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  • How to make teaching the career choice for Millennials

    by Kathy McKnight

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    Ask a group of American kids what they want to be when they grow up, and odds are you’ll hear “teacher” less and less. In the US there are some disturbing indications that teaching is increasingly falling out of favor as a career choice. Between 2008-09 and 2012-13, there was a massive 30% drop in enrollments to teaching preparation programs; while The New York Times reported that applications for Teach for America, a well-respected program to recruit elite college graduates to teach in high poverty schools, declined by 10% from 2013 to 2014. It is perhaps even more troublesome that teaching also seems to be falling out of favor with teachers - a 2013 MetLife survey indicated that just over one in three teachers reported to be “very satisfied”, down by almost 40% in just four years.

    One of the reasons put forward for this trend is the perceived narrowness of the teaching career path, especially amongst Generation Y ‘Millennials’. This is, according to research, the demographic that’s impatient to realise their ambitions, demanding of choice and opportunity, and certain that their careers will move forward on their terms - features they do not relate with teaching.

    So three years ago Pearson, with several key partners, set out to understand how the teaching profession can evolve to meet the 21st century career expectations of those who currently teach, and those that might one day.

    In that time we’ve studied eight teacher career advancement initiatives in the US, and found there’s much to be encouraged about. From urban to suburban and rural districts; in areas of affluence and high poverty; and in schools with and without strong union presence - there is plenty of evidence for how to improve teacher career pathways, and what happens when you do.

    Here are some of the key highlights from our observations. You can read the full report here.

    Districts observed improved trends in the recruitment and retention of teachers: All districts with teacher career advancement initiatives reported an increase in applicants to teach, and increased retention rates - notably of effective and experienced teachers.

    Creating time for teachers to meet and collaborate is an ongoing challenge for districts: One of the most commonly cited advantages of teacher career advancement initiatives was more collegial interaction, with teachers working with colleagues across grade levels and subject areas. In part this is due to the significant costs associated with releasing teachers full-time for instructional coaching, meaning that mentoring and coaching is often done ‘in-house’ by other teachers. Some districts have even adopted 'hybrid' teaching/coaching roles. The benefit is felt by both mentee and mentor. One mentor teacher from Knox County said to us: “I’ve told so many people that they need to be mentor teachers because just what you learn about yourself is much. I feel like I’ve gotten more back from doing it than I’ve given to my people that I coach.”

    However, we also observed that it takes time and effort to change the culture of isolation to promote sharing of practice and collaboration.

    There is some evidence of a positive impact on teacher effectiveness and some short-term student learning outcomes: There is limited 'hard data' about the impact of teacher career advancement initiatives on student achievement, although there is much anecdotal evidence. Teacher and administrator focus groups almost universally cited the positive benefits on students of teacher collaboration, focused conversations on curriculum and instruction, lesson modeling, and taking time to reflect on teacher effectiveness.

    “This is about closing achievement gaps, and you don’t close achievement gaps by doing the same … things that you’ve done for 50 years,” one Denver administrator told us. Another, from Scottsdale, commented: “It is because of that career ladder culture [that] every single teacher is vested in getting that student growth, doing the best thing they can for their students on campus, in their classroom, at their school… it really has created a culture within our district.”

    Teachers in leadership roles report greater job satisfaction: The general consensus of teacher leaders we interviewed was that motivation and job satisfaction were positively affected by opportunities for collaboration and professional development, recognition as leaders in their district, and opportunities for additional compensation. Interestingly, we also heard that another significant positive feature of the teacher career advancement initiatives is that teachers can take on leadership roles without stepping into formal administrator roles.

    “I knew in a flash that this new [multi-classroom leader] model would bring me my dream job… a teacher who continues to teach while leading a team of teachers…” a teacher from Charlotte-Mecklenburg Schools told us.

    Teacher/administrator relations and the roles of principals change in positive ways, but present new challenges: Our studies found that, as teachers and administrators collaborate more, there becomes a need to manage teams of teacher leaders who now require new skills, and also additional support for principals. A Seattle ‘career ladder’ teacher described her experience to us: “Oh, you’re going to be on this professional development committee which is going to meet every other week on top of the building leadership team, on top of leading your own PLC. It becomes you’re one of five people that are doing everything in the school and that’s not the point of the role.”


    For all the positives coming out of our study, the reality is that sustaining these initiatives is hard work, requiring stakeholder support (teachers in particular), a school/district culture that can deal with change and ambiguity, and external support—either monetary or technical assistance. Funding in particular is the greatest challenge to continuity. Grants, either district funding sources or from external bodies, are typically designed to launch programs, not sustain them. Our study sites are navigating this treacherous territory in different ways, and with differing success. Denver, for example, offers a vision of flattening the organizational structure of schools and replacing some highly paid administrative positions with teacher leaders. A teacher we spoke to there made the point that this was not just about sustaining funding, but also maintaining the right culture.“This needs to be a teacher-led initiative, a teacher supported initiative, because it is about elevating the craft from the peer perspective…”

    The next few years will be critical in determining whether these teacher career advancement initiatives will continue, expand or be modified. With the new ESSA legislation and the focus on developing teaching and the profession, we hope that the lessons learned and recommendations contained in the full report will help propel more schools and districts to implement innovative, sustainable teacher career advancement initiatives. And to make the profession top of the list of what kids want to be when they grow up.


