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'No BS' Guide to AI

Co-written by Professor Rose Luckin, director of EDUCATE at UCL and Priya lakhani OBE, Founder-CEO at CENTURY

What is AI?

Artificial intelligence refers to technologies which are capable of performing tasks as well as, if not better than, humans.

It’s useful to distinguish between what people call Strong AI and its opposite, Weak AI. Strong AI (also full AI or generalised AI) is what we see in sci-fi depictions: sentient robots able to perform any task much the way that humans can.

On the other hand, Weak AI (also narrow AI) is an AI system that can do usually just one task at least as well as a human can. Although movies and media might lead us to believe the robot invasion is just around the corner, in reality, we’ve only got as far as developing Weak AI systems.

Some examples of the Weak AI systems that we have are:

  • IBM’s Watson: Beat a human player at a game of Jeopardy
  • Deep Blue: Beat the current chess champion
  • AlphaGo: Beat the world champion at the game of Go
  • Siri/Alexa: Voice-activated personal assistants that can “understand” natural language and reply in kind
  • Amazon/Netflix/Spotify/Pandora: Recommendation engines that can predict what we will want to buy/watch/listen to based on what we have done before
  • Tesla/self-driving cars: Cars use AI to learn how to safely navigate and drive along roads.

So, is AI the same as Machine Learning?

Machine Learning (ML) is a way of achieving artificial intelligence. Rather than a software developer writing the specific rules and logic steps for a program, which can be hugely intricate and time-consuming, instead the program is “trained” using large quantities of data and basic algorithms are written to allow it to “learn” from this training to perform a specific task.

This means that artificially intelligent programs are far better able to cope with unusual cases, extreme examples or incomplete data. Rather than a programmer thinking of every single possible scenario, the program teaches itself and then draws conclusions. CENTURY is using this technology to understand how people learn and provide them with a personalised education.

I’ve heard people mention neural networks, how do they fit into all this?

Neural networks are a special form of machine learning that are inspired by the design of the neurons in the human brain. Neural networks are small networks of these ‘artificial neurons’. Similar in processing to real neurons, they can form connections and use those connections to detect patterns. This is widely used for image detection and natural language processing. Deep learning is usually mentioned together with neural networks; it is a special variant of neural networks.

You can think of artificial intelligence, machine learning and deep learning as nested within one another: deep learning is a type of machine learning; machine learning is a type of artificial intelligence.

What differentiates AI from other technology?

AI and ML generate an extremely fast feedback loop between result, feedback and learning. With conventional algorithms, results are produced and feedback collected from the user, but the learning is done by a human who will adjust the algorithm. That can take hours, days or months. AI and ML remove the human element and can, therefore, learn from user feedback within milliseconds.

They say you need a lot of data for AI to be developed. How much?

How much data is needed depends very much on the ML algorithm used. Deep learning or other neural networks are the most data hungry, needing tens of millions, up to billions of data points. On the other end, algorithms for ranking and recommendations can get by with hundreds of thousands to millions of data points.

Humans have been constantly processing information drawn from our 5 senses from the day that we were born (and from some senses while we were still in the womb). If we just take visual images and conservatively estimate that a person will see a distinct visual image every 30 seconds, this results in 17,531,520 distinct images by the time someone is 25. And this is just from one of our senses.

We said above that AI is named because it mimics – somewhat – human learning. This is why huge data sets have been associated with AI for as long as it’s been around. Most ML systems require millions, if not billions, of data points to be able to start making sound judgements.

A recent (2017) experiment led by Google and Carnegie Mellon University showed this with an AI trained in image detection. Most image detection AIs are trained on a standard data set of 1 million labelled images. This is the raw data that equates to the machine’s experience. In this experiment, Google wanted to investigate whether access to more data would improve the accuracy of the AI image detection. Because they’re Google, they had access to a data set of 300 million labelled images, which they used to train their AI. They found that as the amount of images in the training set increased, so did the accuracy of the AI.

Recently, huge advances have been made in training AIs with small data sets. In the Google experiment, although the data increase was 300%, the observed increase in performance was just 3%. So, is it really worth going to the trouble of gathering that much more data? The answer may well be ‘no’ – although the jury is most definitely still out on this one!

Some companies, particularly those without the vast quantity of data that a company like Google has at its disposal, are starting to make use of something known as ‘transfer learning’. With transfer learning, an AI that has been trained using a set of data can effectively “give” its knowledge to another AI that is going to use the same dataset, even if the outputs that the two AIs are generating are completely different. For example, an AI learning to recognise cars while driving can transfer the knowledge it has learnt to another AI that is trying to recognise trucks. In effect, one AI becomes the teacher of another.

When the terms ‘Personalised’, ‘Adaptive’ and ‘Differentiated’ learning are used by technology companies, what does this mean? Is this all AI?

The short answer is no. Personalised, adaptive and differentiated learning are outcomes that can be achieved in lots of different ways; AI is just one way to achieve them.

Most existing educational technology (EdTech) companies rely on rules-based technology to create personalised, adaptive or differentiated learning. This means that developers, usually in conjunction with teachers and pedagogical experts, explicitly tell the program what different routes are for students, based on what they’ve done previously. Although the developers might write algorithms, create complex routes and base this on what the user has already done, the algorithms and the machine cannot move past this: they aren’t doing any learning at all.

