Tuesday, February 28, 2017

Fake News: Spinning and Winning

Fake News: Spinning and Winning
“Truth crushed to earth, shall rise again” (William Cullen Bryant)

In Nelson Goodman’s (1954), Fact Fiction and Forecast, the notion of projectible predication arises to differentiate hypotheses based on regularities well grounded in experience and those which are not. There is a parallel treatment of counterfactuals (If X, then Y, and not-x, as in “If this thing in my hand was made of copper, it would conduct electricity but it is actually a wooden popsicle stick”) involving relationships well-grounded in experience and those which are not. What might we say about facts, fictions, and forecasts, in educational research or in the current political climate?

What are some facts in the area of educational research? A study by the 2014 Program for the International Assessment of Adult Competencies (PIAAC) involving 33 countries shows that 7 of those countries scored significantly higher on a literacy scale and six scored significant lower (measured understanding, evaluating, using and engaging with written text) than the USA and the USA was slightly below the average (see https://nces.ed.gov/fastfacts/display.asp?id=69).
Here is an associated counterfactual claim: If an adult person M (say that is me – an American) is a lifelong resident of Japan, then M is more likely to be literate than N (where N is an adult American picked at random). Is that counterfactual claim reasonable?

Here is another claim supported by extensive educational research: Directive feedback (providing corrective information) tends to work well with learners new to a topic or domain whereas facilitative feedback (providing guidance and cues) tends to work well with more advanced learners (Shute, 2007; see https://www.ets.org/Media/Research/pdf/RR-07-11.pdf). Now, suppose that P is a learner new to the domain of logic and epistemology (me, for instance – my dissertation was in that area) and someone claims that P is more likely to benefit from directive feedback in the area of logic than Q (a middle school student in rural Alabama). Is that a reasonable claim?

One way to treat counterfactuals (IF-Then claims with the IF-clause clearly false) is to dismiss them as trivial or even meaningless. Yet some seem to make sense to some people. Other counterfactuals can be used to make jokes as in: “If I knew everything, then I would know _______________ .” I forgot to mention that this was a pop quiz. How did you fill in the blank? I used this phrase: “… then I would know where parallel lines meet.” Math humor is not so humorous to very many people.

On to fictions. I just love fictions. Sometimes I think about my training in philosophy … one of my professors said that the never-ending business of philosophy was to help us understand the boundaries between sense and nonsense. My own take on philosophy is that it is a kind of thought in slow motion. Fictions – claims that do not hold up under scrutiny. Scrutiny is when you close one eye and take a closer look for those of you taking notes. There are some blatant fictions as this one I discovered in a book on medieval logic: “I just ate the last cannibal” spoken in a group of monks who had taken vows of silence. Bouwsma’s (one of my professors) example was this: “I just suffered a fatal heart attack.”

There are many less blatant fictions. Here is one: “Humans only came to the Grand Canyon area about 4,000 years ago.” Here is another one: “All of the fossils found in the Burgess Shale in the Canadian Rockies were fossils of creatures still living somewhere.” Consider this one: “There is no evidence that human activities contribute to climate change.” Some people believe what they want to believe and are reluctant to take a closer look at evidence or consider alternative perspectives or beliefs. There is a difference between advocacy for something and evidence supporting something. A critical issue concerns the nature of good and compelling evidence. Just as there is a fuzzy boundary between sense and nonsense, the boundary between advocacy and research is somewhat fuzzy. 

Just as counterfactuals turn out to be somewhat problematic, there is another kind of IF-THEN claim that is also problematic. I call it an unconditional conditional and it has the general form of If X, then Y, where no matter what is put in for X the person making the unconditional conditional claim will maintain the truth of Y. No refutation of the unconditional conditional is considered possible. In such a case, one cannot conclude that Y is a fiction … one can only walk away from the unreasonable challenge of the advocate of the unconditional conditional in trying to offer evidence that Y or the unconditional conditional with Y as the then-clause may not be true. 

Does this ever happen in educational research? In medical research? In political discourse? The challenge of finding examples in each of those categories is left to the reader – this is the mid-term exam. Hint – the answer to the first set of three questions  is ‘yes’ – this does not constitute timely nor informative feedback. It is merely encouragement to keep on keeping’ on.
When you have completed the mid-term exam, you may want to continue on to forecasts. My forecast is that some of you will pass the mid-term. After all, it was a take-home exam … or take-to-the-bathroom exam.

