Learning in the age of Dataism

Last week, I outlined in this post how modern schools and the modern western education system are built on the principles of humanism, showing how many of the modern assumptions in education are based on humanist claims. For example the roots of what is termed progressive education are based on post-romantic ideas about the beauty of individual experience, an idea that is also the underpinning of capitalism and democracy; two ideas that are practical manifestations liberalism, a creed of humanism. On the other hand ideas within the modern traditional approach to education are rooted in the idea that all humans are created equal and as such have rights to an equal education; an idea that has its roots in Communism, another humanist tradition. In this post I want to explore how the ideas of Noah Harari, written in Homo deus, may relate to the modern education system.

Harari contends that society at large may soon be leaving the age of humanism and entering an age of dataism. Dataism is defined as an emerging ideology in which information flow is seen as the supreme value. It is used to describe the mindset created by the emerging significance of big data.

Harari goes on to argue that Dataism, like any other religion, has practical commandments. A Dataist should want to “maximise dataflow by connecting to more and more media”[8], and believes that freedom of information is “the greatest good of all”. Harari also argues that Aaron Swartz, who took his life in 2013 after being prosecuted for releasing hundreds of thousands of scientific papers from the JSTOR archive online for free, could be called the “first martyr” of Dataism

Big data is only just beginning to make inroads in education and yet already we are seeing its potential. One of the areas that I have begun to witness this is in university guidance. All ready platforms are springing up that aim to utilize big data to help students make sense of the options available to them. Companies like BridgeU use algorithms to help locate universities and courses based on student preferences. Information flow here is already quickly becoming the supreme value and will allow individuals to make slicker, more efficient, choices, perhaps with a lot of time saved to boot. On one hand, this appears to be at odds with the individual focus of human university counseling. Indeed some colleagues have told me that they prefer the platforms, like Unifrog, that have less of a data driven, algorithmic, inhuman agenda. But I actually think that these systems have the potential to improve the lot of many individuals by freeing up time and making research on an overwhelming range of options more focussed. Sometimes less is more.

Elsewhere, big data is behind standardised testing programmes like those administered by CEM and the success of many new pedagogical applications that aim to help to apply scientific findings of learning to course material like the textbooks developed by Kognity.

On the face of it, information flow as a supreme value could seem to be at odds with the current paradigm of education: humanism. Isn’t it the love of more data that can drive poor interventions in schools, like when schools require more frequent testing and measurement of progress, so that students and teachers alike are pressured into making decisions to maximise progress? Often these interventions come at the demise of learning, causing poor behaviours like teaching to the test and cramming. Or how about when teacher spend hours agonising over data collection and data entry instead of planning the next teaching sequence?

Schools love data. Whether it is data on student progress or on student performance, teachers and senior managers love it. However, in some ways many schools have gone through the dataism paradigm already, and come out the other side. The debate, in the UK at least, is shifting away from purely data driven measures of progress to measuring quality of education, by including curriculum measures, something far more qualitative than quantitive. While schools love data they are also fundamentally humanistic in nature. Whatever the motivations of educators have been historically, education is an affair of the human experience. It is a someone who is being educated. It is a someone who is having their mind and thinking patterns altered in someway.

In a sense, though, knowing is data flow. While information and knowledge are not the same thing, knowing relies on using information. It is how the mind works with information that results in knowing. And so, if society were to progress into an age where data would reign as the supreme good, education would still be able to maintain its focus on the individual experience.

Harari analyses human history through the idea of dataflow, the new emerging modern value. He  writes that “the crippling thing about religion is that it reduces data flow“. By this he means that modern religions, are not innovators in religious experience. They are conservative and restricted by holding onto old and outdated traditions and values. I know this first hand. Growing up in my evangelical family I was not allowed to read books by David Hume because he was a “humanist”. This conservatism restricts knowledge transfer to and development within the individual, thus from a dataist point of view: religion restricts dataflow.

Schools, then, could well be institutions that, through learning of knowledge, promote dataflow. Education could develop a dual purpose, the traditional humanist purpose of educating the individual for their benefit or societies, and the modern purpose of ensuring that dataflow is maximised and made efficient through the education of individuals as producers and consumers of data.

