When we hand children “tablets” and walk away it seems they intuitively learn how to use them. But should we really be surprised, if we consider dedicated researchers in computer-human interface design poured roughly 40 years of knowledge and experimentation into their making (Baeker, Grudin, Buxton & Greenberg, 1995)? On The Agenda with Steve Paikin: The Classroom of 2030 Oct 9, 2013 (hashtag #Learning2030), video evidence of this was shown and it was said, “The absence of the teacher becomes a pedagogical tool.” But what do our observations of children’s intuition tell us about what they’ve learned, or about learning how to learn? In the preface to the 21st anniversary edition of his 1995 The Unschooled Mind: How Children Think and how Schools Should Teach (1995/2011; I cite the 20th anniversary reissue, 2005, reprinted 2011), Howard Gardner revealed that, prior to its publication in 1983, he had believed the Theory of Multiple Intelligence (MI) was a contribution to mainstream psychology. He said he wasn’t thinking about pedagogy at all (1995/2011, pg. xiii). Yet the theory, whether one believes it or not, impacted pedagogy greatly, and continues to inform the debate on education reform. This post is for everyone who joins me in respecting Gardner’s contributions, and also finds recent evidence of kids’ intuition when mastering computerized tablets remarkable and encouraging. Howard Gardner found something about children’s intuition “troublesome” (1992, pg. 5). In the Peterson Lecture he presented in Geneva in 1992, Gardner reminded all of us: as children, and perhaps even as “educated” adults, when it comes to the big things, most of our intuition is just plain wrong.

Gardner and the Arts

By 1992 Gardner was celebrating Project Zero‘s twenty-fifth anniversary. Compared to its early years, PZ “…was much larger; more empirically oriented; extended well beyond the arts; and had a strong applied division, which worked in the schools, museums, and other educational institutions.” It was actually educators’ response to MI and the publication of the influential report, “A Nation at Risk” the same year that turned his lens, and that of his Project Zero, on education. The project was conveniently housed at the Harvard Graduate School of Education, but had been “philosophical and conceptual” in the 1970s and by the 1980s was doing “primarily psychological research funded by governmental grants” (Gardner, Perkins, Quense, Seidel, and Tishman, 2003, #3, par. 1).

For Gardner, that ‘to be a musician/artist/performer when I grow up’ is “a viable end state for human development” was a radical departure from Piaget (1992, pg. 1). By this time the seven “intelligences,” the word’s very definition and implications an area of criticism then and now (see for example, Morgan, 1992 or Willingham, 2004), was beginning to morph into five “minds,” introduced around the time of his (post-Peterson lectures) 1995 The Unschooled Mind: How Children Think and how Schools Should Teach. In the introduction to the 20th Anniversary edition he summarizes them. “The first three,” says Gardner, “can be reduced to three words: depth, breadth and stretch” (1995/2011, pg. xxiv). The fourth and fifth minds Gardner feels are “…not cognitive in the traditional sense” (1995/2011, pg. xxiv). The Respectful Mind brings tolerance and acceptance, and the Ethical Mind, while he labels it (too rigidly, I think) “outside the ken of children” (the youngest children, yes, but I think not some tweens, even pre-tweens I’ve known, as he concedes on pg. xxv). I’m inclined to assert that Howard Gardner’s divergence from Piaget has some elements of another extender of Piaget’s work, the moral theorist Lawrence Kohlberg (see Table 1).

On the ridiculous notion of replacing teachers in learning environments

Gardner rejected conflation of MI with “learning styles” (1995/2011, pg. xix), although H. Morgan (1992) points out strong parallels with “cognitive styles” (esp. pp. 4-12). He was coming to see the practical strength of apprenticeship, also uncovered by the “cognitive apprenticeship” framework posited by John Seely Brown, Allen Collins, S.E. Newman, Ann Holum et al. (Collins, Brown & Holum, 1989; Collins, Brown & Newman, 1989), and their work that stemmed from the ethnography of Jean Lave and computer science of Etienne Wenger (Lave & Enger, 1991), which as I’ve pointed out (Fouchaux, 2013) has especially promising and well-documented associations with technology-enhanced pedagogy.