    Follow up with Kathy about this research - @McKni8

  • Intelligence Unleashed: an argument for AI in education

    by Michael Barber

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    For thirty years I have attended conferences where speakers have spoken to slides comparing images of an early 20th century classroom with one from today, and have pointedly asked: ‘why so little change?’ The modern variant goes something like this: smart technologies have already transformed so many parts of our lives – from how we date to how we book a taxi. It would seem that there is no doubt that AI (artificial intelligence) will also significantly influence what we teach and learn, as well as how we do it. And yet...

    Adopting a puzzled stance as to why things have not changed more has some value. It prompts us to examine our assumptions, our habits, and our routines. It only takes us so far, though. More is needed.

    What we need – what we should demand – is an explanation of why and how things could be different. First, we need to be empowered by an understanding of what artificial intelligence in education (AIEd) is, what it delivers, and how it goes about doing that.

    Second, we need a clear explanation of how the field of artificial intelligence can connect to the core of teaching and learning, so that we can avoid general-purpose technologies being used in ways that do not deliver the step changes in learner outcomes we seek. For example, smart technologies that adapt to what is liked, rather than what is learnt, or that deliver more efficient administration, but not more efficient learning.

    Third, we need concrete options that will allow us to make the potential of AIEd real at the system level – that is, at the scale that will allow it to support the teaching profession broadly and impact positively on the learning experience of each and every student. And fourth, we need to ask and answer some profound ethical questions – for example, about the acceptable uses that can be made of the data that AIEd collects.

    In other words, what we need is a degree of specificity about AIEd that allows us to assess, invest, plan, deliver, and test. This is what our new research paper, 'Intelligence Unleashed', offers – a useful primer on AIEd and a compelling argument about what it can offer learning.

    From what AI is and how AIEd-driven learning systems are built, onto its potential role in addressing the profound issue of robots and machines taking over more and more current jobs, it covers a vital range of topics with ease and elegance. It is also a good read, with entertaining references from PacMan and Stephen Hawking, sci-fi and ancient philosophy. And, yes, it is understandable to a non-technical reader!

    To make my own case for reading this paper, let me move to a more local, anecdotal, level. Recently a member of my Pearson team talked to me about a phonics learning app he had bought for his young son. We could easily identify the affordances that the technology brought – perfect pronunciation of 42 phonics sounds, infinite patience, and a healthy spillover of engagement from the software to learning.

    Yet, it was equally easy to identify ways in which some basic AIEd techniques could have made the app so much better. Content was re-presented even after it had been mastered, which led to boredom. Other content was accessible even though it was much too difficult, leading to frustration. And there were no speech recognition capabilities present to verify the learner’s pronunciation, or blending of sounds.

    Asking for these features is not asking for science fiction. Instead, it is asking us to incorporate findings from fields like the learning sciences into AIEd tools so that these insights are realised in cheaper, more effective ways. This paper offers a long-list of where we should look for this combination of learning insights and technology – for example, collaborative learning, meta-cognition (or knowing about one’s own thinking), useful feedback, and student motivation.

    Funders and founders, policy makers and philanthropists – in fact, anyone who takes seriously the urgent need to embark on the next stage of education system reform – should read and debate this paper. Only then will we (finally) make good on the promise of smarter technologies for learning (and, as a side effect, get rid of those boring slides).


    Read the full report - Intelligence Unleashed: An Argument for AI in Education

  • Britain and the EU

    John Fallon

    by John Fallon

    Man walking and wearing a back pack and wooly hat

    Now that the referendum on Britain's membership of the European Union has been set for June 2016, lots of organisations and people are asking what Pearson thinks about the issue.

    First and foremost, we think this is a decision for the British people to make, and no doubt there will be a range of opinions within Pearson, as there are across the country. Each of us in the UK has a vote, and will use it as we see fit.

    We have though been asked by some organisations on both sides of the debate what Pearson's position is and we think it's right to take a view.

    Only a small proportion of Pearson's business relies directly on trade between the UK and the rest of the EU. Nonetheless, we have carried out analysis of how Britain leaving the EU would affect Pearson across a number of regulatory and financial aspects. This analysis has concluded that Pearson would be better served by the UK remaining part of the EU.

    As part of Britain and Europe's education community, we see the considerable value that British membership of the EU brings to universities, colleges, schools, teachers, students and pupils.

    As a global business based in the UK, we believe that Britain, its businesses and its people are, on the whole, better off as part of Europe.

  • The Pearson Affordable Learning Fund: combining social need with business know-how

    by Kate James

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    Tens of millions of children and young adults are missing out on their education due to conflict, threat of attack or the after-effects of natural disaster, some for weeks and months, still more for years at a time. When world leaders came together at the UN in September 2015, this challenge was top of mind as discussion focused on the Syrian refugee crisis and the need for both immediate action; and also with the launch of the 17 Global Goals, long term sustainable solutions to the world's biggest humanitarian challenges.

