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  • There can be many reasons for being concerned by technologies when discussing education: 1.   First of all, we live in what many policy-makers, philosophers, educators, describe in terms of a digital or information revolution.In a sense, the information turn has made of us inforgs (connected information organisms) evolving in the infosphere: a place where distinctions between learning from digital on-line – as opposed to physical, off-line one - interactions and contents are less and less relevant.  Let us imagine walking in the street with our mobile phone in our pocket (not a huge leap of imagination, in fact). Someone calls from far away, we answer and engage in a conversation about a strange art object we are looking at, right in front of us; a picture of the mysterious object is soon taken, and sent to the phone-friend. The phone-friend, tickled by curiosity, searches the Internet for street exhibitions in our town. Meanwhile, we approach the object, and find a code; we then point the camera of our smart-phone onto the code, and an artist appears next to the mysterious object  - on the screen of our phone, of course -, ready to explain the meaning of the artwork, and to guide us  - GPS activated - through an entire maze of no-more so mysterious objects of art that are physically installed in town and through another maze of artworks that the same artist has created with digital tools: representations that are activated by special codes disseminated in the town and that we see on the screen of our telephone, when we point the camera on the real spot. By simply using a smart-phone one can experience that “The digital is spilling over into the analogue and merging with it” (Floridi 2007, p. 64), and that the real world is part of the infosphere (the picture you sent to your phone-friend).What seems to be sure, beyond the promises of augmented reality, is that digital devices are substituting many non digital ones, producing new uses (an exemplary case is represented by the use of the camera mounted on mobile phones, which has a very different use from classic reflex cameras, and by the multiplication of pictures taken and sent every day).Does this mean that kids who are born in this post-informatic revolution world are automatically digitally literate? This inference is implicit in the use of the term “digital natives” introduced by Marc Prensky (2001), and by its opposition with the “digital immigrants”. What should we call these “new” students of today? Some refer to them as the N-[for Net]-gen or D-[for digital]-gen. But the most useful designation I have found for them is Digital Natives. Our students today are all “native speakers” of the digital language of computers, video games and the Internet.So what does that make the rest of us? Those of us who were not born into the digital world but have, at some later point in our lives, become fascinated by and adopted many or most aspects of the new technology are, and always will be compared to them, Digital Immigrants. (Prensky 2001) Prensky goes even further, and describes a sort of anthropological mutation that the advent of digital technologies would have brought in: Today’s students have not just changed incrementally from those of the past, nor simply changed their slang, clothes, body adornments, or styles, as has happened between generations previously. A really big discontinuity has taken place. One might even call it a “singularity” – an event which changes things so fundamentally that there is absolutely no going back. This so-called “singularity” is the arrival and rapid dissemination of digital technology in the last decades of the 20th century. Today‟s students – K through college – represent the first generations to grow up with this new technology. They have spent their entire lives surrounded by and using computers, videogames, digital music players, video cams, cell phones, and all the other toys and tools of the digital age. Today‟s average college grads have spent less than 5,000 hours of their lives reading, but over 10,000 hours playing video games (not to mention 20,000 hours watching TV). Computer games, email, the Internet, cell phones and instant messaging are integral parts of their lives. It is now clear that as a result of this ubiquitous environment and the sheer volume of their interaction with it, today’s students think and process information fundamentally differently from their predecessors. These differences go far further and deeper than most educators suspect or realize. “Different kinds of experiences lead to different brain structures, “ says Dr. Bruce D. Perry of Baylor College of Medicine. As we shall see in the next installment, it is very likely that our students’ brains have physically changed – and are different from ours – as a result of how they grew up. But whether or not this is literally true, we can say with certainty that their thinking patterns have changed. If one thinks about it, the inference from digital natives to tech savvies has nothing automatic in itself: we are born in post-writing revolution, but literacy is still a matter of formal education. For the same reasons, being technologically literate is different from being able to use a keyboard or use apps. It is not identical to being able to write code or program, either. Just like being literate in writing does not require being able to write a novel. For some, digital literacy includes the capacity of using new technologies in a creative way, or at least as tools for creating and in general “doing things” (Resnick,  2002, 2007). Viceversa, certain technologies provide a unique opportunity for developing creativity.  For others, digital literacy includes an attitude towards the opportunities (and side-effects) represented by new media technologies and practices (digital awareness). Established and internationally accepted definitions of digital literacy are generally built on three principles: the skills and knowledge to use a variety of digital media software applications and hardware devices, such as a computer, a mobile phone, and Internet technology; the ability to critically understand digital media content and applications; and the knowledge and capacity to create with digital technology. (Media Awareness Network Canada) The idea that the new generation (digital natives, the net or google-generation) has a different attitude towards technology is, in a sense, trivial: they barely can figure out what it is to spend money for buying films and printing pictures taken by a camera; as the old generation barely understands what it is to go to a public phone place for placing a phone call, rather than calling from home.  But the idea that the new generation is naturally literate in what concerns the use of digital devices seems to be a technomyth. Several studies cited by a joint report of UCL and the British Library show that digital natives or “the Google generation” are not born good at efficiently searching the Internet, for instance. Not only they search by typing entire sentences (Google is not sensitive to sentences) and rarely use Boolean operators, but they continue to do that after years of practice. Searching the Internet gives the false impression of being such an easy task that no one seems to engage in the deliberate practices that is required in order to become experts in any domain, including the use of technologies.Thus, if it is true that we live in a world where digital technologies have changed the way we work, do research, communicate, obtain information, get entertained, this does not mean that we are spontaneously able to take the best from technologies by acquaintance, or to avoid the risks by natural intuition. Quite the opposite, our intuition pushes us to take risks: to exchange with complete strangers (because socialization is a primary concern for humans), to accept with gratitude search results that match with our preferences (and comfort our confirmation bias), or to think that intuitive technologies are easy to use. The first domain that requires to be explored scientifically concerns the impact of technologies, and the debunking of techno-myths, including myths of radical transformation of the human mind. Indeed, the invasion of life by technology has produced strong claims about their effects on the human mind. The debate is often very ideologized and polarized and revolves around the “special skills” possessed by Generation Y or G, and the effects of technologies in terms of addiction, violence, boosted intelligence/induced dumbness. We will discuss them below by adopting an evidence-based attitude. 