In the early 90s, Gardner’s other source of excitement for the future of learning was the emergence of children’s museums like the Exploratorium in San Francisco, or Toronto’s Ontario Science Centre. Gardner developed a vision of school reform that included the expert/apprentice model: Modeling (expert performs a task, verbalizing/illustrating their knowledge and thinking) Coaching (expert observes and facilitates) Scaffolding (expert provides support(s)), Articulation (expert encourages learners to verbalize/illustrate their knowledge and thinking), Reflection (expert enables learners to compare their performance with others) and Exploration (expert invites learners to pose and solve their own problems) (Collins, Brown and Hollum, 1991, pg. 3). While he enthusiastically acknowledged these pieces of all learning situations can all be supported and enhanced by technology, Gardner seems already to have had a feeling for the importance of what is now known as “face to face” (sometimes abbreviated F2F) or “blended learning.”

Like Gardner, devotion to the study of learning and passion for its improvement drove his peers in the 1980s cognitive apprenticeship school to dig below the surface, beneath first impressions. “There are three important distinctions between traditional and cognitive apprenticeship: in traditional apprenticeship the process is easily observable; in traditional apprenticeship the tasks arise and emerge in the workplace; in traditional apprenticeship the skills to be learned are inherent in the task itself. To translate the model of traditional apprenticeship to cognitive apprenticeship, experts need to: identify the processes of the task and make them visible to students; situate abstract tasks in authentic contexts, so that students understand the relevance of the work; vary the diversity of situations and articulate the common aspects so that students can transfer what they learn” (Collins, Brown and Hollum, 1991, pg. 3).

Highly trained, highly respected, “reasonably competitively” paid professional educators

The benefits of training life-long teachers well and elevating the profession are proven and quite replicable. The idea of literally replacing teachers with prerecorded experts, virtual database curators guiding us through virtual museums and so on may sound very futuristic, but it is not one commonly held by serious trained educators who have devoted a life-time of study to understanding how the learning process really works. It’s more the realm of venture capitalists wielding “power tools,” dazzled by dollar signs, trying to take shortcuts past the wicked problem of obtaining consensus, and dismiss the roles poverty and privilege, equity and inclusion play in building a competitive, free and democratic society. Teaching and learning environments will adapt and adopt technology—I fully expect teleconferencing with experts to play a bigger role, experts who probably should have demonstrated superior communication skills and a concept of instructional design up front and/or work in tandem with the advanced preparation of those who do. I’ve seen indications and suspect recordings of live Webinars can retain enough genuine human interaction that they may have some vicarious benefit when observed after the fact. I’ve little doubt we’ll one day see self-driving cars, with speed and safety limits enforceable at the system level providing safe navigation of accident-free highways, travelling on auto-pilot. I ask, is “auto-pilot” a good model to pursue for the education of our children?

Whatever role we see for technology, we all do generally agree that schools fail because of the gap between what we expect them to do, and what we’ve actually designed them to do. Standardized testing, and moreover the purposes to which it is put, is the nemesis of authentic learning—not simply vinegar to its oil, more like a cancer in need of white corpuscles. Gardner has demonstrated the utter and complete failure of the tell and test model to build the kind of critical thinking skills required to connect the dots once we leave the classroom. No amount of technology will ever change this until we rethink and reframe schooling itself, in fact they may only entrench the problems. But to abandon the public social element of schools is to deny the essentially socially situated condition of learning itself (Apple, 2005; Reid, 2005).

What is Schooling?

Gardner believed in 1992 that the role of schooling is to provide “Christopherian encounters,” perhaps similar to what others have called “threshold concepts,” (see for example Meyer & Land, 2010) in order to replace childhood misunderstandings with understanding, which he he says elsewhere is easier to demonstrate if people have more than one way of representing a skill, and use their multiple ways deftly (their repertoire or tool kit, as some might say) in response to their audience or situation (1995/2011, pg. 14).

In the case of misconceptions, in the celebratory year 1992 I recommend Christopherian encounters, named after Christopher Colombus. If you believe the world is flat, but every day or every year you travel around the world and you come back to where you started before, that tends to belie the notion that the world is flat. In a Christopherian encounter you expose your theories to disconfirmation. If your theories are consistently disconfirmed, you will slowly abandon them, and hopefully construct a better theory.

Howard Gardner (1992, pg. 10)
[Emphasis mine. Of course we know
this isn’t always what happens.
Please see his arguments, which follow.]