    At Pearson, we’ve chosen to work with Save the Children to pilot models of sustainable, quality schooling for children in conflict zones, but we also want to address the ongoing education crisis that can be less immediately apparent than that brought about by war - 59m primary-school-age children out of school and nearly 800m illiterate people across the world. For those learners who are in school, there are many other trenchant challenges that plague education systems in sections of the developing world: lack of teachers, poor teacher development, insufficient materials, out of date resources...the list goes on. As we focus on Global Goal 4 - to ensure inclusive and quality education for all and promote lifelong learning - we are looking at ways to ensure every learner has access to a high-quality, affordable education.

    One of the ways we are looking to do this is through the Pearson Affordable Learning Fund (PALF), which invests in entrepreneurs who are helping to meet the demand for high-quality, low-cost education in the developing world. In PALF’s first annual letter, learn more about the impact and reach of our ten portfolio companies as they set out to improve the quality of education for people everywhere.

  • The case for "unbundling" the teacher

    by Michael Barber

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    For most of the past century we have bundled a very complex set of disparate skills into a single role we call the ‘classroom teacher’. Teachers must have deep content knowledge to understand the scope and sequence of a curriculum, and pedagogical expertise to plan effective lessons and evaluate student comprehension and mastery. We also ask them to be charismatic presenters, a coach/mentor to provide support and motivation for students to persevere, and project managers able to keep track of each students academic progress.

    It is incredibly difficult, and perhaps unrealistic, to expect to find such a diverse skill-set in a single individual. As a result the past few years has seen various attempts to “unbundle” the teacher. While much is made of the developed world’s experiments with unbundling, most notably flipped classrooms and MOOCs, some of the most interesting innovations are occurring in the developing world where the dual constraints of limited financial resources and a weak labor pool make the need for new solutions all the more pressing.

    The Pearson Affordable Learning Fund has invested in some exceptional entrepreneurs that are tackling this challenge head-on.

    For example, at SPARK, a school chain in South Africa, a highly trained teacher is in charge of the whole group and guided practice portions of the typical learning cycle, while the independent practice portion of the learning is done primarily with the aid of “e-learning labs.” Here students work to reinforce and extend classroom instruction with personalized computer programs overseen by a more junior assistant.

    This allows the extremely valuable time of the master teacher to be dedicated to the more complex tasks of implementing best-in-class instructional methods and overseeing classroom management. As a result, the cost of delivering high-quality education is substantially lower, while quality is maintained.

    Another example of the same trend is provided by Bridge International Academies, who dedicate the bulk of their six-week teacher training program to focusing on techniques for classroom management, student engagement, and checking for understanding, while a team of world-class educators based in Boston and Nairobi write a rigorous, student-focused lesson script which the teachers read on an e-book during class.

    Visiting a Bridge classroom you will see students being pushed to perform more challenging cognitive tasks (for instance, instead of simply writing down a list of map symbols they will be using these symbols to draw a map of their own neighborhood) with teachers circulating the classroom carefully checking students work. Both of which are rarely found in a typical classroom in Kenya.

    My prediction is that 2016 will see much more piloting, experimenting and testing of these new models. Some will be taken to scale, most obviously through new public-private partnerships that are able to see the value in moving away from the old model of a single, jack of all trades, teacher. This division of labour will allow expertise to be deployed where it is most needed, and where it can best be found - and the impact on learning will become increasingly visible.


    Read more about the work of SPARK and Bridge.

  • Educate the lost generation before it's too late

    John Fallon

    by John Fallon

    A girl being creative

    One of the less visible victims of the Syrian conflict has been education. The war has left almost three million Syrian children out of school - those that have stayed and the refugees who have fled. As the crisis continues to worsen, we need to focus on how to educate these children before they become a "lost generation". I attended a discussion this morning in London as part of the Supporting Syria event led by the governments of the UK, Germany, Kuwait, Norway, and the United Nations. Education was, rightly, high on the agenda.

    It is not enough to sit around and say that something must be done. It is not enough to leave it to governments, to hope the private sector will invest, or to rely on NGOs to bring assistance and order. It is not even enough for those of us with the ​power and responsibility to ‘act’. We have to act together to make the biggest impact we can​.

    For Pearson, that means sharing our expertise in delivering educational products and services at scale. We have the know-how - every year our products help many millions of teachers and students, of all ages, all over the world. But we have little experience of operating in conflict zones or refugee camps or dealing with the trauma of those who have been affected by war.

    That’s why we launched “Every Child Learning” nearly a year ago - a three year partnership with Save the Children that’s increasing educational opportunities for Syrian refugees and their host communities. The partnership has already provided two education centres in Amman, Jordan which are educating 1,400 Syrian five to 13 year olds. We’ve also committed £1m to research, to understand the sort of learning experiences that are needed and will work on the ground.

    If our partnership can have a positive impact for Syrian child refugees, we'll move on and see how we can help teach children affected by wars and emergencies in other parts of the world too.

