Tag Archives: Education

Tick Tock, the clock is ticking for a literate society.

“An unprecedented drop in literacy and numeracy across the OECD”

There has been an unprecedented and disturbing drop in average performance for literacy and numeracy in the OECD, as evidenced by recently published research based on data from 2022. https://www.oecd.org/pisa/. Mean performance in mathematics fell by 15 points (equivalent to nine months of learning) and in reading by 10 points (six months of learning loss). Fortunately, average scores for science were maintained.

One in three functionally illiterate

In my home country, The Netherlands, which is one of the richest and most socially progressive places on Earth, with a high commitment to education, the data indicate that one in three students are at risk of being functionally illiterate when they leave school. One in three! That’s up from one in four in the research from 2018. What an enormous loss of potential for these children and our society.  It also makes you wonder how we can spend 12 years and €100,000 per student on education with an outcome that one in three cannot read at the level required to function at school or in society at the end of the journey.

Problem pre-dates pandemic

It would be logical to think that COVID-19 might be the primary cause of this negative development. However, the trend analysis indicates that the decline had begun before the pandemic and peak performance was 10-15 years ago. There are longer-term issues at play. 

Resilience factors could guide the way forward

Some education systems (especially in East Asia and the Baltics) showed both resilience to the disruption from the pandemic, and structurally high learning outcomes. PISA observed 10 factors that contributed to this resilience, and could be helpful in bolstering future approaches, three of which particularly relate to digital, namely:

  1. They ensured good access to skilled teachers, high-quality digital learning materials and devices and developed guidelines for their use.
  2. They limited distractions from digital devices in the classroom (particularly from smartphones and social media) by policies at school.
  3. They prepared students for autonomous and remote learning.

(Screen)-time well spent?

Overall, the evidence shows that using digital/devices for learning purposes in schools yields higher outcomes than not doing so, with the effect tapering off after about five hours per day.  Somewhat surprisingly, the impact of using devices for leisure purposes at school was also correlated with higher learning outcomes, although this turns more sharply negative after about two hours per day.

Most schools have articulated policies about using digital devices on site. However, the least common practices were i) not allowing the use of cell phones (34% of students attended such schools), and ii) having a specific policy about using social networks (51% of students).  In The Netherlands (2022 data), less than 10% of students attended schools where the use of cell phones was not allowed and one in three reported that every or most lessons were disturbed by digital devices.

Tick Tock, the clock is ticking to maintain a fully literate and numerate society

With good quality materials, a focus on learning outcomes and sensible rules of engagement, the use of digital in classrooms enables a positive impact on learning.  

However, smartphones and social media are disturbing the classroom and learning experience and this is likely contributing to why one in three of the kids around here could be functionally illiterate when they leave school.

No time to lose

We need to think again how we systemically approach this better for current and future students and what we can do to bolster the life-chances of this cohort of students with lower literacy and numeracy skills.  Education is a long play, with impact not only on individual lives but crossing generations. There is no time to lose.

How will AI impact teachers?

Super-charger

ChatGPT has recently triggered tremendous excitement about AI and its potential impact on education. Much interest has focused on the learner experience, including the ability to personalise learning. There have of course also been concerns around cheating and plagiarism.

However, AI also has the potential to super-charge teachers.

According to McKinsey, 20-40% of current teacher time comprises tasks that could be automated. They estimate that teachers could re-direct approximately 13 hours per week towards activities that raise student outcomes and increase teacher satisfaction.  The tasks of preparing lessons, administration, evaluation and feedback are flagged as high potential for AI.

Love’s Labour’s Lost

These results echo those of Sanoma’s Learning Impact Survey, in which teachers indicate a desire to go digital in those areas which were most labour intensive, flagging essentially the same areas.  This suggests both that the opportunity is in these tasks and that the profession is looking for solutions.

present_vs_ideal

Teaching profession under pressure

The teacher is arguably the most positive intervention in education.  However the teaching profession faces significant challenges.  UNESCO estimates an additional 69m teachers need to enter the profession by 2030 to fulfil global demand.  In some parts of the world, teacher turnover is high, for example in parts of the USA annual teacher turnover exceeds 15%.  In the UK more than 80% of teachers are considering leaving the profession due to dis-satisfaction.

