Saturday, May 19, 2012


Part Two of this series mechanically depicted the factors that might need to be assessed to match digital technologies – hardware and software – to K-12 classroom needs.  Deductively the variables itemized and subsets of those variables all play rolls in what technologies fit which learning situations. 

At the same time common sense and experience tell us that many of those combinations are self-evident, or would not generate even a just noticeable difference in mediating classroom performance, or changing a test score.  Part Three explores the proposition that fitting technology into K-12 is both method and art, with hard stuff but importantly mostly dependent on soft stuff.

Hard Versus Soft

For some readers the failure to launch into a Consumer Reports-style assessment of named/branded digital devices may be disconcerting.  In reality, that hardware while a major dollar commitment, is the least important factor in K-12 technology evolution, most easily substitutable, and most vulnerable to obsolescence.  The logic of higher order learning-linked methodology, then its expression in software drives the devices, in turn, becoming entwined with classroom teaching/learning reasoning and practice; that is the disruptive K-12 change needed.  

The quixotic and dynamic nature of hardware evolution is nicely illustrated by the “Google glass” project, a hands-free eyeglass frame device that conceptually could replace smart phone, camera, conventional Internet hardware, word processor, video conferencing, potentially even become a full operating computer; with more transistors put on a chip of silicon, or futuristically on a coated sheet of (carbon) graphene one atom thick, with power supplied by solar cell technology woven into your shirt or blouse.

Contemporary hardware is sexy, but the half-life of new digital devices is now measured in fractions of a year.  With basic research developments of materials now promising to extend Moore’s Law (that the number of transistors that can be put on an integrated circuit doubles every 18 months to two years), the educational constraints of absorbing digital technology are not hardware, but the capacity for K-12 to use its own intellect and creativity to envision applications for learning that move beyond last century's phenotypes.
Two massive examples underscore a first paradox, and disconnect between what digital technology can do or enable, and has in consumer markets, yet eludes education:  This week's Facebook IPO produced a $105B valuation, secured for technologically fairly simplistic social networking, a version of which could easily support models of group learning if so structured; and a nearly $70B gaming market is served by simulation and graphics logic and programming that could offer stunning learning effects in K-12 if so directed. Both technologies, because they perceptually appear as entertainment frequently provoke contempt from educators, rather than being recognized as simply different flavors of serious digitally enabled modeling.  Simulation modeling, with us for over a half century, and AI (highly sophisticated and complex artificial intelligence modeling, just beginning to firm up as usable technology) may be K-12 education's best chances to evolve better learning protocols and better HOTS assessment testing. 

Two More Vexing Paradoxes

The second paradox that haunts the technology integration issue for public K-12 explains some of the cynicism about using more formal methods versus gut feel to elect technology usage.  As noted above, some technology fits are intuitively obvious or simply emerge seemingly autonomically because of prior learning or teaching experience, while others are not perceived or recognized, short-circuiting creativity.  The greater the logic and software content of a digital education tool, the greater the greater the risk of missing a non-traditional application.  Ignoring common sense – not unheard of in present public K-12 reform trajectories – by pro forma paper assessments, inviting analysis paralysis, creates bureaucratic detritus on top of bureaucracy; the opposite, ignoring the search for more formal or creative awareness of where technology can augment learning imposes opportunity costs.  How do you differentiate the options and choose a vector?

There is a third paradox – usually billed “the technology paradox” – that while applied to technology adoption generally, also fits K-12.  Basically, the assertion is that technology adoption should increase productivity, but initially does not, the situation in the U.S. in the 1970s and 1980s.  However, in the 1990s there was evidence of substantial improvement in productivity attributable to that same technology.  Explanations are dual:  First, when technology was first introduced its use was primarily to automate existing processes whether they were otherwise effective or not, so some performance improved and some failed faster, and at the cost of acquiring and implementing the technology; and second, when improvements finally occurred they were attributable to structural revision of those processes to integrate technologies, to organizational learning, and to the ubiquitous learning curve that describes how complex systems absorb change and adapt but systemically and over time.  Both effects are hovering over current K-12 technology adoption.

The materiality of the above is that there is no magic bullet for K-12 technology use, nor will the vastly overused Bloom’s taxonomy point to a simple set of heuristics or model for technology matching to any given learning setting.  Seems obvious as well; however, daily the media feature technology naysayers claiming that public K-12 needs to return to the red brick schoolhouse, and that the technology device of the day has failed to produce greater learning.  Keep the “technology paradox” in your kit of tools to assess with greater perspective what is seen and read.

A Paradigm for Thinking About Technology x Learning

The first piece of the puzzle is getting beyond Bloom's taxonomy, that has seemingly dominated K-12 learning stage thinking.  One approach has been labeled HOTS, or higher order thinking skills.  There are multiple structures for present thinking on HOTS, and one of the better depictions was authored at Florida State University.  That approach posits five HOTS dimensions: Metacognition; critical and creative thinking; thinking processes; core thinking skills; and relationship of content area knowledge to thinking.  Each dimension has been exploded into related concepts, then into related elements.