Having said a few things about IF-THEN claims, it seems natural to apply some of that discussion to forecasts, as these often come in the form of complex IF-THEN statements, such as:” “If W, and X and Y, then Z” – W might refer to the learning or instructional context and X might refer to the students or teachers and Y might refer to the intervention or treatment. Obviously, each of the parts of the complex IF clause could be compound, which means that the forecast result Z depends  on a conjunction of a set of contributing factors. If Z does not occur, the advocate of Z is likely to look for one or more deficiencies in the set of contributing factors. Another approach is to construct a replication study or a revised version to see if Z might occur. Yet another approach is to revise Z and conduct a replication study. Forecasting or predicting and then confirming or refuting or refining is not easy … it is what scientists and meteorologists and other investigators are trained to do. 

I have a vague memory of reading Fact, Fiction and Forecast about 45 years ago. I was fascinated by the concept of the hypothetical predicate ‘grue’ for things that are green before some future date and blue after that date. At this time, ‘all emeralds are green’ and 'all emeralds are grue’ are both true and confirmed by the same evidence. However, few believe that after that future date that emeralds will all be blue. I also realized that I did not understand what a meteorologist meant by a forecast of 40% chance of rain. Was it that 40% of the area covered by the forecast would surely receive rain, or that any random spot in the forecast area would have a 40% chance of rain or that it will rain 40% of the day or ??? Forecasting still bewilders me. I recall a sports enthusiast being asked to predict the outcome of an event about to begin. The sports enthusiast replied “Let’s just watch and see what happens.” My respect for sports enthusiasts rose significantly that day.

I suppose we need a final exam since we have had a pop quiz and a mid-term exam. The final exam is a single multiple choice question:

Which of the following statements is true?
  1. There is someone in this room who loves all and only those persons in this room who do not love themselves.
  2. Never in the course of human history have events so resembled the present as they now do.
  3. It is a fact that X leaked Y but that fact is fake news
  4. There are an even number of planets in the Milky Way galaxy
  5. If X is a human being, then X knows less than X is typically inclined to believe that X knows.
  6.  More than one of the above is true
  7. More than one of the above is false.
 Truth? What is truth? I will go where you go, answered Ruth. My trumpet is louder than yours so follow me said someone else. The truth they are telling might only be the truth that is selling. And the slow one now will later be fast said the Nobel laureate.

Sunday, January 15, 2017

So much beauty ... so little ...

So much beauty, so much tragedy, so much nonsense …what shall we make of it all?

From CNN - Myanmar's Mergui Archipelago

Lake Louise in Canada:
My own picture taken in Bali in 2016:

And another  one of LA (Lower Alabama) coast at sunset:

I have been so fortunate to see so much natural beauty in so many different places.

Then I think about the beautiful people I have known – especially my children and grandchildren and their spouses. So many acts of kindness and understanding I have witnessed through them – makes me want to be  more kind and understanding.

I need to have these thoughts of beauty when I think about so many tragedies in so many places, from Aleppo to Haiti and too many other places to mention, many of which are closer to home. Natural tragedies such as hurricanes and earthquakes are beyond our control, but many tragedies are within our spheres of influence, yet they continue to occur, in my own country and elsewhere around the world.

Like Lawrence Ferlinghetti, I am waiting (see https://www.poetryfoundation.org/poems-and-poets/poems/detail/42869) – seems it has been a long time coming … and a lot of waiting for that rebirth of wonder … seems we may have to wait another 4 or 8 years or more … but we should do more than wait. Hope is not enough, either. What can one do? One can find another and create a small place in which wonder can be reborn. Or maybe it takes more than two?

Learning Context

What constitutes a learning context and why should we care?

It is a reasonably well-established view that context is in large part what determines the meaning of an utterance. Context – or more specifically, use, which occurs in a context - in part determines meaning (see https://plato.stanford.edu/entries/pragmatics/ for an elaboration). The point is that use and context are critical factors in determining the meaning of what someone has said. Likewise, the use and context are critical factors in determining whether, how and why learning might or might not be occurring in a particular situation. So, to determine if meaningful learning is or is not occurring or likely to occur, one needs to consider the learning context and what the learner might be doing or not be doing in that situation.

The simple approach to providing a description of a learning context is to indicate what is around the learner during a learning activity. It might be other learners, a teacher, a book, and a computer as in a typical classroom setting, or it could be music playing in a coffee shop with other people around who may or may not be learners, or it could be many other situations in which learning is intended to occur.

