Category Archives: technology use

We Got the School Reopening Story Wrong (Nat Malkus)

Nat Malkus is a resident scholar and deputy director for Education Policy Studies at the American Enterprise Institute. The article appeared in The Hill October 20, 2020.

“It’s the politics, stupid” may be the aphorism for our times. In the age of Trump, the seductive narrative that uber-polarized identity politics can explain everything, including reopening plans for schools, appears obvious. After all, the president repeatedly proclaimed that schools must reopen, and for monthspolls have shown pronounced partisan divides on whether students should return in-person or not. While we still don’t have a full accounting, early analyses indicate that schools in Trump country are more likely to be back in-person this fall, often despite high COVID rates.

Partisan politics is a familiar and intuitive, but ultimately inadequate explanation for school reopening patterns.

close examination of emergency remote learning in spring 2020 reveals large differences between Red, Blue, and Purple states, with Red states often coming up short. Those gaps are due in part to challenges which still exist this fall. National political theater undoubtedly affects local reopening decisions, but it is a poor explanation for why more Red states’ schools are returning in-person — not only because it ignores the differences in remote learning Red states provided last spring, but also because it cannot explain them.

After spring closures, about a third of schools in Red states offered students synchronous learning platforms, like Zoom, compared to about half in Purple and Blue states. Assistance with devices and internet access were also much lower in Red states. Thus our common mental picture of remote schooling — students connecting to teachers through online video instruction — was less common in Red states, and their students undoubtedly suffered. Gaps extended beyond technology, because fewer schools in Red states expected one-on-one contact between students and teachers, posted explicit expectations for student participation, or took attendance after buildings were closed (which turned out to be a quarter of the school year).

There are plausible explanations for these differences. Broadband access — the vital infrastructure for online learning — was far lower in Red states. The digital divide is even more pronounced in rural areas, which are more common in Red states. Of course, many districts laid out substantial sums to bridge that divide, but building that bridge was not only more expensive and time consuming in Red states, the payoff would be lower because their school years end earlier. These are not just excuses: They are structural reasons why well-intentioned district leaders, not partisan ideologues, made rational decisions that lead to different outcomes.

Remote learning was rough everywhere last spring, but it was rougher in Red state districts. Against that backdrop, their tendency towards in-person reopening this fall looks more pragmatic than political. Summer polling showing that Republican-leaning respondents were more concerned about students falling behind pushed in the same direction, but school leaders did not need polls or survey evidence to see the damage done to their students last spring. With no quick fix for broadband access this fall, it is understandable that they disproportionately saw providing the option to return to in-person learning as the best way forward.

You may find this logic wholly unconvincing when politics is a simpler, more familiar alternative. It is possible to look at this evidence and still believe politics influenced Red states inhabitants’ expectations about the length or threat of the virus, which caused remote learning differences last spring and still drive reopening decisions this fall. However, if political polarization explains schools’ pandemic responses in the fall, it should also explain the actual differences evident in Red states in the spring.

Politics alone is a weak explanation for those differences. All school districts in Red, Blue, and Purple states shut down in the spring, and all districts retooled their schools to provide remote learning platforms. Red, Blue, and Purple states diverged in the kinds of platforms schools offered, and there is nothing inherently political about providing lessons on Zoom or using alternatives like Google Classroom or instructional packets.

Structural factors, like broadband access, shorter school years, and more rural students, are more directly connected to the forms of learning offered in the spring. Those non-political factors combined to produce less effective remote learning in Red states in the spring, created yet another compelling reason for pragmatic school leaders to prioritize in-person reopening so that students could make up lost ground.

If “It’s the politics, stupid” cannot explain the differences seen in remote learning last spring, we should doubt its power to explain reopening this fall.

In this age of polarization, nearly every aspect of our lives is colored by politics, and questions about reopening schools are no exception. But rank politics is better for selling papers and enflaming indignity than adequately explaining professional decisions.

The future may show that returning in-person this fall proved foolish, or that returning remote was excessive caution that cost students dearly. Until then, we should remember that most school leaders are making difficult decisions in good faith while considering a host of factors ahead of politics, like they did last spring.

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Whatever Happened To Vocational Education?

Where and When Did Vocational Education Begin?

In the mid-19th century, school reformers made the distinction between the head and hand learning in children and youth–both had to be schooled. After the Civil War, reformers introduced “manual education” into schools. Working with tools to fashion wood, iron, and other metals into useful objects, balanced the nearly total focus on academic subjects (see here and here). While adding such courses to the high school curriculum was common in the closing decades of the 19th century, separate manual training high schools in cities were also built such as the duPont Manual High School in Louisville (KY), Manual High School in Denver (CO), and Armstrong Manual Training School in Washington, D.C.

But the economy that welcomed artisans in carpentry, brick masonry, and farriers was shifting to industrial workplaces where different skills and different gatekeepers to jobs were needed.

In the early decades of the 20th century, business and civic leaders called for a different kind of “hand” schooling to prepare youth for newly created industrial and manufacturing jobs as machinists, iron and steel workers, etc. Many of these leaders had visited Germany, a global competitor now outstripping the U.S. in selling its products. They saw how Germany had established vocational education and apprenticeships in secondary schools and how these schools provided a ready supply of workers fitted to a rapidly changing industrial economy. By World War I, U.S. high schools had added “vocational” subjects to the academic curriculum and districts opened newly established, separate vocational schools.

What Problems Did Vocational Education Intend To Solve?

incorporating vocational education into the high school curriculum sought to solve two problems. First, the wholly academic curriculum of the 19th and early 20th century high school drove most students to dropping out of school while in grammar school (grades 1-8) or immediately after graduating. Adding work-related courses that could equip students with workplace skills and lead to actual jobs enticed students to continue going to school. In a democracy, Progressive reformers wanted the high school to educate all students, not just to those who prepared for college.

Second, public high schools with their concentration on academic subjects were largely divorced from the economy. As the nation became an industrial democracy, Progressive reformers pressed for a better fit between schools and the economy. In 1917, the Smith-Hughes Act had the federal government for the first time funding local schools that introduced vocational subjects into the curriculum for both boys and girls. Since then the federal government and states have repeatedly legislated vocational education as a key part of work training in U.S. high schools. Thus, Progressive educators were victorious in adding the goal of vocational preparation by the 1920s (see here and here).

Third, racial discrimination dominated the ways of bringing Blacks into industrial and skilled jobs within a highly segregated society that dictated what Blacks and whites could do for a living (e.g., trade unions banned Blacks from entering apprenticeships and journeyman postions through mid-20th century).

In the decades following the Civil War, vocational education in the Black community had a model to follow in the work of Samuel Armstrong at the Hampton Institute in Virginia and Booker T. Washington at Tuskegee Institute in Alabama. The vast majority of Blacks lived in the South and were tenant farmers renting acres from white landowners within a rigid racial caste system. The Hampton and Tuskegee models prepared craftsmen and women for a largely agricultural economy that was slowly shifting to an industrial one–the emphasis is on “slowly” between 1870-1930.

