Allow ICT in exams? Denmark’s simple approach

As information and communication technology (ICT) use has increased in education, there has been some discussion in recent years concerning the use of ICT during school exams. One of the main concerns regarding the use of ICT in education in general is the perceived potential for cheating. This certainly is a real concern, especially regarding exams which are intended to give a reliable measure of what students have learned. In some countries, however, steps are being taken to increase the use of ICT in general and in exams. See information here from the Danish Ministry of Education, on experiences in Denmark of increasing ICT use in the classroom, on assignments, and even on exams.

There’s plenty of research that highlights students’ indiscriminate use of available information resources which sometimes borders on, or are blatant examples of, plagiarism. Yet, there are many reasons for increasing the use of ICT which arguably outweigh the potential for misuse, especially to link students’ everyday use of technology to their school use to promote the use of ICT as a learning tool in all facets of life. The struggle to accommodate technology in education has resulted in a range of approaches, some of which are highly questionable given the aims, ex. blocking access to the Internet or specific web-based services that students commonly use outside of school. Lassen suggests a highly effective alternative approach that has been used to allow ICT use on exams in Denmark – almost deceptively simple but sensible when you think about it – just change the questions from “when and who” to “how and why”. This is an example of changing the practice to accommodate the technology rather than the more common approach of trying to change the technology to fit the practice.

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Technology foresight: Learning from early attempts

Irvine & Martin’s (1984) seminal Foresight in Science: Picking the Winners, provides fascinating insights into early attempts at technology foresight. The authors describe a comparative case study of technology foresight in France, (what was then) West Germany, the US and Japan in the 1970s and early ’80s. The study reveals some of the trials and tribulations of early foresight programs and some of the successes. Despite being almost 30 years old, the book is just as relevant today for those interested in technology and research and social policy as it was when it was published.
The book shows how early attempts at technology foresight suffered from a limited understanding of the relation between technology and society, unsophisticated methodologies, and a lack of confidence in the technology foresight approach itself. Most of the foresight activities described relied too much on experts from scientific communities, who were often motivated more by their concerns for their own fields rather than the broader concerns that the exercises were intended to address. As a result, many of the foresight exercises described failed to produce useful results or the results had little impact on policy.
Japan is presented as a notable exception to the rather unimpressive efforts in the other countries studied. In fact, the authors seem at times to be so impressed with Japanese foresight activities that it might in itself constitute a justifiable criticism of the book. Nevertheless, the Japanese foresight activities described are deserving of much of the authors’ praise. The Japanese approach to foresight, starting in the 1960s and extending through, and beyond, the 1970s, comes much closer to what contemporary foresight activities strive to be. The Japanese based their foresight activities on a very deliberate vision of a technology-driven society and, therefore, were more comprehensive in their approach as regards their methodologies and the scope of the exercises. The Japanese used a bottom-up approach, mixed quantitative and qualitative methods, and included a broad range of key stakeholders, including the scientific community, and social and cultural experts. Participants were significantly invested in the projects and the outcomes had considerable impact on Japanese R&D and social and economic policy, and continues to do so to this day.
The authors derive, from the Japanese study, a hint of a framework for technology foresight activities that has been referred to as the five c’s:

  • communication between disparate groups of participants
  • concentration on the long-term future
  • coordination of future R&D activities
  • creation of consensus on future priorities
  • commitment to results to ensure that they become self-fulfilling

This framework is further developed in the authors’ later book, Research Foresight: Priority-Setting in Science (Martin & Irvine, 1989), which I will write about in a later post.
References
Irvine, J. & Martin, B. R. (1984). Foresight in science: Picking the winners. London: Francis Pinter.
Martin, B. R. & Irvine, J. (1989). Research foresight: Priority-setting in science. London: Pinter Publishers.

