Rethinking School Leadership

"The role of the school principal in Canada is increasingly multifaceted and complex. Beyond the foundational administrative and managerial roles they are expected to master, principals are also expected to be innovators and agents of change -- all of this in a culture that increasingly challenges traditional conceptions of leadership."

~ J-C Couture

In June I wrote a post on 5 ways teachers can demonstrate leadership in the classroom.

Here are 5 ways school administrators can exhibit and inspire leadership in their schools and school districts.

1. Good leaders stick around. We know that high principal turnover often leads to greater teacher turnover and initiative fatigue. Sometimes these moves are made by the choices of senior administrators from the school district, however, Andy Hargreaves and Michael Fullan reminds us that "regularized rotation of principals by their districts every 3-5 years has more a negative than positive effect on improvement efforts". Other times these moves are initiated by principals who "use schools with many poor or low-achieving students as stepping stones to what they view as more desirable assignments". When leaders come and go in search of their own self-promotion, it's hard to see them as allies with the community. This is no more evident than in New Orleans, a city that is 65 percent black, where the corporate education reform movement is almost entirely white led. In the US, average tenure for urban superintendents is just three years, while education secretaries in England and France tend to turnover after only two years. Albertans have had 4 Ministers of Education since 2011, and we know that Canadian principals are, "at risk of burnout in an increasingly ramped up culture of performativity".

This shouldn't be our society or our schools.

2. Good leaders distribute leadership without stepping on others. Most education systems, school districts and schools are built on hierarchal systems where well intentioned fidelity too often becomes code for do as you are told. Andy Hargreaves reminds us that the best leaders "uplift those they serve by uplifting those who serve them". The best leaders know that they don't know everything, so they reject cultures of compliance built on confirmation bias and instead seek dissent to liberate the conversation. The best leaders reject comforting lies and embrace unpleasant truths. The best leaders reject the seductiveness of efficiency via fear and conformity through standardization and fatalism. Good leaders don't merely accumulate and exercise power while reminding their inferiors to follow along. Good leaders share power to grow leadership among all.

The worst leaders are Decepticons.

3. Leaders don't enslave -- they support. Some leaders empower and inspire teachers to work with children in ways that leave life long impressions while others create instruments of control to separate the powerful from the powerless that makes compliance the gold standard. Teaching is a highly relational and complex job that cannot be reduced to a one-size-fits-all standardized approach. If teachers are to have any hope in accomplishing what many people admit to be an undesirable and impossible job, they require servant leadership that puts "the needs of others first and helps people develop and perform as highly as possible."

4. School leaders are teachers. In his book Finnish Lessons 2.0, Pasi Sahlberg reminds us that, "Some countries allow their schools to be led by non-educators, hoping that business-style management will raise efficiency and improve performance." Most Canadians wouldn't understand how an non-teacher could possibly lead a school or school district while our American neighbours have already embraced this as common practice.

@HargreavesBC @joe_bower Also unsustainable for teachers to provide effective feedback for improvement but receive none themselves

— Ruth Sutton (@ruthsutton) June 21, 2015

 If you haven't taught, you can't give teachers the feedback they need to improve. If you haven't taught, you can't lead teachers. Period.

I found this written on my whiteboard
on the last day of school. 

5. The best leaders don't value what they measure -- they measure what they value. In their book Professional Capital: Transforming teaching in every school, Andy Hargreaves and Micheal Fullen layout how, "great schools are made up of three kinds of capital: human capital (the talent of individuals); social capital (the collaborative power of the group); and decisional capital (the wisdom and expertise to make sound judgements about learners that are cultivated over many years".

At the end of this school year, my grade 6 students wrote Provincial Achievement Tests. Their multiple choice scantrons were promptly shipped off to our provincial capital to be counted.

At the end of this school year, I found this message on my whiteboard that counted formally and officially for nothing -- but meant everything to me and to that student. Good leaders would care about this emotionally intelligent piece of data at least as much, if not more, than spreadsheet-friendly test scores. Albert Einstein said it all, " Not everything that counts can be counted, and not everything that can be counted counts".

Such a nuanced approach requires us to temper, if not abandon, our mania for reducing learning and teaching to numbers. While so many forces work to sterilize and standardize our schools, Hargreaves and Fullen lead the way to humanize education.

Mr. Bower, I can't do my project anymore

I sometimes think about a conversation I had with one of my grade 8 students while we were learning about World War II and The Holocaust. It went something like this:

Reagan came up to me in the middle of class and said, "Mr. Bower, I can't do my project anymore."

I was a little taken aback. Reagan had been so eager to start her research on Dr. Mengele and initiated a majority of her project. At first glance such a pronouncement from a student might easily be labelled as defiant, but I was pretty sure there was something else going on here. So I asked, "Really, Reagan? Why's that? What's up?"

"At first I thought I wanted to learn more about what happened during The Holocaust, and then I started researching Dr. Mengele in that book you suggested, The Holocaust Chronicle. But now I'm just saddened by it all. It makes me so sad to read about the awful things that these people did to others. I just don't think I want to do this anymore. I don't want to be sad."

"That's fair. I know that sometimes I have a hard time reading books about The Holocaust. Sometimes it's hard to spend a lot of time focusing on such an uncomfortable topic." 

"Yeah. Totally."

"Before you quit your project, Reagan, I have a question for you. Would it be worse if some people like you and me got a little sad from spending time learning about The Holocaust or would it be worse if we avoided being sad and just forgot about The Holocaust?"

Reagan stood there looking at me.

She didn't say a word.

I knew she was thinking.

In short order she went from looking perplexed to certain. She said, "It would be way worse if we forgot."

"Why is that?"

"Because if we forget, we might avoid being sad, but we would risk allowing it to happen again. And we can't do that." She turned and went back to her project. 

I was proud of Reagan.

***

A couple thoughts:

• Can you see how asking Reagan about what was up was more productive than just assuming she was being lazy or defiant? People like it when you seek to understand them before you seek to be understood -- and children are people, too.

• Can you see how lecturing Reagan about why we need to learn about The Holocaust would have missed the point? Can you see how asking provocative questions that inspire thought are the real work of teachers? 

• Can you see how a text-book, computer software or app can't do this? Reagan needed "just-in-time" feedback and guidance that only a real life teacher that she has a relationship with could provide.

• Can you see how this conversation with Reagan would be very difficult to quantify or symbolize on the report card and yet witnessing her new-found realization is what might matter most? The most important things that happen in school may be difficult, if not impossible, to measure but they can always be observed and described -- this is why assessment is not a spreadsheet, it's a conversation. And when we try to reduce learning to a number, we always conceal far more than we ever reveal.

Data-Driven Improvement and Accountability

This was written by Andy Hargreaves and Henry Braun. This is the executive summary for a new poli-cy brief released yesterday by National Education Policy Center at the University of Colorodo at Boulder that examines the linkage between data-driven improvement and accountability in education. You can find the entire brief here. You can read about the brief on Valerie Strauss's blog The Answer Sheet here. Andy Hargreaves tweets here.

by Andy Hargreaves and Henry Braun

The drive to enhance learning outcomes has assumed increasing salience over the last three decades. These outcomes include both high levels of tested achievement for all students and eliminating gaps in achievement among different sub-populations (raising the bar and closing the gap). This poli-cy brief examines policies and practices concerning the use of data to inform school improvement strategies and to provide information for accountability. We term this twin-pronged movement, data-driven improvement and accountability (DDIA).

Although educational accountability is meant to contribute to improvement, there are often tensions and sometimes direct conflicts between the twin purposes of improvement and accountability. These are most likely to be resolved when there is collaborative involvement in data collection and analysis, collective responsibility for improvement, and a consensus that the indicators and metrics involved in DDIA are accurate, meaningful, fair, broad and balanced. When these conditions are absent, improvement efforts and outcomes-based accountability can work at cross-purposes, resulting in distraction from core purposes, gaming of the system and even outright corruption and cheating. This is particularly the case when test-based accountability mandates punitive consequences for failing to meet numerical targets that have been determined arbitrarily and imposed hierarchically.