Rules-based adaptive learning platforms were beneficial because they were the first step along the road away from a ‘one-size-fits-all’ education. However, it is not genuine personalisation. Because the rules are human-derived and have to be explicitly programmed into the software, the number of routes available is finite. In practice, this means that learners are grouped into cohorts and each cohort has its own route. We can think of rules-based adaptivity like the standard clothes sizing: some parts of it will fit well, other areas not so much and you probably have to compromise on fit in one area to get a good fit in another. It was good when it was all we had, but it’s not good enough anymore. AI can provide the equivalent of made-to-measure: genuine, full adaptivity and personalisation for a student.

Rather than developing specific rules for different routes, artificially intelligent learning platforms learn for themselves what the best route through the content is for a specific student in a specific moment. The ML algorithms will constantly learn, never leaving their training phase so that the intelligent insights they deliver are constantly improving, much like the best teachers are. This makes AI learning platforms significantly better for students than rules-based ones and allows education to fully move from the ‘one-size-fits-all’ model into genuine ‘one-size-fits-one’ personalisation.

CENTURY uses artificial intelligence to generate unique, truly personalised learning pathways for each and every student. As students complete diagnostics, learn and answer formative assessments on CENTURY, the AI picks up on their strengths, weaknesses and gaps in knowledge and immediately reacts to build on and scaffold the student as required. Not only does the AI determine what topic a student should study, it also learns what material is most appropriate for a student and automatically differentiates to their learning needs.

What about ‘algorithm’, then? That sounds pretty intelligent…

Although Artificial Intelligence technology is built using algorithms, so are all computer programs, even the most unintelligent of them: An algorithm is just a set of instructions, written for a computer to execute. So really, it’s a bit of a tautology when people say their platform is driven by algorithms. In the case of AI, the algorithms carry instructions for how the machine will learn what steps to follow, whereas in a standard program, the algorithms define exactly what the computer will do.

Lots of education technology companies will say that they use algorithms to help personalise learning. Usually, this will still be rules-based and so face the same limitations as described above. A good rule of thumb to follow is to assume if they don’t mention AI, machine learning or neural networks, they probably aren’t using any.

What happens to my data?

This very much depends on what the AI company is trying to do with your data. But, in general, data will be stored in databases depending on the type of data it is. Most companies will keep the data about what you do on their site separate from the data about who you are. This is to ensure that private data, such as your name and email address, is kept secure, whilst data that is going to be used by the AI system can be processed and analysed.

Data collected by CENTURY Tech is split into three distinct categories: personal data, learning data and content. These three sets of data are stored separately from each other. Learning data is anonymised and used to improve our algorithms. Content is stored in our CMS database to allow learning. Personal data is, of course, private, stored securely and only used when needed.

What can AI do for me?

AI is a tool, just like any other. There is no point trying to use any technology just for the sake of it, it needs to be used where it can make a difference to teaching and learning.

Artificially intelligent learning platforms, like CENTURY, provide genuine adaptivity for learners: Students can learn at their own pace, while teachers and parents can rest assured that their child is adequately supported and challenged and making the progress they should be. See this quote from the economist about personalised learning if you need convincing:

In nearly all the 41 studies which compared pupils using adaptive software with peers who were taught by conventional means the software-assisted branch got higher scores.

Teachers are also supported and enabled by AI. Take flipped learning, where students self-study a topic before it is taught by the teacher, allowing classroom time to be spent on higher-yield analysis, evaluation and problem solving tasks, rather than on basic knowledge acquisition. The EEF funded a study in conjunction with Shireland Collegiate Academy (Sir Mark Grundy’s pioneering school) which found that flipped learning can add up to 2 months of progress each year. An AI platform like CENTURY can enable and support flipping the classroom: teachers can access teacher-created learning material and assign it to their students. In their own time, students complete this work, getting immediate feedback from the platform and supported by the AI insights. The teacher can access rich learning data in realtime without having to do any marking or data entry. At the beginning of the lesson following the flipped homework, a teacher knows exactly where each of their students has struggled and excelled and so can pitch their lesson to meet the needs of the students.

It might sound too good to be true, but AI is here to change education.

CENTURY in the classroom

Improve your students’ learning outcomes, access real-time insight into each learner and reduce your workload.

Lesson planning and preparation can be the most time consuming part of teaching. Ensuring your lesson meets the learning needs of each and every student in your class, both supporting the weakest while challenging the most able, takes careful and lengthy planning time.

Fortunately, technology can help.

CENTURY learns how each student learns and presents them with a unique route through the curriculum that addresses their individual learning needs. This means that, unlike other online learning resources, students do not all begin their learning journey at the same point: weaker students are directed towards consolidation activities, whereas the more able are pushed towards harder topics and more complex questions. As a result, teachers do not have to look through each individual exercise to choose an appropriate level for each student; the platform automatically adjusts to the needs and preferences of the learner, thereby reducing teacher workload.

As an online, cloud-based resource, CENTURY can be accessed at anytime and from any place. Within the classroom, teachers can use CENTURY to develop a blended learning environment, combining teacher input with student led learning and automatic feedback. For example, a teacher will introduce a topic, then students will consolidate and build on their knowledge using the associated learning material (which we like to call ‘nuggets’ of learning) on CENTURY. Teachers can use the data presented to them to plan their follow-up lessons and identify any misconceptions among their students.