However, simply describing what is around a learner falls short of providing a good or complete understanding of a learning context. What the learner is doing or might do is also relevant. If the learning situation happens to be in a coffee shop with music playing, then a learner is not likely to benefit much from an audio or audio-video file played on that learner’s laptop computer. The coffee shop situation does not provide effective affordance or support for audio-based learning. Likewise, in a classroom setting, if the learner is working with a small group of students who are busy chatting on their smartphones, that context might have too many distractions to support learning to solve a complex problem, unless the chatting happens to be about that problem and is providing some insights about what to do.

The point I am trying to make is quite simple. When describing a learning context, it is reasonable to include all of the things that a learner can touch (or see or hear or smell or taste) as well as all of the things that can touch the learner. In addition, just as the speaker is part of the context when it comes to determining the meaning of what is said, the learner is part of the context when it comes to understanding to what extent (and why) meaningful learning might be occurring.

Of course what is to be learned is part of the learning context as well. What is to be learned includes the general topic, the level of understanding sought, as well as the specific knowledge, skills and attitudes that are part of the learning goal and expected outcomes. 

Tuesday, January 10, 2017

The More Things Are Called Smart …

It used to be the case that there were a few people one might call smart. Now, we call phones smart, whiteboards smart, computer programs smart, learning environments smart, technologies smart, and even automobiles and cities smart. What has become of the meaning of the descriptive adjective ‘smart’?

What I really crave is a smart chocolate ice cream cone. I suppose someone has an answer for that as well … perhaps one that has no sugar, no calories, and no reason to ask for seconds. I am wondering about the meaning of ‘smart’ because I was asked about it in a meeting with faculty and graduate students in the Educational Technology Department in the Institute of Education at Tsinghua University in Beijing.

Perhaps the location of an educational technology program within a university reflects or influences how ‘smart’ is conceptualized. One can find educational technology programs in a college or faculty of education, or in a college or faculty of information, or information science, and even in an arts and sciences college or faculty. In an education college or faculty, one might imagine the emphasis to be on technologies that can be used to make people smarter. In a college of information or information science, one might imagine the emphasis to be on devices and technologies that did things that people who used to be called smart used to do. It would be an interesting exercise for someone to look at where educational technologies were located within a university structure, the various emphasizes and perspectives reflected in those programs, and any patterns or correlations that might emerge from those data.

My own views are shaped by my experience – first with philosophy and later with computer science. My philosophy perspective is based in skepticism (e.g., recognizing the limits of knowledge and the ease with which we are inclined to believe we know more than we actually know or believe that the world happens to conform to the limits of our knowledge) while my computer science perspective is based on artificial intelligence and expert systems. I have seen the word ‘smart’ used quite differently in both of those contexts.

I would consider Socrates smart, for example. He would elicit ideas about such things as justice and virtue from the sophists and show that their beliefs led to contradictions or absurd conclusions, such as a virtuous ruler as one who manages to squeeze the most work and highest taxes from citizens, applying the notion of virtue as that which benefits the stronger – with the conclusion that what is good for one is not necessarily good for another. I was fascinated early in life by the logic of such an indirect proof. I had also seen it used in mathematics, as in the common proof that pi is an irrational number – assume it is rational and then step by step one arrives at a contradiction which means the point of departure was not sound. Pi must be irrational – aren’t we all from time to time?

And then to earn a living, I took up computer science and became fascinated with expert systems and the representation of human expertise in software programs. I was attracted to complexity and the notion that somehow software might be able to extend the ability of people to deal with complexity, which could be conceived as a way of making those persons smarter – able to perform more like experts.

One vivid memory I have of my time as a practicing computer scientist involved being responsible for some 400 plus programs written in Assembly Language and Fortran running simultaneously on five different computers, four were 32-bit Perkin-Elmer mini-computers and the fifth was a 30-bit graphics computer. The application was real-time simulations of air combat training. One task I had was to add software tracking of the sun’s position along with a number of fighter jets that would simulate firing air-to-air missiles at enemy aircraft and record probable hits and misses and then debrief the pilots after the exercise. The task was to show the pilots the location of the sun in their cockpit views when they fired a heat-seeking missile, as it would go after the sun and miss the target. Getting that simple change to work proved a very complex and challenging task. I got stuck trying to make it work as every time I thought I had it figured out, the software would crash (in simulated runs rather than in actual exercises – we always made sure the software would work before using it in live exercises).

