Who said, “If we teach today’s students as we taught yesterday’s, we rob them of tomorrow.”?

JohnDeweyStamp

Dude makes a lot of cents!

This is arguably one of the most referenced Dewey quotes about education on the Internet, as well as in various other places. It’s an interesting and thought provoking statement that seems relevant to contemporary discourse. Remarkable that Dewey would have had the prescience to put it in writing almost a century ago. But, to tell the truth, I don’t think he did. Continue reading

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Hypothetica does foresight – an illustrative hypothetical case of CHAT analysis

This is part two of a two-part article. See part one, Technology foresight and organizational change: A CHAT perspective, here.

now_leaving_futureFor the sake of illustration, let’s consider what the application of Engeström’s extended CHAT framework to a technology foresight program (TFP) might look like. We’ll use the OECD’s well-known Schooling for Tomorrow (SfT) program as an example. What we are going to look at is how the immediate outcomes of the SfT program are used to produce change at an organizational level.

We’ll create a hypothetical persona, named Hypothetica, who participated in the SfT program activities on behalf of a Dutch teachers’ union. Having participated in the SfT program, Hypothetica now needs to go back to her Dutch teachers’ union and communicate what she gained from her participation in the SfT program in a way that produces organizational change; that change being that the organization becomes more forward-looking and future-oriented in the way that it addresses issues. Continue reading

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Technology foresight and organizational change: A CHAT perspective

This is part one of a two-part article. See the second part, Hypothetica does foresight – an illustrative hypothetical case of CHAT analysis, here.

now_leaving_futureForesight researchers and evaluators tell us that technology foresight programs (TFP) produce outcomes in three stages: the immediate; the intermediate; and the ultimate. The problem is that they don’t have much to say about how we transition from one stage to another. Almost all studies of TFPs focus only on the immediate outcomes, i.e. those that occur during and directly following program implementation. It’s clear, though, that if we want TFPs to contribute to lasting change over significant periods of time, which is a stated goal, then we need to know more about how we get from the immediate outcomes to the intermediate and, finally, the ultimate.

The intermediate outcomes of TFPs involve the transfer of knowledge, values, connections, etc. gained from TFPs, to organizational contexts, where they are institutionalized in the form of new practices and new ways to address issues. Although there have been many studies focusing on immediate outcomes, there have, to my knowledge, been no systematic studies of intermediate outcomes, at least not in cases involving educational policy (please correct me if I’m wrong). Therefore, we have no clear examples of applicable frameworks to use. Frameworks are important because they indicate what we can expect to happen in certain types of situations. Without them, we’re looking at something with no context; no way to make sense of how the various things we see happening work together. It’s sort of like if we were reading a text and could understand individual words, but couldn’t make sense of the sentences that they form. Now, we can’t just pick a random framework. We need to choose one that fits the context such that it provides a way of making sense of how the pieces in our analysis fit together. I have come to the conclusion that Engeström’s analytical framework based on Cultural-Historical Activity Theory (CHAT) is a very good fit for our purposes. I describe the framework below and discuss why I think it will be useful. Continue reading

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Four unexpected ways artificial intelligence will influence education – Are we ready for this?

Shadow_Hand_Bulb_largeStephen Hawking recently published a brief op-ed on artificial intelligence (AI) in the Independent. In it he discusses possible implications of rapidly developing AI and the need to prepare for the changes it will bring. Media decided to put its own twist on the matter. In the past week we have been inundated with headlines like, “Stephen Hawking Is Terrified of Artificial Intelligence”, and “Stephen Hawking: Artificial Intelligence ‘Potentially the Worst Thing to Happen to Humanity’”. Is the great Stephen Hawking really the neo-luddite that these headlines seem to suggest that he is? Is he really warning us about a technological leap that should be avoided at all cost?

No, nothing could be further from the truth. I think Hawking makes it clear in his article that what is to be feared is not AI or other technological developments, but rather our (as in ‘we humans’) lack of foresight and planning to ensure that technology develops in a way that produces the greatest benefits for humanity. Although this applies generally, one of my big worries is that education is especially lagging in this regard. Not only are we woefully unprepared for the impacts that AI and other technological developments will have on the field of education, but I think that relatively few are even aware that the potential for significant impact is even there, and closer than many think.

