deteriorated nap and dirt marks.

Brand new tennis ball among eight used ones – Image by Horia Varlan CC-BY

These findings do not reveal substantive evidence of learners contributing to multiple hashtags, which may suggest that learners did not find Twitter to be a useful space that provided added value or responded to their needs. Ultimately, these results demonstrate the need for greater intentionality in integrating social media into MOOCs.

I am linking to the pdf pre-print of this article below.

Veletsianos, G. (in press). Toward a Generalizable Understanding of Twitter and Social Media Use Across MOOCs: Who Participates on MOOC Hashtags and In What Ways? Journal of Computing in Higher Education.

 

Multidisciplinary, interdisciplinary, and cross-disciplinary research on MOOCs and digital learning

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On July 2, 2015

In moocs, my research, online learning, scholarship

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.

Emerging Practices in Open Online Learning Environments

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On February 23, 2015

In emerging technologies, moocs, my research, NPS, online learning, open, scholarship

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:

-Students generally stop watching online videos after 4-5 minutes. This then encourages the creation of 4-5 minute lecture videos
-Students fall in discrete categories when they are in MOOCs. For example students who are just sampling content, students who are disengaged,  or they are on track for completing. Once you identify categories you can identify and support learner needs

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.

To summarize:

1. Online learning is becoming more interdisciplinary, but we need to work together and address our assumptions
2. There is excitement about learning analytics, but we also need to understand why people do the things that they do
3. For example, we see that online education needs to accommodate lives as opposed to the other way round
4. And we see that by interviewing people we can get a better sense of the things that they do that don’t get captured by the digital trails they leave behind.

Thank you for being a great audience. I am really excited to hear the speakers that follow me, as I am sure you are!

visual

A visualization of my talk, created by Giulia Forsythe

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