Higher impact & happier teachers needed!

Furthermore, on average teachers spend only half of their time actually teaching.  This represents not only lost productivity from the core task but is also demotivating for many teachers whose passion is to teach rather than the ancillary tasks around it.  Enabling teacher workflow could therefore not only increase productivity but also make the profession more attractive.

SVGZ-AI-boon-Ex1.svgz

$400bn impact & opportunity

The opportunity to solve this productivity gap is huge.  Measured in terms of financials, assuming global spending on education to be some $6trn, of which 45% is on K-12 education,  and of which 75% is spent on staff salaries, this implies a global spend on teaching/staff salaries of some $2trn per year.  A 20-40% uplift in productivity through AI could arguably be worth some $400-800bn per year in terms of paid and unpaid output!  Which is not to say that this is a saving governments could make or a revenue that education companies could earn, because a significant slice of that value should rightfully return to teachers through higher salaries and quality of life, and another part would rightfully get re-directed to teacher-student interaction to increase outcomes and professional satisfaction.

20%

Help the teacher to focus on teaching!

It’s my belief that the teacher will continue to be the killer app in education, and that the biggest opportunity to make not only a positive impact on learning and teaching in K-12 but also to build a successful business, is to enable the workflow of the teacher.  Probably by combining it with the other side of the same coin: the learn-flow (learning experience) of the student.  

Looking forward >>

It will be exciting to see how we deploy AI in the coming years for a positive impact on learning. Looking forward >>.

Paper – where efficacy meets equity

I was excited to read about this $270M Series D round for Canadian-based ubiquitous tutoring solution Paper – where efficacy meets equity.

A thousand blossoms blooming

Bloom’s seminal work on the 2 Sigma Problem, carried out in the early 1980’s is a classic must-read for edtech ventures today. The outcomes of the research are startling, showing that an average student under tutoring performs about two standard deviations above the average performance of a conventional class. 

Or put another way, an average student following a tutoring program outperforms 98% of students in a conventional classroom!

Since then, the private tutoring market has grown significantly, although new regulations in China last year driven by concerns around equity and student well-being did have a significant negative impact on that market. 

Efficacy AND equity

The good thing about the private tutoring market is its efficacy – it raises learner outcomes.  The disadvantage however is that the rich tend to benefit disproportionately, because they can afford it. The resulting inequity can’t be a good design principle for the provision of education.

Since Bloom, the search has been on to provide solutions that yield similar efficacy at scale.  Paper is potentially such a solution.  For a fixed price, Paper sells licenses to schools and districts to make its online tutoring support available to every student, around the clock, with no cap on usage. Students can connect with a trained tutor for homework help, writing feedback and study support across all K-12 subject areas. Teachers at schools can access these sessions, see which students need support, and adjust their instruction accordingly.

I’m enthusiastic about this approach because it enables both efficacy and equity in education. The risk of inequity isn’t completed removed of course because richer schools might be more likely to adopt the solution than poorer.  Yet with most K-12 education systems funded publicly, that risk could be mitigated by policy. A second risk could be increased competition between schools and tutoring companies for teachers.  Yet the deployment of university students and new/re-entrants into the profession could also work to increase the overall talent pool of teachers available.

Looking forward >>

I’m very interested to see how Paper will grow in the coming years and believe there could be international potential for this type of solution.

DeepMind uses AI to understand life.

Life at the molecular level that is.

Last week saw the breakthrough news that Google has essentially solved the protein folding problem with AlphaFold from DeepMind. I was especially interested in this since this was the area of my PhD.

Function follows structure

Proteins carry out a variety of functions from DNA replication to catalysis to structuring the cytoskeleton.  Each protein is built up from a unique sequence formed from 20 different amino acids. Some 200M sequences are currently known, growing by about 30M per year. The chain of amino acids folds into a unique 3D structure.  This structure determines its functionality.

