Tag Archives: policy to practice,

Looking Anew at How Teachers Teach

Today, reformers from both ends of the political spectrum push Common Core Standards into classrooms. They champion charters and more parental choice of schools. They want teachers to be evaluated  on the basis of student test scores. Policymakers, philanthropists, and vendors send tablets to classrooms. Look at these reforms as blood relatives fixed on changing how teachers teach so students can learn more, faster, and better. An old story to be sure.

Why old? Two traditions of teaching have competed with one another for millennia.  Each has had a grab-bag of names over the centuries: conservative vs. liberal, hard vs. soft pedagogy, subject-centered vs. child-centered, traditional vs. progressive, teacher-centered vs. student-centered, mimetic vs. transformational.

Each tradition has its own goals (transmit knowledge to next generation vs. helping children grow into full human beings);  practices (teacher-centered vs. student-centered); and desired outcomes (knowledgeable and skilled adults ready to enter the labor market and society versus an outcome of moral and civic engaged adults who use their knowledge and skills to help themselves and their communities). No evidence, then or now, has confirmed advocates’ claims for either tradition. These are choices anchored in beliefs. While posing these traditions as opposites, I, Philip Jackson,  and others have pointed out that most teachers, including the very best, combine both ways of teaching in their lessons.

Educational battles have been fought time and again over these traditions in how teachers should teach reading (phonics vs. whole language), math (“new” vs. traditional), science  (learning subject matter vs. doing science) and history (heritage vs. doing history). Yet even at the height of these public wars fought in words and competing policies, teachers  taught lessons that combined both traditions.

Since the early 1990s, however, states have embraced standards-based reforms, accountability measures, and mandated testing with No Child Left Behind (2002-2015), Common Core standards and tests (since 2010), and Every Student Succeeds in 2016. How, then, in the past quarter-century of standards and accountability-driven schooling have teachers organized instruction, grouped students, and taught lessons?

For those who listen to teachers, the answer is self-evident. Classroom stories and teacher surveys have reported again and again that more lesson time is spent preparing students for high-stakes tests.  And what is taught has narrowed to what appears on tests.

Such stories and research studies describe classroom instruction, particularly in largely poor and minority schools, as more teacher-centered, focused on meeting prescribed state standards and raising test scores. Teachers have felt pressured to drop student-centered activities such as small group work, discussions, learning centers, and writing portfolios because such activities take away precious classroom time from standards-based curriculum and test preparation.

To confirm or challenge these stories and surveys, I  and others have gone into scores of classrooms across the nation. I can sum up the evidence during these years of strong state and federal backing for standards-based reform and accountability into the following statements:

*Teacher-centered instruction has increased in those districts and schools that performed poorly on state tests.

Where state and federal authorities threatened districts and schools with restructuring or closure for low student performance, shame and fear drove many administrators and teachers to prepare students to pass these high-stakes tests. Teachers spent time in directing students to get ready for the skills and knowledge that would be on the state tests. Yes, a shift in classroom practices occurred with more whole group instruction, more seatwork, and more teacher-directed tasks such as lectures and worksheets in secondary school classrooms

All were aimed at improving student performance on state tests. The record of that improvement, however, is, at best, mixed.

*Even with that shift to more teacher-centered instruction, hybrids of the two teaching traditions still prevailed.

As an historian of teaching practices, I have written about how teachers decade after decade have combined both teacher- and student-centered instruction in both elementary and secondary school classrooms.

Even with the current concentration on standards and testing, blends of teacher-centered and student-centered practices still prevail. In short, teachers have had a degree of autonomy—some more, some less–to arrange their classrooms, group for instruction, and choose among different activities for the lessons they taught even in the midst of being labeled failures and school closure threats.

On the whole, then, since the early 1990s when standards, accountability, and testing came to dominate U.S. classrooms, there is a tad more teacher-centered instruction but mixes of the two traditions remained very much present.