Subsequent reformers kept channeling minorities into vocational courses even after the Brown decision thereby continuing that school-based segregation (see here).

What Does Vocational Education Look Like in Classrooms?

Here are some classroom photos from early 20th century:

With policy criticism of vocational education as a dumping ground for minority students accelerating since the 1960s, especially after A Nation at RIsk report appeared in 1983, federal and state efforts to merge academic and vocational skills together in acquiring not just jobs but pursuing careers led to a re-casting of vocational education classes into Career and Technical Academies (see here and here)

Did Vocational Education Work?

The effectiveness of vocational education since the mid-20th century has been contested by both policymakers and researchers.

One measure of effectiveness has been getting actual jobs in the specific fields that students prepared for (e.g., trade and industry such as auto repair, electrician, brick mason, . Another measure has been preparation for a suite of jobs in the vocation or career (e.g., business, health care, sales, information technology, human service occupations). A third has been to increase participation in vocational education and career and technical education. Researchers have reached negative, positive, and mixes of both conclusions (see here, here, and here).

At best, then, the research on effectiveness of vocational education remains contested.

What Happened to Vocational Education?

Since the early 1980s, it has had major surgery. Today it is called Career and Technical Education (see here). Major infusions of donor and federal funds has re-made CTE in a darling of policymakers, especially after the merger of academic and vocational experiences that opened up routes to higher education than had ever existed under the aegis of 20th century vocational education. With the policymaker mantra that everyone goes to college, CTE leaders march in cadence to that slogan.

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As More Students Head Back, Here’s What We Now Know (And Still Don’t) about Schools and COVID Spread (Matt Barnum)

This article appeared in Chalkbeat, October 22, 2020. Matt Barnum is an education journalist.

Two months ago, Ashish Jha, the dean of Brown University’s School of Public Health, was something of a school reopening skeptic. In places with relatively high COVID rates, like Florida and Texas, K-12 school buildings should stay shuttered to protect the health of teachers, students, and their communities, he argued.

Now, his view is changing.

“The evidence so far suggests that we can likely open schools — especially K-5 — pretty safely in most parts of the country,” he said, as long as those schools take precautions like requiring masks. “I’m getting slowly but surely persuaded that I may have been too cautious.”

That’s because where schools have reopened, things have gone relatively well, as least as far as scientists and public health officials can tell right now. Many European countries have reopened schools with apparent success, too. That consensus is pushing more schools to reopen buildings, even as case counts rise across the country, and is driving increasingly confident claims that there is little or no relationship between schools and COVID spread.

It’s also true, though, that the existing evidence is still limited, and some epidemiologists say it’s simply too soon to reach firm conclusions.

There has been no effort from the federal government to systematically track school openings and COVID outbreaks. That means we are often relying on data from those who volunteer it, and lack good information about how schools that have reopened might differ from those that have not.

Then there is the inherent difficulty of the project: It’s tough to isolate the effect of a single factor like school reopening on community COVID spread, particularly when testing data is also limited.

That tension — more data, but all of it limited — is at the heart of the school reopening debate right now, several epidemiological and education researchers suggest. Jha, for one, is optimistic.

But, he cautions, “The strength of the evidence here is shaky.”

The case for school reopening

As more and more schools across the country have reopened their buildings, many local officials say they haven’t seen a strong connection to COVID spread in their communities and that outbreaks have been relatively rare, unlike what’s happened at many universities.

In New York City, random tests of over 16,000 staff members and students turned up only 28 positive results.

In Colorado, 43 schools — out of more than 1,900 in the state — have experienced outbreaks in which public health officials documented transmission within the school building since schools began reopening in late August.

Nationally, among over 1,000 schools voluntarily reporting data, test positivity rates are very low: 0.14% among children and 0.36% among staff.

“A lot of people expected, oh, we would have 100 cases of COVID day one — and places aren’t seeing that,” said Preeti Malani, the University of Michigan’s chief health officer, referring to K-12 schools. “They’re not closing down. They’re able to find a way to continue on.” That’s pushed her to believe that schools generally can and should reopen.

A national study of childcare providers showed that those who continued working were just as likely to say they had contracted COVID as those who stayed home.

Reopenings seem to have gone well in many European countries, too. In Germany, one of the most rigorous studies on the question found reopening schools was actually linked to lower, not higher, rates of COVID spread.

It’s also clear that children are less likely to suffer severe symptoms from COVID, and deaths among children are very rare (although Black and Hispanic children have been disproportionately affected).

A recent overview of research from around the world concluded that “widespread transmission can occur among school-age children, but that there is very little evidence, at least in the context of relatively low community transmission, that schools have been a driver of transmission.”

Jha says the growing collection of data points has swayed his opinion. “I’ve got eight or 10 pieces of data, every one of which is super weak — but they’re all pointing in the same direction,” he said.

There is also largely undisputed evidence that school closures do major harm to students, academically and otherwise.

“Not only are there benefits to being in school, there are also risks of not being in school,” said Sarah Cohodes, an education researcher at Teachers College at Columbia University.

Instances of child neglect have likely gone unreported. Children are more socially isolated.And they have missed months of in-person instruction, with uneven remote learning. One recent study out of Belgium, using actual student test scores, showed sharp declines in learning.

“The evidence in terms of learning is clear — that learning is better in person, especially for younger children,” said Cohodes, who has compiled research on a number of aspects of COVID and education.

Alicia Riley, a postdoctoral scholar in epidemiology at UC San Francisco, goes further, noting that some prior research has even found that more education helps people lead longer lives. In other words, keeping schools closed may have its own long-term deleterious effects on health.

“Our concepts of safety — we’re only calculating in the COVID risk,” she said. “But if we’re thinking about the real long-term health harms, schooling is protective for health.”

The case for reopening caution, and better data

Some epidemiologists view the same data with more wariness.

“I think it’s premature to say that school reopening has been successful. For a start, it’s an ongoing process linked to what’s happening in the community generally,” said Zoë Hyde, a senior research officer at the University of Western Australia. “If community trans mission rises, then you will see outbreaks in schools. This has become very apparent in Europe as they battle their second wave.”

A number of experts are concerned that we’re not getting a full picture because of incomplete testing. “While we know we are only seeing part of ‘the iceberg’ of all infections, we don’t know exactly how much of that iceberg we are seeing,” said Kim Powers, an epidemiologist at the University of North Carolina.

That may be particularly concerning with children, who are often asymptomatic and thus less likely to be tested. “It’s quite likely that we’re not spotting a lot of the infections which are occurring in children,” said Hyde.

“If we’re just doing symptomatic testing and we’re only counting cases in which kids are symptomatic, it’s kind of impossible to trace this adequately and to really understand what’s going on,” agreed Riley.