If this is right, perhaps this is more cause to be concerned with the fad of 21st century skills. In this previous post I partially outlined why there is no such thing as generic skill acquisition. Real 21st century skills will require lateral thinking, stress management and an ability to see the big picture as well as know the details and have expertise. All of this requires knowing. The more you know, the easier it is to learn more. Yes, humans may never be able to outcompete computers for what they can know but that doesn’t mean we should give up learning. Actually we need to give more careful thought to what our students do know.

One of the areas where dataism and big data may well come to play a larger role in the education system and also benefit the liberal philosophy of many schools is through personalised learning. The ability of big data, algorithms and artificial intelligence to tailor learning experiences to individual needs to is already being seen in a plethora of learning applications and websites that are adaptive in formative assessment and tailoring of content. I imagine that we will see a lot more of these tools becoming available in mainstream schools as we progress through this century.

Post 100: Learning in the age of Humanism

In the UK, prior to the Renaissance, learning in schools mainly consisted of the trivium of grammar, rhetoric, and logic and the quadrivium of music, astronomy, arithmetic and geometry. Pupils were taught these to prepare them to progress on to the study of theology, law and medicine and education primarily served the church and state.

Following this, the ideas of humanism, the religion that replaces god with the experience of mankind, began to take their root in the philosophy of education, leading to the idea that education is a right for all and that is should be administered by the state to ensure that that right is gained by all. In the 19th century the three great humanist projects of Communism, Facism and Liberalism were born and in some way each has contributed to the modern humanist education agenda. In this century we are at the zenith of the age of humanism, with even modern religions adopting a humanistic outlook, according to the work of Noah Harari.

Modern schools and the modern western education system were built on the principles of humanism and many of the ideas in education make humanist assumptions about the individual. For example the roots of progressive education are based on post-romantic ideas about the beauty of individual experience, an idea that is also the underpinning of capitalism and democracy; two ideas that are practical manifestations of the philosophy of liberalism. On the other hand ideas within the traditional approach to education appear to be rooted in the idea that all humans are created equal; an idea that has its roots in Communism, another humanist tradition.

Schools today are very much humanist institutions. But many educators today are confused on this front. Hence some fight against factory schooling, using the factory as a metaphor for an education system that is dehumanised. It was humanist ideas that led to an education system that prepared indivduals for an industrial society. It was humanist ideas that demanded that everyone had the right to an education. It was humanism that led to the organisation of state run schools. Factory-like in that they were exposing lots of different people to ideas that generations before had not had the luck or rights to access. Factory-like, in that this is an efficient model of mass production. Mass production of more (compared to their parents) knowledgable citizens. The irony here shouldn’t be lost on you. It’s ironic that it was ideas tied to liberalism that made the industrial revolution possible (Governments and Businesses needed to care about the individual in a way that they just didn’t need to before) now serve as a metaphor as to why schools are perceived by some as being dehumanising.

Really, the confusion here is due to a misunderstanding of history and ideas. Educators who use the factory as a metaphor don’t understand their history and the world view is informed more by liberal humanism the communist or fascist humanism.

Educators also get their modern politics confused. It surprises some that teachers who self-identify as being “trad” are labour voters. See this blog. They mistakenly think that anyone who advocates for traditional teaching must be a conservative. In his book Why Knowledge Matters E.D. Hirsch, draws a distinction between, community and knowledge centered education versus individual and skills centered education, arguing that the former acts to reduce inequality, while the latter cherishes the individual experience of the learner. Both are fundamentally humanist in their paradigm.

If the aim of traditional education is to reduce inequality by ensuring that ALL students receive the same knowledge centered education then it is easy to see why this is left leaning idea. Traditionally the left leans towards communist humanism, valuing equality over freedom, while the right leans towards liberal humanism valuing  individual freedom over equality. That is, of course, an oversimplification but it roughly works.

If you spend anytime on edutwitter or reading about educational history you won’t have missed this tension at the heart of the philosophy of education. This debate is often personal and vitriolic. Writers come down hard on each other, often forgetting that their opponent want the same thing as them: the best outcomes for the individual. In this sense both of these opponents are humanist and believe in the humanist agenda. But a bit like the schisms in the Christian church that saw Catholics and Protestants burn each other at the stake over their differing interpretations of the same creed, modern day “philosophers” of education are happy to figuratively hang, draw and quarter their opponents for having slightly different views. Understanding this should be the basis of finding points of convergence in a debate.