Outside of the classroom, teachers can use the platform to set and collect homework in the form of nuggets or typed essay style questions. Nuggets are auto-marked, providing students with immediate, personalised feedback, and teachers with insight into each learner. Having access to immediate learning insights also makes CENTURY an essential tool for flipped learning. Teachers can provide audio feedback by recording their voice on the platform, allowing students to have access to their feedback whenever needed. Audio feedback not only reduces teacher workload, but allows the feedback to be more detailed. Studies have shown that students pay little attention to written feedback (preferring just to know their grade or score), however, personalised audio feedback can be a far more powerful tool.

The data generated by CENTURY is invaluable for intervention purposes. Teachers and teaching assistants can see detailed feedback on students’ achievement, strengths, areas for improvement and skills, both in terms of effort and attainment. They have access to in-depth topic analyses which enable educators to easily pinpoint students’ areas for improvement. Nuggets can be repeated after a teacher-led intervention to measure impact and record progress. CENTURY’s advanced technology encourages students to revisit nuggets regularly so that knowledge is consolidated over time. By regularly revisiting material, students develop vital revision skills and are fully prepared for exam time.

So next time you find yourself planning, marking or data-inputting into the early hours of the morning, consider how much time technology could have saved you.

Written by Tom Thacker, Curriculum Lead at CENTURY Tech. Tom began his career as a Teach First maths teacher in the Midlands. Since then he has been Head of Department, Assistant Principal and School Governor. Tom then moved to Uganda where he taught for a further two years, before moving back to the UK and joining CENTURY.

CENTURY Tech wins prestigious Innovate UK grant to improve education

CENTURY is the first learning platform that learns how you learn. The groundbreaking platform uses artificial intelligence and data science, underpinned with insights from cognitive neuroscience, to provide students with a personalised education and to reduce teachers’ administrative burden. CENTURY has recently won a grant from Innovate UK, the UK government’s innovation agency, which will allow CENTURY to accelerate their innovation and continue to develop their revolutionary learning platform.

Priya Lakhani OBE, CENTURY’s Founder CEO says “At CENTURY we work tirelessly to improve education and develop groundbreaking and innovative technology that makes a real difference to the lives of many. It is fantastic we have been recognised by the UK’s leading innovation agency!”

CENTURY helps solve two of the biggest pain points in education – students being disengaged with their education and teachers dealing with huge, and often unmanageable, workloads. CENTURY gathers data on students via their interactions with the platform; every click, every score, every interaction is recorded. This data feeds into machine learning algorithms that learn how each individual student learns. The platform plots the most effective route through learning material to ensure that all children are adequately supported in their learning. Gaps in foundational knowledge are quickly identified and remedied, weaknesses are scaffolded and strengths built upon. Rather than a student having to wait weeks for work to be collected, marked and returned in order for misunderstandings to be corrected, CENTURY can intervene at the point of need.

CENTURY selects the most effective content for a student from a large bank, reducing the amount of time teachers need to spend planning lessons and preparing materials. CENTURY automates administrative tasks by marking formative assessments, gathering data and tracking homework, further reducing the admin heavy workload faced by teachers. The platform gathers data insights about each student, including their achievement, knowledge, skills and performance against assessment objectives, which are presented back to the teacher in real-time via easy to use dashboards. This data enables teachers to deliver timely, targeted interventions and to employ evidence based teaching strategies.

Feedback from CENTURY users:

“It’s great to have a diagnostic tool which accurately and constantly reflects what the student knows.” Headteacher, Sussex

“CENTURY offers a truly individualised and tailored approach to the preferred and most effective learning techniques of each and every student.” UK Secondary Academy Trust Director

“I like the way CENTURY adapts to my level of learning and helps me understand topics. It is also fun and easy to use.” CENTURY student, Kent

 

To find out more, please call 0800 612 6535 or email info@century.tech  

The future of education

The UK is renowned for having a world-class education system, yet is underperforming when compared with its peers. Fifteen year olds in the UK are ranked 22nd and 27th respectively in reading and maths when compared with other OECD countries in the Pisa tests, trailing behind much smaller economies such as Estonia, Poland and Vietnam. With 76% of teachers seriously considering leaving the profession due to their ‘unmanageable’ workloads, schools facing severe budget cuts and increasing class sizes it can begin to feel like schools are reaching crisis point. What can be done to improve this?

Well, we know that students benefit from immediate and constructive feedback; we know that differentiated lessons enable students, who learn in different ways and at different speeds, to make similar progress; we know that accurate data can be used to identify key strengths or areas for improvement more quickly. We also know that doing all these things for all students all of the time is hugely time consuming. As teacher numbers reduce and student numbers increase – pupil numbers are expected to grow by one million in the next decade, leading to a shortage of 30,000 teachers by 2020 – and with teachers spending up to 60% of their time on admin and data management, the time they have available to dedicate to each student is severely limited. This is resulting in a one-size-fits-all method of teaching often being used, leaving some students struggling and others under challenged. Clearly something needs to be done to help education as it is currently failing both the teachers and the students. But what is the answer?

When we look at other industries, such as travel, healthcare and retail, there is one thing that has helped revolutionise them all – artificial intelligence (AI). AI has made them more efficient, more personalised, helped to reduce their costs and allowed them to make more data driven decisions.