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Technology foresight: The difficulty of peering into the future

As I mentioned in an earlier posting, technology foresight emerged from the future studies and technology forecasting fields and seeks to apply outcomes from these fields to policy- and decision-making (see the earlier posting for a discussion on what technology foresight is). A major concern for policy-makers is the quality of outcomes from future studies and technology forecasting fields. Regrettably, there are a number of self-proclaimed “futurists” that have cast shadows of doubt over these fields. An important consideration for any technology foresight activity is then how to ensure reliable information and how to identify questionable predictions or forecast. In this post, I’m going to focus on the negative. I discuss a few high profile futurists who tend to be very prominent on the Internet and other very accessible resources, whom scholars have been very critical of, and for good reasons. The point I wish to make is that when considering what to base future-oriented policy decisions on, it is important to evaluate the methodology and substance of the informational inputs used. This posting is not intended to be critical of the futures and forecasting fields as such. Indeed the futures and forecasting fields have developed a number of rigorous and objective methods to produce highly reliable data. I will discuss those in future postings when I get more into methodologies.
Ray Kurzweil is perhaps one of the world’s best known “futurists” whom many commentators and scholars have questioned. Among Kurzweil’s well known predictions are the imminent “technological singularity” and his related prediction, i.e. as one consequence of the technological singularity, that humans will overcome death in the near future. Kurzweil bases his predictions on an extrapolation of the well known Moore’s Law (ML) concerning the number of transistors that can be placed on an integrated circuit. For Kurzweil, ML demonstrates an example of exponential development which results in increasingly accelerated technological advancement. From Moore’s Law, Kurzweil derives his “Law of Accelerating Returns” (LAR). Kurzweil’s LAR does two things in regards to ML: it extends ML to technologies other than transistors, and it equates increasing transistor density with increased technological capability. Both of these assumptions are highly dubious. Furthermore, Kurzweil assumes that ML is on par with a natural law while many scholars and commentators have suggested that the reliability of ML is more a product of its inadvertent normativity rather than any descriptive properties, i.e. that ML pressured technology developers to sustain the “law’s” predictive power rather than the other way around (van Lente & Rip, 1998; Gardiner, 2007). In any event, Kurzweil’s attempt to derive various future predictions based on his reading of ML makes for some very questionable futurism.
Whereas Kurzweil’s weakness lies in his theoretical assumptions, John Naisbitt, the “Megatrends” guy, has mostly been criticized for his methodology. John Naisbitt has written, or co-written, a series of books named Megatrends this-and-that since the early 1980s. Most of them, if not all, have been bestsellers. His first book, titled Megatrends: Ten new directions transforming our lives, was criticized for the fact that Naisbitt did not reveal much about his methodology other than that it was based on “content analysis” of a bunch of newspapers and such. He has addressed the methodology issue to some degree, but it hasn’t really changed his approach; his books are still mostly a summary of things that are being discussed in select information outlets with only a superficial analytical component at best. Naisbitt tends to be a dedicated optimist; it seems that all trends indicate a fabulous future that we’re all just going to love (for ex. he seems to miss things like recessions and terrorism)! The result is that Naisbitt’s books tend to come across more like propoganda, striving for self-fulfillment, than realistic visions of the future. The most striking example of this is his and Doris Naisbitt’s recent China’s Megatrends: The 8 pillars of a new society which has been widely criticized for presenting an overly optimistic government-sanctioned view of modern China. For the Naisbitts’, it would seem that dissidence is almost non-existent in China and that the Chinese are grateful that the government assumes the tedious, but necessary, role of separating the wheat from the chaff on the Internet for them, or what we (at least I) would usually refer to as censorship.
A third somewhat visible “futurist”, and collaborator on Kurzweil’s “Singularity University”, is Dr. James Canton of the Institute for Global Futures who published The extreme future: The top trends that will reshape the world in the next 20 years in 2006. It contains such prescient items such as that in the future criminals will create fake-bank webpages to steal our information (if I really thought that this was not a current concern in 2006 I almost would have deserved to have my information stolen). His blog on the Institute for Global Futures website is a real gem. For example, on May 10, 2009, Canton posted an item about the “Ghost Hack that is now embedded in about 100 million computers, perpetrated by an Asian secret organization”. Scary stuff! Unless you’ve seen the 1995 anime film Ghost in the shell, of which this is essentially the synopsis. Canton is not a very prolific blogger (I guess he’s too busy on the speaker circuit). His most recent blog post is from November 24, 2009 and warns us about the megacity explosion; “Over 50% of the planet lives in MegCities (sic.) today. We are forecasting over 65% by 2025.” Canton is so way off here that I really have no idea what he is talking about. Megacities are defined as urban areas with a population of 10 million or more (Canton includes this definition in his post). According to UN data from 2009, there are 21 urban areas in the world that meet that criteria. The combined population of these urban areas accounts for, at most, about 8% of the total world population.
There are at least two properties that all of the above futurists (and others of their ilk) display. First is a tendency toward sensationalism. Their predictions are meant to evoke more of an emotional response (whether it be intense optimism or desperate gloom) than a rational reflection on how to plan for the future. The other is that their methodology is mostly limited to selective and superficial environmental scanning that is more oriented toward reinforcing their own theories or sentiments regarding the future than providing objective data. Nevertheless, these authors, if by no other means than their popularity, do demonstrate the increasing recognition of the importance of long-term future-oriented planning. However, they also show us how important it is to critically evaluate any information that is intended to inform policy-making processes.
Gardiner, B. (April 24, 2007). Does Moore’s Law Help or Hinder the PC Industry? Extremetech.com. Retrieved August 29, 2010.
van Lente, H. & Rip, A. (1998). Expectations in technological developments: An example of prospective structures to be filled in by agency. In, C. Disco & B. v.d. Meulen (Eds.) Getting new technologies together: Studies in making sociotechnological order. Berlin: de Gruyter. Available on Google Books