After a week of pondering over the crashes and narrowing the logic failure to a few lines of code among the thousands of lines involved, my mentor and a senior programmer (Walt Davis) advised me to make a single random change in those few lines and see what happens. He also could not see a problem with the logic and agreed the problem had to be among those lines of code. The change I settled on was to reload a memory location with the same doubleword that was just loaded in the previous line of code – yes, that was in Assembly Language. Unbelievably, the change solved the problem. What I had thought had to be a problem with the logic proved to be a timing problem. By reloading that register with the same information, the other programs running in parallel had time to catch up and do their tasks. Walt was smart. He did not know what was wrong but he knew I needed to get more information, and making one small change was a way to start getting more information.

Perhaps a smart computer processing system would have suggested a similar change, but I have yet to see such a system perform with the smartness of a Walt Davis. I suppose that might become possible at some point.

Back to my point – what is with all these uses of the word ‘smart’. Is it not hard enough to identify a smart person much less identify which devices are smart or which are only being called smart so as to improve sales. Some leaders and leaders to be call themselves smart. The sophists with whom Socrates interacted called themselves smart. Self-attribution of smartness seems to be a likely indication of lack of smartness.

At least devices are not yet able to call themselves smart. Yes, that will probably happen at some point. But then I recall Bob Gagné’s advice to me while working together at the Air Force Armstrong Laboratory in San Antonio. He said, “our job is to help people learn – to help them become smarter … better at solving problems.” Oh yes. We might even be able to use various devices and techniques in doing that all important job.

Friday, December 30, 2016

Last Day of the Year Ideas

I am at Beijing Normal University’s Smart Learning Institute (SLI) as I make these notes on the last day of the year of 2016. Among other things, I am working on an introductory textbook on advanced learning technologies and advising on a number of SLI projects and efforts.

This is typically a time for reflection and making plans for a brighter future. My reflections are more dark than I dare admit as they are focused mainly on the undemocratic election of an incoming President in the USA and all of the ugliness and bitterness that occurred during that process. I occasionally think about global issues beyond the boundaries of the world’s most spoiled nation – for example, such things as 2016 being the warmest year on record worldwide and the many tragedies that occurred in various places (e.g., Hurricane Matthew in Haiti, the siege of Aleppo, etc.). I vaguely remember a song by the Kingston Trio from my youth called “The Merry Minuet” ( see the lyrics at this URL: http://www.oldielyrics.com/lyrics/the_kingston_trio/the_merry_minuet.html). 

Remembering that Kingston Trio song brought back the memory of another song – Malvina Reynolds’ “Little Boxes” – see https://www.douban.com/note/221995170/. Too much negativity (as in the Presidential campaign of the person who was elected while losing the popular vote) – better to recall the song “Simple Gifts” – see http://www.musicnotes.net/SONGS/05-SIMPL.html and sung so beautifully by Judy Colllins – see https://www.youtube.com/watch?v=kWTDgc96bg8 .

Enough reflection – on to preflection – thinking about the future in this case – specifically about the future of smart learning and advanced learning technologies. Advanced? What counts as advanced? Something new? Not a good criterion. There are too many new things and not all of them represent improvements. With regard to technologies in support of learning and instruction, what would count as an advance would be a technology that provided significant and sustained improvement on a large scale for many in a variety of learning and instructional contexts. There have not been many such advances over the years of investing in educational technology. Not many. Which ones come to mind? Then ask, were improvements significant, sustained and attained on a large scale? What remains? Perhaps Sesame Street. What else?

Smart technologies? Smart? What counts as smart? It is hard enough to identify a smart person. Some people claim to be smart – the incoming President, for example. Well, I have known a few people whom I would call really smart and none of them would dare call themselves smart. For example, Bob Gagné is one. His memory was amazing. He could recall the entire text of Edgar Allan Poe’s “The Raven” (see http://www.houseofusher.net/raven.html) from memory. When I asked him if he had to memorize it for a course, he said no. When he met Pat, the woman he later married, he went to the library to read about love and found that poem and he was able to recall it verbatim some 50 years later. He also remembered a children’s German song that he was able to recite when introduced to a German colleague of mine – a song he had learned 50 or so years earlier when studying German as an undergraduate. There are many other examples of his amazing ability to remember things and people that add to his many accomplishments in the area of educational research. He was smart, but he never boasted about being smart, at least not to my knowledge.