Even so, research-backed efforts to add further fuel to the embers that  have burned over the centuries glow between Progressives and Traditionalists are found in the push for Direct Instruction. Often scripted materials for teachers to follow with their students, researchers have found time and again that such instruction shows gains in student test scores ( here, here and here). Yet from Distar to Open Court, elementary school teachers in particular, have been reluctant to embrace such materials.

The struggle over how teachers should teach continues. Policymakers, researchers, practitioners, parents, and, yes, students need to know that both constancy and change have occurred in teaching over many decades. Knowing that these competing traditions of teaching–whatever label is given to each one–turn up in classrooms in 2016 call up anew the persistent progressive and conservative beliefs that have divided policymakers, practitioners, and parents for decades.

 

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New Project in Technology Integration in Schools and Classrooms (Part 2)

In Part 1, I laid out my reasons for shifting my focus from disappointments and failures in uses of new technologies to best cases of such use in districts, schools, and classrooms. I also laid out two puzzles that have bugged me for a long time that may find solutions in describing and analyzing exemplars of technology fusion into schools and classrooms. In Part 2, I want to share my current thinking about how I plan to do the project in the next year or so and the obstacles that I see in front of me.

How do I plan to do the study?

The design of the project is a series of case studies drawn from districts and schools. The methodology I will use is interviews with district administrators, school principals, and classroom teachers. Also I will directly observe lessons, sit in on meetings on technology integration, and related professional development. Analysis of district, school, and classroom documents will provide the context of goals, strategies, assessments, and outcomes at different levels of schooling. Finally, describing the history of the district and schools insofar as access and use of new technologies over past quarter-century. All of these data make up each case study.

Where will I do the study?

I have chosen Northern California because it is the epicenter of techno-optimism about new technologies transforming the direction and nature of  both K-12 and university education. Major high-tech firms located there such as Google, Apple, Oracle, Intel, and others have launched major initiatives in both software and hardware that focus on improving the practice of schooling. Some of these firms have designed specific educational software, trained teachers, and offered products directly to schools (see here, here, here, and here). Specifically, I will focus on the Bay area which includes “Silicon Valley”–an area that covers San Jose through San Francisco. Early adopters and unvarnished fans of technology are in ample supply. A pervasive ideology across the region is anchored in taken-for-granted beliefs that new technology improves every aspect of daily life. Cultural norms among established firms, start-ups and wannabe entrepreneurs prize innovation, accept failure as part of life, and turn out beta versions of the “next new thing”daily. That ideology and culture is in the water Northern Californians drink and in the air they breathe. So exemplars of technology infusion in K-12 schools, powered by  hallowed beliefs in the power of new technologies to alter habits and institutions, would surely exist here.

Thus far, one high school district and one charter management organization in Northern California have invited me to do this research this Spring. Where I go after February and March, I am uncertain. So far, so good.

What obstacles do I anticipate?

The first barrier I have to get around is defining exactly what is meant by “technology integration” or “technology infusion.” Not an easy task. Multiple definitions abound (see here and here). Moreover, standards used to inspire action and then judge to what degree “technology integration” occurs in a district, school, or classroom vary widely (see here, here, and here). Rather than pick one among many definitions, I plan to find out how teachers, principals, and district administrators I interview and observe in action define technology integration and determine to what degree it is occurring in their locations.  Moreover, I will have an array of standards for technology infusion from which to choose such as the International Society for Technology in Education (ISTE), National Education Association (NEA), National Association of Secondary School Principals (NASSP), and similar organizations.

Another barrier is determining whether the example I describe and analyze in a district, school, or classroom is “good” technology integration. Why an obstacle? Because conceptions of “good” teaching and learning vary among educators and non-educators. Furthermore, because I am not looking at students’ test scores and other common measures of success to determine “goodness,” I cannot say that what I find out about “technology integration” can be attributed to student outcomes, be they high, plateauing, or low.

Then there is the problem of the design and generalizing from what I find. Doing case studies and figuring out to what degree I can generalize about “technology integration” becomes an issue to think through because the sample (districts, schools, and classrooms) is both small and unrepresentative–they are, after all, exemplars of integration. One way around the issue of generalizing is, of course, comparing what I find with other district and school case studies elsewhere in the U.S. The issue is a perennial one when doing case studies.