    Education in emergencies and conflicts remains the most underfunded of all humanitarian areas. According to UNESCO only 2% of global humanitarian aid was allocated to education in 2014. Yet improving the provision of quality education in these settings will often be the catalyst to peace and stability. The challenge may be great, but the prize is much greater.

    All of us involved in education have a responsibility to ensure that there's no lost generation in Syria, or anywhere else in the world. At Pearson we’ll continue to work with others on all sorts of challenges - our allies in the Global Business Coalition for Education, our partners in Project Literacy, our business colleagues at the Pearson Affordable Learning Fund - anyone who believes like us that the best way to help people make progress in their lives is through access to quality education. It’s a responsibility that eclipses sectors or politics or ideologies. It is, very simply, a battle for the basic human right to learn.


    Read more about 'Every Child Learning'.

  • The Pearson Affordable Learning Fund: delivering access and progress

    John Fallon

    by John Fallon

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    In Kenya, many children who attend Bridge International Academies are getting results in the top 5% nationally. In India, what began as a single classroom helping children in slums to learn English has grown into 800 schools serving 200,000 students who outperform ‘traditional’ classrooms by between 20-60%. And over 3,000 children in the Philippines are benefitting from being at schools where teachers received a 100% pass rate on their licensure tests.

    These are just some of the extraordinary outcomes being achieved by a new generation of education entrepreneurs around the world – entrepreneurs that Pearson has been helping to guide.

    In recent years the debate around how to fix global education has shifted. It is no longer enough just to talk about getting every child into school (though alas not because that has been solved.) Just as important is what happens when they’re there. When the world pats itself on the back that 43 million more children now go to school than five years ago, someone needs to keep asking, “what next?”. In other words, is the increase in access leading to improvements in progress?

    Through the Pearson Affordable Learning Fund (PALF) we are helping local entrepreneurs across Asia, Africa and Latin America to go further and faster in improving education in their local communities. From Ghana to India, our team has found brave innovators, exploring how new teaching and learning approaches can serve their communities. As my colleague Katelyn Donnelly, who heads up PALF, says: “It was clear everywhere we went—from Pakistan to Ghana to the Philippines—parents, students, and heads of state saw education and skill development as a critical gateway to a more prosperous life and a stronger economy. What was lacking was organization, knowledge and capital.”

    Where governments are sometimes unable to take on risks, entrepreneurs and startups can focus on the most difficult challenges in education—job readiness, early childhood education or teacher training—and make a big difference in a short space of time, from which the public sector can eventually benefit.

    Launched in May 2012 with an investment in Omega Schools in Ghana, PALF has now invested $15m in 10 education companies in five countries. With our partners we have helped educate 350,000 people, many of whom would not have had an education, let alone a good one. And importantly, they are all solutions that are based on sound business plans, so are sustainable, scalable and replicable.

    By getting behind local entrepreneurs, with our money and our know-how, we’re also helping to stimulate thriving communities - not just business people, but teachers and parents and anyone who relishes the opportunity to take on the trickiest problems in education.

    The late Professor C.K. Prahalad, a Pearson author and board member, said: “The big challenge for humanity is to get everybody, not just the elite, to participate in globalisation and avail its benefits.” The work of PALF is heavily influenced by that belief in inclusion, and in allowing everyone, not just those at the top of the pyramid, to have a chance.

    My colleagues in PALF have just published their first report into the impact of the investments they have made. It is well worth a read.


  • How to kickstart an education transformation

    by Michael Barber

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    Transforming anything needs bold people to kickstart it. And if you’re in any doubt that education needs some bold transformation, then you don’t have to search too far for the evidence. For example, the 101 million children not in school in Sub-Saharan Africa, or the 93 million women there classed as illiterate. Or how about the 14% of US adults who cannot read. In its latest report the OECD stated that “no country, no region in the world can claim in 2015 that all of its youth have attained at least a minimum proficiency in foundation skills.

    We can all play our part in kickstarting a transformation in education, because we all own the culture of education. Teachers, parents, students, governments, businesses… we all define the culture that sets the standards. The ‘right’ culture is one of the key explanations for the dominance of South-East Asian nations at the top of most education league tables; that believes that every learner can succeed rather than deciding at the outset that some are smart and others not; that as well as ambitious expectations has clear goalposts, high levels of community involvement, and a strong sense of accountability among all stakeholders. It’s what Hwy-Chang Moon, a dean of Seoul National University, calls “a mentality of the first-tier.”

    Our education kickstarters are the people social scientists would refer to as the ‘innovators’, those on the left of the bell curve of adoption.

    They are the minority that, if all goes well, morph into the majority. And to their far right, the laggards, the chorus of cynics sayingWhat’s all this nonsense of new ideas and technology!.  They will try to derail you, mud wrestle you into distractions by asking how you’re going to get ‘buy-in’ and ‘take people with you’. But you don’t win hearts and minds and then make the change; you make the change, and the hearts and minds will follow.