Think about a person you consider smart. Then think about the characteristics of that person and why you consider her or him to be smart. Is it due to that person’s memory? Analytical abilities? Creativity? What makes a smart person smart? I am not sure, but I have two ideas. One is based on a hierarchy of things that begins with data at a low level, and then up to information (structured data) at a higher level, and then to knowledge (rules and principles connecting various kinds of information) at a still higher level, and then to wisdom (e.g., the ability to apply or choose not to apply knowledge in various circumstances and perhaps even to create new knowledge in the form on new rules and principles). Who among us in wise?

My father was wise – or at least that is what I would say. He was a Rabbi and he came from a long line of Rabbis. He never pressed me to become a Rabbi although at one time that was expected. He told me that a Rabbi was a teacher, and a teacher was the voice that encourages, the ear that listens, the eye that reflects, the hand that guides, the face that does not turn away … and I saw him practice those abilities in many situations and came to believe that I could not meet his standards.

The other idea I have about being or becoming smart is that it is the result of disciplined inquiry – first one asks a question, then one becomes preoccupied with having that and subsequent questions. To have a question is to admit that one does not understand, to commit time and effort (a lot of time and serious effort) to finding answers, to be willing to explore alternative explanations and answers, and to question one’s assumptions.

It is now quite popular to talk about edutainment – mixing education with entertainment. I see very limited potential for advancements in learning based on edutainment. My notion can be called edunishment – a mixture of education and punishment. The punishment is in the form of things one gives up in order to attain very high levels of understanding and expertise. Sustained and focused inquiry takes a great deal of time and effort and may leave little time for the things that so many others enjoy. The joy then has to be in attaining understanding and insight. 

I am now reminding myself of T. S. Eliot’s “Chrouses from the Rock” and these lines: “The endless cycle of idea and action, Endless invention, endless experiment, Brings knowledge of motion, but not of stillness; Knowledge of speech, but not of silence … The things that men count for happiness, seeking The good deeds that lead to obscurity, accepting With equal face those that bring ignominy, The applause of all or the love of none. All men are ready to invest their money But most expect dividends. I say to you:  Make perfect your will. I say:  take no thought of the harvest, But only of proper sowing.” (see the entire poem written in 1934 at http://courseweb.ischool.illinois.edu/~katewill/spring2011 502/502%20and%20other%20readings/eliot%20choruses_from_the_rock.pdf – some think only of the dividends, recalling the recent election, but others think of something more meaningful – such as can be found in many of the songs of the year’s Nobel Prize Winner in Literature – Bob Dylan – see http://www.azlyrics.com/d/dylan.html and especially the lyrics to “The Ballad of Frankie Lee and Judas Priest” including these ending lines – “Well, the moral of the story The moral of the song Is simply that one should never be Where ones does not belong So when you see your neighbor carryin' somethin' Help him with his load And don't go mistaking Paradise For that home across the road.”

The message for the advocates of emerging educational technologies – “don’t go mistaking paradise for that home across the road.” It’s about the learning – not the technology.

Well, that is all by way of a prologue and a foundation for thinking about an advanced learning technology. I call this idea the Buddy Pack. It is a kind of back pack but typically meant to be in front rather than on one’s back. It is aimed at kids between the ages of 3 and 10 – the developing years … the years when a basis for inquiry can be established but rarely is. The Buddy Pack has embedded technologies that enable it to perform as a kind of companion – a carry along buddy to provide information, give guidance, and even ask questions from time to time.

v  Buddy Pack Characteristics and Features

Ø  can be worn as a front pack or as a back pack as it has shoulder straps but also slips over the head
Ø  is waterproof since it contains some electronics
Ø  is in the shape of an endangered animal (e.g., a panda, a tiger, a dodo bird, etc.)
Ø  has two digital cameras, one on the front and one on the back
Ø  has built-in speakers nears the top (near the ears) and a built-in microphone so as to support two-way communication with the child
Ø  has databases covering many general topics (e.g., world geography, world history, history of science, animals of the world, plant life, human anatomy, and so on)
Ø  has built-in WiFi that facilitates communication with larger data repositories as well as communication with parents and friends
Ø  has a fold out keyboard and input device with a touchscreen to facilitate the kind of capability available on a tablet device
Ø  has the ability to automatically call for help with a simple mechanism
Ø  has face and fingerprint recognition of the child and parents for security purposes
Ø  has the ability to be put into quiet mode at night, on an airplane or in a move theater
Ø  has built-in GPS so that it knows where the child is, can tell the child about the location, and the parents can locate the child if necessary
Ø  has a solar panel on the top back to keep the battery charged when outdoors

All of the technologies to support the Buddy Pack exist. There is some evidence that a companion technology can impact early learning. Perhaps such a device is worth exploring. Perhaps. I want one. I want mine to be in the shape of a gorilla. 