Add even another obstacle to the list. “Technology integration”–a desired change–is a reform. District policymakers want teachers to alter how and what they teach in order for students to learn more and better than using conventional classroom approaches. In most districts, such a “reform” is often part of a larger package of desired changes that district policymakers seek (e.g., Common Core standards, school-site decision-making, revised budget formulas). Thus, sorting out the effects of “technology integration” on teachers and students becomes very tricky because it is one of many initiatives undertaken in a district or a school. The temptation to attribute any degree of success–however defined–to, say, schools and teachers integrating technology into their daily routines is a common error (see here, here, and here ). I want to avoid making that mistake.

The list of obstacles is incomplete and this post is running too long. If viewers have any suggestions for me as I begin this work—particularly around obstacles that I anticipate–I welcome your advice and counsel.

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Math, History, and Science: Political Battlegrounds in Schools

The previous post offers a re-framing of the math wars that have marked the past century of teaching math. Historians and critics have pointed to the culprits of “curriculum wars” as Progressives fighting Traditionalists (e.g., 1900s, 1960s, now) or the influence of particular “thought leaders” (e.g., John Dewey, James Conant, Ted Sizer). In re-framing these tired tropes, Christopher Phillips points out that these debates about teaching and learning math are,

debates about how educated citizens should think generally. Whether it is taught as a collection of facts, as a set of problem-solving heuristics or as a model of logical deduction, learning math counts as learning to reason. That is, in effect, a political matter, and therefore inherently contestable. Reasonable people can and will disagree about it.

By seeing these cyclical “math wars” as political skirmishes between different interest groups (e.g., teachers, high-tech companies, foundation officials, state administrators, business leaders, parents) disputing which ways are best for teachers to teach and students to learn thinking skills, Phillips makes the case that

[A]s long as learning math counts as learning to think, the fortunes of any math curriculum will almost certainly be closely tied to claims about what constitutes rigorous thought — and who gets to decide.

Overall, I agree. Splits over the teaching of Common Core math standards essentially arise from politics in schooling. But one crucial item is missing from Phillips’ analysis. He fails to mention that deeper and competing values beyond math numeracy are also involved as rival interests collide (e.g., conservative groups’ resistance to the federal government supposed ramming Common Core standards down states’ throats; liberal groups’ insistence that top-down policy decisions to craft higher and demanding standards is essential for students, especially low-income minority ones, to do better academically). Such value conflicts go beyond which ways of teaching and learning skills though math are better. They point to the politics of who decides about adopting Common Core math standards and putting them into practice.

Decisions about what constitutes rigorous thought and the adoption of standards are, then, political. One needs to look no further than the history, design, and adoption of Common Core standards to see how national, state, and local politics of decision-making played out at each level of schooling (see here, here, and here). That teachers, parents, and reformers continue to debate math Common Core standards is evident today as they recycle familiar arguments from earlier reforms (see here, here, here, and here).

As political decisions determine how math is taught in kindergarten, middle school, and Algebra II, so have politics come into play in teaching and learning U.S. history.

In the mid-1990s, the battle over new history standards culminated in a U.S. Senate resolution condemning these new standards. This was neither the first nor last time that political controversy over what history content students should study. For example, the swings between teaching history to cultivate loyalty to nation and civic participation and teaching history as historians practice their craft have occurred repeatedly and remains in play in 2015 (see here, here, here, and here).

Ditto for science. The more obvious political decisions that have occurred over the last century have been over the teaching of evolution and climate change (see here and here). Beneath such controversies, however, have been two distinct purposes for teaching science that have vied for attention over the past century. First, students must come to know bodies of organized scientific knowledge and, second, students must see science in their daily lives. Of the two aims, the former has dominated curricula since the late 19th century, although the latter purpose has been evident in periodic bursts of reform, especially during the past century. As with the teaching of evolution and now with climate change, policymakers have made political decisions on what’s best for students in learning science (see here and here).