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Technology foresight in educational policy and planning

One of the problems that plagues educational and other social policy regarding technology, is that it tends to chase technology in a hopeless game of cat and mouse. Policy is formulated based on currently existing technology (or what is in the sphere of policymaker’s knowledge at that time) and is ill equipped to deal with new technology developments. As a persistent problem in developed areas of the world, this tendency is transmitted to other parts of the world in the form of programs and initiatives meant to stimulate ICT development. In developed parts of the world, there is considerable evidence that policies lead to a knee-jerk reaction on the part of decision makers to limit the use of technology that is not explicitly covered by existing policy. We see this for ex. in the outright banning of cellphones, social networking applications and other technologies in schools even though they have been shown to be effective learning technologies when used right. The rapid rate of technological development and change makes this unviable. What is needed in educational policy-making is technology foresight and longer term planning, i.e. policies that take into account expert views on anticipated or preferred technological developments and are able to accommodate rapidly developing technologies.
The term “technology foresight” is a fairly recent concept that has emerged from the future studies and technology forecasting fields. Irvine and Martin (1984) first used the term to describe a long-term, strategic activity specifically intended to inform policy-making. Since then, and especially throughout the 1990s, there has been significant interest in technology foresight and a number of notable national-level foresight programs, although definitions of the term and the precise nature of the activities tend to vary somewhat. Some use “technology foresight” to describe the interplay between a range of future-oriented activities, including, technology assessment, technology forecasting, and future studies, with lesser emphasis on the actual policy-making process. Many of the case studies presented in the informative Handbook of Technology Foresight (2008) demonstrate this, where the emphasis seems to be more on the foresight generating activity than policy-making processes. Slaughter (1995), however, makes a point of specifically relating technology foresight to decision making, although he is more concerned with technology foresight in organizations than public policy.
There’s a distinct difference between the two uses of the term “technology foresight” described above. First, “technology foresight” is used to describe the product of a range of forecasting methods. Second, “technology foresight” is used to describe a property of the decisions and policies formulated on the basis of the forecasting activities. I have a problem with the first use of the term and it has to do specifically with the word “foresight”. In our everyday language, foresight is not an artifact that can be generated as the first use of the term would seem to suggest. We generally encounter the term “foresight” as a descriptive property of an action, i.e. someone did something with foresight to mean that someone’s actions took future implications and expectations into account. Pertaining to the first instance, and has been pointed out by Miles, Harper, Georghiou, et al (2008, p. 8), “technology foresight” tends to be used as a catchall term for a wide range of future forecasting and assessment activities, and as such, is not especially helpful in clarifying the way that these activities affect policy-making. Hence, I’m more inclined to accept Slaughter’s (1995) formulation of the term “technology foresight” as focused primarily on the use of rigorously and objectively generated future-orientations in decision-making or policy-making activities.
Despite a growing body of literature on technology foresight, and perhaps partly due to the conceptual fuzziness that I’ve described, little attention has been paid to the actual policy-making process, especially how anticipated and preferred futures, generated by technology foresight programs, inform policy-making activities. One very interesting question is how anticipated and preferred futures become significant policy issues? The literature on policy-making fairly consistently emphasizes that for policy action to occur there needs to be a well formulated, broadly accepted, and solvable policy problem. It’s interesting, then, to consider how an anticipated or preferred future, n.b. something not yet in existence, is translated into a critical social policy problem worthy of policy action, ex. new educational policy.
The issue of how anticipated and preferred futures affect policy-making is the topic of my dissertation research, so expect to read a lot about it here on my blog in the coming months. There are a number of countries that have implemented what I would consider foresightful educational policies at the national level with some success, such as for ex., Finland and Singapore. Nevertheless, the methods that have been used to inform the policy-making process and the resulting policies differ in many ways. My plan is to focus on a single country, Finland, instead of doing a multi-country comparison, since I think that this will allow me to get at the issue in more depth.
Here are some links to resources related to technology foresight for those who are interested:
Foresight: The journal of future studies, strategic thinking and policy
Richard Slaughter’s Foresight International
European Foresight web site
European Foresight Monitoring Network (hasn’t been updated for awhile but some good resources on the site)
References:
Georghiou, L., Harper, J. C., Keenan, M., Miles, I. & Popper, R. (2008). The handbook of technology foresight: Concepts and practice. Northampton, MA: Edward Elgar Publishing.
Irvine, J. & Martin, B. (1984). Foresight in science. London: Frances Pinter.
Miles, I., Harper, J. C., Georghiou, L., Keenan, M. & Popper, R. (2008). The many faces of foresight. In L. Georghiou, J. C. Harper, M. Keenan, I. Miles & R. Popper (Eds.), The handbook of technology foresight: Concepts and practice. Northampton, MA: Edward Elgar Publishing.
Slaughter, R. A. (1995). The foresight principle: Cultural recovery in the 21st century. London: Adamantine Press.