Why even the best students in the best schools do not understand

Most of the elements elaborated upon in his 1995 recommendations for schools were already part of his 1992 guest lecture in Geneva. Subject by subject he reveals how only experts master the subject matter, while many (most) of the the most highly “educated” fail to make the connections they’ve invested years in education presumably to be able to make. He said it affected all disciplines and documented its impact on each, developing terminology where necessary.

Pure and applied sciences: Aristotelians, Rigid Algorithms

“Most people remain five-year-olds or Aristotelians even though they studied physics,” says Gardner (1992, pg. 7), and gives examples from astronomy and other sciences, as well. 23 out of 25 Harvard astronomy graduates ignore everything they’ve just studied and regurgitated on tests to do with the earth’s seasons or axis, and state the earth is warmer in summer because it’s closer to the sun than in the winter. Students “…who have taken not one, but two or three courses in biology focusing on the topic of evolution, still do not understand the basics of evolution. They still believe that something in one generation can be passed on to the next, even if it was acquired in that generation.” What he encounters in mathematics are not so much misconceptions as “rigid algorithms,” learning to plug numbers into a formula, by rote (pg. 7).

Problems in Economics and Statistics

Economics presents a bridge area between mathematical thinking in the social arena. “College-educated subjects outperformed those without a college education, but there was little difference between those college students who had studied economics and those who had not. […] Misconceptions or stereotypes were found across both groups. […] Such primary rules seem to occupy a place similar to a rigidly applied algorithm: When in doubt, invoke the rule triggered by a word like interest or inflation” (1995/2011, pg. 181). Gardner tells of a well-known set of studies by Amos Tversky and Daniel Kahneman, and their colleagues asked students to answer questions calling for the use of statistical principles, and gives only 5 of their astonishing examples. In one, given a sample in which they’re told up front the ratio of engineers to lawyers is 7:3, and asked which a particular subject who just happens to be good at debate is more likely to be, trained statisticians abandon their schooling and go with the stereotype (pg. 183).

The Arts and the Humanities: scripts, simplifications and stereotypes

The Star Wars script is one very powerful script we develop as children, it goes, “it’s good to be big; you should be big yourself; if you’re not big, align yourself with somebody who is big. If you look like that person, you will be good and people who look different will be bad.” But history majors who write papers on the complex nuances of WWII approach current events in what some might call Manichaean terms of good guys vs. bad guys (1992, pg. 8). Gardner’s unschooled mind presented quite embarrassingly in the arts in a much earlier 1920s study by literary critic and poet Ivor Armstrong Richards. He removed the poet’s names from classics by John Donne, Gerald Manley Hopkins and others and “…found that the students did not have a clue about which poems were good (according to the critics) and which were bad” (1992, pg. 8) Gardner tells us “…you have very, very good students who have studied literature, who, when the book clue is removed (namely this is by a good poet, this is by a bad poet or by a non poet), display the same kind of taste that someone with no education in literature would exhibit” (pg. 9).

Schools presumably seek to present three kinds of knowledge across disciplines: notational sophistication, concepts within the discipline, and forms of exposition and reasoning within the discipline (1995/2011, pg. 143). Gardner has ideas on how to address the failings that lead to each type of misconception, some of which I’ve outlined already.

A repertoire and toolkit for repair

As I said earlier, Gardner speaks of deftly using multiple ways to represent, practice and experience skills and knowledge. He offers “…five different “windows” into the same room.” They are 1. Narrational—basically the story mode. 2. A quantitative, logical rational way of dealing with numbers, principles, causality. 3. A foundational way, asking who? what? where? when? how? …why? 4. Aesthetic—looks, configurations, impressions. 5. Finally, hands on—“What is it actually like to be this thing, to do this thing? …what is it like to breed drosophila? If you are studying democracy, what is it like to be in a group that decides by consensus as opposed to one that decides by autocracy, oligarchy or some other political principle” (1992, pg. 12)?

John Seely Brown’s Institute for Research on Learning (IRL), a cross-disciplinary team of researchers from anthropology, education, linguistics, computer science and psychology found Seven Principles of Learning: “Learning is fundamentally social; Knowledge is integrated in the life of communities; Learning is an act of membership; Knowing depends on engagement in practice; Engagement is inseparable from empowerment; “Failure to Learn” is the normal result of exclusion from participation; We already have a society of lifelong learners” (Collins, Brown, and Holum, 1989; Collins, Brown, and Newman, 1989). This project in particular led to the cognitive apprenticeship framework, with immediate recognition of its potential enhancement by technology (Fouchaux, 2013, Appendices B, C, & D).