The dominance of content divided into separate scientific disciplines is (and has been) obvious in most U.S. secondary schools where science lessons are taught in 45- to 50-minute periods, and where teacher-centered instruction is geared to dispensing scientific information to 25-35 students. The quest to link scientific knowledge to daily life-the second purpose-emerged strongly in the 1930s, and 1990s, occasionally penetrating classroom practice. Schools experimented with reorganizing their age-graded structures, revised schedules, and invented curriculum linkages between classrooms and daily life—“kitchen chemistry”–that differed substantially from what most secondary schools were doing. Over time, such efforts disappeared. Yet now with newly published science standards–a political decision made as competing groups vied for their version of science– there is another progressive impulse in revising curriculum toward linking how scientists work and scientific content to daily life (see here, here, and here).

Decisions on what math, history, and science get taught in schools (and why) end up being political choices that policymakers make.

 

 

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Some Kids Have To Fail: A History of Labels (Part 1)

As long as there have been tax-supported public schools in the U.S., some children and youth have failed.  “Experts,” educators, and policymakers have given names for those students who left school in the late 19th century, early 20th century, and now. And those names for failing students and their early departures from schools have changed over time mirroring reform movements and policy shifts in perceptions of who was (and is) responsible for the failure.

A history of labels for these “misfits” can be summed up quickly: blame the kids for lacking intelligence, blame the kids and their families for not adjusting to schools, and blame the schools for failing students. I describe in a later post where U.S. educators are now in describing those students who fail to fit into the age-graded school.

Students who failed in the late-19th and early 20th centuries

Terms used over a century ago to describe those urban elementary school students who failed academically in their age-graded school focus entirely on an individual’s genetics, character and attitudes. Here were some of the common phrases educators and policymakers used: born-late, sleepy-minded, wandering, stubborn, immature, slow, dull   (PDF DeschenesCubanTyack-1).

Children who left urban elementary schools were mostly children of immigrants and young ( 10 to 12 years old); they went to work immediately in a rapidly industrializing economy. When reformers of the day saw that children were in the streets cadging coins, selling newspapers, and working in factories,they lobbied state legislatures for child labor laws to prevent the young from entering the workforce. Helen Todd, for example, inspected factories in Chicago looking for underage children. She found boys and girls making paper boxes,stripping tobacco leaves, running errands, and shellacking canes in what even then were unsafe and unhealthy workplaces.

Todd asked the young boys and girls would they rather work or go to school if their father had a good job and they did not have to work to bring money into the family. Eighty percent of the child-workers said they would rather work than go to school.Why, she asked? Some answers they gave:

“School ain’t no good. When you works a whole month at
school, the teacher she gives you a card to take home that says how you
ain’t any good. And yer folks hollers on yer an’ hits yer.”

Another told Todd: “You never- understands what they tells you in school, and you can
learn right off to do things in a factory.”

Repeatedly, child-workers told Todd that teachers beat them for not learning, or not listening to teacher or forgetting the correct page (PDF DeschenesCubanTyack-1).

In these decades, the age-graded elementary school (less than 10 percent went to high school then) required students to move through the required curriculum during the school year and learn the skills and content demanded for the next grade. Those children who could not keep up the pace because of language, cultural differences, family issues, or other reasons, performed poorly and soon left school. In effect, the age-graded school produced “misfits,” a retrospective term seldom used then or now.

Early to mid-20th century

With the discovery and development of intelligence testing, a spinoff of mass testing of draftees in World War I, a generation of Progressive reformers applied the lessons learned from sorting adults for the U.S. Army to public schools. And a legion of new terms entered policy-driven reformers’ and educators’ vocabularies (DeschenesCubanTyack-1) to describe children who did poorly in school. Common phrases were:

[P]upils of low I. Q., low division pupils, ne’er-do-wells. sub-z group, limited, slow learner, laggards, overage, backward, occupational student, mental deviates, backward, occupational student. mental deviates, and inferior.