For years now websites have been gathering data on our online behaviour. This data generates insight into who you are, allowing the technology to learn about your preferences, likes, dislikes and identify your needs. Google uses this technology to learn about your search preferences, Amazon uses it to make relevant shopping recommendations and advertisers use it to place relevant adverts in key places. This technology can be applied to classrooms to learn how a student learns and provide them with a personalised education. By doing so, the time teachers need to spend analysing each student and planning differentiated lessons would be reduced, allowing them more time to focus on the learning and development of the student. Additionally, the students would benefit from a personalised education that is tailored to their unique learning needs, the end result being improved learning outcomes – the aim of any teacher or school.

Imagine a classroom where a teacher is armed with real-time data on each student, allowing them to quickly and easily identify which ones are struggling, which ones need pushing and what topics need to be revisited. This would super-charge teachers, allowing them to make timely and targeted interventions and make evidence based decisions in the classroom. Students would no longer have to wait weeks for work to be submitted, marked and returned for issues in their learning to be identified. Teachers would be reacting to up to the minute data, just like managers in other industries are. This is the future of education.

As education reaches crisis point and people look for a solution, there is a slow emergence of AI in education. Whilst it is a relatively new phenomenon, there are a few revolutionary AI learning platforms that are making waves. So next time you despair about the lack of time you have to plan a differentiated lesson, the amount of hours you spend marking, or the lack of time you have to recommend next steps to a student, remember – there is a solution. AI in education is new, it’s exciting and it could help solve some of the industry’s biggest pain points.  

CENTURY Tech links with the Your Life STEM campaign

April 2017

CENTURY Tech is a revolutionary online learning platform that uses artificial intelligence and data science to improve education for the teacher and the student. CENTURY Tech’s groundbreaking platform recommends learning topics for each individual student in order to address any gaps in knowledge or skills and teachers have access to shared content and real-time data insights into their students’ learning. Your Life, led by a board of directors chaired by Edwina Dunn, co-founder of dunnhumby and CEO of Starcount, is a three-year STEM campaign to ensure the UK has the Maths and Physics skills it needs to succeed in today’s competitive global economy. The Your Life campaign engages young people by creating inspiring video content and by running activities such as memorable visits to the U.K.’s most exciting STEM workplaces.

So, how are CENTURY Tech and Your Life joining forces?

On CENTURY, students access learning content and artificially intelligent algorithms plot the most effective route through the material. CENTURY provides courses mapped to the National Curriculum and Your Life create videos that are used as learning material throughout these courses. The videos provided by Your Life have been embedded into captivating mini-courses for extracurricular and lifelong learning and are also dotted throughout CENTURY’s GCSE Maths and Physics courses. CENTURY Tech and Your Life are continuing to work together to create exciting courses to inspire students to study STEM subjects by providing engaging material and a personalised route through their learning.

CENTURY Tech has been shortlisted for the prestigious Pitch@Palace programme

April 2017

CENTURY Tech, an artificially intelligent online learning platform, has been selected for participation in Pitch@Palace. Vote now to help them win the People’s Choice Award!

Pitch@Palace was established by The Duke of York to support entrepreneurs in the development of their business ideas. Entrepreneurs present their innovative ideas to an audience of CEOs, investors, angels and influencers. Attendees have the ability to catapult the entrepreneurs’ ideas to the next level, whether they be potential mentors, investors, or business partners. The theme for Pitch@Palace 7.0 is ‘human tech’, so all of the entrepreneurs’ business ideas explore the potential impact of technology on improving our lives.

CENTURY Tech’s purpose is to improve education for the teacher and student. This is achieved by using artificially intelligent technology to learn how each student learns and provide them with a personalised learner path based on their unique learning needs. By learning on the platform, students generate data which is then presented, in real-time, to the educator and provides insight into their strengths, weaknesses, completion and effort level. The platform also auto-marks short, formative assessments and selects suitable learning content for the student, helping to reduce the admin-heavy workload faced by teachers.

People can vote for their favourite business idea by voting for the People’s Choice Award, which is now open. The winner will be announced at St James’s Palace on 25th April. Vote for CENTURY Tech today at http://pitchatpalace.com/vote/.

Priya Lakhani, Founder CEO of CENTURY Tech said:

“Our aim at CENTURY is to improve education for everyone. We really hope people support us by voting for CENTURY in the People’s Choice Award so we can spread our message and help even more students and teachers!”

The Duke of York said:

“I am immensely proud of the achievements of the Entrepreneurs in the Pitch@Palace 7.0 programme. In less than three years, there have been over 500 pitches at events all over the United Kingdom and they have shone a light on the diversity and imagination across the country, clearly demonstrating that pursuing an idea or dream can be realised with knowledge and determination. I wish all those taking part in the People’s Choice Award and the final of Pitch 7.0, every success. ”

What is spaced learning and why does it matter?

April 2017

What is spaced learning?

Spaced learning is the principle that information is more easily learnt when it is split into short time frames and repeated multiple times, with time passing between repetitions. For example, if you have 30 minutes to spend studying one topic, it is better to split the time into three 10-minute study sessions than to lump it into one 30-minute session, and repeat again the next day.

Why does it matter?

Karpicke’s research (2012) identified that memory degrades quickly if information is not reviewed. Despite this, students in schools ‘mass learn’, where they study a topic in one go then move on to the next one, only reviewing the topic when they come to revising it for an exam. Revision often involves intensely studying a topic for a short amount of time, retaining the information for the exam and then forgetting it as they have not built a robust memory of the information. However, new research builds on the suggestion that spaced learning, where a topic is studied in short bursts and then reviewed at a later date, may be a more effective way of learning and retaining information.