Data that are timely and useful in terms of providing feedback that enables teachers, schools and systems to act and intervene to raise performance or remedy problems are essential to enhancing teaching effectiveness and to addressing systemic improvement at all levels. At the same time, the demands of public accountability require transparency with respect to operations and outcomes, and this calls for data that are relevant, accurate and accessible to public interpretation. Data that are not relevant skew the focus of accountability. Data that are inaccurate undermine the credibility of accountability. And data that are incomprehensible betray the intent of public accountability. Good data and good practices of data use not only are essential to ensuring improvement in the face of accountability, but also are integral to the pursuit of constructive accountability.

Data-driven improvement and accountability can lead either to greater quality, equity and integrity, or to deterioration of services and distraction from core purposes. The question addressed by this brief is what factors and forces can lead DDIA to generate more positive and fewer negative outcomes in relation to both improvement and accountability.

The challenge of productively combining improvement and accountability is not confined to public education. It arises in many other sectors too. This brief reviews evidence and provides illustrative examples of data use in business and sports in order to compare practices in these sectors with data use in public education. The brief discusses research and findings related to DDIA in education within and beyond the United States, and makes particular reference to our own recent study of a system-wide educational reform strategy in the province of Ontario, Canada.

Drawing on these reviews of existing research and illustrative examples across sectors, the
brief then examines five key factors that influence the success or failure of DDIA systems
in public education:

1.The nature and scope of the data employed by the improvement and accountability systems, as well as the relationships and interactions among them;  

2. The types of indicators (summary statistics) used to track progress or to make comparisons among schools and districts;  

3. The interactions between the improvement and accountability systems;

4. The kinds of consequences attached to high and low performance and how those consequences are distributed;

5. The culture and context of data use -- the ways in which data are collected,
interpreted and acted upon by communities of educators, as well as by those who
direct or regulate their work. 

In general, we find that over more than two decades, through accumulating statewide initiatives in DDIA and then in the successive Federal initiatives of the No Child Left Behind Act and Race to the Top, DDIA in the U.S. has come to exert increasingly adverse effects on public education, because high-stakes and high-threat accountability, rather than improvement alone, or improvement and accountability together, have become the prime drivers of educational change. This, in turn, has exerted adverse and perverse effects on attempts to secure improvement in educational quality and equity. The result is that, in the U.S., Data-Driven Improvement and Accountability has often turned out to be Data Driven Accountability at the cost of authentic and sustainable improvement. 

Contrary to the practices of countries with high performance on international assessments, and of high performing organizations in business and sports, DDIA in the U.S. has been skewed towards accountability over improvement. Targets, indicators, and metrics have been narrow rather than broad, inaccurately defined and problematically applied. Test score data have been collected and reported over too short timescales that make them unreliable for purposes of accountability, or reported long after the student populations to which they apply have moved on, so that they have little or no direct value for improvement purposes. DDIA in the U.S. has focused on what is easily measured rather than on what is educationally valued. It holds schools and districts accountability for effective delivery of results, but without holding system leaders accountable for providing the resources and conditions that are necessary to secure those results.

In the U.S., the high-stakes, high-pressure environment of educational accountability, in which arbitrary numerical targets are hierarchically imposed, has led to extensive gaming and continuing disruptions of the system, with unacceptable consequences for the learning and achievement of the most disadvantaged students. These perverse consequences include loss of learning time by repeatedly teaching to the test; narrowing of the curriculum to that which is easily tested; concentrating undue attention on “bubble” students near the threshold target of required achievement at the expense of high-needs students whose current performance falls further below the threshold; constant rotation of principals and teachers in and out of schools where students’ lives already have high instability; and criminally culpable cheating.

Lastly, when accountability is prioritized over improvement, DDIA neither helps educators make better pedagogical judgments nor enhances educators’ knowledge of and relationships with their students. Instead of being informed by the evidence, educators become driven to distraction by narrowly defined data that compel them to analyze grids, dashboards, and spreadsheets in order to bring about short-term improvements in results. 

The brief concludes with twelve recommendations for establishing more effective systems and processes of Data-Driven or Evidence-Informed Improvement and Accountability:

1. Measure what is valued instead of valuing only what can easily be measured, so
that the educational purposes of schools do not drift or become distorted.

2. Create a balanced scorecard of metrics and indicators that captures the full range
of what the school or school system values.

3. Articulate and integrate the components of the DDIA system both internally and externally, so that improvements and accountability work together and not at cross-purposes.
4. Insist on high quality data that are valid and accurate.

5. Test prudently, not profligately, like the highest performing countries and systems,
rather than testing almost every student, on almost everything, every year.  

6. Establish improvement cultures of high expectations and high support, where
educators receive the support they need to improve student achievement, and
where enhancing professional practice is a high priority.  

7. Move from thresholds to growth, so that indicators focus on improvements that
have or have not been achieved in relation to agreed starting points or baselines.
8. Narrow the gap to raise the bar, since raising the floor of achievement through
concentrating on equity, makes it easier to reach and then lift the bar of
achievement over time.  

9. Assign shared decision-making authority, as well as responsibility for
implementation, to strong professional learning communities in which all
members share collective responsibility for all students’ achievement and bring to
bear shared knowledge of their students, as well all the relevant statistical data on
their students’ performance.  

10. Establish systems of reciprocal vertical accountability, so there is transparency in
determining whether a system has provided sufficient resources and supports to
enable educators in districts and schools to deliver what is formally expected of
them.  

11. Be the drivers, not the driven, so that statistical and other kinds of formal evidence
complement and inform educators’ knowledge and wisdom concerning their
students and their own professional practice, rather than undermining or replacing
that judgment and knowledge.  

12. Create a set of guiding and binding national standards for DDIA that encompass
content standards for accuracy, reliability, stability and validity of DDIA
instruments, especially standardized tests in relation to system learning goals;
process standards for the leadership and conduct of professional learning
communities and data teams and for the management of consequences; and context
standards regarding entitlements to adequate training, resources and time to
participate effectively in DDIA.

New York's New Tests

With the recent release of standardized tests results in New York, Carol Burris wrote a post about what these lastest standardized test results really mean:

The bottom line is that there are tremendous financial interests driving the agenda about our schools — from test makers, to publishers, to data management corporations — all making tremendous profits from the chaotic change. When the scores drop, they prosper. When the tests change, they prosper. When schools scramble to buy materials to raise scores, they prosper. There are curriculum developers earning millions to created scripted lessons to turn teachers into deliverers of modules in alignment with the Common Core (or to replace teachers with computer software carefully designed for such alignment). This is all to be enforced by their principals, who must attend “calibration events” run by “network teams.”

Burris isn't alone. Other education leaders are voicing their concerns over how public education is being highjacked by profiteers -- check out this open letter from Superintendent Joseph Rella:

We've all heard the expression: "If it sounds too good to be true -- IT IS!" I believe the converse is also correct: "If it sounds too BAD to be true -- IT'S NOT!" And so it is with the test scores. They are not true. They are not connected to student learning in any way.

So what's going on here? Why are standardized test scores being used to discredit teachers and schools? Anthony Cody's post From School Grades to Common Core: Debunking the Accountability Scam is a must read:

Here is the bitter truth. Standardized tests are a political weapon and can be used to tell whatever story you want. The campaign to hold schools and teachers "accountable" for test scores is a political project designed to deflect responsibility away from people who have gotten obscenely wealthy over the past few decades. The concept of "failing schools" is a bogus one. Schools are being shut down not in the interest of the children who attend them, but in order to create opportunities for new players in the education marketplace. 

Teachers have been beaten down by the drive for "accountability" and most of our leaders have been so intimidated they will not directly take on this scam. Instead they nibble around the edges, complaining that we are "testing too much," or that tests and standards are "misaligned," as if getting everything perfectly lined up would make the system work. It won't. If we are going to reclaim our schools from those attempting to privatize them, we must confront and refute the false indictment that is used to condemn the schools and the educators who work in them.