Meanwhile, there’s general agreement that existing data is insufficient, and that it can be difficult to generalize the conclusions.

The tracker of COVID test results from schools being compiled by Brown researcher Emily Oster and others, for instance — the most comprehensive national database available — is only able to include the fraction of public schools that voluntarily provide information, with results that may not be representative. The study of childcare workers was also based on an online survey that the researchers described as “not fully representative.”

Other international research acknowledges that it simply cannot disentangle the effect of school reopenings from many other factors. Pinning down how outside factors — low rates of community spread, many students staying home, mild temperatures allowing for open windows and good ventilation — might have contributed to success stories could guide school officials elsewhere.

There is also some evidence on the other side of the ledger, though it comes with its own caveats. Data compiled by the American Academy of Pediatrics show that the number of children with new COVID cases has been rising slightly in recent weeks, though that doesn’t mean cases are necessarily linked to schools.

Idaho has seen upticks in cases among children and adults, with the governor saying reopened schools has been one factor. In suburban Salt Lake City, a school district saw cases rapidly emerge at some of its schools, forcing a shutdown of three high schools and a middle school. In different parts of the country, reported COVID cases in schools or among school staff have continued to tick up, though the numbers appear relatively low overall.

A recent Swedish study found evidence that COVID infection rates were higher among teachers (and their partners) whose schools didn’t close this spring, compared to teachers whose schools did close. (Notably, mask use in schools did not appear to be widespread at the time.)

“The overarching message is that the evidence is still evolving and pretty scant,” said Rebecca Haffajee, a health policy researcher at RAND.

Meanwhile, reopening buildings right now comes with its own often unacknowledged trade-offs. Since many districts are still allowing students to learn from home, and some only allow students in a few days a week, teachers have had to divide their attention between students who still learn virtually and those who are in person. It also means time and energy is being spent on building safety rather than improving the online instruction that many students will still rely on.

Ultimately, there is widespread agreement among experts that more and better data is needed to help school leaders make decisions.

Cohodes described it as “absolutely ridiculous” that researchers have been left trying to collect data on their own. “The federal government should have set out guidelines for collecting this and worked with state departments of education,” she said.

“All of this is frustrating to me because we’re in such a weak data zone and we should have much better data,” said Jha.

Just this week, though, Education Secretary Betsy DeVos described this as not her job. “I’m not sure there’s a role at the department to collect and compile that research,” she said.

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Does Classroom Use of Computers Cause Gains in Students’ Academic Achievement?

A decade ago when a surge of interest in placing computers in classrooms was joined to available public and private money, U.S. schools went on a rampage of buying and distributing devices to students and teachers. At that time I wrote a post about a puzzling fact that was overlooked  or simply ignored:  With increased access to new technologies, there is little reliable and valid evidence showing that these technology investments have yielded gains in student achievement.

That was then and this is now. Amid a pandemic-induced shift of face-to-face lessons to online instruction, the question is irrelevant. The need is that every single public school child must have a device to use for remote instruction.

While there was certainly a digital divide a decade ago even amidst the splurge spending for devices, school closings due to the pandemic have pushed districts to triple-time distribution of devices and Internet connections to families lacking either or both.  Yet, the lack of solid evidence that student computer use–especially now when lessons are online–is strongly associated with increased test scores and other academic outcomes remains puzzling. So I updated that post and publish it now.

After decades of school and classroom use of new technologies, some facts have emerged that puzzle me.

Here’s one.

Since the early 1980s, the federal government, states, and districts—not to mention philanthropists—have invested billions of dollars in wiring schools, buying and deploying machines, and preparing teachers and students to use high tech devices. Nearly all teachers now have access to one or more computers at school. As for students, the number of students per computer across the U.S. has gone from 125 per computer in 1983 to 4 per computer in 2006. Teacher and student access to computers has increased even more in the past decade with thousands of schools issuing computers to each and every student and teacher.

With increased access to new technologies, there is little reliable and valid evidence showing that these technology investments have yielded gains in student achievement.

Why?

One answer is simply that access to machines does not necessarily lead to teachers regularly using high-tech devices in daily lessons. Consider that after nearly 30 years of access to computers in the U.S., based on national surveys and research studies of schools, over 60 percent of teachers are regular users, that is, using computers for instruction one or more times a week (see here). These teachers use interactive white boards, laptops, and hand-held devices to have students do Internet searches, turn in typed rather than hand-written homework, take notes on lectures, watch videos, and other familiar classroom activities. A small sub-set of these teachers, however, do use electronic devices weekly, even daily in far more creative and imaginative ways inside and outside classrooms with their students.

But the majority of teachers, most of whom–paradoxically–use their home computers a few hours each night, are either occasional or non-users in integrating available machines into their daily lessons.

So one explanation for the first puzzling fact is the flawed assumption that deploying computers to teachers and students will lead to teachers regularly using high-tech devices for instruction. Note that without regular use by teachers, establishing either a correlational or causal link between computers and, say, student test scores, is impossible.

Another explanation for the puzzle of so little linkage between computers and student achievement examines how researchers go about studying the connections between technology and student outcomes.

Many researchers fail to consider that the common designs and methodologies they use to determine linkages between classroom technology use and student achievement cannot capture the inherent complexity and unpredictability of teaching and learning. So researchers use shortcuts to get around that complexity and unpredictability.

I need to unpack the previous sentence. Consider that teaching students involves many factors relating to who the teacher is, what content and skills are taught, and what activities and tasks occur while teaching. Also consider student factors: who they are, what experiences, motivations and interests they bring to the classroom, and what they do during lessons. Then consider the school itself, its organization, culture, and its neighborhood. Finally consider the district, its resources, leadership, and culture of learning or non-learning that it cultivates. All of these interacting factors, sometimes unpredictably, affect classroom teaching and learning.

Yet look at the majority of research designs and methods used to determine the effects of teachers using computers with student. Most common are surveys of teachers and students who report their perceptions of classroom use supplemented by researchers’ descriptions of practices, and interviews with teachers and students. Some researchers set up comparison groups of classes that use computers to study a topic with classes not using computers studying the same topic. Then the classes using and not using computers are pre- and post-tested.

Both research designs have serious defects. Short of establishing an experimental and control design with students and teachers randomly assigned to each group, it is nearly impossible to establish a causal linkage between the use of high-tech devices and student achievement. Such experimental or quasi-experimental designs are uncommon and usually too expensive to mount.

Because surveys, class-comparisons, or studies of small groups of students using computers are less expensive in dollars and labor, thousands of studies have been done since the introduction of desktop computers into schools in the early 1980s. Many show minute gains or “no significant difference” in test scores from student use of computers. The results, however, are correlations—associations between presence of computers and gains in test scores, not evidence that student use of the machines caused a rise in test scores (see here).

Here, then, are two ways to make sense of the puzzling fact over the paltry results in student outcomes of so much investment in high-tech devices and so little return on those dollars.