    In an increasingly globalised world, a bold vision doesn’t just have to stand up to where you’re coming from, but where everyone else in the world is at. I was reminded of this on one of my visits to Punjab, Pakistan, where I have been working with the Chief Minister for a number of years (unrelated to my role at Pearson.) A government official was very proud to tell me how only 5% of kids cheated in exams, which was a huge improvement. I reminded him that in England the figure is 0.014%, 400 times better.

    Obama called it “the audacity of hope”, but hope alone is not enough. Transformation is much more forensic than that. It needs a plan that spells out that this is where we are now, and this is where we can get to, and this is who’s going to need to do what, when, and how. And this is how we’ll know if it’s working.

    Data will let you do that last one. And the closer to real-time that data is, the better. The world moves far too fast for data to have a shelf life. In Punjab we went from having no insight into what was happening in schools, to now collecting data against 16 indicators from 55,000 schools every month. Additionally we collect data from 25,000 schools in Khyber Pakhtunkhwa, the Province of Pakistan on the border with Afghanistan, prone to terrible winters, earthquakes, and terrorism. If you can do it there, you can do it anywhere.

    The data will indicate where the plan is veering off, so you can decide how to get it back on track. Dig deeper, disaggregate it, find the hotspots where it’s working, where it isn’t, do more of the former and stop doing the latter.

    When you marry all this together - the bold vision, the clear plan, the execution of that plan, and the real-time data that tells you how to adjust - that’s when you do real transformation. It’s how you move from small steps of incremental change to giant leaps of extraordinary outcomes.

    What might an education transformation look like when it’s done? (Of course, it’s never ‘done’!) A school where technology is ubiquitous, classrooms have become wide open spaces, data is helping identify struggling students, progress is measured by grit and resilience as much as English and maths, and Artificial Intelligence diagnoses when a learner is bored, or frustrated, or confused before performing, with the help of an outstanding teacher, a well-designed intervention.

    None of this is to say that education transformation isn’t already happening. Some countries are on the path - Poland and Singapore to name just two; and individuals too, such as, CP Viswanath, founder of Karadi Path. From small beginnings in the slums of India the company now has 800 English language schools across the country. Led by where the evidence has taken them, their students outperform ‘traditional’ classrooms by between 20-60%.

    Last week I was in Davos at the World Economic Forum, where the major challenges facing the world - extreme poverty, civil rights, clean energy, gender equality, affordable healthcare were examined. We don’t have a hope of transforming any of these if we don’t first transform education.


    Michael Barber is our chief education advisor. Connect with him on Twitter - @MichaelBarber9

  • Why the world’s learning company has to love data

    by Dr. Kristen DiCerbo and Dr. John Behrens and Dominic Collard

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    This article is a response to a piece we published on this blog by Dr Ben Williamson of Stirling University, in which he explores an “emerging criticism of Pearson among education researchers”. In his piece Dr Williamson refers to two activities of Pearson: the Centre for Digital Data, Analytics and Adaptive Learning and The Learning Curve. Dr. Kristen DiCerbo and Dr. John Behrens of the Centre jointly author the response on the former; and Dominic Collard responds on the points made in relation to The Learning Curve.

    We would like to thank Dr. Williamson for his interest in Pearson’s use of data and our research efforts. We believe strongly that open dialogue is key to the world making progress in education.


    Dr. Kristen DiCerbo - (Centre for Digital Data, Analytics and Adaptive Learning.)

    As one of the questions Dr. Williamson asks is “Who at Pearson is collecting the data, designing the algorithms to analyse it, and checking the analytics for their accuracy?”, I’d thought that’d be a good place to begin. I have written this with my colleague John Behrens, who is referenced with me in Dr. Williamson’s article.

    One of our great delights in our years at Pearson is how much the company values our varied backgrounds as social science researcher-practitioners and supports our involvement in public and academic discourse. My Ph.D. is in educational psychology; after completing a school psychology program and becoming a certified psychologist, I worked in schools as a school psychologist and continued on to a research career that included observing classroom instruction around the world. John was a social worker before obtaining degrees in special education and educational psychology with cognates in instruction and cognition, as well as measurement, statistics & methodological studies. He was a professor for 10 years and gave up tenure to work in contexts in which he could apply learning and analytics at scale.

    So when Dr. Williamson writes that Pearson is, “beginning to challenge the existing authority of social scientists and psychologists to study, understand and produce new knowledge about key aspects of education such as assessment and learning.” we find this a surprising conclusion, since we in fact identify as social scientists and psychologists (and technologists and educators).

    Like Dr. Williamson, we believe the digital revolution is a remarkable event in the evolution of human interaction. We study this phenomenon and participate in academic communities to reflect, discuss, and have broad interchanges about these societal changes. We, and other colleagues at Pearson, publish papers, present in open scientific forums, and provide ongoing community service through external advisory boards, editorial boards, and support of journals with peer review, among other activities. We support graduate student training with internships and mentoring and have had a broad range of collaborations with academics in fields related to our interests. This provides future scholars with unique access to both the processes and challenges of research and innovation in business environments.