  • 2.  The second reason for discussing technologies in a course about education is that even if education is not the place where technologies are the most present (they are certainly not as present as in our workplaces, or in the most of our homes), technologies have been developed for education well before the diffusion of educational video games, electronic whiteboards, or even portable computers. In 1954, the psychologist F. B. Skinner had described a machine for teaching. The machine was to be distinguished from purely “passive” technologies such as audio-visual supports. The teaching machine was, just like a teacher, an interactive machine, and interaction was then considered as a crucial aspect of the process of learning and of education. The terms trough which Skinner described his teaching machine are much similar to what we can say today of computers and in general of digital technologies for education: they allow to personalize learning, reduce stress, enhance motivation, reinforce learning, and all this because they allow each student to follow her own rhythm and to receive immediate feedback. Just like a real teacher, in a tutoring condition.Today’s teaching machines are more sophisticated, but they still resemble this description. Naturally, there are some remarkable differences. Namely, thanks to modern teaching machines-      the interaction is not limited to answering questions, one student can also interact with other students. (Let's call it “The social network” effect.)-      students (and teachers) can retrieve information from real and virtual places, and use it in place or in the school-      students can access information, teachers can present information in new ways, but they can above all create this information. Access and presentation of information are almost certainly the mot diffused uses of technologies in education-      students can interact with simulations of events (models) that cannot be easily reproduced in school, and that cannot be easily  manipulated. Models have a pedagogical value as compared with the interaction with real situations also because they select and enhance relevant information-      students can interact with special simulations, in a playful way. This possibility encompasses different uses: from adopting the content of existing video games as occasions for teaching and learning, to adopting the structural elements of video for inspiring teaching, to creating video games for learning (educational or serious games). Do teaching machines work? Which ones work better and why? Are there learning domains for which learning machines or certain types of learning machines are more appropriate? There are now many studies on the use of specialized technologies for specialized learning contents: among others, simulators for learning how to fly a plane or how to cut into a human body or perform a medical intervention. But there are also studies on more generalist machines – such as video games – and their apparent effects on flying and surgical skills. We will briefly present some empirical results of their evaluations below. The first thing to say is that when adopting an evidence-based attitude we should give up the temptation of pronouncing general judgments starting from local data: the effects of one type of technology in one particular context of use
  • 3. During the last decade some have moved from the idea of using technologies in education to the idea of transforming education because of what the observation of technology (namely video games) suggests about learning – e.g. of devising new methods for education that are inspired by the notion and the practice of gaming (Squire 2005, Halverson 2005, Gee 2005, Shaffer, 2005). These methods include the use of technology but not necessarily technology that has been designed for education. We are thus faced with the third reason for getting interested in technologies when dealing with education, which is: the validation of methods that exploit or are inspired by principles instantiated by digital technologies. This consideration concerns in particular video games and multi-media interactive technologies; e.g. GBL or Game-based learning preconizes the use of video games for teaching and learning because of their intrinsic pedagogical value. E.g., James Paul Gee describes the structure of video games as an incredibly well-thought tool for learning; in fact, players do learn quite quickly how to play (or they quit and the producer fails). Gee lists 36 good learning principles that would be embedded in video games and invites teachers at adopting them, even if they do not feel ready to adopt video games as tools for learning (Gee, 2003; Gee, 2005). 1. Active, Critical Learning Principle2. Design Principle3. Semiotic Principle4. Semiotic Domains Principle5. Metalevel Thinking about Semiotic Domains Principle6. “Psychosocial Moratorium” Principle7. Committed Learning Principle8. Identity Principle9. Self-Knowledge Principle10. Amplification of Input Principle11. Achievement Principle12. Practice Principle13. Ongoing Learning Principle14. “Regime of Competence” Principle15. Probing Principle16. Multiple Routes Principle17. Situated Meaning Principle18. Text Principle19. Intertextual Principle20. Multimodal Principle21. “Material Intelligence” Principle22. Intuitive Knowledge Principle23. Subset Principle24. Incremental Principle25. Concentrated Sample Principle26. Bottom-up Basic Skills Principle27. Explicit Information On-Demand and Just-in-Time Principle28. Discovery Principle29. Transfer Principle30. Cultural Models about the World Principle31. Cultural Models about Learning Principle32. Culture Models about Semiotic Domains Principle33. Distributed Principle34. Dispersed Principle35. Affinity Group Principle36. Insider Principle Will video games change the way we learn? We argue here for a particular view of games—and of learning—as activities that are most powerful when they are personally meaningful, experiential, social, and epistemological all at the same time. From this perspective, we describe an approach to the design of learning environments that builds on the educational properties of games, but deeply grounds them within a theory of learning appropriate for an age marked by the power of new technologies. We argue that to understand the future of learning, we have to look beyond schools to the emerging arena of video games. We suggest that video games matter because they present players with simulated worlds: worlds which, if well constructed, are not just about facts or isolated skills, but embody particular social practices. Video games thus make it possible for players to participate in valued communities of practice and as a result develop the ways of thinking that organize those practices. Most educational games to date have been produced in the absence of any coherent theory of learning or underlying body of research. We argue here for such a theory—and for research that addresses the important questions about this relatively new medium that such a theory implies. (Shaffer, Squire, Halverson, Gee 2004) 
  • Once established that there is an interest in dealing with technology in education – dealing with this issue is rather inescapable, indeed – the case is made that the issue should be handled scientifically: searching for empirical evidence about what works (which educational technologies, in which contexts and for what kind of content produce the effects they are claimed to produce; which methods inspired by technology work, with the same constraints as before; which effects technologies produce in terms of impact on cognitive abilities such as attention, memory, visuo-spatial capacities, eventually proneness to violence) and knowledge about what plausibly might happen, or should not, when the human mind is over-exposed to technologies of different kinds in terms of modification of neural circuits and its behavioral consequences. In other words, the convergence of technology and education is a further reason for adopting an evidence-based  theoretical knowledge-inspired attitude.
  • The first thing that we should recognize once this attitude adopted is that several limits affect the existing empirical research on the effects of video games and other technologies on learning and the acquisition of new skills. Also, that several difficulties are inevitably present in this kind of research; while we cannot eliminate them all – better: because we know we can’t eliminate them all – is all the more important to be aware of them and make them clearly readable in any statement about the results of empirical and theoretical researches.
