Professor & Canada Research Chair in Innovative Learning and Technology at Royal Roads University

Category: online learning

Imagine a future in which technologies teach humans

Posted on October 17th, by George Veletsianos in emerging technologies, my research, online learning, papers, scholarship. No Comments

Pause for a few minutes and imagine a future in which technologies teach humans. Call them robots, bots, chatbots, algorithms, teaching machines, tutoring software, agents, or something else. Regardless, consider them technologies that teach.


Vector created by Freepik

How far into the future is that time?

What do these technologies look like? Are they anthropomorphous? Are they human-like? In what ways are they human-like? Do they have voice capabilities, and if so, do they understand natural language? Are they men or women?  Do they have a representation in the way that one would imagine a teacher – such as a pedagogical agent – or do they function behind the scenes in ways that seem rather innocuous – such as the Mechanical MOOC?

Do these technologies teach humans of all ages? Do they teach independently, support human teachers, or do human teachers assist them? Are they featured in articles in the New York Times, The Guardian, and The Economist as innovations in education? Or, are they as common as desks and chairs, and therefore of less interest to the likes of the New York Times? Are they common in all learning contexts? Who benefits from technologies that teach? Is being taught by these technologies better or worse than being taught be a human teacher? In what ways is it better or worse? Are they integrated in affluent universities and k-12 schools? Or, are they solely used in educational institutions serving students of low socioeconomic status? Who has access to the human teachers and who gets the machines? Are they mostly used in public or private schools?

How do learners feel about them? Do they like them? Do they trust them? Ho do learners think that these technologies feel about them? Do they feel cared for and respected? How do learners interact with them? How do human teachers feel about them? Would parents want their children to be taught be these technologies? Which parents have a choice and which parents don’t? How do politicians feel about them? How do educational technology and data mining companies view them?

Do teaching technologies treat everyone the same based on some predetermined algorithm? Or, are their actions and responses based on machine learning algorithms that are so complex that even the designers of these technologies cannot predict their behaviour with exact precision? Do they subscribe to pre-determined pedagogical models? Or, do they “learn” what works over time for certain people, in certain settings, for certain content areas, for certain times of the day? Do they work independently in their own classroom? Or, do colonies of robo-teachers gather, share, and analyze the minutiae of student life, with each robo-teacher carefully orchestrating his or her next evidence-based pedagogical move supported by Petabytes of data?

Final question for this complicated future, I promise: What aspects of this future are necessary and desirable, and why?

Being online: Recommendations for early-career academics

Posted on May 15th, by George Veletsianos in Ideas, my research, online learning, open, papers, scholarship, sharing. No Comments

When I wrote my book Networked Scholars, I was very intentional in my writing. I wanted to avoid writing a “how to” book. Not that there’s anything wrong with “how to use social media” books, but there’s plenty of those, not to mention countless blog posts and advice columns on outlets like Inside Higher Ed, The Chronicle, etc.

Beyond that though, my interests aren’t social media per se. My interests are on the ways that people learn online and the ways that knowledge is managed, negotiated, developed, and shared in digital environments. Though social media are central to these process these days – and let’s face it, most media are social nowadays – there are practices central to knowledge exchange and dissemination that have nothing to do with the technology, such as open access publishing and self-archiving.

What does this have to do with networked scholars? Well, I think the time is ripe to actually write a book of suggestions, principles if you will, for early-career academics (PhD students, new assistant professors). The suggestions will go beyond social media, aiming to (a) help people be more effective and productive online, and (b) help faculty and faculty trainers prepare people in these efforts.

This book will be different. It will be laconic and will nudge individuals to be more awesome in their online practices. I’m partnering with a graphic artist to create it. Below is a page from our early work.

Do you know of a publisher who might be interested? Are you a publisher that is interested? I am exploring Punctum Books, but would love to hear other suggestions.

Liberate your research

Digital Learning and Social Media Research Funding: 2017

Posted on March 9th, by George Veletsianos in my research, online learning, papers, Royal Roads University. 2 comments

Digital Learning and Social Media Research Funding for 2017

Description of Opportunity

The Canada Research Chair in Innovative Learning and Technology at Royal Roads University invites applications from advanced doctoral students (i.e. those who completed their graduate coursework) and post-doctoral associates to conduct research with the Digital Learning and Social Media Research Group.