Total detail for this depiction is less important than the recognition that the system of classification points you toward action learning steps, none mysteries, that are links to how any hardware and software delivery might fit, and how it might be differentially effective versus present practice.  (For reference this document [a], and a complementary display [b], are linked for online access in the appendix to this post.)

Step two follows from the ending arguments in Part Two of this series. Stripped to essentials, the matching issue is:  Being able to articulate for the classroom learning situation (e.g., some HOTS organization of processes) what a hardware/software solution can deliver, expressed in cognitive contribution, communications, experiential, or sensory terms, versus, in those same terms, what any specific hardware/software asset needs to deliver in the content areas of relevance to meet stated learning goals.  Note that there is no elaborate model required; the solution can be straightforward human assessment when the dual knowledge implied is available in one resource, but becomes more formal and organizationally driven when group decision making is dictated by specialized knowledge and multiple decision-makers, and especially in most K-12 system environments where decisive decision processes tend to be rare.

If the adoption assessment process ended there it would still mean sifting through options based mostly on inferred learning effects, but a solution is also subject to seat time positioning and factors beyond the direct classroom application.  Importantly, school, classroom, and student environments, special education demands, and all of the technology support factors are part of the equation, along with the complication that some hardware and/or software capabilities will be highly dedicated to narrow learning delivery, while some will be applicable across virtually all classrooms and operations.

Hardware adopted is also subject to cost and funding issues; life expectancy, downtime risk, maintenance requirements, upstream support investment required, and obsolescence, all becoming administrative factors.

Step two segues into another level of analysis, step three, further criteria used to assess the hardware.  For example, a general laptop seems benign enough; but the fit to classroom need may require assessment of speed, memory, graphics, durability, visual quality, aural capability, battery life, and other dimensions, along with the other administrative impacts of the prior paragraph.  Demonstrating the generic versus dedicated use issue, a laptop may serve multiple needs, versus a pad, smart phone, or similar device that is capable of communications delivery but would necessitate another device be available for scaled up calculation chores.

Step four gets into the nitty-gritty of determining both the absolute and relative capacities of various devices married to specific software to, essentially, create a better teaching performance with the technology than without it.  That means getting behind the curtain to assess the wizard.  Some teachers, with highly developed skills and great experience may find some to many technologies even a detriment to learning in their classrooms; one size does not fit all in spite of that fantasy in the current bogus public K-12 reform movement.

Knowing What We Know, and Don’t Know?

A simple but powerful metacognitive tool is branded the “knowledge paradigm,” made infamous by our former U.S. secretary of defense’s invocation of “unknown unknowns.”  But parsed out, its message is elegant, particularly the cell categorized “don't know what we don’t know,” the bane of good decision-making.

From the above, specifying the hardware/software mix to be set into a classroom is neither at times as much a mystery as frequently envisioned, nor a process that at our present levels of education research the stuff of easy digitization and a pat solution.  We can also observe that there is little hard research about the efficacy of various technologies in delivering better learning performance in the classroom, versus delivery by a properly trained, equipped, supported, and motivated human teacher/coach.  Lastly, we also know deductively that there are going to be few fully generic or vanilla solutions to technology adoption; rather the choices of technology augmentation are going to be specific to the individual classroom, and most of its functions, to be absorbed and productive.

Can heuristics, or checklists, or rubrics be specified that can guide one who has to select and implement technology in K-12?  Certainly, and there are the bits and pieces of that knowledge in the education literature, and especially in the explosion of now online teacher-authored treatises on the question.  Is there an organized database of research-based findings on how technology types create better learning results?  Not so much, for the reason that neither the USDOE, nor most of our schools of education, nor our K-12 schools, nor most of the vendors profiting from such adoptions have made those investments.

So a fourth paradox surfaces.  The online world is now populated by an amazing array of professional but anecdotal examples of technology applications in the K-12 classroom, but few if any of those observations – that may be valid and even transferrable – have been systematically assembled, even as meta-research to determine if technology gains can be generalized.  A proposition is that the history of bureaucratic and risk averse public K-12 education bears some responsibility for the status.

Public K-12 has long been driven, from Ausubel through Werthheimer, and all between, by deductive approaches to learning because it was (mistakenly) assumed it could never be empirically described or explained.  There is little tradition of regularly empirically testing the input variables to learning against student HOTS demonstration, or longitudinal downstream use of that learning, or perhaps in future true neural-biological effects.  Hence, it is probably explicable why the rallying cry for those advocating present standardized testing is a shrill, if naive, “give us accountability.”

It is ironic, when in the last few days science has demonstrated that we have the capability to physically do work by simply thinking it into action, that the U.S. K-12 public education establishment is still too frequently and dogmatically functioning based on science of the last century.

Technology Applications

The premise of this post was originally that an example or two of technology applications in the classroom would be its conclusion, to balance its conceptual approach to technology assessment against what is happening metaphorically in "K-12 on the street.”  The reach and wealth of actual albeit ad hoc classroom applications recovered in searches changed the plan.  Below are annotated links to the first several dozen citations located – encompassing hundreds of classroom examples – of how technology is penetrating some K-12 schools.  Far better than trying to paraphrase what teachers are reporting, those links are below.  Self-study beggars what this post could offer in the form of attitude-, opinion-, or belief- changing assessments.