  • Fair test: be aware of… slippery slopes Here’s a short list of examples of slippery slopes in the domain of technologies and their impact on learning:- CausalityIn the domain of video games Rosser et al. have studied surgeons that practice laparoscopy; they have observed that surgeons that are also video games players perform better at tests of oculo-manual coordination and even at laparoscopy as compared with non players. Both coordination and performance at laparoscopy are evaluated through video game-like technologies, however. Moreover, the study consists in a cross-sectional comparison and is only suitable for extracting correlational and not causal considerations. In fact, it is possible that players are more skilled from the start, and this is why they play, rather than being the case that play trains coordination capacities (Rosser, 2007).There is an enormous problem of causality in the literature about the effects of technologies upon cognition, both positive and negative. More than establishing whether a certain technology is effective or harmful, most of the existing studies show that a certain technology correlates with good performances, or rather with violent behaviors. At best, causal studies show effects at short term or effects that are not proved to correlate with real world behaviors and capacities.In the case of technologies that are suspected to produce negative effects (e.g. violence, addiction or lower grades at school) the main reasons for such a limited evidence are ethical: one cannot ask children to play at violent video games for months or even years and measure whether this has affected their behavior, or to play every day and evaluate whether this affects school performances.
  • - Equivalence between experimental and control groupAn experimental study on the effect of video games playing has shown positive effects upon flight performances of playing flight simulation games. Notwithstanding that  the training with full-flight simulators is widely accepted as a substitute for real flight training, the pilots of the flight simulator training group received extra-training as compared to the control group (Gopher 1994).It is very important that the experimental and the control group are equivalent for everything but the factor that is measured. Otherwise, it is impossible to affirm that the measured effect is caused by the training with the video game rather than by other factors (such as time spent on training). Several conditions can in fact influence the result of an experiment and produce better results: one is the fact that the intervention has been effective, but it is not the only one. For instance, the subjects of an experiment tend to do better when they know they are observed (Hawthorne effect), or when they want to please the experimenter (Pygmalion effect). In order to control for this kind of bias it is necessary to treat experimental and control group subjects as much the same as possible, and to leave them ignorant about who's who. In the domain of medicine, experimental and control groups receive pills with the same external aspect, in the same quantity and form of administration; no one knows whether the pills contains the active substance or placebo. It is also important that the experimenter who analyses the results is blind in connection to who's who, or she risks being influenced by what she thinks about the effectiveness of the active substance. So, patients are assigned blindly to the experimental rather than the control group and their outcomes are also evaluated blindly. In one case in which the analysis of the results was not done blindly, homeopathic pills appeared to do better than placebo; but once the blindness of the analysis established, the difference between water and homeopathic water has vanished (BBC). It is important to keep this kind of examples in mind, even if they do not belong to education, because they make us understand how easy is to be fooled by experimental studies that do not comply with the rules of production of gold evidence: randomized, double-blind tests.
  •  - Active controlsRobertson (2009) describes an experiment with 32 schools and 634 children; the experiment uses randomized assignment to two groups: the experimental group trains with Nintendo DS Dr Kawashima Brain Train half an hour a day, 5 days a week for a period of 9 weeks. In the control group the teachers are asked not to change their normal routine. The data collected include pre and post measures of computation (accuracy and speed) and various self-measures (e.g. mathematics self-concept). Statistical gains on accuracy and speed are ascertained in both groups, with mean greater gain for experimental group (no effect on self-esteem). The control group is passive because there's no use of technology different from the video game. The experiment cannot prove that video games have positive effects as compares, say to the simple use of a computer, or the introduction of an innovation in the daily routine. The subjects cannot ignore that they belong to a “special group”. Finally, the test concerns exactly the trained capacities.In the domain of mind and behavior there's a further condition to respect, whenever it is possible and required: the control should be active and not passive; the analogous situation in present in medicine when a substance is compared not with placebo but with another substance. In many cases in fact, we are not interested only in knowing whether a certain intervention is better than nothing, but also whether the intervention (possibly a new one) is better than another one (maybe one that is in use).When an intervention exists, and the experiment aims at establishing effectiveness (not cost-benefits, for instance), the control group should perform a task that is as similar as possible to the one of the experimental group, or we run the risk of overestimating the effects of technology and underestimating those of training tout court. If our aim is that of establishing that more training is always good and that it doesn't matter whether it is effectuated in a real or in a simulated cockpit, then the passive control is OK. But if we aim at demonstrating that the virtual simulation is better than a real training, then the two groups must perform the same number of hours of training, virtual and real.This example brings about two mains considerations that it is useful to keep in mind when considering evidence about the effectiveness of educational methods: the first, that there is not a unique way of forming the control group and of setting other experimental conditions; the second, that “wrong” control groups can be adopted in order to produce positive results (e.g. a treatment can be shown to be better than placebo, but in this way can be hidden the fact that the treatment is not better than other cheaper treatments or event that the treatment is harmful in other respects).
  • -      Expected effectIn an experiment conducted by the BBC television (Big Bang Goes the theory), Owen and colleagues have divided 11000 subjects in three groups: one group was asked to connect to a web site and perform reasoning, problem solving, and planning, the second was asked to perform short term memory, attention, visuo-sapatial capacities, mental calculation exercises, and the third one was asked to search the net for answering abstruse questions (Owen et al 2010). The three groups trained for 6 weeks, at least ten minutes three times per week. They are pre- and post-tested with a battery of tests that includes reasoning, memory, and learning and that is normally used in order to assess minimal variations in cognitive capacities at the onset of mental troubles induced by drugs or disease. All the groups do better at the post-test: this is normal, because repetition tends to lead to better performances; also, every group improves in its specific form of training. But no sign of transfer is noticed in the second group in respect to executive functions or in the first group in respect to reasoning capacities.It is important that the expected effect of the intervention is clearly stated before the experiment and that it is not confounded with other effects that appear during the experiment. Also, that minor gains are not “sold” as big effects only because the expected effects are inexistent. More specifically, it must be acknowledged that the experiment in itself produces certain effects; but these effects are not meaningful for validating the theory.