Funding for five (5) research opportunities are available.

The Digital Learning and Social Media Research Group ( is an international and interdiciplinary team of researchers investigating the ways that social media and other emerging technologies are used in learning, teaching, scholarship, and institutional settings. The group is led by Dr. George Veletsianos (Canada Research Chair & Associate Professor, Royal Roads University) and Dr. Royce Kimmons (Assistant Professor, Brigham Young University). The Digital Learning and Social Media Research Group executes the CRC’s program of research.


The research funding opportunities aim to involve applicants in the scholarly endeavors of the research group and thus provide experiential mentoring focused on supporting the students’ or post docs’ scholarly and professional development. With a mentor, each student or post doc will co-plan, execute, and submit for publication a research study.

Funding is available for research that focuses on one or more of the following areas: networked scholarship, social media use in education, digital/online learning, open learning, emerging technologies, learning analytics, social network analysis, or educational data mining.


Potential researchers should submit their application materials by April 15, 2017.

Start date is around May 15th


Submission of a co-authored research study to a peer-reviewed journal.


Research opportunities are expected to last anywhere from 3 to 5 months


  • Advanced doctoral student status (usually in the 3rd or 4th year of their studies) OR post doctoral status having completed a graduate degree (PhD/EdD) within the last 3 years.
  • Enrolment in or having attained a graduate degree (PhD/EdD) in education, educational technology, learning technologies, learning sciences, curriculum and instruction, cognitive science, or other related field.
  • Individuals must be Canadian citizens or permanent residents of Canada, or must hold a valid employment visa or work permit issued by the Government of Canada.

To be well-suited for this opportunity, individuals must have excellent organizational abilities, analytic skills, and be familiar with methodologies involving the analysis of quantitative or qualitative data.


Questions regarding this opportunity can be send to

Application Process

Interested applicants are invited to submit the following materials to  April 15, 2017:

  • Curriculum Vitae (CV)
  • A single-authored paper (single-authored class papers are acceptable)
  • An expression of interest or research proposal (not to exceed 2 single-spaced pages) that includes the following:
    • Description of a research project that the applicant wishes to complete under the auspices of the research group (This description should include at least 2-3 research questions of interest and a proposed methodology)
    • Description of experiences analyzing quantitative or qualitative data

Applications will be evaluated by an academic panel.

Though the research group is interested in any proposal examining digital learning and social media use in higher education, we are especially interested in proposals focusing on analyzing large-scale datasets such as those gathered from public sources (e.g., Twitter, university websites, and YouTube). The research group has expertise in this area and can collect, structure, and organize data necessary for such endeavors. Thus, we welcome applications from those with and without technical expertise. Past studies conducted in this context include the following:


Research question Data sources
How do students and professors use Twitter? ~600K tweets from ~400 Twitter profiles
What narratives do institutional Twitter acccounts construct for students and faculty? Images posted by public Canadian Universities on Twitter
How well do institutional websites meet mandated accessibility requirements? ~3,000 U.S. university homepages
What does informal learning look like on YouTube? ~1.4 million YouTube comments

For examples of research studies in this area conducted by the research group, please refer to:


The individuals receiving funding in 2016 have:

  • Used historical twitter data to study the discourse surrounding openness over time
  • Examined the ways that instructional design & technology programs use Twitter
  • Investigated whether empathy, civility, and thoughtfulness are present in the comments posted in a YouTube community


$2,000 CAD upon submission of the study.

Categories of renewable assignments

Posted on March 8th, by George Veletsianos in online learning, open. No Comments

John Hilton III wrote an excellent entry describing three categories of renewable assignments:

  1. Renewable Assignments that Primarily Benefit the Public,
  2. Renewable Assignments that are Primary Course Resources such as Textbooks, and
  3. Renewable Assignments and Secondary Learning Resources Designed to Improve the Understanding of Future Students

A fourth one might be Renewable Assignments that are Original Scholarship. One example might be the collection and subsequent analysis and publication of data that are then made available for use by other students or scientists. Such projects can often be found under the citizen science category. For example, here are some whale sighting data around Vancouver Island. As long as collected data and resources dependent on that data have appropriate permissions attached to them, such projects may fall under the renewable assignment as scholarship category. This category might also include books (but not textbooks that might be classified under category 3 above). For example, when my students wrote essays on their experiences with open online learning back in 2013, those essays captured student experiences and perspectives around MOOCs and open education as a time when scholarly literature on the topic was nascent.

