Helping you explore how science works with post-16 students

About these resources

Better learning

Learning concepts
Concepts such as genetic inheritance, electromagnetism and thermodynamics include many abstract ideas that are far from the everyday experiences of students. Giving students an understanding of how theoretical ideas go beyond data can support their understanding of concepts in science.

An understanding of how scientists assess the quality of data can help students in evaluating their own investigative work.

Trials of the materials available on this site have shown that students find the lessons both demanding and enjoyable. Many students said that they appreciated the opportunity to think more deeply about how science works in real contexts. 

All the teachers involved in the trials were very positive about the resources, finding it challenging but also refreshing to take a new approach in their teaching.

Challenging misconceptions

1. The nature of theoretical explanations in science

Students tend to believe that theoretical models emerge directly from data, and that all features of a theoretical model correspond directly to features in the real world.

Students often fail to recognise the conjectural and tentative nature of many scientific explanations, and that scientific explanations are often expressed in terms of theoretical entities which are not 'there to be seen' in the data.

2. Assessing the quality of scientific data

Students tend to see examination of the quality of scientific evidence as simply making a judgement about whether the scientists involved had made any mistakes.

Students often fail to recognise the inherent uncertainty of measurements and have little idea of how scientists deal with this uncertainty. Few students use ideas about the validity, reliability and repeatability of evidence in evaluating its quality, or recognise the significance of examining the spread of a set of data.

3. The purposes of scientific investigations

Students tend to see scientific investigation as a process of careful description. For such students collecting a 'good' set of data is the end of the data interpretation process.

Students often fail to recognise that many investigations involve the testing of ideas. The need to interpret the data in terms of scientific ideas is not recognised.


Media reports about issues such as 'mad cow' disease, genetically modified crops and the health effects of mobile phone use, often include evidence from scientific investigations. Providing students with an understanding of how such evidence is generated, and how its quality can be judged, helps them to make informed personal judgements about the significance of such findings.