The Education Endowment Foundation (EEF) recently conducted a feasibility study into spaced learning. Researchers conducted a 3-day preliminary investigation into whether gaps of 10 minutes and of 24 hours increase memory retention. Teachers were given 36 minutes of teaching material for three different subjects and students were split into the following groups:

In a subsequent test, the students in Test group 3 performed better than any other students. The researchers suggest that the combination of 10 minute breaks and 24 hour repetition results in better memory than traditional “massed” learning. They note that previous research emphasises the importance of the 10 minute break being a ‘distractor task’ rather than a simple break. By having multiple, shorter study sessions with distractor tasks in between, the learner will build a more robust memory of the information for longer as they have more practice at actively retrieving the information from memory.

Putting it into practice

At CENTURY our purpose is to improve the learning outcomes of all students using our platform, so we have spent time devising features that will encourage the long term retention of information.

When students study on CENTURY, they complete ‘nuggets’, which are small topics of learning that include a formative assessment. All nuggets are between 7 and 10 minutes long. Additionally, we have implemented other principles of retrieval practice and spaced learning into our learning platform. Firstly, we implement spaced learning into the Recommended Learner Path directly by reviewing previously studied material periodically; and secondly, we interleave nuggets from different topics (breaking up learning material on one topic with learning material from other topics), meaning that micro-gaps are achieved, even when students are studying in one longer single stretch of time.

Neuromyths in Education

Feb 2017

Neuromyths in education are nothing new. The Guardian has highlighted four of the most common, which our Cognitive Neuroscientist discusses.

There is no surprise that teachers should be interested in psychology and neuroscience. As a cognitive neuroscientist, it is encouraging to see so many teachers trying to incorporate evidence from the science of the brain into their lessons. However, neuroscience is anything but simple and the prevalence of so-called ‘neuromyths’ in the classroom is cause for concern.

The Guardian (2016), TES (2016, 2014, 2013), The New Scientist (2014), the BBC (Radio 4 programme, 2013) have all featured articles on this problem, calling out the common neuromyths and dispelling them. And yet, they persist.

Do we really need to worry? So what if people think that you can be left-brained or right-brained? How bad can it be to believe in learning styles even though there is no evidence to back this up?

Well, expert Paul Howard-Jones says it can be pretty bad, actually. He claims that belief in these neuromyths can hinder effective teaching. Usha Goswami, a researcher at Cambridge University (PDF), suggests that the best way to teach new material is through a range of styles. This contradicts the neuromyth that we have a specific learning style (Visual, Auditory or Kinesthetic). If children only receive learning materials in one of these styles — due to the mistaken belief that this is beneficial — their learning has been impeded.

So, what should the teacher interested in neuroscience in education do?

Luckily enough educational neuroscience is a rapidly growing area of research and it’s beginning to produce some interesting results. In 2014, the Wellcome Trust partnered with the Education Endowment Foundation (EEF) to fund further research into promising educational strategies. There is plenty to interest teachers looking to incorporate cognitive neuroscience understanding into the classroom. Currently being investigated are projects into Growth Mindset, Working Memory, Spaced Learning and Gamificationin the classroom.

They have also compiled a Teaching and Learning Toolkit which is a summary of educational research on teaching 5–16 year olds and is constantly updated to reflect the latest understanding of teaching strategies.

CENTURY is committed to incorporating the best teaching and learning research into our platform. Our recommendation engine currently includes adaptivity based on active retrieval practice (spaced learning and the testing effect) to encourage robust memory formation. We include cognitive messaging around our site to encourage growth mindset, resilience and grit to develop independent, confident learners. We are also piloting an investigation into the role of emotions in learning and long-term memory.

Cognitive neuroscience can provide useful strategies for improving learning outcomes. But we have to be aware of neuromyths, of overselling the evidence and of drawing conclusions that aren’t warranted. If we can do this, then we can drive powerful change in the classroom and beyond.

What’s the big deal with Growth Mindset, anyway?

Feb 2017

Growth mindset is a term coined by Professor Carol Dweck at Stanford University. She distinguishes between growth mindset and fixed mindset. A growth mindset of intelligence is the belief that intelligence can change over time: it is possible to increase your abilities by applying effective learning strategies. In contrast, a fixed mindset is the belief that intelligence is a fixed, innate attribute that cannot be changed: the ability you have at the outset is as good as it will get.

We see mindsets at work everyday, both in the classroom and out. Typical fixed mindset statements look like this:

“I can’t do maths”

“I’m just not creative”

“Oh, I’ve never been sporty”

In all these statements there is a fixed mindset declaring that there is no control over ability.

It’s easiest to see growth mindset in action around games. If you lose a level during a videogame, you typically start it again trying to do better this time:

“Oh, I nearly had it that time! This time I’ll get it”

When you start a game, you believe that you are capable of winning, even if you don’t win straight away. In other words, you have a growth mindset towards the game.

Why does it matter?

Let’s pretend we have a class of two: Alex and Sam. They are given a problem to solve and they both get it wrong. What happens next?

Well, Alex has a fixed mindset so he believes that his ability to solve this problem is already set. There is no point in trying to solve the problem again, no point in learning more about it, trying to understand other ways to solve it. He is either intelligent enough to solve it the first time around or he isn’t. He didn’t, so there is nothing more he can do.

Sam has a growth mindset which means she believes that with effectively applied effort she can solve the problem. She will keep on trying: trying new strategies, trying to understand more; trying to solve it. Sam believes that she will be able to solve the problem eventually.