A sample…

Does “World of Warcraft” cause you to cringe and bemoan a generation that has drifted to the edges of fantasy?  Another perspective, Simulation, Social Networking, and Gaming, from resources who do real science, MIT, and parenthetically, may spawn the next IPO and billionaire.

Visit eight years of examples of specific technology applications in a spectrum of classrooms from READING rockets.

From the UK, and places of some renown – Oxford and SRI International – some dynamic technology applications in the classroom.

For an unabashedly proactive endorsement of classroom technology, visit this personal statement from Mashable Tech.

From the Journal, teacher talk about BYOD; for the technology impaired, “bring your own device.”

Also from the Journal, a provocative dialogue about moving the teacher from the front of the room to its center and the learning action.

From Education World, archives covering the spectrum of digital issues and applications.

Three tips on integrating technology into the classroom, from US NEWS & WORLD REPORT.

From Edudemic, a pictorial trip down the classroom technology memory lane.

An understated but prescient discussion of technology in the classroom, circa 1999, by a Vanderbilt-educated PhD educator and researcher, sponsored by the International Reading Association, Inc.

How one school system has used the “wiki” as an educational tool.  (Parenthetically, Edunationredux is essentially a wiki site, that took in its initiation almost a whole 45 minutes and zero coin to create.)

The “Technology Integration Matrix,” produced by the Florida Center for Instructional Technology, College of Education, University of South Florida.  Follow the arrows for a documented tour of integration organization and guidelines.

From Educause Quarterly, a 2004 narrative about the merits and issues of K-12 classroom technology.  Eight years ago, testimony to public K-12’s sense of urgency and creativity?

Thoughts on technology use for early childhood education from Scholastic/Teachers.

A slide show course on technology in K-12, from Slideshare.

Large collection of specific hardware/software applications from one school district’s technology specialists, underscoring the support issue mentioned earlier.

From EmergingEdTech, although the issue may have about the same ambience as fingernails on a traditional blackboard, how to use Twitter in the classroom.

Best practices of technology integration in Michigan schools, sponsored by the Michigan Association of Intermediate School Administrators.

From Education Week/Teacher, overview of classroom technology issues.

A wiki on good examples of classroom technology use, by a private sector source of technology integration consulting, PBWORKS., Secondary Education, on integrating technology into the classroom.

A wiki, Literacy Pathways, describing examples of classroom technology adoption.

Also from Literacy Pathways, a comprehensive report on technology in K-12 from The New Media Consortium, funded by Microsoft.

From educator training at Haverford and Bryn Mawr, a well documented example of using technology to support secondary biology classroom education.

From teAchnology, an online teacher resource, tutorials on use of technology in the classroom.

An archive from USDOE, Education Reform Studies, on evaluating technology use in the classroom.  "Archive," go figure.

From the University of Michigan, Center for Research on Teaching and Learning, review of “Teaching Strategies:  Technology in the Classroom.”

From a blog, THE THINKING STICK, dialogue on virtues of classroom technology.  (Note:  As in the case of many online treatments of a topic, the most revealing inputs are the comments by readers.)

Lastly, with tongue-in-cheek, the premier world science journal, Nature, reserves its last text page of every issue for a fictional short story based on science, usually sporting some unconventional humor.  Nature’s May 10, 2012 issue featured a story blending the classroom and technology, very short on political correctness, and evocative of the ambivalence of "digitizing" the classroom.  Enjoy.

The above represents only a small fraction of the commentary about classroom technology available online.  That integration of those experiences in our actual classrooms is incomplete, and seemingly addressed by few education research and/or codification dollars; for example, compared to the funding being poured into faux to pedestrian standardized testing and slavishly accepted by public K-12.  That is not exactly ringing endorsement of public education leadership, or state-level oversight, or of the USDOE.
Indeed, it poses a disturbing question:  A decade from 2012, which effort – expanding low-level repetitive standardized testing to every grade level and even preK as "accountability," mechanizing teaching validation with VAM, commercializing it with TFA, and privatizing schools, or, installing the best learning technologies along with more sophisticated assessment (and testing) of HOTS in public K-12 schools – is more likely to contribute to systemically viable and stable K-12 infrastructure, knowledge dissemination, and a thinking population?

Postscript:  Part Four

Part four, and the last in the series, will attempt a risky polemic venture, to project or at least speculate how technology could modify U.S. K-12 education over the next couple of decades.  One common point of view is that we cannot know the future, so it is foolish to speculate.  Another, however, is that while the future is subject to “black swans,” much of our future is written under the surface in past trajectories, and providentially in the case of technology, in paid-in extant research that once in motion eventually surfaces as potential innovation.  Whether public K-12 can survive the current epoch attacks of corporately-, politically-, and contempt-driven faux public K-12 reform, to benefit from technology bubbling to the surface, may be a race; between public K-12's adoption of tradition-breaching entrepreneurship and technology advocacy, and the hazards of “black swan theory.”

Reference Appendix:

No comments:

Post a Comment