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Durham University

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A research project of the School of Education.


Imperial College is the lead institution in a Practice Transfer Partnership for STEM outreach groups in HE. This small project was to scope the possibilities for the University of Durham to offer HEIs involved in the PTP the opportunity to utilise a data sharing mechanism that uses data from activities carried out in the outreach labs and that can then be used to carry out other activities in classrooms using shared data. The document produced sets out a structure by which that data sharing could take place, along with the rationale for offering this facility within the PTP. It offers illustrations of how the data visualisation tools can enable a richer view of the role of data in science to be accessible to students and their teachers. The text below summarises the key ideas.


The project is funded by the following grant.

  • Stem Labs (£1500.00 from EXICOE)


Data visualisations - can they enhance learning in sciences and mathematics?

Much of the experimental work in school science is constrained by the limited time available. Students work individually, or more often in pairs or small groups, to conduct an experiment and record values of (typically) a pair of variables – such as temperature and time, or mass and spring extension etc. Once the experiment is completed and students write up their observations, there will normally be a class discussion of the results and their interpretation. The data from any experiment will normally go no further than the group who collected that data.

The vision here is that Reach Out Labs within the PTP might develop experiments involving more than 2 variables. An individual group of students attending a particular Reach Out Lab would use a prescribed level of some controlled variables and take measurements of the behaviour of the other variables. Other groups of students attending that lab on other days, or attending other labs, would conduct similar experiments using other levels of the controlled variables. By collecting some data for themselves, but contributing it to a larger repository of data to which they have access, students are mimicking good practice in the wider scientific community. The ambition is that the experiments they undertake in such a programme will allow a much richer view of the nature of scientific processes (and will circumvent the idea that experiments in school science are trivial). 


Science curriculums now require students to critique media accounts that cite scientific evidence. We believe that the use of data visualisation to allow multiple variable data to be actively explored will enhance student capacity to understand the significance of some of the issues where new science is being discussed in the media. For example, in understanding statements about risk where new drug treatments are being discussed, it is important to understand both the relative risk and the absolute risk involved, and how these may vary between certain groups. For example, students should ask if the new drug is equally effective for all people. It is not hard to imagine differences between males and females, different age groups, different ethnic groups, (and, further, to ask if there are any other health conditions, such as elevated blood pressure, obesity, smoking and alcohol consumption, or pregnancy for which the effect of the drug could be substantially different from the ‘standard’ outcome.

In principle, this sort of data offers a significant opportunity for a detailed exploration of real scientific data (and especially how they impact real social issues) in schools. However, at present, the way the data is presented (typically in tabular form) poses real problems for pupils. As well as the fact that an individual table can be inherently difficult to work with, there is an additional problem in that pupils need to work with multiple tables to build up a good understanding of the evidence.


From the School of Education