  • -      Polarized, ideologized debate and the power of anecdotesThere are especially hot issues in the field of assessing the impact of technologies on life and the human mind (Pasquinelli, Forthcoming). One is addiction: are video games, the Internet, computers and mobile phones – especially smart ones – powerful addicting practices? The literature is growing but not necessarily getting better; it is dominated by anecdotes about extreme cases such as the death of some China game player after days of connection without eating, drinking and sleeping (China was the first country to open a wealth of clinics for the disintoxication of teenage gamers). Or by anecdotes that any parent can collect about children becoming rude playing video games when they should do their homework, notes going down while the number of games in their Nintendo goes up, and so on. Social networks are especially threatening. And I have myself some anecdotes about a low, uninterrupted buzz produced by finger taping during lessons. But 1000 anecdotes do not sum up into 1 small fact. The problem is, that the debate is so heavily polarized that anecdotes are presented even by those who should care about evidence-based policies: the scientists.  This is even more true when we come to the violence issue: adopting a science-based certain position about media violence risks to be seen as a concession to the industry, which is always Big and Bad (from Big Pharma, to Big Tobacco, to Big Entertainment Industry). And this is not all. Behind studies on the negative impact of media violence on violent behavior (which is far from being scientifically proved) lies a view of human nature that is strongly ideologized – and almost certainly wrong: the denial of human nature itself. Many of those who defend the view that media violence can only be bad for our mental health consider that the mindset is shaped by experience, and experience only. We are what we see, hear, experience, individually - nothing else can come from our long history as human beings and evolved animals. The myth of the blank slate is heavily present in the debate, and flaws it.  As a matter of fact, the western world is not more violent than primitive societies (there’s nothing like a peaceful, love-dominated state of nature) and is not more violent after that violent video games have hit the market (with great success). Those who plead against media violence have the hope that fighting media violence will solve societal issues; they fear that if violence is not just a matter of culture it won’t be completely eradicated, ever. But fears and hopes (ideology) have no impact on nature: science does not describe things as they should be, but as they are. It is up to us – to our moral values and ingenuity – to figure out how to straighten things that do not fit with our plans: the course of a stream, differences between sexes or a natural predisposition for violence e.g. by exploiting our knowledge about the natural bases of empathy and collaboration. 
  • -        Undue interpretations of experimental and correlational studies, or: don’t rush to conclusionsThe literature on media violence and cyber-addiction is exemplary of another slippery slope: the undue translation of laboratory results into more general considerations. For ethical or practical reasons, experimental studies of media violence are necessarily restricted to short-term exposition and to short-term evaluations of the effects of exposing someone to violent scenes. Also, evaluations mostly concern minor behaviors and attitudes, such as using a violent vocabulary or feeling more aggressive, eventually being less helpful towards others, but not behaving violently towards another person. It is difficult to come up with a proof that violent media produce violent behavior, starting from this kind of limited study. On the other side, we have longitudinal, long-term studies that are not suitable for proving causality because they are by definition correlational studies: they check how exposition to violence and violent behaviors are related and in some cases co-evolve, but they cannot exclude the existence of a common cause that leads someone to behave more violently and prefer a kind of violent entertainment. In summary what we have are laboratory studies that are scarcely valid (they do not measure violent behavior, and often they do not employ violent media, unless one considers Wile Coyote and BipBip as being comparable to Game of Thrones) and predictive, and correlational studies that are not suitable for proving the causal role of violent media. We are faced with similar difficulties to those that were faced by physicians and medical researchers when dealing with lung cancer and tobacco, but in that case the difficulties were brilliantly solved by epidemiologists and by adopting healthy scientific attitude: a checklist of conditions that must be filled in order to consider correlational studies as good indicators of causality. This is not the case in the domain of psychology and technology, yet.
  • Evidence about cognitive effects and learning Let’s now get back to the issue of proving positive effects of new technologies upon learning. We will use brain training and video games as mind trainers as case studies for illustrating one of the major problems in technology-enhanced learning and teaching and in learning and teaching in general: transfer.We’ve seen that classical, commercialized brain training exercises do not seem to produce results that go beyond the fact of getting better at playing the game or at doing the exercise. In particular: their results do no transfer to skills evaluated through tests different from the pre-test. This kind of skepticism about transfer from capacities acquired in the game to life is confirmed by other studies, e.g. on the effect of memory, problem solving and visual identification exercises in the elderly: while participants to the study do better at the post-tests, in a way that is directly proportional to the quantity of exercise, they do not seem to do better in real life tasks (Ball et al 2002). In the same way, mental exercise of the brain training type does not seem to do any good at protecting the elderly from Alzheimer disease, and this is the result of a meta-analysis (Papp et al 2009).
  • Green and Bavelier have taken objections transfer and methodological issues very seriously (Green & Bavelier 2008, Bavelier, Green & Dye 2010). In spite of the difficulties of transfer they seem to have proved that action video games are not only correlated but causally related to better performances in a series of tasks that can be measured through tests that are not identical to the situations that are present in the video game. In other words, action video games would produce modifications at the level of certain cognitive skills (namely attention, visuo-spatial and temporal) that transfer to near contexts: The effects of playing video games on perceptual and cognitive skills are particularly remarkable given the typical specificity of skill learning. Indeed, in the case of action video game training, the tasks used to measure the various perceptual, attentional, and visuomotor skills are quite a departure from the “training paradigm” (i.e., action video games). There are few obvious links between chasing monsters across a star-spotted “spacescape” and determining the orientation of a single black ‘T’ on a uniform gray background, or between driving a car through a crowded cityscape while shooting at rival vehicles and counting the number of white squares that are quickly flashed against a black background. Although one can certainly argue that individuals are making use of similar underlying processes in action video games and in the psychophysical tasks (rapid object identification for instance), this argument flies in the face of the great many articles demonstrating that no transfer is observed if something as seemingly minor as spatial frequency or orientation is changed. Along a continuum of task similarity, it seems natural to consider orientation discrimination around 45° as closer to orientation discrimination around 135° than to avoiding laser blasts from spaceships.However, it is not the case that action video game experience leads to enhancements in every perceptual, attentional, and/or visuomotor skill. Furthermore, it is essential to convey the fact that not all types of video games lead to similar effects. Our work and, to some extent, the majority of the literature, has focused specifically on the effect of action video games, that is, games that are fast paced and unpredictable, require effective monitoring of the entire screen, and necessitate that decisions be made extremely rapidly. Other game types, such as puzzle games, fantasy games, or role-playing games do not have similar effects (although they may influence other types of processing).” (Green & Bavelier 2008) However, Boot and colleagues have not been able to replicate the same results, even with very similar tests. This result might suggest that transfer is really hard!  Eleven expert video game players and ten non-video game players were recruited from the Urbana-Champaign community. Participants were considered experts if they played seven or more hours of video games per week for the past two years. Non-gamers were selected such that they played video games one hour a week or less.Eighty-two college students and members of the Urbana-Champaign community participated in the longitudinal portion of the study. To maximize the likelihood of observing improvements, all participants in the longitudinal groups were non-gamers and reported playing less than one hour of video games a week over the past 2 years.Participants in the longitudinal practice groups completed fifteen game sessions in the laboratory over a period of four to five weeks. The duration of thirteen of these game sessions were 1.5 h, but the duration of the first and last session was only 1 h (the remaining .5 h of those sessions were devoted to completing a portion of the cognitive battery described later. Participants assigned to the MOH and RON groups started game practice by completing a game tutorial. Given the relative simplicity of Tetris, participants were given a brief explanation of the game but did not complete a tutorial. This schedule resulted in a total practice time of 21.5 h for each participant in each of the longitudinal gameParticipants in the control group played no video games, but were tested on all cognitive tests three times. The time between each testing session matched that of participants who were in the MOH, Tetris, or RON game groups.”Longitudinal participants (including the control group) completed a battery of cognitive tests three times : Visual and attentional task, Attentional blink, Enumeration, Multiple object tracking, Visual short-term memory, Spatial processing and spatial memory (Corsi block tapping), Mental rotation Executive control and reasoning (Task switching, Tower of London, Working memory operation span, Ravens matrices). (Boot et al 2008) But the most interesting fact about the comparison of the two studies is the comparison itself. The practice of replicating the same experiments in different laboratories is a characteristic of good science: it allows to control the hidden biases that might pass unnoticed when the same people replicate their experiment. 