Have a Happy New 2017

Monday, November 7, 2016

No Citizen Left Behind

On this election eve, I am no longer willing to watch television and the campaign advertisements. I voted early, but I am still quite concerned about the election and what happens afterwards.

It is not the best of times nor the worst of times. It is perhaps the least thoughtful of times. It is the Alt-Right waging war against socialists. The tea and beer party against the wine and cheese party. What happens afterwards?

I recall a war waged in my discipline (instructional design and technology) between those who favored direct instruction and those who favored discovery learning. 

That war is being abandoned by a more pragmatic approach that favors what works for whom in which circumstances. Sometimes, for some learners, some learning tasks and some situations, direct instruction is effective and efficient. On other occasions, for some learners, learning tasks and learning situations, discovery learning is effective and even efficient given an appropriate time perspective. What matters is supporting every learner (and teachers) in every different learning situation. What matters is what works and not what ism one invokes.

What is needed afterwards is a set of common goals and shared values. It should be possible to identify a few of these. Some of these might involve national aspirations. For example, the USA  might aspire to have the lowest infant mortality rate – right now we are about 46th – far from the lowest – see http://www.infoplease.com/ipa/A0934744.html

Or, we might aspire to be number one in terms of longevity – we are  not even in the top ten today – see http://www.infoplease.com/ipa/A0934744.html

Or we might agree to lower the rate of illiteracy in the USA – now about one in five adults in the USA cannot read at a 5th grade level. One in five! 

Well, the USA is in the top ten with regard to spending per capita on defense – see https://en.wikipedia.org/wiki/List_of_countries_by_military_expenditure_per_capita.

If we were to agree to a few common goals and then agree to the general principle of not leaving anyone behind or out, then the healing could begin. When has that ever happened, I wonder? I hope someone has an answer.

J. Michael Spector
Election eve, 2016

J. Michael Spector, Ph.D.
Professor, Department of Learning Technologies
College of Information, University of North Texas
3940 N. Elm St., G150, Denton, TX 76207   USA
TEL +1 940 369 5070 / +1 706 202 9350 / FAX +1 940 565 4194

Wednesday, August 17, 2016

the impact of technology vs. the impact of using technology

I have been working in the area of assessing progress of learning in complex problem-solving domains for almost 20 years now (not much progress I am embarrassed to admit), and I have also doing evaluations of university programs, grant projects and large European networks of excellence for about 15 years. In both cases, I have come to the conclusion that it is formative assessment (of learners) and formative evaluation (of programs, projects, and products) that matters most. The primary goal is to help students progress and develop and to help programs and projects achieve their intended goals and objectives. Secondary goals include reporting the extent of progress and success.

In addition, I have been speaking at numerous venues on emerging educational technologies and have come to adopt the mantra that it is not about the technology – it is about the learning and instruction. It is not technology that impacts learning and instruction. It is the use of technology that might impact learning and instruction – use by teachers and students, support for effective use by teachers and students, ongoing training for teachers and students in the effective use of technology … it is how a technology is used and integrated into learning activities that makes a difference (when a difference is in fact reported, which is somewhat rare).

One problem that really gets under my thin skin (and skull) is the advocacy for a particular technology as THE solution. If only every student had a laptop … or an iPad … or an iPhone … nonsense. If only every student learned to think critically, to reflect about the problem space and alternative solution approaches, to question assumptions, to monitor progress of learning … if only … then there might be some real impact on learning. Technologies can be used to support those goals (critical thinking, inquiry learning, reflection, hypothesis testing, self-regulation, etc.), but what matters are the processes associated with learning … not specific technologies. Yes, I am a founding member of the national technology geek society … guilty as charged … but I have seen silly uses and implementations of powerful technologies that resulted in no significant difference … so I am now officially a geek drop-out and advocate of the three Rs – reasoning, reflection, and reliability … I am considering founding a new society to be called R3-D3 for the three Rs plus doubting, deliberating and determining … membership is free and  open to all.