The modern drive for personalised education is a manifestation of the principles of humanist liberalism and, in its present form, appears to conflict with the ideas of a community-centered education system whose aim is to reduce inequality. To my mind it is educational equivalent of “organic” farming, it market’s itself very well but is hard to scale up and is incredibly inefficient in its resource consumption.

In my next post I want to explore how personalised education may fare as we move deeper into the 21st century. Everyone assumes that this is the way we are going as an education system, but is it. In his books Harari writes about Dataism, and how this new philosophy may end up replacing humanism. I am interested in thinking about what this may mean for the modern education system.

Developing a progression model for IBDP biology

I recently completed Daisy Christodolou’s “Making good progress?”. You can see my notes here. In the final chapters, after presenting an argument building up to this, she outlines the key aspects of what she terms a “progression model”. In this post I want to line up some ideas about what this may look like in delivering the IB DP Biology course.

In her book Christodoulou suggests, and I agree, that to effectively help students make progress we have to break down the skills required to be successful in the final assessments into sub-skills and practice these. This is a bit analogous to a football team practicing dribbling, striking or defending in order to make progress in the main game.

In the book she also stresses the difference between formative and summative assessments, what they can and can’t be used for respectively and why one assessment can’t necessarily be used for both.

A progression model for biology

A progression model would clearly map out how to get from the start to the finish of any given course, and make progress in mastering the skills and concepts associated with that domain. In order to do this we need to think carefully about:

  1. What are the key skills being assessed in the final summative tasks (don’t forget that language or maths skills might be a large component of this)?
  2. What sub-components make up these skills?
  3. What tasks can be designed to appropriately formatively assess the development of these sub-skills or, in other words, What does deliberate practice look like in biology?
  4. What would be our formative item bank?
  5. What could be our standardised assessment bank?
  6. What are appropriate summative assessment tasks throughout that would allow us to measure progress throughout the course?
  7. What could be our summative item bank?
  8. How often should progress to the final summative task be measured i.e. how often should we set summative assessments in an academic year that track progress?

Key skills in biology

This is quite a tricky concept to pin down in biology specifically and in the sciences in general. What skills exactly are kids being assessed on in those final summative IGCSE or IBDP/A Level exams. I haven’t done a thorough literature review here so currently I am not sure what previous work has been in this area.

However,  I would contend that most final written summative exams are assessing students conceptual understanding of the domain. If this is the case then the skill is really, thinking and understanding about and with the material of the domain. Students who have a deeper understanding of the links between concepts are likely to do better.

In addition, those courses with a practical component, like the IBDP group 4 internal assessment are assessing a students understanding of the scientific process. While it may seem like these components are assessing practical skills per se, they only do this indirectly, as it is the actual written report that is assessed and moderated. To do well the student is actually demonstrating an understanding of the process, regardless of where their practical skills are in terms of development.

Indeed if we look at the assessment objectives of IBDP biology we see that this is very much the case. Students are assessed on their ability to: demonstrate knowledge and understanding and apply that understanding of facts, concepts and terminology; methodologies and communication in science etc.

Sub-skills

How can we move students to a place where they can competently demonstrate knowledge and understanding, apply that understanding as well as formulate, analyse and evaluate aspects of the scientific method and communication.

The literature on the psychology of learning would suggest breaking down these skills into their subcomponents. This means we need to look at methods that develop knowledge and understanding from knowledge. Organising our units in ways that help students see the bigger concepts and connections between concepts within the domain will also help. For more on this see my previous post here. I think that understanding develops from knowledge.

I recently read that Thomas Khun claimed that expertise in science was achieved by the studying of exemplars. Scientific experts are experts because they have learned to draw the general concepts of the specific examples.

