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Edtech history, erasure, udacity, and blockchain

This thought in Audrey’s newsletter (update: link added March 30th) caught my attention, and encouraged me to share a related story.

 [Rose Eveleth] notes how hard it can be to tell a history when you try to trace a story to its primary sources and you simply cannot find the origin, the source. (I have been thinking a lot about this in light of last week’s Udacity news. So much of “the digital” has already been scrubbed from the web. The Wired story where Sebastian Thrun claimed that his startup would be one of ten universities left in the world? It’s gone. Many of the interviews he did where he said other ridiculous things about ed-tech – gone. What does this mean for those who will try to write future histories of ed-tech? Or, no doubt, of tech in general?) Erasure.

 

Remember how blockchain was going to revolutionize education? Ok, let’s get into the weeds of a related idea and how most everything that happened around it has also disappeared from the web.

One way through which blockchain was going to revolutionize education was through the development of education apps and software running on the blockchain. Around 2017, Initial Coin Offerings (ICOs) were the means through which to raise money to build those apps. An ICO was the cryptocurrency equivalent of an initial public offering. A company would offer people a new cryptocurrency token in exchange for funds to launch the company. The token would then provide some utility for ICO holders relating to the app/software (e.g., you could exchange it for courses, or for study sessions, or hold on to it hoping that its value would increase and resell, etc). The basic idea idea here was crowdfunding, and a paper published in the Harvard International Law Journal estimates that contributions to ICO’s exceeded $50bn by 2019. The Wikipedia ICO page includes more background.

A number of these ICOs focused on education. Companies/individuals/friends* would create a website and produce a whitepaper describing their product. Whitepapers varied, but they typically described the problem to be solved, the blockchain-grounded edtech solution they offered, use cases, the team behind the project, a roadmap, and the token sale/model.

To give you a sense of the edtech claims included in one of those whitepapers:

“The vision is the groundbreaking disruption of the old education industry and all of its branches. The following points are initial use cases which [coin] can provide … Users pay with [coins] on every major e-learning platform for courses and other content they have passed or consumed… Institutions can get rid of their old and heavy documented certification process by having it all digitalized, organized, governed and issued by the [coin] technology.”

I was entertaining an ethnographic project at the time, and collected a few whitepapers. For a qualitative researcher, those whitepapers were a treasure trove of information. But, looking online, they’re largely scrubbed, gone, erased. In some cases, ICO’s founders’ LinkedIn profiles were scrubbed and online communities surrounding the projects disappeared, even as early as ICOs didn’t raise the millions they were hoping for.

Some of you following this space might remember Woolf, the “world’s first blockchain university” launched by Oxford academics. And you might also remember that, like other edtech projects, it “pivoted.” See Martin Weller’s writing and David Gerard’s writing on this. Like so many others, the whitepaper describing the vision, the impending disruption of higher ed through a particular form of edtech, is gone. David kept a copy of that whitepaper, and I have copies of a couple of whitepapers from other ventures. But, by and large, that evidence is gone. I get it. Scammers scam, honest companies pivot, the two aren’t the same, and reputation management is a thing. But, I hope that this short post serves as a small reminder to someone in the future that grandiose claims around educational technology aren’t new. And perhaps, just perhaps, at a time of grandiose claims around AI in education, there are some lessons here.

 

 

Video, tapes, histories of educational technology, and growing up in Cyprus

One of the courses I teach examines the foundations and histories of the field. Writings about the histories of educational/instructional technology/design predominantly identify and examine particular technologies that were in vogue at particular periods of time.  For instance, Martin Weller discusses the use of streaming video in his 25 years of edtech series. One might do the same with radio, overhead projectors, mySpace, and so on. Here, I want to share with you a personal story, a story about a particular VHS cassette.

VHS tape – By Evan-Amos – Own work, Public Domain

My Twitter bio identifies my location as Canada and Cyprus. Cyprus is where I grew up, and where I tell people I am from when they ask me the seemingly innocuous but loaded question “Where are you from?,” as if people can be from just one place. Growing up in a divided country like Cyprus, I was constantly reminded of conflict, war, occupation, fleeing, and loss. I grew up with textbooks emblazoned with the slogan Δέν Ξεχνώ, a nod to a national policy aiming to convince GreekCypriot children to “never forget” the occupied areas of Cyprus. It wasn’t just the not-so-hidden national curriculum. I know of many people who were and are refugees and people who were directly or indirectly impacted. Friends. Friends’ parents. Uncles and aunts. My parents. My maternal grandparents.

In the 1980’s my grandparents were given a tape. Someone – an acquaintance of an acquaintance of a family member – visited the occupied areas and drove for hours, recording what they could from their car. I don’t remember the details. I do remember that the video was grainy and mostly uninteresting to a pre-teen. But, it brought us together to discuss issues more important than the roads, farmlands, and abandoned villages depicted in the tape: war, coup d’état, peace, borders, the “other.”

My aunt and uncle owned a video store in the 80’s. I spent many days in the summers there and watched my fair share of tapes. But that tape, that grainy tape, is forged in my memory. The impact of video on education reveals a worthwhile pedagogical story because it often culminates in how video replaces other media and rarely causes pedagogical change. Particular artifacts though, in particular situations, at particular times, with particular participants, do. That may not be the norm in formal educational environments, but I can at least point to one instance where a tape had impact.

Do you have any similar stories?

Imagine a future in which technologies teach humans

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?

The most solid advice for researchers studying the use of technology in education

If you are engaged in any sort of inquiry into the use of technology in education (whether a student, research, instructor, etc), the following recommendation cannot be emphasized enough:

“Given the increasingly complex role that technology now plays in education and the growing need for clarity around what technology can and cannot do to improve learner success, it is critical that the research we do addresses real-world educational needs and is disseminated in a way that can meaningfully inform design practice. It is, therefore, becoming increasingly clear that the field’s major outlets for disseminating our scholarship should be organized around the problems we are trying to address (flagging learner engagement, poor teaching, rising costs of education, lack of accessibility) rather than the things we are using to solve those problems (learning analytics, online learning, gamification, 3D printing, and the like).”

In short: study problems, not things.

The quote comes from the call of proposals for AECT’s latest Handbook of Research in Educational Communications and Technology.

New Open Access Book! Emergence and Innovation in Digital Learning

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

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 2013-2015The International Review of Research in Open and Distributed Learning, 17(2).

 

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

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.

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