  • The trouble with transfer and generalization GeneralizationThe interrogation about transfer and generalization of acquisition is not new and is not bound to video game technology. In the late ’80s it represented one of the major preoccupations of the Cognition and Technology Group at Vanderbilt, in particular in relationship to their approach called “anchored instruction” (CTGV 1990, 1992, 1992). During the '80 the Cognition and Technology Group at Vanderbilt has experimented a technology for fostering understanding of mathematical concepts by presenting them in the form of problems anchored in concrete situations (represented by the problems encountered by the hero of a series of videos: Jasper Woodbury) to be solved thank to specific mathematical tools. It was not a video game yet, but with very similar characteristics. The Group became soon aware of the problem of disentangling the mathematical solution from the concrete situation in which it was used. They thus proposed to present a number of situations with the same inner structure (and thus solution), but a different apparent surface. The result would be that of implicitly suggesting that the same solution can be applied to a number of situations, provided thy have the same structure. Unfortunately we do not seem to be good at grasping the inner structure of problems, either, since we apparently tend to stick to the surface. A striking example is represented by the following experiment:“College students were presented with the following passage about a general and a fortress (Gick and Holyoak, 1980:309). A general wishes to capture a fortress located in the center of a country. There are many roads radiating outward from the fortress. All have been mined so that while small groups of men can pass over the roads safely, a large force will detonate the mines. A full-scale direct attack is therefore impossible. The general's solution is to divide his army into small groups, send each group to the head of a different road, and have the groups converge simultaneously on the fortress. Students memorized the information in the passage and were then asked to try another task, which was to solve the following problem (Gick and Holyoak, 1980:307–308). You are a doctor faced with a patient who has a malignant tumor in his stomach. It is impossible to operate on the patient, but unless the tumor is destroyed the patient will die. There is a kind of ray that may be used to destroy the tumor. If the rays reach the tumor all at once and with sufficiently high intensity, the tumor will be destroyed, but surrounding tissue may be damaged as well. At lower intensities the rays are harmless to healthy tissue, but they will not affect the tumor either. What type of procedure might be used to destroy the tumor with the rays, and at the same time avoid destroying the healthy tissue? Few college students were able to solve this problem when left to their own devices. However, over 90 percent were able to solve the tumor problem when they were explicitly told to use information about the general and the fortress to help them. These students perceived the analogy between dividing the troops into small units and using a number of small-dose rays that each converge on the same point—the cancerous tissue. Each ray is too weak to harm tissue except at the point of convergence. Despite the relevance of the fortress problem to the tumor problem, the information was not used spontaneously—the connection between the two sets of information had to be explicitly pointed out.” (Bransford et al. 2000, p. 52) Variation upon concrete examples is thus not enough for favoring generalization and transfer: explicit information about underlying, common features between domains between which knowledge should be transferred has to be provided. In other words, learning car hardly be only implicit, and the addiction of explicit instruction that favors the understanding of the underlying structure of the problem can favor transfer, as in the following case: In one of the most famous early studies comparing the effects of "learning a procedure" with "learning with understanding," two groups of children practiced throwing darts at a target underwater (Scholckow and Judd, described in Judd, 1908; see a conceptual replication by Hendrickson and Schroeder, 1941). One group received an explanation of refraction of light, which causes the apparent location of the target to be deceptive. The other group only practiced dart throwing, without the explanation. Both groups did equally well on the practice task, which involved a target 12 inches under water. But the group that had been instructed about the abstract principle did much better when they had to transfer to a situation in which the target was under only 4 inches of water. Because they understood what they were doing, the group that had received instruction about the refraction of light could adjust their behavior to the new task.” (Bransford et al 2000, p. 44) TransferA further consideration that is crucial for the domain of education is transfer. Imagine that a small, peaceful country is being threatened by a large, belligerent neighbor. The small country is unprepared historically, temperamentally, and militarily to defend itself; however, it has among its citizens the world’s reigning chess champion. The prime minister decides that his country only chance is to outwit its aggressive neighbor. Reasoning that the chess champion is a formidable strategic thinker and a deft tactician … the prime minister asks him to assume responsibility for defending the country. Can the chess champion save his country from invasion? ” (Bruer 1993, p. 53) Apparently not. Master chess players do much better than beginners and non players at remembering configurations of chess pieces on a chess board; but when configurations are erratic and do not comply with chess rules, master players fail to overcome beginners and non players. In other words, the brain is nothing like a muscle that can would become generally more tough with training in a specific domain and knowledge tends to stick to the contents and the context for which it has been acquired: In one study, a chess master, a Class A player (good but not a master), and a novice were given 5 seconds to view a chess board position from the middle of a chess game. After 5 seconds the board was covered, and each participant attempted to reconstruct the board position on another board. This procedure was repeated for multiple trials until everyone received a perfect score. On the first trial, the master player correctly placed many more pieces than the Class A player, who in turn placed more than the novice: 16, 8, and 4, respectively.However, these results occurred only when the chess pieces were arranged in configurations that conformed to meaningful games of chess. When chess pieces were randomized and presented for 5 seconds, the recall of the chess master and Class A player were the same as the novice—they placed from 2 to 3 positions correctly. (Bransford et al. 2000, p. 23) The difficulty of transferring skills (memory skills) from one domain to another has been confirmed by several studies, e.g.: Ericsson et al. (1980) worked extensively with a college student for well over a year, increasing his capacity to remember digit strings (e.g., 982761093 …). As expected, at the outset he could remember only about seven numbers. After practice, he could remember 70 or more… How? Did he develop a general skill analogous to strengthening a "mental muscle?" No, what happened was that he learned to use his specific background knowledge to "chunk" information into meaningful groups. The student had extensive knowledge about winning times for famous track races, including the times of national and world records. For example 941003591992100 could be chunked into 94100 (9.41 seconds for 100 yards). 3591 (3 minutes, 59.1 seconds for a mile), etc. But it took the student a huge amount of practice before he could perform at his final level, and when he was tested with letter strings, he was back to remembering about seven items. (Bransford et al. 2000, p. 40) There's a logic in this apparent limitation of the brain: an infinitely malleable brain that would change a wealth of configurations for each new acquisition would risk to loose useful capacities just because of a new acquisition in a completely different domain. A certain level of modularity and segregate learning effects seem to be justified, in addition to be widely demonstrated in many studies about perceptual, motor and cognitive training.This is a serious theoretical threat to many products that are invading the market with the label of “brain training”. The brain is nothing like a muscle! It can change (functionally at least) under the effect of learning, but does not seem to become generally “stronger” at solving problems or at memorizing in virtue of repeated exercises. Expertise requires more than repeated exercises, and skills related to a certain form of expertise seem to stick to the domain of acquisition, and even to the contents of the acquisition.The limits of transfer are a big preoccupation for educators (and not only for brain trainers), because education is meaningful only when it transfers towards ecological situations – that is outside the classroom or away from the video game console: in the real life. Brain training exercises that help old people solving brain training exercises more quickly and effectively are not as interesting as exercises that help them keeping in mind the shopping list.