Useful sub-skills would be:

  • Fluency with the terminology of the domain
  • Ability to read graphs and data
  • Explicit knowledge of very specific examples
  • Explicit knowledge of abstract concepts illustrated by the specific examples
  • Ability to generate hypothesis and construct controlled experiments

Deliberate practice in biology

Thinking about these sub-skills, then, we can see what may constitute deliberate practice in biology and thus what would make useful formative assessments within the subject.

Fluency with the terminology can be gained through the studying of terminology decks like those available on quizlet. In addition, the work of Isabel Beck. Suggests that learning words isolated from text is not that helpful to gaining an understanding of those terms. To gain this, students need to be exposed to these words in context. Therefore there is a lot to be said for tasks and formative assessments that get students reading. Formative assessments could then consist of vocab tests and reading comprehension exercises of selected texts.

Reading and interpreting data can be improved through practice of these skills. This is an area where inquiry alone won’t help students make progress. Students need to be shown how to interpret data and read tables and graphs before making judgements. Ideally, in my opinion they should do this once they have learned the relevant factual knowledge of a related topic. Formative assessments focussing on data interpretation should therefore come a little later once students have covered a bulk of the content.

To build up conceptual understanding, students need to be exposed to specific examples related to those topics as I outlined in this post. Tests (MCQs) that assess how well students know the specific details of an example could be useful here to guide learners to which parts they know and those they don’t.

Following this we can begin to link examples together to build knowledge of a more abstract concept. Concepts can then be knitted together to develop the domain specific thinking skills: thinking like a biologist.

Formative assessments

Formative assessments could take the form of MCQs but as outlined above, vocab tests, reading comprehension activities, and other tasks may well have their place here.

Summative assessments for measuring progress

I am now thinking that to truly assess student progress against the domain, individual unit tests just won’t cut it. As Christodolou argues, summative tests exists to create shared meaning and do that need to be valid and reliable. Does scoring a 7 in a unit test on one topic of an 11 topic syllabus mean that the student is on track to score a 7? Not necessarily. Not only is the unit test not comparable to the IB 7 because it is only sampling a tiny portion of the full domain, but the construction and administration of the test may not be as rigorous as that of the actual IB papers.

Clearly it isn’t ideal to use the formative assessments described above as these are nothing like the final summative assessment of the course, plus their purpose is to guide teaching and learning, not to measure progress.

I would argue that summative assessments over the two-year course should use entire past papers. These past papers sample the entire domain of the course and performance against them is the best method of progress in the domain. A past paper could be administered right at the start of the course to establish a base line. Subsequent, infrequent, summative tests, also composed of past papers could then measure progress against this baseline.

Why should summative assessments use past papers? What not use unit tests? Unit tests, aggregated, is not the same thing as performance on a single assessment sampling the whole domain. They cannot produce the same shared meaning as an assessment that samples the entire domain. In addition the use of many single unit, high stakes tests will cause teaching to the test as well as much more student anxiety. Instead lots of formative testing and practice of recall should help to build students confidence in themselves.

Developing a school wide Academic Honesty Policy I

One of my focuses this year as Diploma Programme Coordinator will be to work with the schools educators to devise a secondary wide academic honesty policy. This is the first time I have had to lead a collaborative project across the secondary and I am spending a lot of time thinking about how best to implement this.

The easiest thing, and the first thing that I considered, would have been to simply lift policies from previous schools (with permission of course – oh the irony!) and adopt it in the new context. On reflection I decided not to go down this path because doing so would have meant we lost a good opportunity for collaboration amongst the team and would have probably also ensured that we didn’t get the buy in and subsequent up-skilling, that we need if the policy is going to be successful.

Teaching academic honesty is one of those things that I think it is easy to expect everyone on the teaching team to be able to do and assume that they know how to do it when in fact there may well be understandable knowledge gaps within the team. Different people also respond to their own knowledge gaps differently. Not admitting to knowledge gaps is an behaviour that can develop insidiously in educators due to perceived peer, parent and student expectations. The culture of a school may well be one where, admitting ignorance is something that is frowned upon. I am also aware that simply admitting ignorance isn’t enough. People need to be motivated to fill the gaps once identified and this process takes effort. We all avoid the effortful path at times.

For this project, I decided to go down the long road and start afresh. I want buy-in from the team and I want to identify skill needs amongst the team so that we can begin to help teachers develop their own skills in this area, as well as develop a deeper understanding of the IB requirements for academic honesty.

