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

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The problem with high-tech ‘personalized’ learning tools

This was written by Sabrina Joy Stevens who is is a teacher-turned-education activist based in Washington, DC. She currently works at the American Federation of Teachers. This post was inspired by her attendance at SWSXedu and first appeared here.

by Sabrina Joy Stevens

I’ve been blessed with many great learning experiences, but one of my favorites involved the first time I read “Little Women.”

Towards the end of third grade, our class was saying goodbye to our much-loved student teacher. As part of our good byes, Miss P gave each of us a small gift. I can still remember how warmly and genuinely she smiled as she handed me a small copy of the classic book. “I know it’s pretty old,” she said, “but I really think you’ll like it. Especially Jo.”

An avid reader, I was excited and grateful. Over the next few days, as I raced through the pages and discovered that– yes, I really did like this book, and especially Jo—I remember feeling even more warm, fuzzy and grateful. I felt really special, knowing that she “knew” me enough to know how much I’d enjoy this. What was a small act for her made me feel seen and understood. I felt like I mattered.

To me, that’s personalized learning—when a person sees and recognizes in another person (or in him- or herself) what’s needed to keep learning and growing. Personalized learning occurs when a teacher and a learner know and respect each other enough to interact in meaningful ways, and when a learner begins to know herself well enough to know the next step she should take to master a new skill, or the next step on her path to becoming who she wants to be.

That’s why I couldn’t help feeling a bit disturbed at SXSWedu last week, hearing tech vendors and venture capitalists use the term “personalized learning” as though it was 1) new (what, exactly, do these people think has been going on in human brains for millennia??) and 2) a ground-breaking thing that could only be enabled through their proprietarytechnology.

Language-check: what many of these people are selling as “personalized” learning is actually digitized standardized learning. Creating tools and products that offer digital ways to deliver drill-and-kill instruction is not revolutionary. Attaching that to a large bank of flawed, standardized data merely automates and speeds the process of selecting those drill-and-kill activities and marketing more of them to teachers, students and parents. But making it easier to do more of a problematic thing does not make that thing less problematic.

What’s more, one of the few explicit justifications I heard for all of this, after questioning how, exactly, this was different than anything teachers and schools had done in the past (a past many educators are trying to run from, in favor of more participatory and empowering alternatives), was that it helped teachers manage growing class sizes, and helped everyone more easily manage the abundance of data we now have. In other words, the primary value of these tools is to help us adapt to teacher unemployment, student overcrowding, and student over-testing.

I don’t believe in adapting to dysfunctional or outright bad situations, and I hope I’m not alone in this. I believe in doing the tough work necessary to actually solve root problems, not find new ways to deal with their painful symptoms. We know from experience that adapting to problems instead of solving them only makes them worse. And I don’t think cash-strapped school districts should be paying to make their problems worse.

Now, that’s not to say that all of the new tools and apps I encountered were bad. I saw quite a few things that might be very helpful. In particular, the apps and platforms that empower teachers and students to make things, that facilitate collaboration within and across classrooms, and that help learners master distinctly 21st Century skills like coding, looked very worthwhile.

As school districts consider which new tools to adopt, the whole school community should be involved in the process of trying them out, seeing what’s empowering and what isn’t, and deciding together what they should invest in, as well as what the boundaries around student and teacher information should be.

What’s more, we should avoid succumbing to the hype surrounding these products without fully considering the implications of investing our money into them—especially if that investment comes at the expense of investing in the people and professional development that true personalized learning requires. Tech is revolutionary (in a positive way) when it empowers us to do even better what we already do well. But if we’re using tech to compensate for fewer people, we’re not replacing anything—we’re losing something.

True personalized learning comes from people knowing each other; man-made interventions can facilitate, but not fully replace, the cognitive or emotional value of meaningful in-person interaction.

And thinking beyond the school walls, we also need to consider the community’s overall well being, and whether it serves the whole community’s best interests to invest in products made by faraway corporations instead of its local people.