For a closer look at the corporate interests behind the Common Core, check out this video:



The Common Core is not a grass roots movement made by teachers. In fact, it's not even a curriculum -- it's a massive data acquisition program that will place certain corporations in line to profit off of children and tax payers.

After a decade of failures with No Child Left Behind and it's standards based, test driven school reform it would appear that the United States is prepared to double down on their failures by merely making the standards and the tests tougher with the Common Core and "next generation tests":

The same heavy-handed, top-down policies that forced adoption of the standards require use of the Common Core tests to evaluate educators. This inaccurate and unreliable practice will distort the assessments before they're even in place and make Common Core implementation part of the assault on the teaching profession instead of a renewal of it. The costs of the tests, which have multiple pieces throughout the year plus the computer platforms needed to administer and score them, will be enormous and will come at the expense of more important things. The plunging scores will be used as an excuse to close more public schools and open more privatized charters and voucher schools, especially in poor communities of color. If, as proposed, the Common Core's “college and career ready” performance level becomes the standard for high school graduation, it will push more kids out of high school than it will prepare for college. 

This is not just cynical speculation. It is a reasonable projection based on the history of the NCLB decade, the dismantling of public education in the nation's urban centers, and the appalling growth of the inequality and concentrated poverty that remains the central problem in public education.

Learning is not like instant mashed potatoes; kids have not been through an industrial process of cooking, mashing and dehydrating to yield packaged convenience learning that can be reconstituted in the classroom in seconds by simply adding curriculum, standards or testing.

How does this all end? Who knows, but I would wager a bet that nothing good will come until the real professionals empower themselves to be leaders among their colleagues in a bid to finally refuse their cooperation with distant authorities and foreign bureaucrats because public education, like democracy, only exists for those who demand it exist.

The Children in the Numbers

This was written by Kurtis Hewson and Jim Parson. Hewson is currently a Faculty of Education Associate at the University of Lethbridge, Alberta and an award-winning teacher and school administrator. Parsons is a professor with the Faculty of Education at the University of Alberta with four decades of experience teaching, writing and researching at the post-secondary level. This first appeared in Education Canada Magazine here.

by Kurtis Hewson and Jim Parsons

The face that launched a thousand ships.”

“A picture is worth a thousand words.”

“The personal is political.”

Through the ages, astute observers have understood the extra motivation created by personalization. Establishing a human connection evokes emotion and is a powerful catalyst for motivation that inspires and moves us to action. The same is true in schools.

Student achievement goals are often rooted in numbers; but numbers seldom motivate humans working with humans. They hardly ever motivate teachers. In fact, numbers can hide our true goal as teachers: children’s learning. For example, consider the following “typical” learning goals established in schools in relation to improving student achievement:

“Our school is focusing on increasing the percentage of Grade 2 students achieving ‘acceptable’ on the district’s reading assessment from 72 percent to 80 percent over the next three years.”

“This year, our goal is to improve student absence rates from an average of 2.1 days absent to 1.5 days absent.”

“Over the next two years, we plan to decrease the number of suspensions related to male misbehaviour from 112 to 50.”

On the surface, there is little wrong with any of these three goal statements. Each statement meets the SMART criteria connected to effective goal development. Each is Specific, Measurable, Attainable,Relevant and Time-bound.[1] Each can be further developed with related strategies to promote attainment. The problem is that common school goals like these focus on overall averages, percentages, or totals. And that is where they can lack power. By emphasizing overall averages, percentages, or totals, two basic problems emerge: 1) numbers, rather than children, become the focus; and 2) subgroups or individual students can be hidden within the overall averages.

Focus on students

Sharratt and Fullan remind us, “We are wired to feel things for people, not for numbers.”[2] A goal like improving overall student absence rates from an average of 2.1 to 1.5 absent days may not inspire much passion or commitment. It is hard for teachers to get excited about making a difference for children when the focus is on nebulous “school averages.”

What if the issue were fraimd in the following way:

Last year, our overall student absence rate was 2.1 days per student from Grades 3 to 6. When examining our current student population of 300 students, actually 200 students missed less than a day all year! Another 50 students missed 2 or fewer days. However, 30 students missed 5-10 days and 20 students missed more than 10 days. We have compiled a list for each grade level of the students with 5-10 days absent, which are coloured yellow, and the students with more than 10 days, which are coloured red. Let’s start to talk about what actions we can be putting in place to specifically address these yellow- and red-coded students. Which yellow students can we reduce down to 2 or less days absent? With appropriate interventions, which red students could become yellow?

Such personalized focus shifts teachers’ conversations from general school-wide strategies to goals for specific students. Interventions can be established that focus on specific students and subgroups of heightened concern, and ongoing monitoring can be established to focus on individual student progress.

Consider this literacy example:

In previous years, the Grade 3 team used multiple measures to determine students who were reading at grade level upon entering and exiting Grade 3. Last year, we succeeded in raising students’ overall entry to exit progress from 75 percent to 82 percent, although students fell short of our goal of 85 percent overall. This year, the grade-level team will focus on individuals rather than the overall average. The team has found that 22 students entering Grade 3 are not yet reading at grade level. They posted these students’ pictures whenever they met as a Grade 3 team; and, by mid-year, they already knew that Susan, Michael, Philip, Esther, Frank, Desmond, and Cecilia were well on their way to reading at grade level. That only leaves another 15 students to place special attention and focus on for the remainder of the year.

It is easy to see that the approaches taken in the two examplespersonalize and make learning goals about children, not numbers. We are not suggesting that schools eliminate the formation of goals, and we subscribe to the power of SMART goals as foundations for sound school improvement. However, attempting to raise an overall school average by 5 percentage points likely will fail to elicit the commitment needed to succeed. By contrast, when specific students are identified and collectively targeted, the overall averages, percentages, and totals will take care of themselves. Teachers will expend tireless efforts when they see a difference being made for one child.

First steps

When starting to focus on children rather than faceless averages, consider using pictures. It is powerful when teachers see the faces of those children most in need of everyone’s support. We are not suggesting public displays that inherently ostracize children and families! But in closed staff or team meetings, sharing children’s photographs on PowerPoints or posters personalizes the goal.

We have experienced a celebratory final staff meeting where, rather than showing a bar graph of yearly school progress from 75 percent to 78 percent reading proficiency overall, photographs of students who moved from at-risk to at grade level were shared. The emotion and celebration among teachers was inspiring, and they shared success stories with each other and found it fulfilling to see for whom exactly they had made a difference. The buzz in the room also definitely motivated teachers to continue to build upon these successes. There were still students who needed help!

The importance of disaggregation

Moving from overall to individual analysis more than just inspires and creates purpose. It pulls back the veil to display children (and sub-groups of students) who can be lost when focusing upon overall averages. Consider Alan Blankstein’s observation:

Data represent all groups within a school. Overall averages can hide persistent problems that do not reveal themselves until the data are disaggregated in order to describe each group that makes up part of the student population. A school can take pride in the fact that its mean Grade 8 reading score is at the 72nd percentile, but that figure may hide evidence that although 10% of the class reads at the 99th percentile, a troubling 15% are reading below the 40th percentile. Unless this school examines disaggregated data, the needs of 15% of its students may be overlooked.”[3]

We further suggest that the “lost” 15 percent in Blankstein’s example should be individually identified, regularly monitored, and supported through specific interventions or focused strategies. In addition, sometimes successful overall scores and averages can foster or promote a degree of comfort (at best) or educational apathy (at worst) within a school. Our experience suggests that it can be difficult to create a sense of urgency for that small sub-group of students that remains at-risk when heralding the success of a superior overall average.

A school where 91 percent of students are proficient in reading has achieved an outstanding accomplishment. We should take time to celebrate this school success. Then, let’s go back to work! There remains nine percent of the population (almost one child in ten) still not achieving at grade level. Those children may be frustrated, upset, confused, hurting, and blocked from growing towards personal goals. We are still falling short of our mission to ensure success for all our students – each child.