So, here are what I think are several overlooked aspects of AI and related technological developments that educators should be preparing for:

1. Self-driving cars – Not many educators are likely to see any immediate connections between the development of self-driving cars and education, and for the most part, they’re right. However, it is clear that the powers that be have envisioned a near-term future (next 5-10 years) where self-driving cars will become the norm (see pg. 7 in link) and are vigorously pursuing ways to make this a reality. This means, among other things, that advanced AI technology needs to happen and it needs to happen quickly. However, advanced AI developed for self-driving cars will not only serve the auto industry. The technological hurdles that need to be overcome on the path toward viable self-driving cars, including advanced AI, will fuel developments in other areas and will do so very quickly. Whether educators want it or not, advanced AI will be in, and affecting, the learning environments that they construct around the time that children being born today start school.

2. Superdupercomputing – Effective AI requires a lot of computing power, in fact massive amounts of it, the kind of power that only the most super of supercomputers can supply. In our minds, supercomputers are something that you find in advanced science instutes; not something that we, the lowly commoners, interact with. That is wrong. Much of what we do with information and communication technologies today involves some of the most powerful supercomputers being deployed today. We are no longer beholden to the limitations of the device we have before us. The increasing availability and accessibility of high-speed data networks allows us to pass on many of our intensive processing tasks to supercomputers. In the past, when we heard about the vast processing power of one or another government-funded supercomputer, it had little relevance for the everyday technology-user. Today, when we hear about Watson’s or other supercomputers’ amazing new capabilities, it means something is about to happen that will affect us.

3. Computer-generated information – Computers are data-processing machines. They are very good at sifting through abstract data, identifying patterns, sorting, and that type of stuff. Making sense of patterns in abstract data and being able to communicate that in a meaningful manner is a whole other ballgame. Humans are far better at making sense of stuff than computers that see abstract data as meaningless tokens. Increasingly advanced AI is challenging our predominance in this area. Already, media outlets are using various software solutions to generate brief, concise news items from abstract data far more quickly than humans can. There are already a range of services and applications that generate anything from brief news items and blog articles to extensive reports and books. A recent study showed that while computer-generated articles tended to be somewhat dry, participants in the study were not able to distinguish between them and articles written by humans. If you are a teacher, it may very well be that you have already received from a student some sort of paper that was entirely generated by a computer. The accessibility of these types of services will increase as AI technology develops.

4. Change faster than the speed of the human mind – As computers increasingly take on the task of generating information from data, rates of change in various knowledge domains will increase to levels that are beyond our ability to keep up. This is already happening in some areas. The increasing use of software to facilitate financial transactions is perhaps one of the best current examples. It is estimated that computer-driven high frequency trading (HFT) already acounts for around half, or more, of all US equity trading volume. With modern computers and complex trading algorithms, trades of this type occur in microseconds. Consequently, significant market fluctuations can occur before we mere humans would even be able to figure out what happened, nevermind formulating a reasonable response. Use of automated article-writing software is creating similar circumstances for journalists who thrive on “breaking the story”. Computers are able to grab data, put together a concise news report and publish in the time that it would take us to get to our computer and orient our fingers on the keyboard. Just a month ago, the Los Angeles Times broke the story about a major earthquake in Southern California just minutes after it occured. The news item was generated by reporter and programmer, Ken Schwencke’s, Quakebot, software that he created that monitors U.S. Geological Survey’s communications and writes up a story the moment a significant event occurs and automatically posts it to the LA Times LA Now blog.

These all pose significant challenges for educators and others involved in education that need to be addressed. But, each also offers possibilities of fantastic opportunities, as long as we prepare ourselves. The threat here is not in the technology, it is a question of how prepared we are for some pretty dramatic changes.

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Smoothing space for collaboration and innovation

I delivered a keynote at an eTwinning workshop being held in Reykjavík, Iceland this weekend. My slides are below. The context (i.e. what I said as opposed to only what’s in the slides) is that knowledge creation is dependent on our ability to traverse conceptual, virtual and real spaces. information technologies allow us to smooth whatever terrain we find ourselves in to increase our capacity for collaboration, knowledge creation and innovation and emerging technologies have the ability to take us places that we’ve never been before.

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Is innovative thinking in education “dangerous”?

Festival of Dangerous ideas logoThe College Development Network in Scotland hosted a “Festival of Dangerous Ideas” on education a couple of weeks ago (see also the festival blog here). As per their website, the goal of the festival was to:

“to re-establish the importance of dangerous ideas as agents of change in education – to shift the axis of what is possible!”

Great idea, great initiative! But, concerning the message being delivered, what are the real “dangerous ideas” in education today? Are the ideas that are intended to produce change the dangerous ones? I would suggest that the truly dangerous ideas are the ones that hold us back – the ones that reinforce the status quo in times of increasingly rapid change. Are we helping ourselves if we promote what we feel is the appropriate way forward as “dangerous”?

I know, I’m being a bit nitpicky but this just got me thinking…

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