To these Progressive reformers and policymakers, failing students simply did not have smarts. The I.Q. tests confirmed that “fact.” The instructional solution to these students was to teach them different content in a different way in a different place. The language of science provided an objective rationale for sorting students into different curricula (or tracks). And these reform-minded Progressives made the age-graded school even more efficient.

Late-20th to early 21st centuries 

Beginning in the 1960s, especially after poverty was rediscovered by Presidents John F. Kennedy and Lyndon Baines Johnson, “culturally deprived” entered the language of reformers, policymakers, and educators. With many cities now de facto segregated even after Brown v. Board of Education (1954), and obvious inequities existing between social classes  the phrase became code for black, brown, and other children living in urban ghettos. As federal funding of programs sharply increased in the mid-1960s, civil rights reformers fought against applying the label to minority and poor children because of the racism embedded in the phrase: low-income, mostly minority families and children have no culture. By the early 1970s, the label exited reformers’ vocabulary to be replaced by “the disadvantaged.”

With the introduction of “disadvantaged,” the adverb in front of it became contested. Socially disadvantaged? Educationally disadvantaged? The former pointed the finger at families  sending unprepared children to school, thus becoming the prime cause for low academic performance. But the use of “educationally disadvantaged” by reformers brought the school, its rules, culture, and staff under the microscope. This occurred in the late 1970s and early 1980s with the growth of the reform-driven “effective schools” movement. And has lasted since with “No Excuses” reformers in the past decade. Nonetheless, labeling children failing school continued.

By the late-1980s, another term, “at risk,” became popular in describing children and youth that earlier generations had called “misfits.” For some analysts it is a borrowed phrase from A Nation at Risk (1983) and applied to low-income children and youth of color who receive an inequitable schooling. Others see the phrase coming from epidemiology where individuals and groups heart disease, diabetes, lung cancer, and other ills display “at risk” factors. Whatever the source, the phrase is now commonly used among policymakers, reformers, and educators.

So here is a continuing story of different generations of reformers using catch-phrases to salvage the rejects produced by the rigidly organized age-graded schools. Over time, the phrases have morphed from indictments of individual failings to searching examination of the deficit-ridden school in meeting the needs of those who have received (and continues to receive) an inequitable schooling.

The next post looks at the use of “at risk” to describe children today.

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How Small a Part Research Plays in Making and Implementing Educational Policy

Beliefs, opinions, and politics matter more in making policy decisions than applying research findings to schools and classrooms. A recent Canadian study (1905-8719-1-PB ) confirmed what amounts to a fact in U.S. policymaking. Candadian researchers looked at provincial policy elites (in U.S., they would be state-level decision-makers) and district officials (school board members and superintendents) and found across Canada what is very evident in U.S. districts as well: politics and beliefs trump use of research in adopting policies aimed at improving practice (see here and here).

As one would expect in academic circles, the language of applying research findings to educational policies has expanded. Canadian researchers Gerald Galway and Bruce Sheppard note that new phrases have entered the vocabulary: “knowledge transfer, evidence-informed policy, data-driven decision-making and knowledge brokering, to name a few. Knowledge mobilization (KM) has been touted as a useful all-encompassing term because it conveys the notion of direction instead of random interaction and it ’embodies the idea that the use of knowledge is a social process, not just an intellectual task’ ” (p. 9). Whatever phrase is used in Canada or the U.S., the pattern of applying research findings to forming, adopting, and implementing policies remains similar on both sides of the border.

Galway and Sheppard studied “senior bureaucrats” in provincial ministries and local board trustees and administrators at two points in time, 2006 and 2012. They used surveys, interviews,and focus groups to generate the data they analyzed.

A typical response from  “senior bureaucrats” in provincial ministries about research and policymaking was (M refers to “ministry” official):

M1: I guess that what I find with university research is that those who are doing it
appear to be somewhat removed from the immediacy of it all; it’s not engaged, as it
were, and [university researchers are] somewhat reluctant to engage those who are
involved in a particular issue on a daily basis. That’s being pretty general; that’s not
the case with all university research.