I’m sure there are other examples, and like John, I’d love to hear other ideas on the topic!

A large-scale study of Twitter Use in MOOCs

Posted on February 1st, by George Veletsianos in moocs, my research, online learning, open, papers. 4 comments

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.


Learning Design at Pearson

Posted on December 21st, by George Veletsianos in learner experience, my research, online learning, pedagogical agents, scholarship, sharing. No Comments

Last week, a reporter from EdSurge reached out to me to shed some light on what Pearson called their Learning Design Principles. The EdSurge article is here, but below is a more detailed rough draft of the points that I made to share. I am posting them here for a fuller picture of some of my thoughts.

  1. Nothing proprietary (yet, perhaps). I saw a number of sources note that Pearson released their proprietary learning design principles. There’s not much proprietary in the principles. All of these ideas are well-documented in the literature pertaining to educational technology found in cognitive psychology, learning sciences, instructional design, and education literature.
  2. It’s good to see that Pearson is using findings from the education literature to guide its design and development. Some of these principles should be standard practice. If you are creating educational technology products without considering concepts like instructional alignment, feedback, and scaffolding, authentic learning, student-centered learning environments, and inquiry-based learning, you are likely creating more educational harm than good. The point is that using research to guide educational technology should be applauded and emulated. More educational technology companies should be using research to inform their designs and product iterations.
  3. BUT, since around 2011, the educational technology industry has promoted the narrative that education has not changed since the dawn of time. With a few exceptions, the industry has ignored the history, theory, and research of the academic fields associated with improving education with technology. The industry has ignored this at its own peril because we have a decent – not perfect, but decent – understanding of how people learn and how we can help improve the ways that people learn. But, the industry has developed products and services starting from scratch, making the same mistakes that other have done in the past, while claiming that their products and services will disrupt education.
  4. Not all of the items released are principles. For example, “pedagogical agents” is on the list but that’s not a principle. Having studied the implementation of pedagogical agents for more than 7 years, it’s clear that what Pearson is attempting to do is figure our how to better design pedagogical agents for learning. Forgive me while I link to some pdfs of my past work here, but, should amagent’s representation match the content area that they are supporting (should a doctor look like a doctor or should she have a blue mohawk?). Table 1 in this paper provides more on principles for designing pedagogical agents (e.g., agents should establish their role so that learners have a clear anticipation of what the agent can and cannot do: Does the agent purport to know everything or is the agent intended to ask questions but provide no answers?)
  5. As you can tell from the above, I firmly believe that industry needs research/researchers in developing, evaluating, and refining innovations.

But more importantly, happy, merry, just, and peaceful holidays to everyone!

Digital Learning Environments, Networks, Communities. Your thoughts on a new course?

Posted on October 17th, by George Veletsianos in courses, Ideas, online learning, open. 3 comments

At the School of Education and Technology at Royal Roads University, we are very excited to be redesigning our MA in Learning and Technology. We will share more about the program in the near future, but for now we’d love any input that you may have on one of the courses my colleague Elizabeth Childs and I are designing. The course is called Digital Learning, Environments, Networks, and Communities. The link sends you to a Google Doc that hosts a very rough first draft of the course. We would love to hear your thoughts, critiques, ideas, gaps, etc on the Google Doc. Are we missing important details/readings? Are there additional activities that we should consider? What questions do you have? How can this course be better?

Some background information on the program follows.

Context: This is the first course in a two year MA degree in Learning and Technology (33 credits). The degree is offered in two modes: fully online and blended. The online group of students and the blended group of students come together in the third course. Thereafter, they continue together and complete the rest of the degree fully online.

Program Goal:

The program is founded upon principles of networked learning, open pedagogy, personalization, relevance, and digital mindsets. Students collaborate and contribute meaningfully to digital learning networks and communities in the field. Graduates will be able to create and evaluate digital learning environments. Students will apply theoretical and practical knowledge to critically analyze learning innovations and assess their impact on organizations and society.