When one shifts to the evidence of online instruction being associated with academic achievement gains, a similar story unfolds.

A brief look at the many K-12 and higher education studies that have sought an answer to the question of the effectiveness of online instruction in producing student gains in achievement may help readers.

Scores of studies of outcomes for online instruction have been contested because most have had serious design and methodological flaws. Moreover, many of these studies lumped together full-time virtual schools, hybrids, and online courses, And the results have been underwhelming.  That is where heartburn enters the picture (see here).

Even when researchers over the past few decades have performed meta-analyses of a smaller number of studies that have met higher standards of quality they found that virtual instruction in its various modes, at best, is equivalent to regular face-to-face classroom instruction. At worst, some studies showed less achievement gains than traditional teaching. And keep in mind that these meta-analyses were of studies where online instruction occurred in mostly math, reading, and science courses—not other academic subjects. Nor in areas of great concern such as kindergarten and primary grades, the arts, and social and emotional learning. The overall picture is considerably dimmer than promoters of full- and part-time virtual schooling have promised or leaders had expected. *

So with such little evidentiary support for huge expenditures of school budget funds for hardware, software, maintenance, and professional development, why keep buying the stuff?

There was one explanation I omitted when I wrote this post in 2010 because it did not register with me then but over the following years has emerged as a powerful reason for more classroom use.

The rationale for giving devices to every student and teacher has shifted from linkage to student outcomes to the simple fact that all standardized testing will be online.  With the Covid-19 pandemic, insuring that every student had access to a device and the Internet took precedence over teacher’s decisions to use or not use devices for their lessons. Until in-person schooling resumes for most U.S. students, all lessons will continue to be online–for better or worse.

____________________

*Cathy Cavanaugh, et. al. “The Effects of Distance Education on K–12 Student Outcomes: A Meta-Analysis.” 2004 Naperville, IL: Learning Point Associates ; Rosina Smith, et. al.  “A Synthesis of New Research on K-12 Online Learning”. 2005, Naperville, IL: Learning Point Associates; Barbara Means, et. al., “Evaluation of Evidence-Based Practices in Online Learning: A Meta-Analysis and Review of Online Learning Studies,” (U.S. Department of Education, Office of Planning, Evaluation, and Policy Development, 2010).

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“We Can Only Hope” (Terence Freeman)

Freeman is an English teacher at Lawton High School in Lawton, Oklahoma. He has taught 14 years at the U.S. Military Academy at West Point and 26 years at Lawton High School. This story appeared in the Washington Post’s online article, October 6, 2020. Freeman is one of nine teachers the newspaper asked to report on their experiences in returning to remote and in-person instruction during the pandemic.

Hope was on my mind in the summer months leading up to this academic year. I hoped the school had plans and funding for sanitizer, cleaning liquids, paper towels, masks, teacher testing and more; hoped that I and my students would remain healthy; hoped that I could still have the personal relationship with students that enables learning to happen.

I will remember Hands. During Week 2, I took my classes to the library, where the district fulfilled its promise to provide every student with a Chromebook. I now had the option of having students read from a website or from a paper textbook. Call me old-fashioned, but there’s nothing like the heft and texture and tangibility of the printed text.

Yet I worried about students in successive classes touching the same books. So I went on Amazon and ordered three large boxes of nitrile gloves. I’ve placed a pair for every student in a baggie with her or his name on it, and the baggies are stored in separate boxes in the classroom. The students enter the room, wipe down the desks I have sprayed with liquid cleaner, wash their hands with sanitizer, grab the assigned baggie, put on the gloves, grab the book on the desk, read and at the end of class put the gloves in the baggie and the baggie in the box. A terribly makeshift solution, but one that’s been enthusiastically received and executed by the students. They and I each do what we need to do — that’s the can-do spirit of an American.

I will remember Obstacles. Two-thirds of our students elected in-person education. Some technical adjustments were relatively easy — cold breakfast in the classroom, wiping down desks before each period, sanitizing hands, distancing between desks. Masks were harder — not the wearing, but the communication.

On the first morning of school, gloved and masked, I helped do a security check of students’ backpacks/bags/purses before passing the students on through the metal detector. All of the students were masked, and I quickly realized how important our faces are to communication, to the recognition of emotion. A cheery greeting from me, if I got a response at all, generated a reply whose emotional content was muffled, distant, cold. I have had the same experience in class. Conversations involve both hearing and observing, and the masks impede the observations. I and my students have needed to work harder to emote through our eyes and voices.

I will remember the Probe. In Week 3, I took advantage of a free coronavirus test offered by the state’s health and education departments. I made my appointment the day before, showed up 10 minutes early and was the second school employee at the location. The testing equipment beat me to the scene but, unfortunately, the nurses did not. Teacher after teacher arrived at the room, and we milled around in the hallway, awkwardly chattering and trying to maintain social distance.

Thirty minutes after my arrival, two nurses arrived — one female, one male. In due course, I was seated before the male nurse, who proceeded to make a minute-long speech that I understood nothing of — these masks are truly a pain. The insertion of the probe was uncomfortable, the nurse’s count to five unnecessarily slow and the aftermath a slight burning and a watery eye. I high-tailed it back to the classroom and beat the first of my 18 students by about 30 seconds. I used a Kleenex to dab the watery eye — one must maintain one’s image, after all. A result came the next day: “Not Detected.”

I will remember the Extra. On the third day of school, I learned that my Advanced Placement students would have the option of getting a virtual education. I tried hard to find a magic bullet, but the programs and technology suggested to me over the summer would, I came to believe, only allow me to offer a significantly limited version of the in-person curriculum I have developed over the years. So I have found myself trying to construct that limited version (at the moment, for eight students) while at the same time conducting the in-person version. In essence, I feel as if I am being tasked to be two teachers — me and Extra Mini-Me.

So there it is — my first weeks at school. Hands. Obstacles. Probe. Extra. H-O-P-E. I am reminded of the poet Basho: “Every day is a journey, and the journey itself is home.” We can only hope.

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“I’m Hopeful for a Better Tomorrow” (Justin Lopez-Cardoze)

Lopez-Cardoze is a seventh-grade science teacher at Capital City PublicCharter School in Washinton, D.C. He has taught for nine years.

This story appeared in the Washington Post’s online article, October 6, 2020. Lopez-Cardoze is one of nine teachers the newspaper asked to report on their experiences in returning to remote and in-person instruction during the pandemic.

It was the first day of school with students. After eight years of first days, you would think I would feel calm and confident on my ninth. Honestly, each year it gets harder to manage the nerves. You want to do things right; you want your students to like you and say, “This class will be incredible.” On those first days of the last eight years, the moments felt so magical. I would see new faces, bright smiles, goofy personalities and nerves suddenly disappearing. It felt right.