M7: Well, I haven’t had a chance to look at anything [university researchers] are
doing so I really don’t know, but I do find that sometimes, just from past
experiences, that the research coming out of (names university) is not always; well
not the research, but some of the conclusions they draw from their research is not
always applicable….

M2: Well, I don’t really know about it, to be truthful. As I was saying earlier that’s
one of the things that is most surprising to me; that with the amount of research that
is done at the university, how little discussion or impact it’s had on my work as the Minister in this portfolio.

When the researchers turned to trustees–district school board members–survey results and focus group interviews in the 2012 study produced a list of factors that influenced their making of policy.

[W]e presented trustees with 20 potential factors/influences and asked them to
indicate on a seven- point scale, the extent to which each has had an effect on specific decisions or
recommendations that they have made as trustees…. The principal six factors are as follows:
(1) personal or professional beliefs and values,

(2) potential to directly influence student
outcomes/student learning,

(3) advice of district staff and/or colleagues,

(4) the school board’s strategic plan 

(5) past experience.

Trustees and superintendents rated the following six factors as having the least influence on decision-making (my emphasis):

(1) representations of business/private sector,

(2) pressure from special interest or lobby groups,

(3) a situation or event someone told you about,

(4) pressure from government (ministry/department of education),

(5) public opinion/avoidance of negative media attention

(6) university-based research.

Analysis of the data by province showed very little variance in the factors and evidence that influence school board decision-making across jurisdictions.

The Canadian researchers conclude:

We conceptualize use of low research impact partly in terms of trust vs. risk avoidance. In
both policy contexts – provincial departments of education and school boards – we conclude that
decision-making is ambiguous and risky…. [I]n uncertain times, decision-makers value knowledge that is familiar and emerges from their
own community…. This information – now repackaged in the form of staff advice – becomes privileged
and trusted by ministers and senior bureaucrats as authentic knowledge….
readjustment.

Very little found north of the border, then, differs greatly from what U.S. researchers have found in the 50 states (see here, here, and here).

So what?

Keep in mind that none of the above critiques of limited influence of research on policy is restricted to public schooling. Making policy in systems of criminal justice, environmental improvement–think climate change–and health improvement and clinical medicine–think of TV ads for drugs–are subject to similar political factors and personal beliefs rather than what research has found. Calls for more collaboration between university researchers and policymakers have also been heard and ignored for decades. Critics have pointed out many times that the academic culture and its rewards overlap little with the world that decision-makers face every week.

I wish I had a neat answer to the “so what” question and offer a package of do’s and don’ts for those who want evidence-based policymaking.  I am on the lookout for such advice but thus far I have come up empty. The fact is that beliefs, opinions, and politics matter more in making policy decisions than applying research findings to schools and classrooms.

 

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Technology Evangelists, Skeptics, and Those in the Middle

In a recent post from EdSurge (November 5, 2015), the following graphic was shown:

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The text in EdSurge accompanying the graphic said:

Everyone loves a good metaphor–and this week, New Jersey principal Jon Cohen made us think with this “pencil metaphor” graphic posted via Twitter, describing the educator spectrum of edtech lovers and resistors [sic]. Where does your school fall? Do you have a lot of leaders, or or are you struggling to convert the “erasers”? We bet this newsletter can help you “sharpen” your skills, even though we all … suffer a few breaks now and then!

EdSurge evangelizes for more and better high-tech use in schools. They ask entrepreneurs and hard-core advocates of more devices in schools to listen to both students and teachers before marketing their particular mousetrap to the world. But this post is not about EdSurge. It is about two graphics, the one above and one below.

330px-Diffusion_of_ideas.svg

I begin with the pencil graphic. While titled “Integrating Technology in Schools” it slams all those teachers and principals who do not leap on the latest high-tech bandwagon careening through school boards and superintendent offices. The graphic assumes that all high-tech innovations are positive for both teachers and students. Those who wait and ask questions are labeled “resisters.”