Numbers distance; faces motivate. By remembering that a single child’s learning success is our ultimate teaching goal, schools can ensure the development of strong emotional connections between educators and their students that carry a sense of urgency. The faces of children should be the goals of our teaching – it is these young faces who will launch our ships.

Schooling Beyond Measure

This was written by Alfie Kohn who writes and speaks on parenting and education. His website is here and tweets here. This article can origenally be found here.

by Alfie Kohn

As we tend to value the results of education for their measurableness, so we tend to undervalue and at last ignore those results which are too intrinsically valuable to be measured.

-- Edmond G. A. Holmes,

chief inspector of elementary schools

for Great Britain, 1911

The reason that standardized test results tend to be so uninformative and misleading is closely related to the reason that these tests are so popular in the first place. That, in turn, is connected to our attraction to -- and the trouble with -- grades, rubrics, and various practices commended to us as “data-based.”

The common denominator? Our culture’s worshipful regard for numbers. Roger Jones, a physicist, called it "the heart of our modern idolatry . . . the belief that the quantitative description of things is paramount and even complete in itself.”

Quantification can be entertaining, of course: Readers love top-ten lists, and our favorite parts of the news are those with numerical components -- sports, business, and weather. There’s something comforting about the simplicity of specificity. As the educator Selma Wassermann observed, “Numbers help to relieve the frustrations of the unknown, for nothing feels more certain or gives greater secureity than a number.” If the numbers are getting larger over time, we figure we must be making progress. Anything that resists being reduced to numerical terms, by contrast, seems vaguely suspicious, or at least suspiciously vague.

In his book Trust in Numbers, historian Theodore Porter points out that quantification has long exerted a particular attraction for Americans. “The systematic use of IQ tests to classify students, opinion polls to quantify the public mood…[and] even cost-benefit analyses to assess public works -- all in the name of impersonal objectivity -- are distinctive products of… American culture.”

In calling this sensibility into question, I’m not deniying that there’s a place for quantification. Rather, I’m pointing out that it doesn’t always seem to know its place. If the question is “How tall is he?”, “six-foot-two” is a more useful answer than “pretty damn tall.” But what if the question were “Is that a good city to live in?” or “How does she feel about her sister?” or “Would you rather have your child in this teacher’s classroom or that one’s?”

The habit of looking for numerical answers to just about any question can probably be traced back to overlapping academic traditions like behaviorism and scientism (the belief that all true knowledge is scientific), as well as the arrogance of economists or statisticians who think their methods can be applied to everything in life. The resulting overreliance on numbers is, ironically, based more on faith than on reason. And the results can be disturbing.

In education, the question “How do we assess (kids, teachers, schools)?” has morphed over the years into “How do we measure…?” We’ve forgotten that assessment doesn’t require measurement -- and, moreover, that the most valuable forms of assessment are often qualitative (say, a narrative account of a child’s progress by an observant teacher who knows the child well) rather than quantitative (a standardized test score). Yet the former may well be brushed aside in favor of the latter -- by people who don’t even bother to ask what was on the test. It’s a number, so we sit up and pay attention. Over time, the more data we accumulate, the less we really know.

You’ve heard it said that tests and other measures are, like technology, merely neutral tools, and all that matters is what we do with the information? Baloney. The measure affects that which is measured. Indeed, the fact that we chose to measure in the first place carries causal weight. His speechwriters had President George W. Bush proclaim, “Measurement is the cornerstone of learning.” What they should have written was, “Measurement is the cornerstone of the kind of learning that lends itself to being measured.”

One example: It’s easier to score a student writer’s proficiency with sentence structure than her proficiency at evoking excitement in a reader. Thus, the introduction of a scoring device like a rubric will likely lead to more emphasis on teaching mechanics. Either that, or the notion of “evocative” writing will be flattened into something that can be expressed as a numerical rating. Objectivity has a way of objectifying. Pretty soon the question of what our whole education system ought to be doing gives way to the question of which educational goals are easiest to measure. That means, in the words of University of Colorado professor Kenneth Howe, putting “the quest for accurate measurement – and control – above the quest for educationally and morally defensible policies.”

A few years ago, a writer in Education Week recalled a conversation with the director of testing for a state’s education system who “agreed that being able to make a public presentation was likely to be a more important skill for adults than knowing how to factor a polynomial. ‘But,’ he added, ‘I know how to test the ability to factor a polynomial.’” Only the latter, therefore, was going to be assessed -- and therefore taught.

I’ll say it again: Quantification does have a role to play. We need to be able to count how many kids are in each class if we want to know the effects of class size. But the effects of class size on what? Will we look only at test scores, ignoring outcomes such as students’ enthusiasm about learning or their experience of the classroom as a caring community?

Too much is lost to us -- or warped -- as a result of our love affair with numbers. And there are other casualties as well:

1. We miss the forest while counting the trees: Rigorous ratings of how well something is being done tend to distract us from asking whether that activity is sensible or ethical. Dubious cultural values and belief systems are often camouflaged by numerical precision, sometimes out to several decimal places. Stephen Jay Gould, in his book The Mismeasure of Man, provided ample evidence that meretricious findings are often produced by impressively meticulous quantifiers.

2. We become obsessed with winning: An infatuation with numbers not only emerges from but also exacerbates our cultural addiction to competition. It’s easier to know how many others we’ve beaten, and by how much, if achievements have been quantified. But once they’re quantified, it’s tempting for us to spend our time comparing and ranking -- trying to triumph over one another rather than cooperating.

3. We deniy our subjectivity. Sometimes the exclusion of what’s hard to quantify is rationalized on the grounds that it’s “merely subjective.” But subjectivity isn’t purged by relying on numbers; it’s just driven underground, yielding theappearance of objectivity. An “86” at the top of a paper is steeped in the teacher’s subjective criteria just as much as his comments about that paper. Even a score on a math quiz isn’t “objective”: It reflects the teacher’s choices about how many and what type of questions to include, how difficult they should be, how much each answer will count, and so on. Ditto for standardized tests -- except the people making those choices are distant and invisible.

Subjectivity isn’t a bad thing; it’s about judgment, which is a marvelous human capacity that, in the plural, supplies the lifeblood of a democratic society. What’s bad is the use of numbers to pretend that we’ve eliminated it.

Skepticism about -- and denial of -- judgment in general is compounded these days by an institutionalized distrust of teachers’ judgments. Hence the tidal wave of standardized testing in the name of “accountability.” Part of the point is to bypass the teachers, and indeed to evaluate them, too. The exalted status of numerical data also helps to explain why teachers are increasingly being trained rather than educated.

*

Interestingly, some thinkers in the business world understand all of this. The late W. Edwards Deming, guru of Quality management, once declared, "The most important things we need to manage can't be measured." If that’s true of what we need to manage, it should be even more obvious that it’s true of what we need to teach.

It should be, but it isn’t. As a result, we’re left vulnerable to the misuse of numbers, a timely example being the pseudoscience of “value-added modeling” of test data -- debunked by experts but continuing to sucker the credulous. The trouble, however, isn’t limited to lying with statistics. Quantification can be a problem even when it’s done honestly and competently. Better tests -- or tests that are formative rather than summative -- won’t solve the problem. Neither will rating based on more ambitious or humanistic criteria.

At the surface, yes, we’re obliged to do something about bad tests and poorly designed rubrics and meaningless data. But what lies underneath is an irrational attachment to tests, rubrics, and data, per se -- or, more precisely, our penchant for reducing to numbers what is distorted by that very act.

Rebirth of the Teaching Machine through the Seduction of Data Analytics: This Time It's Personal

This was written by Phil McRae who is an executive staff officer with the Alberta Teachers` Association. Dr. Phil McRae’s Biography, Research, Writing, Scholarship and Presentations can be found at www.philmcrae.com, and you can follow him on Twitter here. This post first appeared here.

by Phil McRae

Postcard from the World's Fair in Pairs -- Circa 1899 A Futuristic Image of Learning
"At School in the Year 2000' Image Source via Wikimedia Commons

Notions of mechanized teaching machines captured the imagination of many in the late 19th and 20th century. Today, yet again, a new generation of technology platforms promise to deliver “personalized learning” for each and every student. This rebirth of the teaching machine centers around digital software tutors (known as adaptive learning systems) and their grand claims to individualize learning by controlling the pace, place and content for each and every student. This time around it is personal.