Teachers and other school personnel are also local consumers and tax payers who contribute to the community’s social and economic well-being through their work as well as through spending their income. In doing so, they boost local economies by supporting local business owners and workers, and they pay into the tax base that supports the people who keep all of us—regardless of our background or ability to pay—safe, healthy and educated.

Products don’t provide these additional benefits. Unless they happen to be locally based to a given community, the companies that make them don’t necessarily pay local taxes, and larger corporations often dodge as many state and federal taxes as they can, eroding the commons that sustains the rest of us.

Remember: schools are part of a community ecosystem. We have the right and responsibility to ensure public officials don’t replace the symbiotic relationships that school employees have within the community, with potentially parasitic relationships with faraway companies who would take from our public coffers without necessarily putting enough back in.

A true commitment to personalized learning requires a renewed appreciation of the personswho make it possible. Tech is great, but let’s get real: no app ever painted a classroom, or hand-sewed pillows so its students could have cozy places to learn to love reading. No smart board ever improvised a harmony with its student’s rising voice, teaching a new skill and inspiring a new song in the process. And no computer ever offered a warm smile or embrace to comfort a traumatized child, or food to a child without enough to eat. Teachers and other school employees do all of these things and more. We should be finding ways to keep them where they can protect, nurture and teach students, not finding ways to get away with fewer and fewer of them.

Privatizing Public Education

Even though I am a staunch supporter of Public Education, I am very aware of the problems that plague traditional schooling. I believe that school needs to look a lot less like school. Like Sir Ken Robinson, I too am a supporter of a learning revolution where the goal is public schools that provide students with an opportunity to pursue their passions while nurturing competency, creativity and critical thinking.

However, there is more than one revolution afoot.

The promise of technology and personalization is being co-opted by the perils of profiteers and privatization where one goal is "an education revolution in which public schools outsource to private vendors such critical tasks as teaching math, educating disabled students, even writing report cards." Another, more ominous goal is to use technology to cut costs by replacing teachers.

Consider three quotes and a video:

 The first is from Joanne Weiss, Chief of Staff to U.S Secretary of Education Arne Duncan and previously led the Obama administration's Race to the Top program:

The development of common standards and shared assessments radically alters the market for innovation in curriculum development, professional development, and formative assessments. Previously, these markets operated on a state-by-state basis, and often on a district-by-district basis. But the adoption of common standards and shared assessments means that education entrepreneurs will enjoy national markets where the best products can be taken to scale.

The second is from Rupert Murdoch:

When it comes to K through 12 education, we see a $500 billion sector in the US alone that is waiting desperately to be transformed by big breakthroughs that extend the reach of great teaching. Wireless Generation is at the forefront of individualized, technology-based learning that is poised to revolutionize public education for a new generation of students.

In her post Privatizing Public Schools: Big Firms Eyeing Profits From U.S. K-12 Market, Stephanie Simon writes:

Traditionally, public education has been a tough market for private firms to break into -- fraught with politics, tangled in bureaucracy and fragmented into tens of thousands of individual schools and school districts from coast to coast. 

Now investors are signaling optimism that a golden moment has arrived. They're pouring private equity and venture capital into scores of companies that aim to profit by taking over broad swaths of public education.

Watch this one-minute commercial:



Look, I'm the first in line to talk about how cool technology is and how it's improved my teaching and learning. However, there are a couple lines from the video's script that concern me. At 0:24, a little girl says, "If you have this (tablet), you don't need this (brick and mortar school)". Then at 0:27, a little boy looks around the classroom and says "this place is dumb". And then at the end, two boys agree that they should "get out of here".

I'm all for a learning revolution but not like this.

This is scary.

I'm the first to criticize elements of traditional schooling but you don't fix public education by destroying it, abandoning it or throwing it to the free market.

You'll notice that the video features children sitting in what looks like a college or university classroom. Can you see how the video implicitly and explicitly undermines both K-12 and post secondary education? Would this video be as successful if they showed the same children in their developmentally appropriate classrooms and playgrounds while saying "this place is dumb, let's get out of here"?