    We are, however, not just researchers, but practitioners as well. A common concern for researchers and sponsors of research is the lack of mechanism for translating learning science research into practice. An embedded research group is one way to make that happen. We feel privileged to work side by side with product design and engineering teams to help build the most efficacious products and services we can for our customers. This means not just studying corporations and other loci of innovation and development, but working within them. We believe that we have a responsibility as stewards of educational data to conduct research to further our understanding of both learning and data methodology. There is no reason this activity should be the sole province of academia or organizations based on their tax status. Education is a complex endeavor and as Dr. Williamson points out, requires many actors and perspectives.

    Our theory of action

    So, what exactly is Pearson trying to accomplish with the funding of data and learning science research? Dr. Williamson asks, “why is Pearson investing in such a massive effort to conduct educational data science?” Our answer is simple: we want to serve students, parents, teachers, and administrators in the best possible way, by considering all the tools that can be fruitfully brought to bear.

    Like our goal, our theory of action is simple: Better data analysis → better understanding of students’ attributes/curriculum/learning trajectories → better instructional decisions → improved learner outcomes.

    By using better data analysis techniques applied to data captured from better designed activities, we hope to build more complete and accurate models of learners’ knowledge, skills, and attributes that will provide better information to teachers and learners and provide systems that are relevant to each student’s individual proficiency levels, interests, and current states. As we discussed in Impacts of the Digital Ocean on Education (DiCerbo & Behrens, 2014), our starting point on this journey is not that we should make the natural activity of society more digital, but rather that, as it is already happening organically, the educational community needs to understand the opportunities and challenges that emerge. If students are working in digital systems throughout the year, we think it essential to give them feedback along the way, and irresponsible to ignore the opportunity. Indeed it is our hope that increased awareness about learner progress throughout the year can change the balance of need for the much-maligned annual test.  We are proud to work at a company that emphasizes learner outcomes (see our efficacy efforts for more on this) and whose results can be accepted or rejected by the consumer.

    Our belief system

    Dr. Williamson states that one of his main concerns is that our work is, “premised on a kind of big data belief system which assumes that massive quantities of data can reveal truthful and meaningful patterns about the reality they’re taken from—that the data can speak for themselves free of human bias.”  While this is a common characterization of modern analytics writ large, a simple review of our writing suggests a different stance. Way back in 1997 John wrote (with Mary Lee Smith in the Handbook of Educational Psychology) that data analysis must be understood in the “context of history, the context of application, the context of practice and the context of alternative methods” (p. 945). More recently he advised the Learning Analytics community that “The successful learning analyst will avoid two common errors: Failure to understand the context and failure to become intimately familiar with the data.” (Learning Analytics & Knowledge Conference, 2013).

    In the Impacts of the Digital Ocean on Education paper, the following figure is one of our favorites:

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    In the paper, we write, “Data is only a representation or symbol of what happens in the world. In most contexts, the goal of data collection and analysis is to provide insight and inform decisions. Accordingly, there is a long chain of reasoning that needs to be considered.” We recognize that data is a representation of the world and like all representations, it is an imperfect system which will not perfectly capture the detail of the world. We also believe that all of the activity coming after that (analysis, interpretation, etc.) is a human endeavor, involving all the benefits and challenges that implies. This view of data analysis as human process that requires understanding of meaningfulness of context and social negotiation is, in fact, a consistent theme over our careers as reflected in such works as Why People Are the Real Power Behind Big Data, Technological Implications for Assessment Ecosystems, and Activity Theory and Assessment Theory in the Design and Understanding of the Packet Tracer Ecosystem. Finally, interested readers can read more about how to avoid being “fooled by data” in our writings on exploratory data analysis (here, here, and here, for example).

    Final thoughts

    We hope that Dr. Williamson is correct that we are well-positioned to create new knowledge and methods. Pearson is a dynamic and evolving company working in a dynamic and evolving set of social, technological, political and economic contexts.  We are energized by the opportunity to serve the global community of learners and educators, and to work at the intersection of academic exploration and end-user service.

    Dr. Williamson asks about what our work looks like “from the inside.” Given our experiences across a variety of research settings, we think he would be surprised to see how much the work we do looks just like work done in education research labs everywhere, with the added component that we are directly implementing our findings to impact the lives of learners. Just as with anyone else interested in what we do, we would be delighted to take him through our work in more detail.


    The Learning Curve (Dominic Collard)

    At Pearson, we believe that data helps unlock the secrets of learning. That alongside the know-how and experience of teachers and educators, data can reveal things that are invisible to the human eye and the human brain, and so help us all make better decisions.

    It’s a belief that requires data to be not just robust, but also seen and used. The professional researcher may be comfortable navigating through labyrinths of numbers, but most of the rest of us are not. Teachers, parents, government officials… anyone interested in what is working well in education - most of us probably don’t have the time, the skills or the inclination to get really deep into the data.

    The Learning Curve - essentially a collection of thousands of education data points collected from all over the world over the last 25 years - is one attempt to make data seen and used by more people. We want people to discover their own conclusions and draw their own correlations between education inputs (ie spend, teacher salaries, class sizes) and education and socioeconomic outcomes (ie literacy levels, graduation rates, crime and unemployment.)