One of the things that I learned as a workshop leader with the IB is that all training sessions with staff should aim to help colleagues develop their teaching skills and share pedagogical techniques as a secondary objective to the primary aims of the session. Thus, when I utilised one staff inset session in October, I planned to use visible thinking routine “chalk talk” as a route to triage where the team was in their thinking and understanding about academic honesty.

I started this session by introducing chalk talk with a practice question. On a prior inset session led by another team member we had looked at Hattie’s research and so to transition from that I chose the question: “Is homework necessary?” to get the team used to the format of the chalk talk.

For the main event, I took questions from the IBO’s documentation on academic honesty and grouped them into categories. I prepared the session in advance by writing questions onto the back of the paper I was going to use. In this chalk-talk, instead of answering one question and rotating through each table, each table had a different set of questions that each group responded too as they rotated through them.

The results can be seen here:

Following from the chalk talk, I asked each group to summarise the discussion and responses prompted by the questions they started with. I gave them 15minutes to prepare a presentation for the rest of the team, and asked them to reflect on that instruction: how do they effectively get their students to collaborate on tasks like this? How do we teach students to work collaboratively or do we expect that they will be able to do it? We ended the session by sharing the general findings from each of the groups.

Following on from this session I have written and disseminated a survey based around some of the concepts surrounding academic honesty and citations, in order to give staff a chance to have some continual input into the formation of our academic honesty policy. In January I hope to be able to review the data collected from this chalk talk and survey to begin working on developing our policy but I am unsure of where to take this next to ensure collaboration and buy-in amongst the team. If you have any ideas I would love to hear them!

Undervalued & under-taught: concepts missing in teacher education

Friere, Piaget and Vygotsky are the usual suspects in the theory that underpins many initial teacher training courses, at least in my experience; I am happy to be corrected. The theories of these men, while useful and, in parts, necessary are often presented as the ground truths of teaching and learning or as outright fact.

Over the past few years I have picked up a little bit of knowledge about certain concepts that, if not completely debunking many of these operational fact-theories, certainly voice a challenge to them and I think it would do a lot to develop educators own critical thinking faculties if these concepts were taught alongside the main teacher training dogma.

Many of these ideas I have been exposed to through my own semi-self directed reading about education. I write semi-self directed because although I am choosing which books to read and when, I rely on the recommendations of colleagues and the educators that I follow on twitter.

While each of these, on their own may not be threshold concepts as such (if such a thing exists) learning about them has had a developmental effect on my thinking as an educator.

In my thirties, I can now begin to trace back my own intellectual interests and growth of knowledge. Originally, I was only interested in biology and things directly related to that field. Working as a teacher, my interest in this subject prompted me to develop my knowledge of neuroscience, among others. From here I developed an interest in the teenage brain and then neuromyths.

During my PGCE top-up, it was clear that subjective research processes were held to be just as valid as objective research methods. I challenged some of the ideas fed to us about subjective & experienced based research, arguing that evidence needs to be as objective as possible. My ideas were met with some scepticism, but I went ahead and tried to summarise some of the work on educational neuroscience and to do some sort of quantifiable research on teachers understanding of neuromyths.

Despite the lack of rigour and balanced curriculum, topping up my GTP to a PGCE was worth it. I wanted to do the PGCE because I felt my GTP had not had any academic focus and I didn’t like the fact that I didn’t know much about the theory behind what I was being told to do in the classroom. My PGCE served to get me academically engaged with the educational theory and it is only since I completed it that I have continued to maintain that engagement.

My interest in this area hasn’t abated but as I learn more it has become more nuanced. I agree that we need to be careful interpreting the results of much cognitive research but I do think that it offers that power to help guide us to what may better versus worse pedagogical techniques. They may well help us hone our pedagogical content knowledge.

Currently, these are the ideas that I believe that all teachers should have some training on (in no particular order):

Where can you go to get more valuable knowledge on these concepts? Here are some of the resources that I would recommend:

The Education Endowment Foundation

Daniel Willingham’s blog

The Education Development Trust

Core Knowledge Curriculum

The Learning Scientists

The Learning Spy