  • Several myths hunt the reflection on technologies and education: - the neuro-myth of the brain as a blank slate, a malleable organ that can modify itself at leisure or a muscle that can be trained for generic fitness- the techno-myth that so-called digital natives are also digital literate, digital aware users.The solution resides in adopting an evidence-based attitude that looks at empirical and theoretical research. Empirical, experimental research is the most suitable to prove the efficacy of new methods (through fair experiments with active controls, randomization); but it is not always ethical or practical to realize this kind of quantitative experiment; also, the knowledge they produce is limited and difficult to generalize. Other kinds of studies, observations and theoretical knowledge should integrate empirical evidence so as to avoid empirical pointillism and to gain in predictive power. Nonetheless, theoretical hypotheses alone are not enough if they are not constrained by facts that help choosing among alternative, conflicting explanations. Technologies in education are thus an exemplary case of the difficulties and opportunity of adopting an evidence-based approach to education grounded on knowledge about how the brain-mind works. 
  • Néanmoins, cette description ne dit rien à propos des compétences. Nous sommes tous nés dans un bain d’écriture sans que cela fasse de nous des lecteurs « naturels » et encore moins de grands écrivains à 6 ans : on apprend à lire et à écrire grâce à l’instruction.Un rapport récent produit au Royaume Uni par UCL pour la British Library et JISC a analysé de manière non systématique la littérature sur les compétences informatiques de la génération Y et conduit des études sur l’utilisation des outils de recherche par les jeunes utilisateurs ; beaucoup de mythes y sont démontés, y compris celui de la compétence : la génération Y ne sait pas nécessairement conduire une recherche sur internet de manière efficace. La fausse impression de compétence que les très jeunes enfants suscitent quand ils ont entre les mains une tablette, un ordinateur, un téléphone pourrait être l’effet du design de ces mêmes interfaces, qui sont faites pour une utilisation manuelle intuitive ; ceci pourrait aussi nous leurrer et nous faire sentir compétent alors qu’on ne l’est pas, donc nous freiner dans l’acquisition d’une compétence réelle.
  • Les technomythes qui entourent les natifs numériques s’accompagnent souvent d’autres mythes concernant la science du cerveau et notamment du mythe de la plasticité infinie et de celui du cerveau muscle. Naturellement il y a du vrai dans la plasticité et il y a du vrai dans l’idée que les entrainements modifient le cerveau. Le problème est dans l’exces: celui de penser que le cerveau n’oppose pas de résistance, n’a pas de contraintes qui font en sorte qu’on ne peut pas tout apprendre et tout faire avec notre cerveau, dans le bien comme dans le mal – dans le sens de l’augmentation ou maintien des capacités cognitives comme dans celui de leur dégradation ou diversion de ce qui constitue la nature humaine.
  • C’est tout de même vrai donc que la pratique des nouvelles technologies a un impact sur le cerveau, comme tout ce avec quoi on interagit ou qu’on apprend.Mais comment? Je dirais qu’on n’en sait pas encore assez. Aussi parce qu’il n’est pas facile d’en savoir plus. Néanmoins, craintes et espoirs, souvent excessifs, entourent les écrans. Est-ce que la génération des écrans est plus stupide, plus violente, plus dépendante, mais aussi plus intelligente, plus « multi-tâche », plus coopérative, plus autonome?Il existe des études qui cherchent à identifier qu’est-ce qu’il y a de vrai dans ces espoirs et dans ces craintes. Il est important que ces études soient conduites avec rigueur scientifique. Elles peuvent nous donner des réponses empiriques aux questions de la causalité: est-ce que tel ou autre écran telle ou autre pratique, a un impacte et lequel sur notre cerveau, nos capacités et notre comportement? Cela va nous aider à trouver des réponses à des questions de santé et de santé publique, en plus qu’avancer notre connaissance du fonctionnement cognitif. Est-ce que la génération G est plus « multi-tâche » ? S’il s’agit d’une description factuelle, c’est possible - quoique non prouvé à ma connaissance - que nous sommes amenés à faire plusieurs choses en même temps – par exemple à parler au téléphone et conduire. Mais notre cerveau est essentiellement sériel : faire deux choses en même temps comporte une perte d’efficacité, car le cerveau passe de l’une à l’autre rapidement mais ne les mène pas en même tempsDes études existent sur la relation entre pratique des jeux vidéo ou « brain training » et différents aspects de la cognition, notamment attention et mémoire. Trois problèmes existent avec ces études : elles sont souvent corrélationnelles et non causales ; même quand on peut mettre en évidence des améliorations des performances, celles-ci ne se transfèrent pas nécessairement et de manière significative aux tâches complexes de la vie réelle ou même à des tâches proches de laboratoire qui mesurent les capacités cognitives ; en plus elles ne sont pas valables pour toute forme de technologie. On sait par ailleurs que les capacités cognitives sont fortement compartimentées et que les nouvelles compétences, non seulement les connaissances, sont difficiles à transférer d’un domaine à un autre : le cerveau n’est pas un muscle. La recherche sur l’entrainement des capacités est donc au cas par cas. Toute assertion trop générale risque donc d’être fausse.C’est le cas aussi pour d’autres controverses, comme celle sur la violence ou la dépendance des écrans. Ces questions nécessitent d’études empiriques, mais ces études ne sont pas faciles à conduire ni à interpréter, d’où des controverses à mon opinion réelles. Ces considérations sont aussi valables pour les craintes concernant la dégradation des capacités cognitives. Est-ce que Google nous rend stupides ? C’est le titre d’un livre où l’auteur, un journaliste, décrit avec horreur sa nouvelle incapacité de lire un livre ou un article de bout en comble, sans sauter ou s’interrompre. Il attribue cette détérioration non pas à l’âge, mais à sa pratique d’Internet qui aurait changé son cerveau, le re-câblant pour une différente forme de lecture.