The “leaders” and “sharp ones” at the pointy end of the pencil are the early adopters, implying that they are both smart and astute about teaching and learning while those further down the pencil’s shaft–the “wood” and “hangers on”–are way behind the curve as adopters. Then those at the “ferrule” and “eraser” end of the pencil are active resisters, even enemies, of using tech in the classroom. This is, of course, nonsense but it does mirror many an evangelist’s view of teachers and students using (and not using) devices and software in schools and classrooms. The title is a misnomer since nothing here is about “integrating” high-tech into school routines or classroom lessons.

The pencil graphic, at best, is a warped version of Everett Rogers‘ “diffusion of innovation” graph that he had published in his 1962 book (it is in its 5th edition now). Diffusion of Innovations has been a staple of those interested in institutional and sector innovation across agriculture, medicine, health care, business, and, naturally, education for over a half-century. But, at worst, the pencil graphic is an unfunny indictment of those teachers, students, and parents who raise questions, express skepticism, and lay out reservations about the wisdom of mindlessly adopting the next new thing produced for schools and classrooms.

Now, look at Roger’s graph of adopters. Rogers avoided the loaded words used to describe adopters except for “laggards.” in the U.S., few teachers would puff out their chest after being called a “laggard.” Rogers was aware that the graph he constructed prized innovation–that it is “good” to adopt a new idea, practice, or technology– and possibly from that core assumption, the word “laggard” snuck into the categories. The five categories Rogers created roughly map onto the “pencil” but note the far more negative and positive language in the pencil graphic.

For each category, there are many examples among teachers. The sixth grade teacher who bought and brought into her school the first Mac machine was an innovator. The first teacher in a building who designed a piece of software just for her class is another innovator. Early Adopters are those teachers who first tried out email, spread sheets, iPods, iMacs, laptops, and tablets in their classrooms shortly after they heard about them or the district technology director invited teachers to demonstrations of the hardware and software. As the number of teachers seeing colleagues using devices and software spread, more teachers asked those early users how it worked, for what kinds of lessons they were used, and even watched the tools being used in lessons. In many schools, two-thirds of the teachers (Early and Late Majority) became occasional (weekly or monthly) to daily users. In short, these teacher-users became the middle of Rogers’ graph. In every school, however, there were non-users and reluctant participants–“laggards,” in Rogers’ phrase.

Seldom did the categories and percentages of “innovators” to “laggards” map perfectly onto specific schools or districts. What Rogers built was a map for researchers and practitioners to use in understanding how innovations–again, a positively charged concept in U.S. culture–spread across sectors and in institutions. It is a heuristic, not GPS directions for innovators.

Evangelists would find the “pencil” to their liking because of the shared assumptions under-girding the clever graphic. Those assumptions are dominant in the U.S. where if you do not have the latest device or software, eyes roll or snide comments get said. Evangelists for technology seldom engage in reflection because they are true believers. True believers seldom entertain questions or skepticism because they are often taken as an attack upon bedrock principles.

And for teachers, principals, parents who ask questions or raise issues about the new technologies, they risk being called resisters, an epithet that in U.S. culture, enamored with innovation and technology, is akin to the Scarlet Letter.

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More Magical Thinking about Technology in Schools

I watched the World Series and saw both New York Mets and Kansas City Royal fans wearing hats, shirts, and displaying signs designed to get their teams to win. I saw similar clothes and painted faces on soccer fans during the World Cup. The belief, the intuition that these caps and jerseys would get their teams to win borders on superstition. And most fans would agree. Yet, yet, yet just maybe wearing the stuff, painting the face, and holding signs aloft would be just the thing that would snatch defeat from the other team. As a recent op-ed put it: fans “have an powerful intuition and, despite its utter implausibility, they can’t just shake it.”  The contradiction is aptly caught in the title of the opinion piece: “Believing What You Don’t Believe.”

