Topic 3.1 Investigations, data and models (90 GLH)

All scientific enquiries require the application of rigorous scientific method. The selection of approaches, interpretation of findings and reflection on the outcomes of investigations enable scientists to improve their practice and add to our understanding of the natural, technological and human world.

Scientific method is applied across the full range of employment sectors in which science is used and also in other sectors that rely on the systematic, investigative approaches to solve problems and address challenges.

The purpose of this topic is to enable learners to demonstrate their grasp of the essential knowledge and skills that underpin all scientific investigations through the application of scientific method to a problem, challenge or question. They will have the opportunity to design, carry out and evaluate investigations and as a result will be able to operate confidently, effectively and safely in a range of environments where scientific enquiries take place. The role of scientific and mathematical models in describing and explaining observed phenomena will be explored and learners will be able to devise investigations that test existing models or develop new models. Through their experience of the design and evaluation of a range of scientific investigations learners will gain a sound knowledge and understanding of underlying scientific and mathematical concepts, principles and techniques, which they will be able to apply to new contexts and problems.

Learners must know and understand:

1. how investigations are used to create and test models, answer questions, respond to challenges and solve problems

2. the purpose of descriptive and explanatory scientific models

3. how scientific models are constructed and tested and the validity of their use in prediction

4. data collection and recording methods, including ICT, and their strengths, weaknesses, benefits and limitations

5. how to design an investigation to ensure data (including qualitative and quantitative) gathered are valid and reliable

6. how scientists collaborate within and across teams to maximise benefits of disciplinary expertise, share information and undertake peer review, respecting confidentiality and intellectual property rights

7. methods used to research and assess the relevance and reliability of data from secondary sources including how to recognise, acknowledge and minimise bias; ability to replicate published experiments

8. what good practice is in a range of environments in which scientific enquiries take place, including how to carry out a hazard or risk assessment and a knowledge of relevant legislation

9. procedures, equipment and materials for use in laboratory and fieldwork

10. numerical computation of data and relevant mathematical scientific notation

11. how to use statistical measures, diagrams and techniques in the interpretation and representation of data including correlation and regression

12. how to use algebraic and graphical techniques to analyse, make sense of and describe real situations

13. how to draw conclusions from data and assess their significance, including identification of errors and causes of uncertainty, and estimation of confidence level

14. how to evaluate the effectiveness of methods used and the validity of results obtained

15. how to report to a specific audience including choice of methods for presenting data, use of references and scientific terminology, supporting claims with scientific evidence and giving reasoned arguments

Learners must be able to:

1. plan a scientific investigation to seek a solution to a question or problem

2. select and justify methods to gather and record data

3. analyse and evaluate data

4. draw conclusions based on data and information

5. evaluate the methods used

6. report findings in a standard scientific format.

In order to engage with this topic effectively, learners must use the following PLTS:

• independent enquirers
• reflective learners
• team workers
• self managers.