  • Il existeplusieursétudessur la dépendance des jeux et sur la violence, tout commesur les effetscognitifs ‘bénéfiques” des jeuxvidéoou des entrainementscérébraux. Souventcesétudessontpartielles, ourencontrent des difficultésméthodologiques. Au total il ne s’agit pas d’études pour lesquelles on peut dire qu’ilexiste un consensus arrêté. Dans le cas de l’addiction, par exemple, ilmanqueunedéfinition unique et standardisée qui permettrait de comparer les différentesétudesexistantes. Le manuelpsychiatrique ne contient pas une entrée pour les “cyberadditctions”, mêmesiceci a étépris en considération. Il contiendradanssanovuelle version une entrée sur le jeupathologique, le jeud’argent, première addiction comportamentale et non chimiqueà faire son entrée dans le manuel. Un deuxièmeproblème avec la notion d’addiction au jeuouà Internet résidedans son étiologie et sesmécanismespathophysiologiques, qu’on ne connait pas pour les addictions sans substance. On parle du circuit de la récompense, mais beaucoup resteà faire pour comprendre son fonctionnement. Enfin, ilexiste des problèmesméthodologiquesdans les étudessur violence et sur les effetsbénéfiques des jeuxvidéo, notammentliés au problèmed’établir la causalité entre activité de jeu et seseffets – et de la distinguerd’une simple corrélation.
  • Ces études ne sont pas encore concluants, mais même s’ils l’étaient ils ne seraient pas suffisantes. Car elles ne permettent pas de comprendre pourquoi nous tenons un certain comportement avec les écrans, quels sont les risques et les atouts par rapport à notre fonctionnement cognitif normal: pourquoi on les aime tant? Pourquoi on aime les spectacles violents? Est-ce qu’on peut faire plusieurs choses en même temps, est-ce que les écrans bouffent notre attention? Comment se protéger de ça? Comment mettre à profit les outils technologiques de nos limites cognitives?

Transcript

  • 1. Teaching and learning in the era of digital technologies TECHNOLOGIES IN EDUCATION EVIDENCE-BASED ATTITUDE NEURO- & TECHNO-MYTHS
  • 2. Large use of technologies in teaching and learning • In formal teaching contexts • In semi-formal • Informal contexts How does it change education? More specifically…
  • 3. 1. The digital revolution What should we call these “new” students of today? Some refer to them as the N-[for Net]-gen or D-[for digital]-gen. But the most useful designation I have found for them is Digital Natives. Our students today are all “native speakers” of the digital language of computers, video games and the Internet. So what does that make the rest of us? Those of us who were not born into the digital world but have, at some later point in our lives, become fascinated by and adopted many or most aspects of the new technology are, and always will be compared to them, Digital Immigrants.
  • 4. Today’s students have not just changed incrementally from those of the past, nor simply changed their slang, clothes, body adornments, or styles, as has happened between generations previously. A really big discontinuity has taken place. Computer games, email, the Internet, cell phones and instant messaging are integral parts of their lives. It is now clear that as a result of this ubiquitous environment and the sheer volume of their interaction with it, today’s students think and process information fundamentally differently from their predecessors. These differences go far further and deeper than most educators suspect or realize. (Prensky 2001)
  • 5. Established and internationally accepted definitions of digital literacy are generally built on three principles: - the skills and knowledge to use a variety of digital media software applications and hardware devices, such as a computer, a mobile phone, and Internet technology; - the ability to critically understand digital media content and applications; And - the knowledge and capacity to create with digital technology. (Media Awareness Network Canada)
  • 6. 2. Teaching machines • • • • • • • • 1900: Educational film 1924: Teaching Machines(Pressey) 1954: Teaching Machines (Skinner) 1966: Sesame Street 1967: Logo Turtles (Papert) 1970s-1990s: Computer based training/learning CBT/L 1970s-1990s: Computer aided instruction CAT E-learning
  • 7. 3. Technology-inspired education 36 good learning principles embedded in video games (Gee 2005)
  • 8. Will video games change the way we learn? We argue here for a particular view of games—and of learning—as activities that are most powerful when they are personally meaningful, experiential, social, and epistemological all at the same time. From this perspective, we describe an approach to the design of learning environments that builds on the educational properties of games, but deeply grounds them within a theory of learning appropriate for an age marked by the power of new technologies. We argue that to understand the future of learning, we have to look beyond schools to the emerging arena of video games. We suggest that video games matter because they present players with simulated worlds: worlds which, if well constructed, are not just about facts or isolated skills, but embody particular social practices. Video games thus make it possible for players to participate in valued communities of practice and as a result develop the ways of thinking that organize those practices. (Shaffer, Squire, Halverson, Gee 2004) Simulation of worlds
  • 9. • • • playing is intrinsically motivating, because one plays for the fun of it and not because one has to. – contradiction: even if games are for fun, if one has to play a game for learning, the game is no more just for fun. playing makes learning fun and effortless – opposed to school learning, which is considered as boring and effortful – Unfair comparison: the kind of learning that is proposed at school can hardly not be effortful because it concerns skills that do not come naturally to us good games are motivating because they are concrete, multimodal, interactive, and involve the player learner in first person actions Motivation
  • 10. Teaching and learning in the era of digital technologies TECHNOLOGIES IN EDUCATION EVIDENCE-BASED ATTITUDE NEURO- & TECHNO-MYTHS
  • 11. How do we know IT works?