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Sorry about unpublished comments

I just realized that a number of readers had commented on posts over the past few months and that their comments weren’t published. My system tagged them as spam and I didn’t see them. I get an incredible amount of spam comments to the site. I had decided that my filters were doing a good job and hadn’t bothered to check on the comments. When I finally did (just now) I saw that my filters were doing too good a job. I do apologize and can’t emphasize enough that I welcome and am thankful for all relevant comments. I’ll try to keep an eye on my filters in the future.

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Augmented reality and education

Earlier this summer I co-developed and co-led a seminar at the University of Minnesota with Dr. Arthur Harkins about augmented reality and the future of classroom-based education. My presentation is here: “Learning in augmented reality”. Augmented reality is the capability of overlaying data on realtime experiences of our surroundings. There are a couple of videos that demonstrate the concept in the presentation. Augmented reality is a fascinating technology that is rapidly gaining momentum, especially with the proliferation of networked location-aware smartphones like the iPhone and Android phones.

There are two things that I focus on in this presentation. The first is that when we start talking about reality in relation to learning, it raises questions about the nature of reality, whose reality it is, and how an individual relates to any given reality. The second is that learning affects our personal reality, i.e. reality, as a description of our relationship to our surroundings (what I’ve referred to as our “functional reality”), reflects things that we have learned and how we have learned them. So, while augmented reality technology has obvious potential in terms of providing enhanced resources for learning, encouraging learners to use the technology to collaboratively create augmented realities is likely to have far more potential benefit since it allows them to interactively extend and take ownership of their reality (i.e. extending their functional reality) through direct experience.

I have another post that I’m working on (the follow-up article has been posted here) where I’ll go a little deeper into considerations about multiple realities, technology and learning (the part I refer to as “learning as ‘realizing'” in the presentation). That should be up in the next couple of days.

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