George Veletsianos, PhD

Tag: education Page 1 of 3

Imagine a future in which technologies teach humans

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On October 17, 2017

In emerging technologies, my research, online learning, papers, scholarship

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.

robo_teacher

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?

Diversity, Justice, and Democratization in Open Education and #opened17

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On July 31, 2017

In Ideas, open, work

This post is more about connecting some dots for myself, and drawing parallels (see 4 especially), than making a fully comprehensible argument.

Blog work-in-progress, they say.

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Diversity by Manel Torralba

1. In 2012, we wrote that the open movement, and thereby the individuals associated with it, assume “ideals such as democratization, human rights, equality, and justice.” We argued that individuals should be vigilant and reflective of their practices, and that “such vigilance should focus both on determining who profits from [open] practices and who is excluded from them so as to combat both under-use by some (e.g., those lacking entry to or knowledge of useful networks) and over-use or exploitation by those with the wealth, power, and prestige necessary to effectively strip mine sources.”

2. I was reminded of this recently, as there has been many conversations around diversity in the open education movement. Some, but not all, of these conversation surround the choice of a keynote talk at the Open Education 2017 conference. Here are a few tweets to contextualize this conversation.

3. As part of the Digital Learning and Social Media Research Group, we’ve been awarding funding to individuals interested in conducting research with us. One of the papers resulting from these research opportunities contributes somewhat here. Michael Paskevicius was interested in examining discourses surrounding openness on Twitter and we analyzed a large Twitter dataset for this purpose. In that (forthcoming) paper, we wrote: “Inherent in the idea of openness is the attitude that all should be able to participate and share and reap the benefits of open communities. However, our results on the national and gender demographics of participants raises questions as to the ongoing diversity of the open education community. Notably, the U.S. dominates English-speaking conversations about openness, and though this might be somewhat expected given the relative size of that country, overrepresentation of males in the community should lead us to consider whether there are social or other barriers of entry for female participants. Interestingly, females gradually gained traction in the community and even overtook males in 2013, but this trend swiftly reversed the following year, and males now participate more than females at a rate of 1.8-to-1. The reasons for this up- and then down-turn is unclear… At any rate, if diversity of perspectives would be valued in any community, we would anticipate that this would be the case within open communities, so we suggest that leaders in this area should consider ways to better understand this issue and the reasons why many who should be participating in these conversations are not.” [emphasis mine] From: Paskevicius, M., Veletsianos, G., & Kimmons, R. (in press). Content is king: An analysis of how the Twitter discourse surrounding open education unfolded from 2009 to 2016. The International Review of Research in Open and Distributed Learning.

4. In response to a question I asked a couple of weeks ago, Martin Weller noted open universities’ contributions to the ideal of democratizing education/learning. Others, noted openness in general. To what extent can an innovation/approach/activity be said to be democratizing when itself could be more diverse and more inclusive? Put differently, can open education be democratizing when itself and its community could benefit from being more democratic, diverse, and just? If i had to venture a guess, I would say that many in the open education community would say “yes, open education can concurrently be democratizing and in need of growth.” Warning: How is this different from techno-utopian SV approaches to educational technology that go like this: “We are democratizing/uberizing/disrupting education, even though we do need to work on our privileged heteronormative ways?” Perhaps what’s different is that in the open education community there seems to be a desire to do better, to be better, or at least, to start with, an acknowledgement that we can do better.

As I said… work-in-progress.

New Open Access Book! Emergence and Innovation in Digital Learning

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On June 6, 2016

In emerging technologies, my research, online learning, open, sharing

emergencecoverAthabasca University Press has just published Emergence and Innovation in Digital Learning, a book I edited that owes its existence to the insightful authors who contributed their chapters on the topic. Like other titles published by AU Press, the book is open access.

Emerging technologies (e.g., social media, serious games, adaptive software) and emerging practices (e.g., openness, user modeling) in particular, have been heralded as providing opportunities to transform education, learning, and teaching. In such conversations it is often suggested that new ideas – whether technologies or practices – will address educational problems (e.g., open textbooks may make college more affordable) or provide opportunities to rethink the ways that education is organized and enacted (e.g., the collection and analysis of big data may enable designers to develop algorithms that provide early and critical feedback to at-risk students). Yet, our understanding of emerging technologies and emerging practices is elusive. In this book, we amalgamate work associated with emergence in digital education to conceptualize, design, critique, enhance, and better understand education.

If you’ve ben following the conversations in the last two years, there will be some themes that you’ll recognize here. To mention a few: defining emerging technologies; not-yetness; data mining; technology integration models; open and social learning; and sociocultural aspects of MOOCs.

In the days that follow, I will summarize each chapter here.

Analysis of the data-driven MOOC literature published in 2013-2015

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On March 21, 2016

In emerging technologies, learner experience, moocs, my research, online learning, open, papers

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).

 

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.

Institutional (strategic) visions for the future

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On March 30, 2015

In sharing

I am in the process of designing a new course for our new MA degree in higher education administration and leadership and one of the activities I will be asking my students to engage with will be an analysis, evaluation, and critique of institutional visions and strategic plans. I am giving providing them with a list of resources/visions, and am asking them to locate their own as well. Here’s what I have so far:

[Webpage] Learning and Living at Stanford 2025: http://www.stanford2025.com/#intro

[White Paper] Flexible learning: Charting a strategic vision for UBC-Vancouver http://flexible.learning.ubc.ca/files/2014/09/FL-Strategy-September-2014.pdf

[White Paper] University of Saskatchewan Vision 2025: From Spirit to Action: http://www.usask.ca/president/documents/pdf/2013/Vision2025.pdf

[White Paper] Institute-wide taskforce on the future of MIT education: http://web.mit.edu/future-report/TaskForceOnFutureOfMITEducation_PrelimReport.pdf

If your institution has one of these that is shared publicly, could you please share it below?

Universities have always been changing

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On February 26, 2015

In scholarship

Serendipity.

I’ve just mentioned to a room full of people that universities have always been changing and that the narrative of the static university unchanging since the dawn of time is a myth. I then look at my RSS feed, and see that Martin Weller writes:

“It is quite common to hear statements along the lines of “education hasn’t changed in 100 years”. This is particularly true from education start-up companies, who are attempting to create a demand for their product by illustrating how much change is required in the sector…If you were to come to a university campus, superficially it looks as though things are pretty unchanged.”

The reality is that universities have always been changing, shifting, largely to reflect the societies that house them. Martin notes a couple of things that have been changing: student demographics and the role of the technology.

Other changes include

  • institutional makeup and diversification: liberal arts colleges, community colleges, for-profit universities, public universities, mega universities, dual-institution degrees, online universities, and the list goes on and on
  • institutional funding: Institutions in the US and Canada used to receive a lot of their funding from the state/province. State/Province contributions have been declining, with some institutions in the US receiving less than 10% of their operating budget from the state
  • Faculty roles and responsibilities have been shifting and I expect that this will continue to happen, with greater involvement of instructional designers and media developers in the course development process

Perhaps when people say that education hasn’t changed or that universities have haven’t changed, they mean that universities have been present for a long time and go on to falsely assert that they haven’t changed their practices. That’s true, universities have existed for a long time, but they are much different than the universities of let’s say 100 years ago.

This of course doesn’t mean that universities are perfect. There’s a lot to improve upon, which is why this is an exciting time to be in the field!

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