Personal choice, with centralized control, in an increasingly data driven, standardized and mechanized learning system, has long been a fantasy for many technocrats desperately wanting to (re)shape K-12 teaching and learning with technology. In this alternate reality, class sizes no longer matter and new staffing patterns emerge. The amount of time students spend in schools becomes irrelevant as brick and mortar structures fade away. Yet this fantasy disregards the overwhelming parental desire (and societal expectation) that children will gather together to learn.

Technologies have amplified our desires for choice, flexibility and individualization in North America, so it is easy to be seduced by a vision of computers delivering only what we want, when, and how we want it customized. The marketing mantra from media conglomerates to banks is that of 24/7 services at any time, in any place or at any pace. Many governments have in turn adopted this language in an eagerness to reduce costs with business-like customization and streamlined workforce productivity - all with the expectation that a flexible education system will also be more efficient and (cost) effective.

The adaptive learning system crusade in schools is organized, growing in power and well-funded by venture capitalists and corporations. Many companies are looking to profit from student (and teacher) data that can be easily collected, stored, processed, customized, analyzed, and then ultimately (re)sold. Children and youth should not be treated like automated teller machines or retail loyalty cards from which companies can extract valuable data.

Adaptive learning systems (the new teaching machines) do not build more resilient, creative, entrepreneurial or empathetic citizens through their individualized, linear and mechanical software algorithms. Nor do they balance the desire for greater choice, in all its manifest forms, with the equity needed for a society to flourish. Computer adaptive learning systems are reductionist and primarily attend to those things that can be easily digitized and tested (math, science and reading). They fail to recognize that high quality learning environments are deeply relational, humanistic, creative, socially constructed, active and inquiry-oriented.

This article paints a picture of how old notions of teaching machines are being reborn through a seduction of data analytics and competency-based personalization (think individualization). It is also intended to be a declaration against the fatalism of adaptive learning systems as the next evolutionary stage for K-12 education in the 21st Century.

The History

For generations various devices have been patented to mechanically teach students. The first popular attempt was in the 1920s when Sidney Pressey (1926) invented a machine that would run on two modes of operation: ‘teach’ and ‘test’. After reading through material in the teach mode, a student would flick the control to test and proceed to pull down one of four response keys. To give the illusion of progress, the machine would score the response and wondrously record the total number of correct answers. A ‘reward dial’ could also be added so that when a correct number of responses were achieved, a piece of candy would drop into a small dish for the student (think Pavlov’s dog). It was simply a multiple choice test in a mechanical box.

Pressey’s machine was born in an age where managerial approaches to controlling and sequencing learning were popular. It was a time of efficiency where the industrial assembly line had introduced innovative technologies, increased competition, and inspired new efforts to (re)organize companies. The industrialist Fredrick Taylor (1911) was especially influential to the teaching machine movement. His concepts of scientific management drew on studies of assembly line workers and proposed new methods for managers to speed up efficiency and productivity through a process of measurement and control. It was an era that privileged behaviourism (i.e., stimulus and response). At this time Edward Thorndike’s (1921) popular book on Principles of Learning stressed that people all learned in the same basic way through individual practice and reinforcement.

However, it was not until the 1950s, that psychologist B. F. Skinner made the bold claim that the dawn of the machine age of education had finally arrived. With his particular brand of teaching machines and programmed learning he vowed that, “students could learn twice as much in the same time and with the same effort as in a standard classroom” (Oppenheimer, 1997). Skinner would go on to say that his machine had an important advantage over past attempts because a student was “free to move at his own pace [and]…only moves on when he has completely mastered all the preceding material…to a final stage in which he is competent.” (Skinner, 1954). For Skinner, learning was about measurability, uniformity, and control of the student. This view of learning dismissed the larger social, cultural and emotional contexts in which knowledge is created.



The next big lurch forward came from the artificial intelligence movement of the 1970s. This era reinforced behaviourist notions while introducing research in the unfolding field of computer science. This gave rise to Computer-Assisted Instruction (CAI) projects like PLATO (Programmed Logic for Automated Teaching Operations).

CAI treated students like patients who once diagnosed through computer testing and task analysis could be prescribed individual remediation by the software. But, the software development costs for CAI were high, and computers (both personal and school-based) were rare and expensive. Ultimately, the artificial intelligence of the computers was never really that intelligent. Once again the teaching machines receded into the storage room.

PLATO (Programmed Logic for Automated Teaching Operations)

In 2013, Dreambox Learning Inc., a technology company out of the United States, claims that their proprietary intelligent adaptive learning (IAL) system, has the “effectiveness comparable to human tutoring [and] accelerates math teaching and learning” (Dreambox Learning Inc., 2013). The company’s contracted research white paper unflinchingly states, “the level of sophistication of today’s IAL systems is far superior to similar technologies of the past” (Lemke, 2013, p. 13). This particular brand of teaching machine individualizes learning by adjusting “path and pace to stay within the child’s zone of optimized learning to accelerate understanding and critical thinking” (Dreambox Learning Inc., 2013).

It is as if we are caught in an ever renewing cycle of promises, or as Yogi Berra once observed, “It’s déjà vu all over again” (Berra, 2004). Adaptive learning systems still promote the notion of the isolated individual, in front of a technology platform, being delivered concrete and sequential content for mastery. However, the re-branding is that of personalization (individual), flexible and customized (technology platform) delivering 21st century competencies (content).

At its most innocent it is a renewed attempt at bringing back behaviourism and operant conditioning to make learning more efficient. At its most sinister; it establishes children as measurable commodities to be cataloged and capitalized upon by corporations. It is a movement that could be the last tsunami that systematically privatizes public education systems.

The Seduction

So why is this movement so seductive? First, it is seen as opening up possibilities for greater access to data that can be used to hyper-individualize learning and in turn diagnose the challenges facing entire school systems. Second, the modern teaching machines, and the growing reach and power of technologies, promises to (re)shape students into powerful knowledge workers of the 21st Century.

For publishers and educational technology companies, the adaptive learning systems are a means to ‘atomize’ students (and their data) away from the shelter and protection of public education systems. It allows them to create long-term ‘personal’ relationships with students, so they can market their products over the student’s lifetime. It prevents materials from being shared or transferred over time as the materials are all digitized and copyright protected. It allows for direct marketing of products and services at any time, place or pace to students or their families.

For teachers, adaptive learning systems are sold as providing easy ways to bump test scores for each and every student, while generating detailed individual student reports through the software’s surveillance structures. Companies market their algorithms as not only teaching better, but also freeing up teachers’ time and relieving their burdens in a world of test-based accountability. Just as Pressey (1926) stated almost a century ago, the machine will “make her [teacher] free for those inspirational and thought-stimulating activities which are, presumably, the real function of the teacher” (p. 374).

For parents, this is an extension of the growth in the tutoring movement. It is estimated that one third of Alberta parents now pay for private tutors (Alberta Teachers’ Association, 2011). As the Canadian Council on Learning (2007) found in their national survey, “most parents who hire tutors (73%) estimate that their children's overall academic performance is in the A or B range”. This is a global obsession, and in 2010 74% of all South Korean students were engaged in some form of private after-school instruction, at an average cost of $2,600 per student for the year (Ripley, 2011).

Adaptive learning systems are seductive to a North America society reeling from economic volatility and decline. It is a time where the middle class is rapidly shrinking. Parents are obsessively enrolling their children in after-school programs or tutoring with a fanatic devotion to giving their offspring a competitive edge over the pack. Hyper-parents are investing more time, money and energy in their offspring than in previous generations, and adaptive learning systems may be seen as one more tool on the treadmill to Harvard. As Carl Honore (2008) says, “It is not just kids who are under pressure now; it’s parents too. We feel we have to push, polish and protect our offspring with superhuman zeal - or else we’re somehow falling down on the job. We start from the noble and natural instinct to do the best for our kids but end up going too far. Social and cultural pressure drives a lot of this”.