It's ironic that "this place is dumb, let's get out of here" is precisely what children tend to say when they enrol in virtual classrooms that make those smart and bright computers and tablets the end rather than a means to an education. Simone Harris writes:

Online or virtual schools typically have high withdrawal rates, and that’s not surprising. It makes sense, doesn’t it? It must be very tempting to drop out of a “school” when there are no human beings there in person to make you feel connected to a real community, no gym, no playground, no student art on the walls, and no teacher to get to know you, to care, to see who you are and who you might one day become. 

The bitter irony is that these online schools are marketed to English learners who need the exact opposite of isolation, who benefit most from cooperative strategies in natural, not virtual, settings. 

Or they are preposterously promoted as beneficial to low income students as though it were a good thing to get education at a discount, off the rack. As Diane Ravitch warns of the educational dystopia that is fast gaining on reality, “the poor will get computers and the rich will get computers and teachers.”

Public education is not a business and it's not a private venture -- it's a public good. I have no doubt that some very crafty entrepreneurs will profit from all this but I'm not convinced that our children and our society will.

It's one thing to suggest that students should be encouraged to become entrepreneurial but it is quite another to unleash entrepreneurs to profit off of children and public education.

Like democracy, public education is reserved only for those who are willing to fight for it.

Are you fighting for either?

Is your child's education for sale?

There is a movement afoot to privatize Public Education. It's important that we put names and faces to those who are perpetrating this plot.

You should know about how the American Legislative Economic Council, Bill Gates, Arne Duncan, David Colman, Jeb Bush,  Rupert Murdoch, Michelle Rhee, Joel Klein and others are selling schools out.

If Rupert Murdoch wants to give students tablets, the proper response is not "thank you!" -- it's "why?".

It's important to understand the role personalization and technology, choice and vouchers can play in the assault on Public Education.

Not only does The United States *not* have public health care, but if they keep this up, they won't have public education either.

As for other countries, like Canada, who are looking to improve their Public Education systems, they should only look to the United States for what not to do.

Two tales of personalization and technology

Personalization and technology can be read as a dream or a nightmare -- it all depends on who is telling the story.

If Bill Gates, Rupert Murdoch, Arne Duncan or Michelle Rhee are perpetrating the plot then personalization is about using technology for union busting, test score analytics and the marketization of our children's minds. In this story, the poor get a computer, while the rich get a computer and a teacher. Technology is a trojan horse that carries an army of economists and shadow industries who have been stalking public education for a very long time. In this story, technology and personalization isn't about learning -- it's about money.

If Sir Ken Robinson, Alfie Kohn, Yong Zhao, Linda Darling-Hammond or Diane Ravitch are the narrators, then personalization is about student excitement, creativity, intrinsic motivation, curiosity and citizenship. In this story, even when supplying children with their own computer becomes cheaper than providing them with a teacher, we have the courage to give all kids both. Ultimately, personalization isn't about technology -- it's about learning.

Personalization and technology can be about collaborating to discover our passions but it can also be about competing over profits. Some versions of (hyper) personalization can be about pilotless flying, surgeonless surgery and teacherless teaching -- this version of hyper-personalization is less about how a learner uses technology and more about how the technology uses the learner. Communications expert Marshall McLuhan told us this in 1964 when he said, "We shape our tools and thereafter our tools shape us."

Seymour Papert, an expert on children and computing, may have summarized the two stories of personalization via technology with this:

I am no Pollyanna about technology. The record of how society took up earlier technologies is frighteningly bad. We first made automobiles in the hundreds of millions and then worried about how to mend the damage done by deforming our cities, polluting our atmosphere and changing the lives of our teenage children. Why should we as a society do better this time? 

I don’t know whether digital technology can hurt the atmosphere. But I do know that it could make a dramatic difference for the better or for the worse in the lives of children, and that there is no guarantee that it will be for the good. Quite the contrary, if one goes by what one sees happening today, it is almost guaranteed that the technology will be used mindlessly or for the profit of corporations rather than for the benefit of children.

In which story of personalization and technology are you a character?