So, why does mindset matter? Because it alters what we do when we encounter set back. Ultimately, mindset matters because it has a strong relationship with outcome. Students who keep trying are more likely to achieve better outcomes.

What’s the evidence?

Blackwell, Trzesniewski & Dweck (2007)

Carol Dweck has done comprehensive research into the relationship between mindset and learning outcomes. In 2013, she conducted a review showing that mindset interventions result in improved learning outcomes for children who have a fixed mindset (Yeager, Paunesku, Walton & Dweck (2013)). Interventions which change the type of praise a student receives have been shown to encourage a growth mindset. Additionally, interventions which teach children how the brain learns or which focus on the try-fail-try-again routine of famously successful figures are effective.

How does CENTURY incorporate this research?

CENTURY encourages a growth mindset in a couple of different ways.

Students get sent personalised cognitive messages which encourage resilience and growth mindset. These messages offer learners effective learning strategies based on their current performance and effort levels. They also inform the students about how the brain learns to more implicitly encourage a growth mindset. All messaging around results is also grounded in growth mindset research to encourage a mindset which can improve learning outcomes.

Additionally, CENTURY has a course which teaches students how the brain learns. Dweck’s research, among others, showed that understanding of the basic functions of memory and learning can help learners see that abilities are not innate. This course was developed in conjunction with HRH Duke of York, as part of iDEA. It is aimed at learners aged 11–14, but there is something there for everyone. Why don’t you give it a go today and see what you can learn?

Citations

Blackwell, L., Trzesniewski, K. & Dweck, C., 2007, ‘Implicit Theories of Intelligence Predict Achievement Across an Adolescent Transition: A Longitudinal Study and an Intervention’, Child Development 78(1): 246–263

Yeager, D., Paunesku, D., Walton, G. & Dweck, C., 2013, ‘How Can We Instill Productive Mindsets at Scale? A Review of the Evidence and an Initial R&D Agenda’, White Paper for the White House meeting, Excellence in Education: The Importance of Academic Mindsets.

CENTURY Tech takes to the TechCrunch Disrupt Battlefield

Dec 2016

With 1.3 million children underperforming in the UK (Ofsted, 2016) and 74% of teachers considering leaving the profession due to unmanageable workloads (TES, 2016), it is clear that the current education system is facing some serious challenges. CENTURY has been created by teachers, students, parents, software developers and neuroscientists with the purpose of improving education for all.

CENTURY’s revolutionary technology has taken centre stage at the TechCrunch Disrupt Battlefield 2016 to showcase its platform which leverages artificial intelligence and big data technology. CENTURY Tech’s technology learns how each individual learns, adapting their learner journey to reflect their learning needs. CENTURY uses a range of adaptive variables including pace of learning, difficulty levels, modality preference and effectiveness, spaced learning algorithms and item response theory.

Priya Lakhani OBE, CENTURY Tech’s Founder CEO says, “At CENTURY, we are passionate about improving education. Our platform uses advanced technology that makes a real difference to both the teacher and student. I am thrilled that this has been recognised by TechCrunch Disrupt Battlefield!”

So, how does it work?

Students access learning material through CENTURY. CENTURY hosts a multimedia library of content including, GCSE maths and English language, and maths and English Functional Skills, Entry Level 3, Level 1 and Level 2, all of which is mapped to the curriculum. Teachers can also easily add their own subjects and content.

Artificially intelligent technology then learns how each student learns, providing them with a personalised and adaptive learning journey, constant, formative assessments and instant feedback. All messages students receive are tailored to their experience and are grounded in cognitive neuroscience, designed to encourage a growth mindset and resilience.

Teachers and SLT are presented with real-time actionable data that supports evidence based teaching and reduces time spent on planning. By tracking homework, auto marking and finding resources, CENTURY reduces the admin burden faced by teachers. The deep insights presented to educators show their students achievement, knowledge, skills and performance against assessment objectives, identifying their strengths and indicating where interventions may be necessary.

CENTURY Tech is currently being used by more than 10,000 students, with several more secondary schools and colleges receiving their logins in January. CENTURY Tech is also a finalist for the BETT Awards and Learning Awards and Founder CEO, Priya Lakhani, recently won the Special Achievement Award at the Mayor’s Fund Awards.

CENTURY will be exhibiting at BETT 2017 as part of BETT Futures, stand F60. During the exhibition, CENTURY will be giving live demos of the platform as well as short seminars on artificial intelligence, cognitive neuroscience and data in the classroom, among other topics. In addition, CENTURY will be offering schools and colleges that sign up during BETT, free access to the platform for the rest of the academic year plus a significant discount for the following academic year.

To find out more, please email info@century.tech

Promoting A Healthy Data-Driven Culture

 Nov 2016

What are good data practices? What should be avoided?

Liz Macfie, Data Scientist at CENTURY, gives us some insight.

Over my years in data science (and also those as a mechanical engineer before that) I’ve had to learn good data practices, often through making mistakes. I’m going to share some of the more easily avoided slip-ups I’ve seen/done with the hope that this might especially help organisations without a dedicated “data” team (or at least without someone as outspoken as me!).

Track everything. Immediately.

Resources can be spread thinly when starting a new project, especially if there are tricky deadlines to hit. Regardless, data gathering has to be an immediate priority, even if nothing is done with it straight away. We can guarantee that in 3 months time some bright spark will ask how current user behaviour compares to past user behaviour.