Program Description:

The program responds to the demand for qualified professionals in the field of technology-mediated learning and education. It addresses the need for individuals who have the knowledge, skills and ability to assume the leadership roles that are required to plan, design, develop, implement and evaluate contemporary learning initiatives. Following several foundational courses, students transition into the inquiry-focused portion of the program. Next, they create digital learning resources based on personalized learning plans and facilitate a student-designed and student-led seminar experience that requires them to draw upon the networks and community(ies) they have been contributing to and cultivating over the duration of the program.  

Your thoughts on our Table of Contents for an upcoming book proposal?

Posted on July 22nd, by George Veletsianos in Ideas, my research, online learning, open. 11 comments

My colleague Ash Shaw and I are working on a book. The book aims to highlight student voices in online learning. The main aims are to surface the experiences of online learners in an evocative and accessible manner, synthesize literature on the topic, and present our original work. Below is our draft table of contents. If you have a couple of minutes, could you take a look at it and let us know if there are any topics/debates/issues that might be of interest to the average faculty member and student that we are missing?

Thank you!

# Topic Summary and questions answered
2 Demographics Examines who today’s online learners are and how online learners demographics have changed over time. Who are today’s online learners? How many students enroll in online courses nationally and globally? How have demographics changed over time?
3 Who succeeds? (or, The online paradox) Investigates the reasons why students who take online courses have greater degree completion rates when online courses are characterized by higher attrition rates.
4 Motivations Investigates the reasons that individuals take online courses. Shows that students take online courses for a variety of reasons, and reveals that reasons differ depending on the type of online course (e.g., some learners take MOOCs for different reasons than online courses).
5 Digital Literacies Examines the need for skills and the skills required to participate productively in online courses.
6 Note-taking Uses note-taking to illustrate that online learning research that focuses on tracking student activity on platforms alone is insufficient to understand the human condition and hence improve learning outcomes.
7 Self-directed learning Investigates self-directed learning as a process necessary for contemporary learners to develop and apply.
8 Openness Investigates the meaning of the term openness in the context of online learning.
9 Personalized learning Examines efforts to develop adaptive learning software and automate instruction (system control), and juxtaposes those efforts with designs that allow learners to personalize their own learning (learner control). Explores instructor strategies and designs to personalize learning.
10 Flexibility Examines the ways that online courses can be designed to accommodate learners’ lives and allow flexible participation. Investigates issues of modality and (a)synchrnonicity.
11 Social Media Investigates how social media are used in online courses and shows how intentional integration of such tools can lead to positive outcomes.
12 Loneliness or “The student who watched videos alone” Examines how online learning can be a lonely and isolating experience and proposes strategies for enhancing presence and immediacy.
13 Emotions Shows that learning online is an emotional experience, calling for a more caring pedagogy and critiquing the calls to employ online learning to simply make online learning offerings more efficient.
14 Lurking or “The student who learned as much by just watching videos” Investigates the topic of lurking. Highlights the visible and invisible practices that online learners engage in. Demostrates…
15 Time or “The student who stole time from his family to study” Explores the topic of time-management in online students’ lives, and investigates how courses can be designed to fit with the complexity of learner’s day-to-day realities (e.g., work and family requirements).
16 Dropout, Attrition, and Persistence Explores the topic of attrition, as online courses often face higher attrition rates than alternatives.
17 Instructor The role of the instructor in online learning environments. Investigates instructor presence, support, and explores how instructors can contribute to meaningful and effective learning experiences
18 Online vs. face-to-face learning Investigates the question as to whether face-to-face learning is better than online learning. Presents the empirical research on the question and highlights (a) how different forms of education serve different needs, and (b) how learning design is a more significant factor in determining learning outcomes than modality.
19 MOOCs or “The student who completed 200 courses: And other, less profound, online learning experiences” Explores the topic of MOOCs and summarizes the empirical research that exists on the topic. Explains the origins of the term, the different designs, and how the concept has evolved over time, with particular emphasis on students’ experiences in MOOCs.
20 The Learning Management System and Next-Generation Digital Learning Environments Investigates the idea that Learning Management Systems contribute little to student learning. Proposes the courses are “nodes in a network” as opposed to hermetic containers of knowledge. Shows how course design differs between these two ideas.
21 Challenges and remediation strategies Investigates the challenges that online learners face and the strategies employed by themselves and others to remediate them.