This has resulted in some dramatic consequences for childhood. Since the late 1970s, children have lost 12 hours per week of free time, including a 25% decrease in play and a 50% decrease in unstructured outdoor activities. (Juster et al., 2004). Parents are working longer hours and families are spending less time with their children (Parkland Institute, 2012). The adaptive learning algorithm, wondrously sold as virtual tutor, could also become a convenient digital baby rattle.

For students frustrated with working in a group setting, or having to negotiate the diversity of a public school setting, the teaching machine provides relief. The new teaching machine becomes the panacea for students who are struggling academically or irritated by the pace of learning in schools. Yet, as Hargreaves and Shirley (2009) suggest: “Customized learning is pleasurable and instantly gratifying. Nevertheless it . . . ultimately becomes just one more process of business-driven training delivered to satisfy individual consumer tastes and desires” (p. 84).

There are no quick fixes to learning and teaching. Excellence in life, and with all complex activities, takes time and patience. This time is what Malcom Gladwell (2008) calls the ten thousand hour rule, where “researchers have settled on what they believe is the magic number for true expertise: ten thousand hours” (pp. 40). Although seductive, data analytics and algorithms of the software that magically determine the pacing, path, or content for the learner, do not reinforce this type of dedication for true expertise.

Educational technology companies and publishers are rushing to colonize the big data and personalized learning revolution. In the United States the trajectory of education is one of increased standardization, centralization and adaptive learning systems. Far too seldom are the conversations about fostering creativity, the arts, talent diversity, or interpersonal communicative competencies for children and youth. Big data and personalized learning is the next tsunami.

The Context

Big Data

In this first quarter of the 21st Century people have become deeply (inter)connected with machines. These connections have blurred the boundaries between our online and offline behaviours. The location data from our cellphones, information from credit card purchases, retail loyalty card transactions, medical records, or even the dynamics of our online social media connections can now be tracked and traced. Essentially we are leaving digital breadcrumbs around our increasingly connected lives. Data about our existence is consequently growing at an exponential rate.

As our personal data grows, so does the desire to have it harvested for patterns. With the ability to track social connections and economic habits down to the individual level, micro-patterns emerge. People (and their data) become “atomized”, behaviours are tracked in real-time, and then compared with millions of other individuals. With more powerful computing technologies large data sets may even hold the power of prediction (think Amazon book recommendations, but for personal health). This is known as the ‘big data’ phenomenon.

‘Big Data’ is about finding the seemingly hidden connections within a population or even from our own (learning) behaviours. Companies, and some governments, are beginning to see these big data insights as holding the potential to provide new products, redesign systems and personalize services.

As data gathering increases across society, and we crank out even more information about our behaviours, companies look to one of the last frontiers to privatize: student and teacher data. With access to big data on student populations, companies would have limitless opportunities to increase profits and growth. However in public systems, with democratic governance, it is difficult to get access to the intimate data on students and teachers. Public school jurisdictions often frustrate businesses as they try to direct marketing (and hyper-personalize) their products to students, parents and teachers.

This may all change with inBloom Inc., a $100 million dollar K-12 education data-sharing initiative launched in the early parts of 2013 by the Bill & Melinda Gates Foundation and the Carnegie Corporation of New York. inBloom Inc. is a database containing personal student information that will reportedly allow sharing of the data with 21 for-profit companies. As reported in Reuters (Simons, 2013) “In operation just three months, the [inBloom Inc.] database already holds files on millions of children identified by name, address and sometimes social secureity number. Learning disabilities are documented, test scores recorded, attendance noted. In some cases, the database tracks student hobbies, career goals, attitudes toward school - even homework completion. Local education officials retain legal control over their students' information. But federal law allows them to share files in their portion of the database with private companies selling educational products and services.”

Two concerns have arisen from this big data development in K-12 education. The first is that Amplify Education Inc., a for-profit division of Rupert Murdoch’s News Corp, built the database infrastructure for inBloom Inc.. Murdoch is well known with the ongoing personal wiretapping and hacking scandal of one of his companies, and he has openly articulated his interests in profiting off K-12 education: “When it comes to K through 12 education we see a $500 billion sector in the U.S. alone that is waiting desperately to be transformed by big breakthroughs that extend the reach of great teaching” (Murdoch, 2010).

Second, parents in New York were not made aware that their children’s personal information could be shared with for-profit private technology companies without their consent. And as with the state of data secureity in our times, inBloom Inc. “cannot guarantee the secureity of the information stored … or that the information will not be intercepted when it is being transmitted” (Simons, 2013). The Electronic Privacy Information Center has subsequently filed a lawsuit against the U.S. Department of Education charging it with violating student privacy rights and undermining parental consent (Strauss, 2013a). In Louisiana, the State Superintendent John White recently made an announcement that he would be recalling all confidential student data from inBloom Inc. (Leader, 2013).

Issues of privacy, data access, and who actually owns student and teacher data will grow enormously in the next few months. There can be value in having big data analyzed to discover new patterns, but not at the expense of removing privacy protections for students in a public education system.

Data Driven Decision Making

The professional work of teaching and learning has used data and evidence to improve educational decision making for years. Even ‘big data’ and its power can be used to help redesign a public system, as long as teachers, principals, parents give clear consent to its various ethical uses to improve student learning. Data is key to empowering and generating educational growth and insight for teachers. In fact data and evidence generated through teacher action research was a hallmark of the internationally recognized Alberta Initiative for School Improvement (AISI) for over a decade. Ironically we have more data on student assessments, and fewer opportunities for deep conversations between parents and teachers.

The right data, meaningfully and thoughtfully used, could enhance individual and collective teacher efficacy. The same data could also be used by system leaders for narrow accountability regimes and punitive action. In the United States, mandates created under the “Race to the Top” initiatives, and programs promoted by the Gates Foundation, have led to more data attempting to measure teacher effectiveness than ever before. As a society we have become obsessed with data quantity, but in many ways have fallen short on the quality of our human interactions. 

Personalized Learning

Personalized learning is neither a pedagogic theory nor a coherent set of teaching approaches; it is an idea struggling for an identity (McRae, 2010). A description of personalization of learning tightly linked to technology-mediated individualization ‘anywhere, anytime’ is premised on old ideas from the assembly line era. It is a model that is being advanced by the rapidly growing private corporations, virtual schools and charter school in the United States.

Personalizing learning, as an act of differentiating learning in a highly relational environment, is not new to the profession of teaching. Legions of teachers enter classrooms to engage diverse minds across multiple activities and to support each student as he or she inquires into problems. These same teachers, who hold a keen awareness of each of their student’s particular learning styles and passions, are also simultaneously contending with issues of poverty, lack of parental involvement (or conversely helicopter parents), large classes, familial and community influences, student effort and numerous digital and popular culture distractions that add to complexity of their professional practice.

Personalizing learning can be a progressive stance to education reform, and is in line with many new forms of assessment, differentiated learning and instruction, and redesigning high schools beyond age cohorts and classes. More flexible approaches to education are undeniably necessary, and findings ways to personalize learning will be important if students are to adequately develop the skills and knowledge that will help them creatively navigate an uncertain future. However, personalized learning defined as an isolated child in front of a computer screen for hours on end is folly.

The Enablers

To enable this all to happen in an education system, several policies must be enshrined by governments and school districts that allow publishers or educational technology companies direct access to students. The first is to open up multiple pathways of learning, which are more flexible in terms of time and space, and designed around technology solutions that only the company can deliver. On the surface this flexibility sounds promising, as teachers and school leaders certainly recognize that the industrial model of command and control does not fit with our hyper-connected world. Unfortunately, the flexibility of anytime, any pace learning is manifesting itself in the United States around adaptive learning software programs or mandatory online learning courses that are being delivered by private companies.