But my ninth first day? I felt uncomfortable. I’m used to hearing and seeing students interacting with each other when I’m presenting on the first day, but in the world of Zoom, all you hear is yourself against multiple tiles on mute — and that day, most of the tiles were blank backgrounds with names. I didn’t hear a laugh. I couldn’t observe body language. What once felt like joy in my classroom quickly turned into emptiness.

I found myself seeking guidance from my principal that afternoon. I felt defeated, but in a unique way, which made me feel like even more of a failure. Last year, I was named D.C. Teacher of the Year, the first Latinx teacher to win that award. Folks were reaching out, asking me to share my expertise and perspectives from all over the District and country. I felt like I was on top of my teaching career. And now, after my first “Day One” in a distance learning program? I felt like a loser. I felt like I couldn’t be the teacher I had worked so hard to become.

I told my principal, “I feel like a first-year teacher again, only worse.” Her response stuck with me. “It feels worse because you have built years of what has worked well for you,” she said. “You have the background, and you have the experience. You have the expectation. Ignorance was bliss for you on your first day on the job several years ago. Now, you’re trying to live up to that expectation when the world has changed so drastically.”

So do I change my expectations? Do I lower them? Do I overhaul everything for the sake of adjusting to the pandemic? My principal told me to keep my expectations high in magnitude and low in rigidity.

“Create a bigger picture to discover the avenues that strive towards the high expectations your students deserve,” she said. “And select those paths as the decisions you will make as a teacher for your students at this time.”

I listened. And 18 instructional days later, I have realized this advice has transformed my students and me into agents of optimal learning. My outstanding co-teacher, Danielle Fadare, and I have helped each other broaden our scopes to provide meaningful and fun instruction.

Did we teach our students how to read a procedure with scientific tools and chemicals this year? No. But we did a demo on making a peanut butter and jelly sandwich while students learned how to co-write detailed procedures in groups to control every move I made to create one.

Did students use compound microscopes to view outdated slides in person? No. But they have learned how to use a virtual platform provided by a local university to investigate cellular structures using a 100X objective lens — a level of magnification that most compound microscopes in K-12 schools don’t have.

For the longest time, I viewed distance learning as limiting my quality of instruction. I thought, “Well, I won’t be able to do this because it just won’t be the same through Google Hangouts or Zoom.” It turns out I was right. It won’t be the same. But I had a choice. Should I accept those limits or should I embrace the potential and leverage my creativity to create promising outcomes? I have chosen the latter.

Is everything perfect? Absolutely not. And there’s a long way to go. There will be lots of magical moments and wins, with lots of failure. But I’ll fail with the intention of finding a different path to follow.

And the kids are excited to be back. Many of them are already super tech-savvy. They’re turning their cameras on. They’re laughing. One thing that I noticed today is that when I dismissed kids to their next class, many wanted to stick around and just talk to me. Not for anything academic . . . just to talk. As crazy as this sounds, I feel like I can relate to my students more than I ever have in my entire career. I’m learning with them. I’m growing with them. I hope we can build trust for one another throughout this time. And I’m hopeful for a better tomorrow.

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A Failure to Disrupt: Why Technology Alone Can’t Transform Education (Justin Reich)

Justin Reich is a Professor at MIT and director of the MIT Teaching Systems Lab. He is the author of the Failure to Disrupt: Why Technology Alone Can’t Transform Education (Harvard University Press, 2020). This article appeared in Teaching Times, August 20, 2020.

Over the last ten years, education technology evangelists have made remarkable claims about how new technologies will transform educational systems. In 2009, Clay Christensen of the Harvard Business School predicted that half of all secondary school courses in the US would be online by 2019, and that they’d cost 1/3 of a traditional course and provide better outcomes. Sal Khan of Khan Academy proposed in a TED talk that he could use short videos to reinvent education.

Sebastian Thrun of Udacity said that in 50 years we’d have only 10 institutions of higher education in the world after massive open online courses colonized the field. As the winner of the TED Prize, Sugata Mitra claimed that students didn’t even need schools or teachers, and that groups of children with access to the internet could teach themselves anything.

A disaster

And then in 2020, the world was blighted by a terrible pandemic. Schools serving over 1.6 billion learners shut down. It was a moment that technologists had promised for years could be transformative, but for most learners and families, remote online learning has been a disaster.

As educators face the challenge of spooling up new online and hybrid schools to serve vast numbers of students, they can choose from three kinds of technologies that support learning at scale. In classifying education technology, the first question to ask is “who controls the learning experience for students?”

There are three answers to this question: instructor-guided online courses, algorithm-guided adaptive tools, and peer-guided networked learning communities. Each of these genres has strengths and limitations; each is good for some subjects, but not others; for some students, but not others.

Very successful students do well

For older students, there are many different forms of instructor-guided, self-paced online courses available: free offerings from Khan Academy or FutureLearn along with subscription virtual courseware from a variety of companies. These cover many topics in the curriculum, but they only serve a subset of students well. Research shows that the learners who are most successful in self-paced courses are those who are already very successful in school—self-motivated and academically well-prepared.

Virtually none of our youngest learners meet these criteria. For auto-didacts, the options are limitless, but for the vast majority of us who need contact with human teachers to help us learn, these kinds of offerings are not very helpful

There are a variety of algorithm-guided adaptive tools that are engaging and beneficial to student learning. Part of the appeal of these tools is that they use a variety of different kinds of automated assessments to determine student understanding, and then they provide personalized learning pathways to students based on their performance.

Theoretically compelling

Theoretically, it’s a compelling model, where each student gets the instruction, the assessment, the feedback, and the experience that they need. But, the model depends on having good automated assessments, which only exist in three domains: mathematics, computer science, and early language acquisition (such as learning to read a native language in primary school, or learning the introductory parts of a foreign language).

Even within these domains, the assessments are only partially useful—in computer science we can automatically assess whether a student has met a well-defined engineering challenge, but not if they’ve made an aesthetically pleasing home page for a new website. Automated math tutoring software can be a useful part of a school systems’ remote learning plans, but there simply isn’t good automated tutoring software for studying literature, science, social studies, or most of the rest of the school curriculum.

While instructor-guided and algorithm-guided technologies attempt to use computers to directly teach students, some technologists have built learning environments where peers teach each other. The Scratch community, where young people learn computational creativity and share their programs, tutorials, and resources with one another, is probably the best example of a peer learning network that has been adopted in schools.

Outside of formal schooling, virtually everyone in the networked world participates in some way in these learning networks, when they peruse and comment on makeup tutorials, or read up on video game wikis, or participate in networks for hobbies and crafts. The kind of learning that people do in these networks is rich and deep, but it depends tremendously on internal motivation. People learn amazing things in online learning networks that tap into personal interests, but they tend not to be useful for teaching and learning about mandatory school subjects.

To sum up: instructor-guided self-paced online courses are great for autodidacts, but not particularly useful for most students; adaptive tutors work great for many learners, but only in a few subject areas; peer networks work well for learning about personal passions, but not so well for mandatory school curriculum.