    None of the data on The Learning Curve ‘belongs’ to Pearson. The Economist Intelligence Unit gathers it all for us, from sources such as the OECD, UNESCO, The World Bank and the International Labour Organisation, to name just a few. Dr Williamson is correct that the EIU is an independent business within The Economist Group, which until recently Pearson had a stake. And it is equally true that few other organisations could manage the systematic and regular collection of the wide range of data that The Learning Curve demands.

    All that data is then presented via a range of interactive visualisations, designed so the user is able to control the parameters of what they are seeing. For instance, you may like to know how the US and the UK compared in 2001 for public expenditure per pupil as a % of GDP. Or you may like to play that comparison out for all countries across 25 years. At a few touches of a button you can do both, and everything inbetween. Or, if you are confident using large spreadsheets of data, then we also give you the option of downloading everything to an Excel file. The Learning Curve has been specifically designed so nobody has to second guess what the user wants to understand, or the method they want to discover it.

    There is another section of the site - the Index - which I suspect Dr Williamson is referring to when he argues it “limits what kinds of analyses can be done and what can be said about the data because it has been designed to prioritize the measurement and comparison of ‘effective’ education…”. The Index is an attempt to rank countries based on their overall education performance - a global league table of education standards. We think the way we have calculated where countries come stands up to scrutiny (and we provide a full explanation of the methodology on the site so people can judge for themselves) - but we also know that you could legitimately calculate this in many, many other ways. We have never suggested the Index should be seen as the final say, and have always gone to great lengths to explain that it is just one interpretation, whose value reduces the more you read it in isolation. Pearson would absolutely agree with Dr Williamson on the importance of understanding “ and cultural context, emotional complexity, and the qualitative dimensions of human relations” in education systems. The truth is though, for now these things are much harder to measure and collect data on. That’s why we see The Learning Curve as the start of the conversation, not the end.

    There is one more point I would like to make about The Learning Curve, that I appreciate is not brought up by Dr Williamson. It is free. As long as you have an internet connection and a device to access it, you can spend as long as you like exploring what it has to reveal; ¾ million people worldwide have done so.

    The Learning Curve is not a modest undertaking for Pearson - in terms of cost or time - and there is no immediate revenue incentive for us either. Of course, we hope that it helps our reputation and so our ability to take part in the conversations that shape education. And, yes, that should then help our commercial performance in the long-run. But the absolute opposite will be the case if The Learning Curve somehow doesn’t stand up; if somehow we are using it to steer people away from the evidence and towards something we’d wish they’d believe, if only it were true.

    Like my colleagues Kristen and John, I’d be delighted to spend time with Dr Williamson to show him behind the scenes of The Learning Curve , and of course get his view on where we might be able to improve things.

  • Educational data, Pearson and the ‘theory gap’

    by Dr Ben Williamson

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    Earlier this month we came across an article in the European Educational Research Journal analysing Pearson's role in education research. In the spirit of open dialogue, we invited the author, Dr Ben Williamson of Stirling University in the UK, to summarise his points, which he does in the following article. You can also read our response to this piece. 


    Pearson has recently become the subject of several major research studies. These studies have sounded a largely critical note about Pearson, particularly around its business ambitions and its political influences. One of the reasons for the emerging criticism of Pearson among education researchers, I believe, is that Pearson is beginning to challenge the existing authority of social scientists and psychologists to study, understand and produce new knowledge about key aspects of education such as assessment and learning.

    I recently published a research article in the European Educational Research Journal on what I described as Pearson’s ‘digital methods.’ The research tried to identify some of the many research methods that Pearson is using to make sense of education, and specifically looked into the statistical methods and the data visualization techniques behind Pearson’s The Learning Curve, and the data science methods used by Pearson’s Centre for Digital Data, Analytics and Adaptive Learning.

    My argument was that Pearson is becoming a methodological gatekeeper with the capacity to carry out new forms of educational research using large-scale datasets, big data and data science methods. These are approaches that many educational researchers working in higher education institutions are ill-equipped to carry out, which puts Pearson at an advantage as more and more digital data is produced about learning and assessment. As a result, a research centre like Pearson’s Centre for Digital Data, Analytics and Adaptive Learning looks from the outside like a seriously-resourced laboratory for educational research and knowledge production that challenges the existing methods, knowledge and theories of educational sociology, philosophy and psychology.

    For example, John Behrens, the director of the Centre for Digital Data, Analytics and Adaptive Learning has claimed that data-mining ‘the billions of bits of digital data generated by students’ interactions with online lessons as well as everyday digital activities’ will challenge current theoretical frameworks in education, as ‘new forms of data and experience will create a theory gap between the dramatic increase in data-based results and the theory base to integrate them.’ In a report co-authored with Kristen DiCerbo (also of Pearson), it is noted that ‘we need further research that brings together learning science and data science to create the new knowledge, processes, and systems this vision requires.’