This is no rant, however, about how emotion trumps reason or how thinking thoughts (or fans waving signs) will produce the desired outcome. Nor will this post elaborate how our cognitive “slow” and “fast” thinking ways do not always work in sync or that our “slow thinking” will correct the impulsive move where we have “trusted our gut. ” In this post, I again look at how local, state, and federal policymakers, high-tech entrepreneurs, and CEOs of major corporations engage in “magical thinking.” Inhabiting a technocratic mind-set, these leaders who rely on experts  believe that more and more use of high-tech tools will provide the adrenaline shot for U.S. schools to match international rivals’ test scores and lead ultimately to a larger share of the global market for U.S. goods and services.

I offer two examples of high-tech industry and civic leader aspirations to link all public schooling to the job market and larger economy that highlight this phenomenon: MOOCs and every child learning to code and taking computer science courses.

MOOCs

Massive Open Online Courses burst on the scene three years ago with claims that such courses offered free to anyone on this planet with an Internet connection will–here come the key words–“revolutionize” and “transform” higher education.  John Hennessey, President of Stanford University, said a “tsumani is coming.” Equity and excellence, values that both liberals and conservatives cherish, will be fulfilled. Nothing of the sort happened (see here, here, and here). In the Gartner “hype” cycle, MOOCs are buried in the “slough of disillusionment.” All within three years. High-tech hyperactivity has compressed time into bytes.

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Coding and Computer Science

Young children learning to code in elementary schools while their older brothers and sisters take computer science in high school is currently in the “Peak of Inflated Expectations” in the above hype cycle. Consider that the British government has gone even further than the mania gripping the U.S. by mandating in its national curriculum that all UK children learn to code and take computer science in their secondary schools (see here and here).  The UK “computing” curriculum is, of course, a national experiment in further vocationalizing public schooling to tie education to the economy. With no national curriculum in the U.S. (Common Core state standards is a pale, decentralized version of such an effort), the surge of interest in coding (e.g., Year of the Code, next month’s celebratory week of Computer Science, coding boot camps), much of it financed by tech industry giants, has seized the spotlight of attention. That attention has shifted from every student having access to computers in school–very close to being a fact in the U.S.–to using these devices in classroom lessons. From kindergartners getting lessons on coding to online courses to blended learning to flipped classrooms, the mania for computers in schools has corralled both public and private funding as the high-tech solution to students becoming equipped with 21st century skills.

To be clear, I do not refer to those tens of thousands of teachers and principals who, with care and thoughtfulness, have slowly integrated their devices and software into lessons to teach content, skills, and creativity. They keep their heads down and often escape the mania I refer to above.

So is there anything intrinsically wrong with pushing coding and computer science in U.S. schools? After all, both are being sold to school boards and parents as ways of teaching logic, thinking skills, as well as preparation for future jobs.  So on the surface, nothing appears to be unseemly. Underneath the surface, however, are two matters that often go unnoted by advocates of coding and computer science.

First, the original trio of goals for computers entering schools and classrooms since the early 1980s were improving academic achievement of students, altering the traditional patterns of teaching and learning, and preparing the next generation for the labor market. Nowadays, few champions of computers in schools even mention academic achievement or talk of “transforming” teaching and learning through laptops and tablets. But the vocational goal does remain in the current joy for teaching children and youth to write code and create algorithms.

Second, is the historic pattern of focusing on public schools as a national problem to be solved (think segregated schools, national defense, drug and alcohol addictions as problems that schools could “solve”) and seeking another “technical” solution to its ills. In this instance, injecting coding and computer science, online instruction into K-16 schooling. Such a technocratic strategy aims to alter traditional curriculum and lessons for one over-riding purpose to get ready for an ever-changing, fast-moving job market and economy.

So here again within a few years, “magical thinking” about the power of technical products to tie schools to the economy via coding and computer science has arisen even in the face of the dramatic shift in goals for these high-tech products over the past three decades and the failure of MOOCs to gain traction in higher education since 2012.

The feel-good attitude of World Series and World Cup fans who wear jerseys and hats believing that to do so will help their teams win is alive and well in the high-tech community.

 

 

 

 

 

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Filed under school reform policies, technology use