The social media boom, the rise of Facebook and Twitter and their inevitable entrance into discussions about teaching and learning have not created new knowledge, nor caused a spontaneous eruption of stunning new ideas. They have only increased the number of people with access to what we have been learning about education and technology since the emergence of these technologies. We have amplified and expanded a conversation we educators have been having for decades. The first Apple Graphic User Interfaces (GUIs) were disrupting the console driven mainframes and finding their ways into the homes of relatively ordinary people and their work places in the 1980s. Nearly 40 years ago they defined the study of systems usability, and they established the practice of watching users use systems, and then measuring the results with the focused aim of making the systems more usable. Children’s “intuitive” adoption and uptake is not magic (Baeker et al., 1995).

Assessment in Context: The Alternative to Standardized Testing

Gardner says “ongoing assessment” or “assessment in context” means “…assessment is taking place all the time by students and by peers as well as by the teacher” (1992, pg. 12). It may be surprising to some readers that Howard Gardner, the man at the centre of the orbit of some of the most highly-esteemed education researchers and projects at Harvard and the private sector, was in 1992 so matter-of-fact in his vehement disapproval of the types of standardized testing that still dominate, and some, especially in the USA, say should be expanded (Gardner, 1992b). It was indisputable to Gardner, just as it was to Xerox CEO John Seely Brown and the set of top-notch educationists, researchers and scholars he used his corporation’s influence to assemble (see Fouchaux 2013, Appendix A), to empower, to enable—but not to dominate nor simply to exploit—in the collaborative communities of practice that characterized experimentation in education of the 1980s and ’90s.

Diane Ravitch has now made clear that, contrary to the claims being made, public school test scores and graduation rates in the USA are the highest they’ve ever been, and dropout rates are at their lowest (Ravitch, 2013). Discourse to the contrary is a concerted effort to destroy public schools in that country, disrupting a 325 year commitment embedded in the Constitution (Dennis, 2000).

Therefor it can not be more plain that those who promote more testing have a different purpose. To say in the 20-teens that one believes eliminating fully trained and accredited professional educators, and all the “thickness” years of exposure to the ideas of men and women who like Gardner, Collins, and Brown, have devoted lifetimes to improving children’s learning bring to the learning situation, can be nothing but an attempt to wrench the helm onto another tack by fiat and coercion. Children’s intuition, as Gardner showed decades ago, isn’t good enough. “Absence” of the teacher is not the same as “removal.” We’ve agreed to dispense with the sage on the stage, but if you don’t have guides on the side who know the ropes, the waters, and the weather, you will certainly get lost. You may run aground, sink and drown, or simply drift away forever upon doldrums no different than the Ancient Mariner’s, you’ll just be taking a more expensive cruise.

Educationists from across the decades and around the world concur. We must re-design schools from the ground up to be highly inclusive public spaces, purposed to build and share learning experiences in collaborative settings. We must cultivate critical discernment and expose would-be apprentices to experts who are themselves students of pedagogy. We must understand that learning is continual and there is no single learner or teacher where 2 or more humans coexist (Collins, Brown and Newman, 1989; Gardner, 1991; Lave & Wenger, 1991; Lave, 1996; Meyer & Land, 2010; Salhlberg, 2011). We must not narrow instruction to rigid algorithms and formulaic responses in science and math, but design situations where experts and novices engage and interact in practice. We must let them create performances of their understanding that convey the internalization of the concepts, awareness of critical connections to prior learning and available information. We must find cohesion and build shared understanding to solve the wicked problem of education reform collaboratively, not authoritatively.

In short, we must learn how to learn, with, not just from, people whose passion it is to understand how learning takes place and what that looks like. We must learn to recognize and celebrate the hard work that’s gone before. Stop experimenting with disproven methods and apply the results of a century of experimentation we’ve already done. Make sure the people driving the school bus want to get the kids where they want to be… not drive certain kids to a certain part of town to park and sell them junk food, not to scrap the bus, nor to sell it for parts.

§

Watch: The Agenda with Steve Paikin: The Classroom of 2030

Watch: TVO on the Road: Learning 2030

N.B. This post has been edited several times—to improve clarity, correct the TVO broadcast date, to fix a broken internal page anchor, and to correct grammar and spelling.