    The ambition to devise new data science methods together with learning science approaches, and then to use these to identify a ‘theory gap’ could cause disquiet among some education researchers. Of course, it’s intellectually healthy to challenge old theories, otherwise we would still be trying to construct behaviourist ‘teaching machines’ like those of Sidney Pressey a century ago. But for a big company like Pearson to position itself in a way which suggests it has the capacity to address the theory gap using its massive data analytic capacity could be seen as a little troubling. Here are two reasons.

    First, Pearson promotes The Learning Curve as an ‘open and living database’ that will encourage ‘evidence-informed education policy’ and help ‘identify the common elements of effective education.’ What is less clear to the user is that The Learning Curve was constructed by the Economist Intelligence Unit (until recently owned by Pearson) whose expertise is in economic forecasting, business intelligence and national comparison. Although The Learning Curve invites the user to engage with the data through an interactive visual interface, ultimately it limits what kinds of analyses can be done and what can be said about the data because it has been designed to prioritize the measurement and comparison of ‘effective’ education according to the methodological preferences of the EIU. What Pearson says is ‘effective education,’ or rather what the EIU measures as ‘effective education,’ or indeed, what data can be included about ‘effective education’ in The Learning Curve in the first place, all point towards its limitations as an impartial, neutral and objective visual and numerical representation of education around the world. The methodological appendix to The Learning Curve even admits as much, stating that ‘because indexes aggregate different data sets on different scales from different sources, building them invariably requires making a number of subjective decisions.’ There is subjectivity to the objectivity offered by The Learning Curve.

    For me as an education researcher with a sociological tendency, this makes me ask questions about the ‘who’ behind the data—who selected it, from where, what did they do to prepare it for inclusion, how did they clean it up, how has it been tweaked, how has it been presented, and, crucially, how much interpretation has been done by the designers of The Learning Curve in advance of its presentation on the site?

    Second, Pearson’s Centre for Digital Data, Analytics and Adaptive Learning is premised on a kind of big data belief system which assumes that massive quantities of data can reveal truthful and meaningful patterns about the reality they’re taken from—that the data can speak for themselves free of human bias. Yet as many researchers of big data have pointed out, data do not exist naturally as a ‘raw’ or truthful representation of an underlying reality—they have to be brought into being through human, social, methodological and technical practices, and are constantly reshaped as they move between human actors, software platforms, and institutional structures and settings, all framed by social, political and economic contexts. Again, human hands, minds and biases, as well as technical platforms and business plans, can all affect the ways in which data are collected, calculated, and communicated back out into the world.

    These examples are significant because Pearson is claiming to be opening up a ‘theory gap’ in our understanding of effective education and learning, and at the same time working on new digital methods and data scientific approaches that might produce new knowledge to fill that gap. As a global educational media company and increasingly a policy influencer, it is then very well positioned to use the insights it gains from the data to come up with new kinds of solutions in the shape of new software products for schools, or even new policy solutions for governments.

    You can see why some critically-minded education researchers would be sceptical—Pearson’s identifying problems for which it might sell solutions! Others might point out that numerical data (no matter how big) and its visualization as heatmaps, time series graphs and so on are only part of the educational picture—that they don’t capture social and cultural context, emotional complexity, and the qualitative dimensions of human relations in classrooms.

    My own critique is different. Instead, my emphasis is on acknowledging the human and social practices that go into the generation of data at Pearson as a new source of knowledge production, and on asking questions about how its new digital methods and data scientific approaches might be challenging the long history of educational theorizing, empirical investigation, and knowledge production. Pearson is positioning itself as a major source of methodological expertise in educational research, driven by ambitions to reconceptualise education and learning, and it has significant global power to influence policymakers, politicians and practitioners alike that its data provides the numerical and visualized facts that can fill the theory gap.

    There is an exciting line of sociological inquiry into the ‘social life of methods’ to draw from here which treats research methods as the object of social scientific inquiry. Those of us trying to understand Pearson from the outside know little about the ‘social life’ of the methodological work being done inside Pearson’s research centres.

    The necessary response, I think, is for education researchers to try to understand the ‘who,’ the ‘how’ and the ‘why’ of Pearson’s current digital ambitions. Who at Pearson is collecting the data, designing the algorithms to analyse it, and checking the analytics for their accuracy—and according to whose policy ambitions, business plans and personal objectives? How are the datasets that Pearson possesses selected, interpreted and presented, and how is the visualization of its data on platforms like The Learning Curve designed in such a way as to shape the possible interpretations that audiences can make? And why is Pearson investing in such a massive effort to conduct educational data science—to identify new market niches for itself, to displace higher education institutions, and to position itself as the dominant global centre of educational expertise and knowledge production?

    Answering these questions may require researchers with a more critical set of methodologies and theories to engage in a dialogue with researchers within Pearson, and to understand Pearson from the inside as a new source of methodological expertise and knowledge production rather than criticising it from the outside as a commercial monster. There is an empirical gap in our understanding of how Pearson is approaching the theory gap in educational research.

    Read Pearson's response to this article. >> 


    Ben Williamson is a lecturer at the School of Education at Stirling University in the UK. He was previously a Research Fellow at the University of Exeter. Follow him on Twitter - @BenPatrickWill.