For a while now, the use of technology has been a prominent area of professional development in mathematics across the key stages but particularly at level 3. Whether it’s built into the aims of a Maths Hub Work Group, a feature of extended PD courses, there to support a subject knowledge live course, or the focus of a one-off event using technology has increasingly played a more important role in maths education.
As the sophistication of hardware and software evolves, the progression of what’s possible leads to a greater need for understanding of what we, as teachers, can bring to the classroom. The rollout of advanced scientific calculators and modern graphics calculators in recent years has meant students can be more hands-on with their learning. This is also the case with the likes of GeoGebra and Desmos (and Polypad for those down the key stages) being more readily available on mobile phones and tablets.
Despite this, in my experience, teachers still see the use of technology as something of a challenge, something they don’t have time for. This is why there has been a desire to show has simple yet rewarding it can be.
With its common content across A Level and Core Maths, statistics has been a recent focus for using technology within professional development sessions that I have run. Both Desmos and Geogebra allow for pasting data into their programmes, fast statistical calculations, taking of random samples, manipulation of probability distributions and, most notably here, produce a variety of graphs and charts. Having a variation of pictorial representations of the same data helps the user see the patterns within the data to a fuller extent and therefore have a better understanding of its story.
Boxplots, dotplots, histograms, scatter diagrams, normal distribution curves, and all required for Core Maths and A Level Mathematics can be created by typing a simple command.
Using the large data set for my own particular A Level course, having students produce these data representations was a great way for students to familiarise themselves with the data’s context and learn about how to interpret data simultaneously. However, the ability for the data to be dynamic within these programmes holds the real power. Changing an element of the data with a simple slider movement allows students to see how the change affects the overall picture of the data.
Does adapting one piece of data affect our overall interpretation? Does taking a different sample size tell a totally different story? Does using different group sizes mean a totally different shape to our graph? All questions help us understand the data we’re engaging with and a vast improvement in learning several procedures to apply to a seemingly arbitrary list of numbers.
If you’re interested in attending session 2 of 2 of our Dynamic Visualisation of Data online sessions, please visit the event webpage.
We look forward to seeing you!
by Tom Carpenter