  • 12. Fair evaluation of effects – Theoretical understanding of the principles (and limits) – Empirical, experimental evaluation of the effects
  • 13. • Causality vs correlation – (Rosser et al, 2007)
  • 14. • Equivalence between experimental and control group – (Gopher 1994)
  • 15. • Active controls – (Robertson 2009)
  • 16. • Expected effect – (Owen et al 2010)
  • 17. • Polarized, ideological debates & the power of anecdotes - Literature on media violence and cyber-addiction
  • 18. • Undue interpretation of experimental and correlational studies, or: don’t rush to conclusions - Literature on media violence and cyber-addiction
  • 19. Case study: Evidence about effects on cognitive performances & learning • • • Cognitive training in the elderly: memory, problem solving, rapid visual identification – Ball et al. 2002 Alzheimer – Papp et al 2009 Brain Training – Owen et al 2010 – Bavelier, Green & Dye 2011
  • 20. • Video-games & Visuo-spatial attention – Green & Bavelier 2008 – Bavelier, Green & Dye 2010 – Boot et al 2008 – Boot et al 2011
  • 21. The trouble with transfer and generalization
  • 22. In one of the most famous early studies comparing the effects of "learning a procedure" with "learning with understanding," two groups of children practiced throwing darts at a target underwater (Scholckow and Judd, described in Judd, 1908; see a conceptual replication by Hendrickson and Schroeder, 1941). One group received an explanation of refraction of light, which causes the apparent location of the target to be deceptive. The other group only practiced dart throwing, without the explanation. Both groups did equally well on the practice task, which involved a target 12 inches under water. But the group that had been instructed about the abstract principle did much better when they had to transfer to a situation in which the target was under only 4 inches of water. Because they understood what they were doing, the group that had received instruction about the refraction of light could adjust their behavior to the new task. (Bransford et al 2000, p. 44)
  • 23. A general wishes to capture a fortress located in the center of a country. There are many roads radiating outward from the fortress. All have been mined so that while small groups of men can pass over the roads safely, a large force will detonate the mines. A full-scale direct attack is therefore impossible. The general's solution is to divide his army into small groups, send each group to the head of a different road, and have the groups converge simultaneously on the fortress. Students memorized the information in the passage and were then asked to try another task, which was to solve the following problem You are a doctor faced with a patient who has a malignant tumor in his stomach. It is impossible to operate on the patient, but unless the tumor is destroyed the patient will die. There is a kind of ray that may be used to destroy the tumor. If the rays reach the tumor all at once and with sufficiently high intensity, the tumor will be destroyed, but surrounding tissue may be damaged as well. At lower intensities the rays are harmless to healthy tissue, but they will not affect the tumor either. What type of procedure might be used to destroy the tumor with the rays, and at the same time avoid destroying the healthy tissue? Bransford et al. 2000, p. 52
  • 24. In one study, a chess master, a Class A player (good but not a master), and a novice were given 5 seconds to view a chess board position from the middle of a chess game. After 5 seconds the board was covered, and each participant attempted to reconstruct the board position on another board. This procedure was repeated for multiple trials until everyone received a perfect score. On the first trial, the master player correctly placed many more pieces than the Class A player, who in turn placed more than the novice: 16, 8, and 4, respectively. However, the se results occurred only when the chess pieces were arranged in configurations that conformed to meaningful games of chess. When chess pieces were randomized and presented for 5 seconds, the recall of the chess master and Class A player were the same as the novice—they placed from 2 to 3 positions correctly. (Bransford et al. 2000, p. 23)
  • 25. • “Ericsson et al. (1980) worked extensively with a college student for well over a year, increasing his capacity to remember digit strings (e.g., 982761093 …). As expected, at the outset he could remember only about seven numbers. After practice, he could remember 70 or more… How? Did he develop a general skill analogous to strengthening a "mental muscle?" No, what happened was that he learned to use his specific background knowledge to "chunk" information into meaningful groups. The student had extensive knowledge about winning times for famous track races, including the times of national and world records. For example 941003591992100 could be chunked into 94100 (9.41 seconds for 100 yards). 3591 (3 minutes, 59.1 seconds for a mile), etc. But it took the student a huge amount of practice before he could perform at his final level, and when he was tested with letter strings, he was back to remembering about seven items.” (Bransford et al. 2000, p. 40)
  • 26. Concrete cases and variation is important but probably not enough
  • 27. • • There's a logic in this apparent limitation of the brain – an infinitely malleable brain that would change a wealth of configurations for each new acquisition would risk to loose useful capacities just because of a new acquisition in a completely different domain – A certain level of modularity and segregate learning effects seem to be justified, in addition to be widely demonstrated in many studies about perceptual, motor and cognitive training. The limits of transfer are a big preoccupation for educators – education is meaningful only when it transfers towards ecological situations – that is outside the classroom or away from the video game console: in the real life
  • 28. Teaching and learning in the era of digital technologies TECHNOLOGIES IN EDUCATION EVIDENCE-BASED ATTITUDE NEURO- & TECHNO-MYTHS
  • 29. Is technology making us more stupid/ intelligent? • Carr 2008 "Dave, stop. Stop, will you? Stop, Dave. Will you stop, Dave?” So the supercomputer HAL pleads with the implacable astronaut Dave Bowman in a famous and weirdly poignant scene toward the end of Stanley Kubrick’s 2001: A Space Odyssey… “Dave, my mind is going,” HAL says, forlornly. “I can feel it. I can feel it.” I can feel it, too. Over the past few years I’ve had an uncomfortable sense that someone, or something, has been tinkering with my brain, remapping the neural circuitry, reprogramming the memory. My mind isn’t going—so far as I can tell—but it’s changing. I’m not thinking the way I used to think. I can feel it most strongly when I’m reading.
  • 30. Is technology making us more stupid/ intelligent? Chabris & Simon 2010 The alarmists cite the concept of "neural plasticity" and talk of technology "rewiring" the brain to convince us that the new distractions make us not just less willing but less able, on a physiological level, to focus. ….The appeals to neural plasticity, backed by studies showing that traumatic injuries can reorganize the brain, are largely irrelevant. The basic plan of the brain's "wiring" is determined by genetic programs and biochemical interactions that do most of their work long before a child discovers Facebook and Twitter. There is simply no experimental evidence to show that living with new technologies fundamentally changes brain organization in a way that affects one's ability to focus. Of course, the brain changes any time we form a memory or learn a new skill, but new skills build on our existing capacities without fundamentally changing them. We will no more lose our ability to pay attention than we will lose our ability to listen, see or speak.
  • 31. Technomyths: Digital natives = digital competents Digital natives = mutants
  • 32. Neuro-myths: The infinitely plastic brain The brain as a muscle
  • 33. CRAINTES ET ESPOIRS
  • 34. ETUDES EMPIRIQUES Addiction Violence Apprentissage Entrainement cognitif
  • 35. MIEUX COMPRENDRE POUR MIEUX TIRER PARTI