1.

It is probably better to attempt a simple project where students can show mastery of the process and develop basic skills on which they can build., rather than tackle a complex problem for which they really don’t have the necessary standard of skills or equipment to obtain meaningful results.

2.

It is far preferable to develop a hypothesis which relates to real-life situations with variables tested which mirror real-life occurrences.  e.g. if studying effect of shampoo in grey-water on lawn growth, calculate reasonable shampoo dilutions rather than “straight shampoo”, “half strength” etc.

3.

It is very important that students do not jump into carrying out tests without first doing some background reading, or discussing the idea carefully with a mentor (teacher/ parent/ scientist in the field), to ensure that the experimental method is “workable” and that all possible variables are considered in the planned method.

4.

Projects that represent basically one or two lessons of experimental work rarely compare with a long-term study where there has been time to assess and review along the way. Especially for any project based on growth or change (eg. effects of substances on plant growth), enough time, maybe months, must be available to track this development., as well as taking into account the appropriate time of the year. If this is the case, in the classroom situation, you may choose to revert to another concurrent unit of study, with perhaps  a short time allocated once a week to monitor and record changes.

5.

Students need to be encouraged to use sample sizes as large as possible. Meaningful comparisons cannot be made with only a few individuals.

6.

Similarly, repetition of experiments  to show natural variability as opposed to causal relationships is important, and the use of simple statistical tools (such as finding averages) is to be encouraged. For older/ stronger maths students, the introduction of the concept of standard deviations might be appropriate. All these things take TIME.

7.

Quantitative data is always preferable to qualitative. How much faster, hotter, higher??? Data should be tabulated and graphed where appropriate, making it easier to compare different data sets. These tables and graphs should be clearly labelled and units noted. Discuss the specific uses of line graphs as opposed to bar graphs etc.

8.

Some judges expressed difficulty in assessing projects that addressed environmental issues, but where data collected did not refer back to an original question or hypothesis. A very blurred effect is found from mixing data from external sources, with full class data and individual data. A whole class project (acceptable at Primary levels) may be better approached by allocating students to study different aspects of the overall issue. They could then write individual reports on that aspect concentrating on the relevance of the data to the overall question.

9.

Presentation IS important. The correct standard science-report format is set out in the booklet/ website. Use of photos and diagrams can show experimental set-up, or certain qualitative differences very clearly, but they must be fully labelled. A display folder or ring binding will both protect their work, and show your students that you are proud of their efforts.