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Several decades ago – long before the level of technological sophistication we experience today -- I was part of a movement begun by the late Julian Stanley, a psychology professor, and the Johns Hopkins University Center for Talented Youth (CTY) to save academically talented youth from boredom in the schools. The most controversial instrument to rescue them was a pedagogical practice called, rather prosaically, "Diagnostic Testing Followed by Prescriptive Instruction" or, shorthand, “DT>PI.” It was principally applied to the pre-collegiate mathematics curriculum and relied on just a few key assumptions and practices:

1. Students already know something about a subject before they formally study it.

2. Test students before a course begins and then just instruct them on what they don’t know.

3. Test students again when you as the instructor and they as learners believe they have competency in a subject.

4. Move immediately to the next level of instruction.

The DT>PI model was placed in a more generous context with the adaptation of Professor Hal Robertson’s (University of Washington) notion of the Optimal Match. Simply stated, pace and level of instruction should match optimally an individual student’s assessed abilities — with the caveat that those accessing that talent would always try to stretch a student beyond his comfort zone. The Optimal Match theoretically could apply to all students at any level of education.

When I used to speak publicly in a wide variety of settings — at colleges and universities, community colleges, schools, education association meetings, parent gatherings -- about what I thought to be the commonsensical notions of DT>PI and the Optimal Match, the reactions were pronounced and fiercely negative. My colleagues and I were accused of presenting educators with the dissolution of the structured classroom as we knew it then; forcing students unjustifiably to proceed educationally without sufficient instructional guidance; destroying the communal, cooperative imperative of an American education; and, producing social misfits because students would finish academic coursework before the schedule established (rather arbitrarily, I might add) by educational professionals for all students of one age at one time. Parents joined often with educators to decry such imagined alienation and damage to a child’s personality.

And then there was a change in 2013.

There are now two closely related pedagogies -- adaptive learning and competency-based learning -- that are embraced by a growing number in higher education as a viable component of educational reform. The Bill and Melinda Gates Foundation is awarding grants to 18 institutions to experiment with 10 different adaptive learning platforms, and President Obama has expressed support for these innovations and urged easing of regulations to make that possible.

In general, adaptive learning uses data-driven information to design coursework that permits students to proceed educationally at their appropriate pace and level. And competency–based learning allows students to be free of "seat time" and flexibly progress as they demonstrate mastery of academic content.

These definitions, when combined, delineate precisely the key components of DT>PI and that of numerous other experiments in self-paced learning over the last few decades. But now, while the naysayers are still out there, an increasing number of for-profits and nonprofits are turning to adaptive and competency-based learning as a component of the next stage of reform in American education.

Why now? Something must have changed in society to accept self-paced, individualized learning when only decades ago it was roundly rejected on pedagogical, ethical and psychological grounds. Those concerns are clearly not as inviolate as they were only years ago. Answering this question might well provide education reformers with insight into what is now possible — even expected -- from students for the learning platforms of the future.

There are at least three reasons why self-paced learning might be more popular now than it was only a few years ago: technological advances, financial exigency and a new self-profile of the learner.

Advances in technology that rely on advances in data mining and data analytics -- predicting future learning behavior by an individual based upon analysis of thousands of earlier learners — permit now a high ability to track, direct, customize, evaluate and advise student learning at instantaneous speeds. What in previous decades seemed to be an impossible task for a teacher or professor to manage in a single course — diverse learning points among students — is at least now technically feasible.

Many institutions are rather intent to find new strategies that will at once reduce their cost of providing an education. Adaptive and competency-based learning are thought to be such "disruptive" opportunities, although how accompanying data-driven, all-knowing and anticipating, high-touch technologies will reduce dramatically both cost and price (tuition) remains elusive.

And, lastly, students have perhaps finally realized the expectation of the self-esteem movement that has dominated instruction in our nation’s schools for several decades. Students might well now believe that they are the center of all activity — to include education — and that they are both the sole focus and the drivers of learning. All instructional effort exists for the purpose of fulfilling their desires.

This "power shift" makes learners, individually — not teachers or professors -- aggregators of knowledge by and for themselves. Any approach to education that places them at the center of learning activity accommodates their perspective on education. Adaptive and competency-based learning accomplish this masterfully. Self-paced, individually adjusted instruction, enhanced by “big data” technologies that guide student progress “lockstep” in a course and beyond, eliminates distracting elements to the individual control of knowledge. Primary among those distractions for students are faculty with their pesky, seemingly inefficient and irrelevant questions.

And thus, in 2013, what was not acceptable several decades ago is now thought a solution to crisis in American education. A combination of new technologies, financial emergency and a shift in who is at the center and in control of learning has caused this to occur.

But all is not settled. The changing circumstances introduce concerns that did not exist decades ago when students were not the arbiters of their own learning, self-paced instruction was not thought to be a solution for all students in American education but only the academically talented and big data did not exist to mine and anticipate every move in student learning.

A defining element of DT>PI was that students must not just study what is the next logical step in a course, but they must through the exhortations of a teacher or professor attempt to go beyond what was thought statistically possible — they must stretch themselves intellectually at every point. Professor Stanley used to constantly quote the line of the poet Robert Browning that one’s reach must always exceed one’s grasp.

Questions remain whether in the absence of a live instructor exhorting a student who is not necessarily academically acute and motivated, students will extend their reach or settle for statistically generated achievement delivered by an electronic adviser (I am referring here to traditional-aged undergraduates, not working adults who are propelled by substantial motivational factors). Such absence of exhortation could be extremely damaging to the majority of American students who often do not naturally attempt to achieve to the levels of which they are capable without personal mentorship.

And one traces in those who are enthralled with "big data" and "data analytics" for solving the maladies of American education a disturbing belief. Student will achieve through data-enhanced technologies the perfectibility of education — perhaps life itself -- by eliminating all resistance, frustration, indecision, trial and error, chance and expenditure of time. For example, Harvard University social scientist and university professor Gary King is quoted in a May 20, 2013 New Yorker article entitled "Laptop U." as saying, “With enough data over a long period, you could crunch inputs and probabilities and tell students, with a high degree of accuracy, exactly which choices and turns to make to get where they wanted to go in life."

And yet, there is growing commentary that it is precisely the absence of frustration, resistance and associated imperfections in a so-called “Me Generation” and its aftermath that is compromising contemporary students' learning and preparation for a life. By educators blithely accepting students’ assertion of self-determination without legitimate maturing experiences (that will include failure and self-doubt) and by arranging learning electronically so that they will make no wrong decisions, they are granting them little ability to deal with inevitable disappointment and frustration in life.

Students are educated without gaining resilience and that is hardly an education of which a nation can be proud or secure, regardless of the utopian promises of the big data enthusiasts. All this reminds me of a call I received decades ago from an entrepreneur who wanted me to comment on his idea of developing a school basketball court that would have the hoop move electronically with the ball so that no student would ever miss a shot and thus, in his words, "suffer humiliation."

So while I am delighted that self-paced education in the form of adaptive and competency-based learning is finally a more generally discussed component of reform in American education, I urge that those advancing it think long and hard about some of the humanly-damaging consequences of learning platforms so perfected by technology that students are offered a Faustian bargain – the comfort of non-resistant and frustration-free learning in exchange for the ultimate loss of a resilience needed for a satisfying life after schooling.


 

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