Sweet spots for distance learning

For two decades, education technology entrepreneurs have promised a disruptive transformation of the learning landscape, but in reality, the field has produced a limited set of tools that only work for some students, in some subjects, in some contexts. Within those sweet spots, learning technologies can be incredibly powerful. But those sweet spots only cover a fraction of all of the learning that typical school systems try to provide for all of their students.

As a result of these limitations, during the pandemic, the vast majority of school systems—both for primary and secondary students and for higher education, have primarily turned not to emerging tools but towards two of our very oldest learning technologies: learning management systems and video telephony.

Learning management systems, like Google Classroom, Schoology, Canvas, or Moodle are digital spaces for sharing, distributing, and collecting online documents. These systems were theorized in the scholarly literature in the 1960s and 1970s, made commercially available in the 1990s, and available in open source in the 2000s. They let teachers assign and collect digital worksheets.

Video telephony was the 1930s name for what we now call video conferencing, services like Zoom or Microsoft Teams that let people see and hear each other online. These two technologies let systems recreate traditional models of schools—teacher lecture, student recitations, individual student practice on worksheets. This hasn’t worked particularly well, but there really aren’t examples of where new technologies are offering much better outcomes to students.

Four dilemmas

What would it look like to have a more robust set of large-scale learning technologies for the next pandemic? To create and implement technologies that work better at large scales, edtech designers and researchers will have to find new ways to overcome four dilemmas that have consistently hindered efforts to transform education with technology.

The first dilemma is what I call the Curse of the Familiar. When technologists create novel and innovative new tools for teaching and learning, educators and students often find them confusing and hard to adopt. If you make something very different from traditional school practice, it won’t fit into schools very well. But on the other side, if you build a technology that digitizes existing school practices—if you make digital flashcards or digital worksheets—they tend to not be that much better for learning than existing practices. The only solution to this dilemma is to recognize that new technology adoptions require substantial professional development efforts.

Second dilemma

The second dilemmas is the EdTech Matthew Effect. As we have seen in tragic ways throughout the pandemic, learning technologies tend to be most useful for affluent students with the financial, social, and technical resources to take advantage of new innovations. New technologies typically widen educational disparities rather than closing them.

Third dilemma

A third issue is that learning requires feedback, but technology designers are only good at evaluating human performance in domains where correct answers are highly structured. Computers can identify the correct answer to a math problem or even a correctly-pronounced word, but they cannot identify whether an essay shows a student effectively reasoning from evidence. The Trap of Routine Assessment observes that many education technologies rely on automated assessments, but computers can’t assess many of the most important things that our students learning.

Fourth dilemma

The Toxic Power of Data and Experiment highlights how new technologies are powerful platforms for research and A/B testing which can be used to dramatically improve computational systems, but only if communities are willing to tolerate risks to privacy and a growing surveillance over education.

Fundamentally, the dilemmas recognize that technology alone can’t transform schools. At best, technology can play a role in helping educators and communities build better learning systems.

These limits are not, in themselves, cause for despair. Improving teaching and learning is immensely hard. Education technology can’t solve all of the challenges of remote learning, but it can effectively address the needs of some students in some subjects.

For communities facing school closures, teaching young children math will prove incredibly difficult through video conferencing. By good fortune, some of our best learning technologies are adaptive tutors in elementary math subjects. That doesn’t solve every problem that primary head teachers face, but it helps with one of them.

For those who are hoping that education technology can transform our existing systems, that’s probably a disappointment. But if you see human development as a slow, painstaking process of gradual improvement, than those kinds of incremental steps are as good as it gets.

J

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When Algorithms Give Real Students Imaginary Grades (Meredith Broussard)

Meredith Broussard (@merbroussard) is a data journalism professor at New York University and the author of “Artificial Unintelligence: How Computers Misunderstand the World.” She is working on a book about race and technology.This op-ed piece appeared in the New York Times on September 9, 2020.

Isabel Castañeda’s first words were in Spanish. She spends every summer with relatives in Mexico. She speaks Spanish with her family at home. When her school, Westminster High in Colorado, closed for the pandemic in March, her Spanish literature class had just finished analyzing an entire novel in translation, Albert Camus’s “The Plague.”She got a 5 out of 5 on her Advanced Placement Spanish exam last year, following two straight years of A+ grades in Spanish class.

And yet, she failed her International Baccalaureate Spanish exam this year.

When she got her final results, Ms. Castañeda was shocked. “Everybody believed that I was going to score very high,” she told me. “Then, the scores came back and I didn’t even score a passing grade. I scored well below passing.”

How did this happen? An algorithm assigned a grade to Ms. Castañeda and 160,000 other students. The International Baccalaureate — a global program that awards a prestigious diploma to students in addition to the one they receive from their high schools — canceled its usual in-person final exams because of the pandemic. Instead, it used an algorithm to “predict” students’ grades, based on an array of student information, including teacher-estimated grades and past performance by students in each school.

Ms. Castañeda wasnot alone in receiving a surprising failing grade — tens of thousands of International Baccalaureate students protested their computer-assigned grades online and in person. High-achieving, low-income students were hit particularly hard: many took the exams expecting to earn college credit with their scores and save thousands of dollars on tuition.

Nor was the International Baccalaureate the only organization to use a computer program to assign students grades amid the pandemic. The United Kingdom’s in-person A-level exams, which help determine which universities students go to, were also canceled and replaced with grades-by-algorithm. Students who were denied university entrance because of these imaginary grades took to the streets, chanting anti-algorithm slogans. Only after an uproar did the government change course, though many students were left in limbo without university admission.

The lesson from these debacles is clear: Algorithms should not be used to assign student grades. And we should think much more critically about algorithmic decision-making overall, especially in education. The pandemic makes it tempting to imagine that social institutions like school can be replaced by technological solutions. They can’t.

The bureaucrats who decided to use a computer to assign grades are guilty of a bias I call technochauvinism: the idea that technological solutions are superior. It’s usually accompanied by equally bogus notions like, “Computers make neutral decisions” or, “Computers are objective because their decisions are based on math.”

Computers are excellent at doing math, but education is not math — it’s a social system. And algorithmic systems repeatedly fail at making social decisions. Algorithms can’t monitor or detect hate speech, they can’t replace social workers in public assistance programs, they can’t predict crime, they can’t determine which job applicants are more suited than others, they can’t do effective facial recognition, and they can’t grade essays or replace teachers.

In the case of the International Baccalaureate program, grades could have been assigned based on the sample materials that students had already submitted by the time schools shut down. Instead, the organization decided to use an algorithm, which probably seemed like it would be cheaper and easier.

The process worked like this: Data scientists took student information and fed it into a computer. The computer then constructed a model that outputted individual student grades, which International Baccalaureate claimed the students would have gotten if they had taken the standardized tests that didn’t happen. It’s a legitimate data science method, similar to the methods that predict which Netflix series you’ll want to watch next or which deodorant you’re likely to order from Amazon.