Prediction: the shape of things to come

Some 170,000 protein structures have been determined to date, and DeepMind has used this dataset to create an algorithm which can predict the 3D structure of a protein based only on its sequence of amino acids, to the same level of accuracy as if actually measured using a technique such as X-ray crystallography.  A reasonably sized protein might take as many as 10300 different shapes, so that’s quite a prediction!

This is relevant because understanding the 3D structure of a protein can inform its function and arguably mis-function, thereby potentially accelerating the rational design of interventions such as drugs against disease states for example.  With 200M proteins in scope, the potential for scientific discovery is massive.

Now we can look to Google not only in search of pizza, but also for the elixir of life.

Determined structures

25 years ago I calculated the 3D structure of a protein essentially by hand (serine proteinase human stefin A, see below) – with a simulated annealing protocol using distance and angle constraints obtained from high-resolution Nuclear Magnetic Resonance spectroscopy.  This took 2.5 years! Multiplied by 200M proteins, it would take quite some effort to map the universe of proteins. The task has now been reduced from years to hours!

Family of 17 solution structures showing the backbone atoms of serine proteinase human stefin A. The protein has a well-defined global fold consisting of five anti-parallel β-strands wrapped around a central five-turn α-helix. There are two flexible regions in this structure which are two of the components of the “tripartite wedge” that docks into the active site of the target proteinase. These regions, which are shown to be mobile in solution, are the five N-terminal residues and the second binding loop. In the bound conformation they form a turn and a short helix, respectively.

The Future of Work in Europe: Back to School

Double dose of disruption

New research from McKinsey suggests that automation and the coronavirus crisis are likely to disrupt many occupations in Europe. They estimate some 51m jobs are at risk due to automation and 59m from COVID-19 to 2030, with a sizeable overlap of 24m jobs exposed to both developments.

Large overlap between jobs at risk from coronavirus crisis short term, and automation long term. @ McKinsey Global Institute

Jobs at risk of being done for

The wholesale & retail, manufacturing, accommodation & food services and construction sectors appear to be particularly exposed, with some 15m jobs at risk.

Jobs at risk by sector @ McKinsey Global Institute

Learn to earn: growth expected in high skills jobs

Some occupations are expected to show significant net job growth in the coming years, with STEM professionals (+4.0m net job growth to 2030), business and legal professionals (+3.9m), health professionals (+2.9m), managers (+2.3m) and education (+2.2m) showing significant potential. These occupations employ a relatively large share of highly educated workers.

Much of the pain is expected to sit in office support, production work and customer service & sales. The great majority of employees in these occupations have not completed tertiary education. 80% of the jobs flagged to be at risk (46m) are carried out by people not holding a tertiary degree.

Europe needs to create more training and career pathways

Education and training have a pivotal role to play in addressing the economic and social impact of this changing job market. Skills are likely to be a key factor in determining recovery from the coronovirus crisis and future prosperity.

Good quality schools, good access to tertiary (particularly STEM) and further education, and the commitment of governments, companies and individuals to ongoing skills development can all contribute to positive employment outcomes.

Re-design for the future

We have rightly seen emergency measures implemented across the World to keep our societies and economies afloat in the midst of the coronavirus crisis. This has come at a huge financial cost. With good reason, the emphasis so far has been to maintain the status quo, to minimise the economic and social chaos.

In the coming period we need to look critically at what the next generation of work will look like and to design interventions that prepare us for that future. This will likely be a job market demanding higher levels of education and skills, and where large numbers of people will need to transition from offices and shops to hospitals and schools for example. How do we organise ourselves for this change?

Best practices

I’m especially interested to learn about initiatives and best practices from institutions preparing for this transformation:

  • organisations that are re-skilling their workforce
  • schools and post-secondary institutions that are adjusting their offerings
  • successful companies that are offering services to close the skills gap
  • new education policies from governments that are intended to enable the transition to new work post-corona.

Feel free to reach out if you know of any great examples!

Looking forward >>