I’d also recommend having a kick-off meeting with all personnel who might eventually want to use the data. Perhaps developers don’t know the whole story and would have left out the tracking of a metric that later became a key business priority.

Avoid vanity metrics

It’s understandable, especially when just starting a new project, to be fascinated with raw user numbers. We want to track every action they take, we want to know how many there are, we want to see live activity. This is perfectly fine and can create a shared excitement as screens go up showing what users are doing in real time. However, we have to go deeper than these metrics for business decisions.

A very simplistic example: Let’s say the most important part of our product is a button, and every time a user presses it, we magically get some money. Obviously we want to measure engagement with this button, so we create a graph showing the number of button presses each day.

We spot that the button press numbers go down at the weekend and start fretting over what this could mean: do users only want to pay on weekdays? Someone then thinks to plot number of daily button presses per number of daily users and gets this:

It turns out there is no problem with button engagement, there are just fewer users at the weekend. Reporting the “vanity metric” (number of button presses) rather than the actionable metric (number of button presses per user) was unhelpful.

Keep numbers accurate

We’ve all been there. The quarterly report is due, and we’re the tiniest of fractions below a particular target. Knowing that there are three kinds of lies (lies, damned lies and statistics) we work out a way to “massage” the data so that it falls on the correct side of this arbitrary line. Ethics aside, there are a couple of major problems with this:

  1. Anyone else wanting to produce the same numbers has to know about our statistical manipulations otherwise there will always be discrepancies, and trust me — if there’s one thing any board hates, it’s discrepancies.
  2. If we actually improve the next quarter, but still don’t hit that target, what do we report? The accurate apparently lower number, or do we engage in more data trickery to also bring this second number above the target, so correctly reporting an improvement?

I say, the more honest you are with data in all reports, the more grateful future-you will be.

Verify all results

I don’t think I’ve ever regretted taking a little longer to check numbers I’m about to report, but I’ve certainly often regretted moving too fast and reporting an inaccuracy. This can so frequently be avoided by having multiple ways to generate the same statistics: perhaps we send website data to two sources; perhaps we store the same information in databases in two slightly different ways; perhaps we carry out a calculation again with the steps in a different order.

In addition to this, there should always be an idea of whether variations being reported are “significant”, but that’s a topic for another post.

And finally… my personal pet peeve…

Throw out the pie charts

Just no. Can we please stop with these now? They are a tool to teach students about circle sectors or to show the proportion of uneaten pizza… they are not a valid data visualisation!

All of these are very basic non-technical ways to start a healthy data-driven culture within any company. After setting these principles, the fun begins!

So, what is Cognitive Neuroscience?

 Nov 2016

CENTURY’s Cognitive Neuroscientist, Alice Little, gives us an insight into what cognitive neuroscience really is.

Let’s start with the ‘cognitive’ bit: what is cognition? Cognition refers to all the stuff that goes on in your brain when you think. It refers to all the stuff that happens when you process the world via your senses. Acquiring knowledge, learning things, perceiving. Any mental action or process is a form of cognition.

Cognitive science is the multidisciplinary field that studies cognition. Understanding the memory process, or perception, decision making, problem solving, language acquisition or emotion regulation are all the domain of cognitive scientists, amongst many other things. If it’s a mental process that involves thought, then cognitive scientists are all over it.

Now for the neuroscience bit. Neuroscience is the study of the physical structure and function of the brain (and nervous system). It is the study of neurons, of the chemicals in the brain, of the electricity flows in the brain. Neuroscientists might look at specific instances of brain damage to deduce what that area of the brain is involved in; they might use imaging techniques; they might look at the function of an individual neuron or a highly specific neurotransmitter. They might investigate human brains, primate brains, rodent brains or even the more primitive brain-like structures in simple organisms. But the thing that brings all neuroscientists together is that they are studying the brain itself.

So, what do you get when you cross a cognitive scientist with a neuroscientist? Well, you get a specific method for studying cognition. Cognitive neuroscientists investigate any aspect of cognition with direct reference to what is going on in the brain: we study the brain to understand what the mind is doing.

In short, cognitive neuroscience is the study of brain processes to understand how the mind works.

And how is CENTURY using Cognitive Neuroscience?

CENTURY’s general principle behind incorporating cognitive neuroscience is the same with any features we design and implement. We trust our data to tell us what is effective and what isn’t effective. We will design implementations of various theories and then let the data tell us whether they are successful for learning. If not, we will iterate and try again. Ultimately, we are attached to no cognitive dogmas; we have no vested interest in seeing one theory succeed or fail. The only thing we are driven by when considering the inclusion of cognitive theories into CENTURY is this:

Does it make the learning better?

There is nothing revolutionary about applying cognitive theories to pedagogical practice, but that doesn’t mean we can’t be innovative with how we do that. In the coming blogs I will give a more detailed picture of a couple of the cognitive principles we are currently using in our software and what the evidence is for their benefit for learning, so look out for What’s the big deal with Growth Mindset, anyway? and Let’s test out the Testing Effect if you’re interested in learning more.

Surviving a year of TypeScript

Nov 2016

Tiago Relvão is CENTURY’s Tech Lead. Here he shares his and the Engineering Team’s experiences, frustrations and revelations using TypeScript.

In October 2015 I joined CENTURY Tech just as they were releasing the first version of their software. It was a monolithic lump of three different apps written in Meteor, Jade and CoffeeScript . Although this was a very custom stack, it was also their first project with it and they were running to a very tight deadline (#StartupLife).