The problem is, data science stinks at making predictions that are ethical or fair. In education, racial and class bias is baked into the system — and an algorithm will only amplify those biases.

Crude generalizations work for Netflix predictions because the stakes are low. If the Netflix algorithm suggests a show and I don’t like it, I ignore it and move on with my day. In education, the stakes are much higher. A transcript follows you for years; when I was 25 and well out of college, I applied for a job that asked for my SAT scores.

In Ms. Castañeda’s case, her failing grade was most likely due in part to the fact that historical performance data for her school was one of the inputs to the algorithm. The computer assumed that the students at Westminster, who are mostly low-income students of color, would continue to do poorly.

“Everyone I know got downgraded one or two levels,” Ms. Castañeda told me. “It’s not fair that our scores were brought down because of our school’s history. It’s unfair to punish students for where they live.”

Another input to the algorithm was teacher prediction of the students’ grades. Teachers tend to have lower expectations for Black and Brown students compared to white students; this bias is well known in the education community and ignored in the data science community. Thus a very human bias prevailed in the computational system.

International Baccalaureate and Ofqual, the agency that administers Britain’s A-level exams, have reluctantly realized that algorithmic grades were a mistake. Since the outcry over algorithm-assigned grades, both organizations have been sued. Many students, including Ms. Castañeda, ended up receiving new, higher imaginary grades.

Roger Taylor, chair of the Ofqual board, apologized in front of a House of Commons educational oversight committee this week. “We are sorry for what happened this summer,” he said. “With hindsight it appears unlikely that we could ever have delivered this policy successfully.”

As we stare down the fall semester online, there are going to be infinitely many technochauvinist calls to transform online education and use algorithmic tools that promise to evaluate individual student learning. Resist these calls.

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How Covid-19 Froze School Reform (Part 3)

Covid-19 has not only frozen prior reforms–BC (Before Covid)–see Parts 1 and 2–but the spread of software and devices throughout schools prior to the coronavirus pandemic has led to a total embrace of online instruction or DC, During Covid-19. Districts are providing families with laptops and tablets like popcorn.

I take up particularly the work of entrepreneurs and school districts to spread “personalization” software and claims of tailoring teaching and learning to each student, a reform that will finally reach the Holy Grail of mass schooling–individualized learning at home and school. Using devices and software is now not a choice, it is a must. *

That is the story I want to tell. I begin with the word, palimpsest:

Palimpsest: “A manuscript, typically of papyrus or parchment, that has been written on more than once, with the earlier writing incompletely erased and often legible (The American Heritage Dictionary of the English Language, fourth edition, 2000, p. 1265).

Personalized instruction in 2020 is like a palimpsest.

Tailoring knowledge and skills to the individual student and given students control over their learning has been the dream of Progressive educators since the early 20th century and put into partial practice then, in the 1960s, and now.

The School of One, Summit Schools, and the Khan Lab school are different contemporary versions of online and teacher-student interactions–a sub-set of what many call “blended learning“–have written over the original Progressive rhetoric and actions of a half-century and century ago.

Knowing that Progressive under-text about past efforts to educate Americans–the “earlier writing incompletely erased and often legible”–could bring a sharper perspective to the contemporary claims that champions of personalized instruction–however defined–bring to policymakers, parents, and teachers. That resurrecting of the under-text highlights  the pedagogical and efficiency-driven wings of the Progressive movement then and today.

What I do in the rest of this post is clarify the original text of Progressive education a century ago, fast-forward to the 1960s when that Progressive impulse surfaced again, and leap ahead to the early 2000s for the current effort to personalize instruction, connecting it to the Progressive reforms decades earlier.

Earlier Progressive movement, 1890s-1940s

In these decades “progressive education” was the reigning political ideology in U.S. schooling. There were two main ideas, anchored in what was then emerging as a “science of education,” that spurred and divided U.S. progressives. First, student-centered instruction, small group and individualized learning (adherents were sometimes called “pedagogical progressives“) and, second, business-oriented advocates of “scientific management” (sometimes called “administrative progressives”) who sought to prepare children and youth to fit into work and society far more efficiently than the traditional schooling of the day. Both wings of the progressive movement drew from the writings of John Dewey and his embrace of science.

School boards, superintendents, and researchers of the day glommed on to “scientific management.” Proud to be called “educational engineers”  during these years, these “administrative progressives” created lists of behaviors that superintendents should follow to strengthen district performance and principals could use to evaluate teachers. They measured everything that was nailed down or moved. These efficiency-minded progressives triumphed politically in shaping schools in the early decades of the 20th century. “Pedagogical progressives”and their yearning for student-centered, individualized learning figured large in the words and imagination of advocates but made a small dent in school practice.

Neo-Progressive Reforms, 1960s 

Revival of Progressive educational ideas occurred during the 1960s amid desegregation struggles, the war in Vietnam, and cultural changes in society. Neoprogressive reformers, borrowing from their  earlier efficiency-driven “administrative progressives,” launched innovations such as “performance contracting.”   Corporations took over failing schools in Texarkana (AR), Gary (IN), and 100 other districts promising that their methods of teaching reading (e.g., new technologies such as programmed learning) would raise test scores fast and cheaply. Partial to the corporate managerial strategies in running schools, these reformers sought accountability through the contract they signed with district school boards. By the mid-1970s, school boards had dumped the contracts.

As for the pedagogical wing of the Progressive movement interested in student-centered classroom activities, small groups, and individualized learning, there was Individually Guided Education and “open classrooms“(also called “open education” and “informal education”).

The story of how a British import called “informal education” became the reform du jour in the U.S. begins with critics’ heavy pounding of schools in the mid-1950s. Across the political spectrum, critics flailed U.S. schools because education, they believed, could solve national problems arising from Cold War competition with the Soviet Union, caste-like treatment of black citizens, and a pervasive culture of conformity that suffocated imagination. Richly amplified by the media, “open classrooms” in its focus on students learning-by-doing in small groups and as individuals resonated with vocal critics of creativity-crushing classrooms. Thousands of elementary school classrooms–out of a few million–became home-like settings where young children sitting on rugs moved individually from one attractive “learning center” for math to others in science, reading, writing, and art. Teams of teachers worked with multi-age groups of students and created non-graded elementary schools. Both the efficiency and pedagogical wings of the Progressive movement surfaced in the mid-1960s, spread its wings, but plummeted swiftly within a decade.

Personalized Instruction During Covid

In the midst of wholesale online instruction during the pandemic and the proliferation of Zoom, the pumped up language accompanying “personalized instruction” resonates like the slap of high-fives between earlier Progressive educators and current reformers. Rhetoric aside, however, issues of research and accountability continue to bedevil those clanging the cymbals for “student-centered” instruction and learning. The research supporting “personalized” or “blended learning” is, at best thin. Then again, few innovators, past or present, seldom invoked research support for their initiatives.