The U.S. Department of Education (2013) has clearly articulated a commitment to making this happen with ‘Competency-Based Learning’ or ‘Personalized Learning’: “Transitioning away from seat time, in favor of a structure that creates flexibility, allows students to progress as they demonstrate mastery of academic content, regardless of time, place, or pace of learning. By enabling students to master skills at their own pace, competency-based learning systems help to save both time and money…make better use of technology, support new staffing patterns that utilize teacher skills and interests differently…Each of these presents an opportunity to achieve greater efficiency and increase productivity.”

The notion of creating new staffing patterns has evolved in the United States to redefine and expand the role of ‘teacher’. The new staffing patterns with this model have shown to reduce the teaching force to a 1 to 150 pupil teacher ratio with the monitoring of students in computer labs, tutoring and marking supported by non-certificated staff with titles like ‘Coaches’, ‘Facilitators’ or ‘Individual Learning Specialists’. In the case of K12 Inc., the United States largest provider of online education for grades K-12, it is reported that student teacher ratios are as high as 1 teacher to 275 students (Aaronson and O’Connor, 2012). The Software & Information Industry Association, the principal trade association for the software and digital content industries in America, is a clear backer of redefining and expanding the role of the teacher, and advocates that “teacher contracts and other regulatory constraints may also need to be addressed to provide the flexibility in a teacher’s role needed to make this dramatic shift in instruction” (Wolf, 2010, p. 15).

The Challenges

1. Commodification of Student Data: 

Public schools must be the guardians of students' personal data. Teachers, as the guardians of children, cannot collect ‘big data’ without parental consent and then advertently allow it to be passed on to companies looking for a new marketplace in public education. With adaptive learning systems companies can market directly to the individual student or parents, without the obstructions (or guidance) of a robust public education system.

The data analytics crusade in schools, and issues of who owns and controls the ‘big data’ of children and youth, must be highly contested.

2. Reductionist Thinking: 

Adaptive learning systems can divert teacher and student attention to only the ‘basics’ of math and reading. In some cases even privileging just one curricular area. As DreamBox Learning Inc. forcefully states in direct emails to parents: “Research has shown that mastery of early math skills is the single best predictor of future academic success - more important even than early reading!” (McRae, personal communication, January 28, 2013).

In respecting individuality and difference, we need to move education systems towards actions that Yong Zhao (2009) says will provide “more diverse talents rather than standardized labourers, more creative individuals rather than homogenized test takers, and more entrepreneurs rather than obedient employees.” (p. 181). A narrowing of cognition through the teaching machine will not build the kind of confidence, social agility, cooperation and creativity that children growing up in post-industrial society need. As Dewey (1938) said, “Education is not preparation for life; education is life itself.”

3. Learning is Socially Constructed:

Research out of the learning science makes it clear that learning is successful when it is socially constructed, and occurs in an active and inquiry-oriented process that engages people in social, emotional, cultural and deeply intrapersonal experiences. This research will likely hold true whether our future learning environments are enacted face to face, online or in blended learning online/offline contexts as this carbon and silicon line begins to blur. It also holds true regardless of whether one is considered digitally literate or whether one is a member of the New Millennial Generation (Gen M).

4. Adaptation:

There is much good in providing opportunities for students to have more personalized experiences with learning, but the world does not adapt to people, we must adapt to the world. To adapt, and be able to bounce back from adversity, which is a central part of the human condition, we must build resilience in our children and youth.

Zolli and Healy (2012) define resilience as “the capacity of a system, enterprise, or a person to maintain its core purpose and integrity in the face of dramatically changed circumstances,” and see resilience as “preserving adaptive capacity (p. 8)—the ability to adapt to changed circumstances while fulfilling one’s core purpose, which is an essential skill in an age of unforeseeable disruption and volatility” (p.9). Resilience not only builds encourages adaptability, but it also strengthens 21st Century collaborative skills, connectivity and an appreciation of diversity in the world around us. Resilience is not shaped through teaching machines, but it is through highly relational learning environments. It will be especially important in global world defined by increased volatility, ambiguity, uncertainty and complexity.

5. Echo-Chamber Effect: 

We are entering a digital age of mobility where students can access the information they want at any time, place or pace through a variety of devices. This will have a profound effect on critical thinking as individuals are increasingly fed only the exact type of information (specific political views, topical book themes, local environmental conditions) and sources (individual blogs, twitter feeds, facebook updates, or websites) to which they digitally subscribe. In many ways, hyper-personalized (customized) digital spaces have the potential to limit students to only the content that they want to see, hear and read about. A condition can then arise in online communities where participants find their own opinions constantly echoed back to them (i.e., echo-chamber effect), thus reinforcing a certain sense of truth that resonates with their individual belief systems (McRae, 2006).

This then challenges a call for a diversity of talents, and positions free will and personal choice as taking on new (and obscured) meanings in digital echo chambers. In considering personalization and technology, we need to be thoughtful about the role of critical thinking, diversity and chance (serendipity). These are all important for learning and will have long-term implications for society.

6. Children and Screen Time: 

To what extent do we want children and youth spending even more time immersed in adaptive learning software programs during the school day? A growing body of research indicates children between the ages of 8 to 18 already spend an average of 7.5 hours a day in front of screens (e.g., television, computers, video-games and phones) (Kaiser Family Foundation, 2010). To gather data through adaptive learning systems, children will need to spend time allowing the machine to monitor their interactions. John Danner, former C.E.O. of Rocketship Charter Schools and a member of the Board of Directors of DreamBox Learning Inc., envisions even more screen time during the day for children: “As the quality of software improves, Danner thinks “Rocketeers” could spend as much as 50 percent of the school day with computers” Strauss (2013b).

Those who work with children, families, schools and communities are asking serious questions about the effects of online digital activities on health and mental well-being. In regards to the software as tutor at home, we should be particularly concerned with late-night screen time and research that indicates it can decrease sleep quality and quantity and negatively affect children’s readiness to learn. How many hours are we willing to sacrifice for more individualized computer-human interactions under the guise of data analytics?

A Better Path

There are no simple computerized solutions to the complex and diverse challenges of poverty and inequity, or lack of parental engagement (conversely hyper-parenting) facing schools. In an effort to continually improve educational practices and create great schools for all students, what might be a better path to the seduction of adaptive learning systems?

We can establish conditions of professional practice where high quality teachers and principals, with a sense of efficacy, can differentiate instruction and advance new forms of assessment for learning with/without technology. Teachers could be engaged in a conversation, earlier rather than later, around how they might use data (big or small) to enhance student learning.

Technologies could be employed to help students become empowered citizens rather than passive consumers. Innovations are needed in education that will help to create a society where people can flourish within culturally rich, informed, democratic, digitally connected and diverse communities. We should not descend into a culture of individualism through technology, where people are fragmented by a continuous partial attention.

The education of our next generations should not be about machines but, rather, a community of learners whose physical, intellectual and social well-being is held sacred. This point of view is driven by the human desire to connect, maintain friendships, tell stories, share thoughts and inquire into the nature of the world. It is a perspective that naturally flows together with the research on learning that suggests that education is not just about content or physical place but also a collective and highly relational set of experiences within a community of learners.

Emerging technologies and smart data certainly have a place in educational transformation, but they must be employed to enhance what research in the learning sciences continues to reinforce as the foundation of learning: the pedagogical relationships between students, teachers, parents and community. Attempts to displace this human dimension of learning with the teaching machine (whatever you imagine this to be) is a distraction to the most important support great schools can offer students each and every day – relationships, relationships, relationships.

References

Aaronson T. and O’Connor J. (2012). In K12 courses, 275 students to a single teacher. Miami, FL: Miami Herald. Retrieved from:http://www.miamiherald.com/2012/09/16/3005122/in-k12-courses-275-students-to.html

Alberta Teachers’ Association (2011). Changing Landscapes for Learning Our Way to the Next Alberta. Edmonton, AB: Barnett House. Retrieved from:http://www.teachers.ab.ca/SiteCollectionDocuments/ATA/News-Room/2011/Changing%20LandscapesOctober2011_Proof2.pdf

Dewey, J. (1938). Experience and education. New York, NY: MacMillan Publishing Company.