After a couple of weeks maintaining that thing, we were all ready for something else — anything else really. The stars aligned and a decision to slowly move into a micro-services architecture was made. We decided to try TypeScript even though no one had any real experience with it. How could that go wrong?!

I started writing some JSON APIs and we decided it was safer to use it server side only to begin with. The idea was that we could use TypeScript as an es6 linter and we would figure out the typed stuff as we went.

That worked surprisingly well. By setting TS in implicit mode and disabling most of the warnings in tsconfig we had this very powerful linting tool, but we were struggling with node modules. We had awesome intellisense for our code but nothing for external dependencies.

We were hooked. We needed to import the type definitions for these JavaScript libraries that made the magic intellisense work. We found definitely typed and tsd, deprecated by typings and now again, in TS2. Fun, right? That allowed us to pull definitions for most of the libs we used.

Great. Types everywhere! But then we needed to release our own node packages. Moving some shared code into their own node modules broke TS — no more types. The same code moved into a node_modules folder failed to recognise type — what was going on?! It seems we also have to export typings in this case.

One of our developers decided to learn all about type definitions by reading the docs. Not Stack Overflow — the actual docs! He is now our go to person whenever TSC starts babbling incomprehensible error messages (you should definitely get one of those in your team if you want to go the TS route!). After a while it all started making sense to us. Until it didn’t again… it’s a recursive process.

Most data is submitted by users, databases or API calls. Your code assumes some sort of type but who knows what gets submitted — users can be a strange breed of human. What was frustrating was all that time spent writing type interfaces that we couldn’t use in runtime, but interfaces aren’t the only way to define types. You can use a class!

This is where we are going now, converting our interfaces into classes that include runtime validation. We still have to define the primitive types as TS annotations but it’s easier to define a validate method that takes care of runtime validation. Writing type definitions is now looking much easier.

Using types is great but be prepared to spend some time writing them. I now love re-factoring/debugging TS code, especially after a couple of weeks when I no longer remember writing it…! So far, I have spent as much of my time re-factoring code as I have writing it, but that is the nature of the beast. I am grateful that our team decided to go with TS. My only regret, maybe, is not spending a couple of weeks learning this stuff. The slow migration from es5 to fully TypeScript (es6 + types) feels a waste of time now that I look back.

By the way, we finally killed the Meteor app. It will not be missed. We replaced the front-end with Polymer and web components, which is also a cool story.

Harnessing technology to make teachers’ lives easier

 Oct 2016

Nadya Thorman is the Chief Operations Officer at CENTURY and previously taught with Teach First for three years. Here she explains how technology can be used to benefit teachers.

When I started my Teach First journey in 2010, I, like many participants, had absolutely no idea what I was getting myself into. I had applied to Teach First after being shocked by the appalling social mobility statistics I had come across in my university studies. Teach First offered an opportunity to address the issue; I could make a real difference to the lives of young people, and I could do it immediately.

Within a few weeks of the school term, that starry-eyed, naïve, young graduate was exhausted and dispirited; I was beginning to doubt whether I could convince Abdul to bring a pen to class, let alone transform the educational opportunities of the students I taught.

Teaching was, and still remains, the most difficult thing I have ever done. Don’t get me wrong — I loved teaching; I loved the students who made me laugh every day, and I loved the colleagues who worked tirelessly to improve the life chances of others. I was even pretty good at it, at least so others told me. But it was hard, and it didn’t feel sustainable, so, after three years and much soul-searching, I made the decision to leave the profession.

Unfortunately, I was not alone in finding teaching a challenge: in a recent survey of teachers, 82% of respondents reported that their workload was unmanageable. I have returned again and again to this dilemma: if good teaching is beneficial to society (and I think we all agree that it is), then how can we make it a more sustainable career? So when I was asked if I would join education technology startup CENTURY Tech, which aims to improve learning outcomes while reducing teacher workload, I jumped at the opportunity.

Teachers know how to make learning happen: we know that students benefit from immediate and constructive feedback; that differentiated materials enable students, who learn in different ways and at different speeds, to make similar progress; that accurate data can be used to identify key strengths or weaknesses more quickly; that for some students, a ‘fixed’ mindset holds them back, and that more than teaching them new skills, we need them to understand that they have the ability to grow their intellect. We also know that doing all these things for all our students is a monumental task. Our intention at CENTURY is to make this task easier.

CENTURY’s learning platform provides students with a personalised learner path at the same time as arming teachers with learner data, so that they are the very best educators they can be. The platform uses artificial intelligence technology, cognitive neuroscience and big data insights to begin to understand how students learn best by analysing students’ behaviour on the platform, e.g. time active, accuracy of answers, media studied, response time, etc. According to the DfE, data management and marking are the biggest drivers of ‘unnecessary and unproductive tasks’ in a teacher’s day. So CENTURY aims to reduce teachers’ workload by automating the marking of students’ work and presenting learners’ data in an easy-to-use dashboard. Teachers are provided with a real-time view of how their students are progressing so that they can intervene as and when necessary.

We have big dreams for the future of education and are busy working with innovative schools and colleges in order to achieve them. We are always looking to collaborate with educators who are excited about the possibilities that technology can bring to education. If you fit the bill, or are interested in finding out more, please email info@century.tec.

We can’t wait to work together to make a difference to the world of education.

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