But accountability in these years of Common Core standards and testing is another matter. As one report put it:

Personalized learning is rooted in the expectation that students should progress through content based on demonstrated learning instead of seat time. By contrast, standards-based accountability centers its ideas about what students should know, and when, on grade-level expectations and pacing. The result is that as personalized learning models become more widespread, practitioners are increasingly encountering tensions between personalized learning and state and federal accountability structures.

With the suspension of state tests during the pandemic, however, few policymakers and present-day Progressive reformers eager to install “personalized instruction” in their schools need look over their shoulders fearful of the state or local parents taking note of these conflicts.

But a puzzle about remote instruction remains during Covid-19. How does an elementary school teacher with 30 students or a secondary teachers with 130 or more students “personalize” instruction online five hours a day. This puzzle has yet to be solved.

Before Covid, innovations such as “personalized instruction,”  “student centered instruction,   and “blended instruction”  were written over the underlying, century-old text of Progressive education. Today, current “pedagogical” and efficiency-minded Progressives committed to “personalized instruction” are writing their script over previous reformers during the discombobulation of schooling by Covid-19. 

___________________

*Elizabeth Brott Beese, a reader of my blog on “personalized” instruction, has researched different ways of parsing “personalized” and come up with her own. See here.

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How Covid-19 Froze School Reform (Part 2)

What was school reform like before Covid-19 ( BC)?

Since the mid-1980s, U.S. public schools had been enthralled with and institutionalized a series of reforms that are now called the “standards, testing, and accountability movement.” It is nearly three decades long.

Recall that the Progressive movement began in the 1890s and, depending upon the historian one reads, lasted until the 1920s or through World War II. The other reform movement that flowed across the schools had a shorter life-span. The civil rights movement spilling over public schools is usually dated by the 1954 Brown decision and peters out by the mid-1970s. Soon to be overtaken by the “standards, testing, and accountability” reforms that readers know so well.

Civic and corporate leaders allied with enthusiastic donors turned public schools in the 1980s to building human capital essential to fostering economic growth and stronger competition for global markets. Their overall strategy was (and still is) to apply a business model of competitiveness, innovation, and efficiency to public schools that fixed attention on the bottom line of test scores and return-on-investment in high school graduates entering and completing college.[i]

These leaders and foundation officials over the past three decades have created beefy portfolios of reform ventures including changes in funding and structural innovations such as vouchers, charter schools, common curriculum standards, testing and accountability including using student scores to determine district and school “success” and “failure.”

No Child Left Behind (2001-2015) collected converted state initiatives into federal policy under Republican President George W. Bush and Democrat Barack Obama. This cobbled together strategy emerged from ideas tossed up by business and civic leaders and entrepreneurial policymakers who cherry-picked anecdotal and statistical evidence from here and there to convince Americans that the result would be strong schools, strong students, and a strong economy.

A jerry-built reform strategy of ventures flung together helter-skelter add up to a movement to improve public schools through expanded parental choice of public schools and instilling market competition into a quasi-monopolistic institution. For-profit companies taking over low-performing public schools (e.g. K-12 Inc., Edison Inc–now defunct), non-profit charter schools (e.g., KIPP, Aspire, Summit Schools, Green Dot), and, under NCLB, requiring districts to meet their Adequate Yearly Progress targets or be closed. NCLB had a legislative do-over in 2016 and is now called Every Student Succeeds Act.

This standards, testing, and accountability regime existed Before Covid-19 hit. With the closing of schools in March 2020 and the stunning shift to remote instruction and uncertainty when most U.S. students will return to face-to-face instruction, these reforms in curriculum standards, annual tests, and accountability mechanisms to insure responsibility for student outcomes are frozen in place. Even state tests for the upcoming school year, if U.S. Secretary of Education Betsy DeVos has her way.

Alfie Kohn believes that the pandemic is a pivot point for school districts to pull back from standardized tests, how colleges admit students, and reassess grades that teachers are required to give. Part of me wants to join Kohn in his belief that the pandemic can trigger deep and important changes.Part of me, the part that has studied school reform, however, says that it is possible but improbable that such changes will occur.

Another major reform strategy existed before Covid-19 struck. Giving all teachers and students access to instructional technology (e.g., laptops, tablets, etc.) and expecting their use in daily lessons, technology-driven reformers saw these devices and an array of software as ways of improving both teaching and student learning.

Technology reforms Before Covid-19

Since the early 1980s with the appearance of desktop computers in schools, questions about their presence in classrooms have been debated. Access to, use of, and results from new technologies have been central issues for a motley coalition of  high-tech vendors, technophile educators, and policymakers eager to satisfy parents and voters who want schools to be technologically up-to-date with other institutions. And this coalition has surely been successful in increasing teacher and student access to desktop computers, then laptops, and now tablets and smartphones.

First, a quick run through the initial goals and current ones in putting new technologies into the hands of teachers and students. Then a brief look at access, use, and results of the cornucopia of devices in schools.

By the  mid-1980s, there were clear goals and a strong rationale for investing in buying loads of hardware and software and wiring buildings . Those goals were straightforward in both ads and explicit promises vendors and entrepreneurs made to school boards and administrators.

*students would learn more, faster, and better;

*classroom teaching would be more student-friendly and individualized;

*graduates would be prepared to enter the high-tech workplace.

By the early 2000s, evidence that any of these goals were achieved was either scant or missing. It became increasingly clear that promised software in math and English (to meet NCLB requirements) fell far short of raising students’ test scores or lifting academic achievement. The promise of algorithms and program playlists tailored to each student’s academic profile (often called “personalization”) had faltered then and even now remains a work in progress (see here, here, and here).

As for the goal that learning to use hardware and software applications would lead to jobs in technology became another casualty of over-promising with few returns to high school graduates. That jobs were hardly automatic for those students who knew spreadsheets and BASIC (Beginner’s All-purpose Symbolic Instruction Code) in the 1980s and 1990s became obvious to students with diplomas in hand. By the 2010s, teaching coding to children and getting the subject of computer science into the high school curriculum spread across U.S. schools.

Those initial goals and rationale for flooding schools with new devices, lacking substantial evidence to support them, have now shifted to another set of reasons for computers in schools:

*Devices are essential since all standardized tests and other student assessments will be on computers.

*Learning to use machines and applications in schools–including coding–will give a leg-up for graduates to get entry-level jobs in most businesses and industries.

*The dream of “personalizing” instruction–in-person teaching and software tailored to individual differences in each and every child–can now become a reality with every student having a device at school and at home.

The constant chasing of a technological solution to a teaching and learning problem captures the BC experience of school reform.

And it is here that BC technology reforms slide over to DC–During Covid Reforms. I take up the nation’s school districts embracing remote instruction as a temporary replacement for in-person schooling in Part 3.

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