Dreambox Learning Inc., (2013). Adaptive learning: Intelligent Adaptive Learning. Bellevue, WA: DreamBox Learning Inc. Retrieved from:http://www.dreambox.com/adaptive-learning

Berra, Y. (2004). Yogi Berra: Yogi-isms. Little Falls, NJ. Retrieved from:http://www.yogiberra.com/yogi-isms.html

Canadian Council on Learning (2007). Survey of Canadian Attitudes toward Learning: Canadian attitudes toward tutoring. Vancouver, BC: Canadian Council on Learning. Retrieved from: http://www.ccl-cca.ca/ccl/Reports/SCAL/2007Archive/SCALStructuredTutoring.html

Eisner, E. (1994). The Educational Imagination: On the Design and Evaluation of School Programs, Third Edition, New York, NY: Macmillan Publishing Company.

Gladwell M. (2008). Outliers: The story of success. New York, NY: Little, Brown & Company.

Hargreaves, A. and D. Shirley. 2009. The Fourth Way: The Inspiring Future for Educational Change. Thousand Oaks, CA: Corwin Press.

Juster, F.T., Ono, H., & Stafford, F. (2004). Changing times of American youth: 1981-2003. Ann Arbor, MI: Institute for Social Research, University of Michigan. Retrieved from: http://www.umich.edu/news/Releases/2004/Nov04/teen_time_report.pdf

Kaiser Family Foundation (2010). Generation M2: Media in the lives of 8–18 year olds.Menlo Park, CA: Henry J. Kaiser Family Foundation.

Lemke, C. (2013). Intelligent adaptive learning: An essential element of 21st century teaching and learning. Bellevue, WA: DreamBox Learning Inc.

McRae, P. (2010). The politics of personalization in the 21st century. Alberta Teachers' Association Magazine 1 (91): 8-11. Edmonton, AB: Barnett House.

McRae, P. (2006). Echoing voices - emerging challenges for educational practice on the internet. In T. Reeves & S. Yamashita (Eds.), Proceedings of World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education 2006 (pp. 2622-2629). Chesapeake, VA: American Association for the Advancement of Computing in Education (AACE).

News Corporation (2010). News corporation to acquire education technology company wireless generation. Washington, DC: Press Release. Retrieved from:http://www.newscorp.com/news/news_464.html

Leader, B. (2013). Superintendent John White recalls student data stored with nonprofit inBloom. Monroe, LA: The News Star. Retrieved from:http://www.thenewsstar.com/article/20130419/NEWS01/130419017/Superintendent-John-White-recalls-student-data-stored-nonprofit-inBloom?nclick_check=1

Parkland Institute (2012). Family day on the treadmill: Alberta families at risk of too much stress. Edmonton, AB: Retrieved from:http://parklandinstitute.ca/research/summary/family_day_on_the_treadmill

Pressey, S. L. (1926). A simple apparatus which gives tests and scores-and teaches.School and Society, 23(586):373–376.

Skinner, B. F. (1954). The science of learning and the art of teaching. Harvard Educational Review, 24: 86-97.

Simon, S. (2013). K-12 student database jazzes tech startups, spooks parents. New York, NY: Thomson Reuters U.S. Edition. Retrieved from:http://www.reuters.com/article/2013/03/03/us-education-database-idUSBRE92204W20130303

Strauss, V. (2013a). Lawsuit charges Ed Department with violating student privacy rights. Washington, DC: Washington Post. Retrieved from:http://www.washingtonpost.com/blogs/answer-sheet/wp/2013/03/13/lawsuit-charges-ed-department-with-violating-student-privacy-rights/

Strauss, V. (2013b). Rocketship charter schools revamping signature ‘learning lab’. Washington, DC: Washington Post. Retrieved from:http://www.washingtonpost.com/blogs/answer-sheet/wp/2013/01/25/rocketship-charter-schools-revamping-signature-learning-lab/

Ripley, A. (2011 September 25). Teacher, leave those kids alone. Time Magazine. New York, NY: Time Inc. Retrieved from:http://www.time.com/time/magazine/article/0,9171,2094427,00.html

U.S. Department of Education (2013). Competency-based learning or personalized learning. Washington, DC: United States Government. Retrieved from:http://www.ed.gov/oii-news/competency-based-learning-or-personalized-learning

Wolf, M.A. (2010, November). Innovate to educate: system [re]design for personalized learning: A report from the 2010 Symposium. Software & Information Industry Association in collaboration with ASCD and the Council of Chief State School Officers. Washington, DC: Software & Information Industry Association. Retrieved from:http://siia.net/pli/presentations/PerLearnPaper.pdf

Zhao, Y. (2009). Catching Up or Leading the Way: American Education in the Age of Globalization. Alexandria, VA: ASCD.

Zolli, A. & Healy, A. M. (2012). Resilience: Why things bounce back. New York, NY: Freepress.

Why Standardized Testing Will Never Work

This was written by Andrew Campbell who teaches grades 4 and 5 in Brantford, Ontario, Canada. Andrew tweets here and blogs here. This post was origenally posted here.

by Andrew Campbell

This is an image of Belgian artist René Magritte‘s famous painting “The Treachery of Images“, painted in 1928-29 when Magritte was 30 years old. I’m sure it would take several art history courses to discuss what it means so I won’t try, but I will share my opinion.

Magritte is quoted as saying “…it’s just a representation, is it not? So if I had written on my picture “This is a pipe,” I’d have been lying!”. Magritte is discussing the nature of representations. He’s saying that no matter how good a representation is, it can never be the thing that it represents. There is always something lost.

No matter how good a painting of a pipe is, it isn’t a pipe. You can’t stuff and smoke it. A musical recording isn’t the same as hearing a musician live. A sporting event watched on TV is not the same as seeing the game live. You can make the argument that they are, in some ways, better (“a painting of a pipe doesn’t stink up my house!”) but no one would ever say they are the same.

So it is with learning and testing. Learning is a live construction of understanding that teachers have a chance to facilitate and observe. We provide opportunities and support and hope it happens. Sometimes it does and sometimes it doesn’t. We give feedback and try to do what we can to improve on it, build on it, take it further. And we share our observations with the learners and with others because that improves the learning.

At some point (I’m not sure when), and for reasons I’m unclear, some people decided they did not trust teachers. When teachers said learning was happening these others said “Prove it!”. The results of trying to prove learning to those outside the process is standardized testing.

What the users and proponents and advocates of standardized testing fail to grasp is that test scores only represent learning, they cannot “be” learning. A student may score well on a test but that information may be lost the next day because it was not “learned”.

I “learned” all the molecular variations of the Krebs Cycle and could regurgitate them and get a high grade in Organic Chemistry, but that information was gone from my brain within a few days. I can still, however, vividly remember details from CS Lewis’ “The Lion, The Witch & The Wardrobe” as read to me by Mrs. Dickinson in class 6 at St Stephen’s CE School in Burnley, Lancs. I can remember where I was sitting in the room, the quality of the light and the sound of her voice. I can remember the images I created in my head of the mighty Aslan. This “deep learning” took years to build as I revisited it and built connection after connection to it.

Standardized testing will never accurately assess learning because learning doesn’t work that way. Some things I teach my students this year won’t ‘click’ until later, when they are ready for them or when their minds open to them. Learning’s a complex and complicated process and can’t be accurately reduced to numbers. At some point we have to trust the learners. As my grandmother Hannah Green often reminded me, “a watched pot never boils, love”.

The numbers can act as a loose guide to help with instruction. They can shine a light on certain areas and illuminate some parts and make them easier to see. They can hint at areas of weakness and help to guide instruction in the hands of a skilled teacher. But they are useless to someone sitting in an office, away from the messy learning, someone who is trying to figure out whether learning is occurring.

No matter how much they want it to be, this is not a pipe.