ESS Internal Assessment and Experimental Program

Individual Investigation – The IA

The Internal Assessment – or IA – is an individual investigation into an environmental issue done by each student. It’s worth 25% of the final grade for Standard Level ESS and 20% of the final grade for HL ESS. Below, you can find some of the resources I use to help students develop, conduct, and evaluate quality IAs that earn high marks from examiners. I will post them as I finish editing them.

Criterion A: Research Question and Inquiry [4 marks of 30]

Criterion B: Strategy [4 marks of 30]

Criterion C: Method [4 marks of 30]

Criterion D: Treatment of Data [6 marks of 30]

Criterion E: Analysis and Conclusion [6 marks of 30]

Criterion F: Evaluation [6 marks of 30]

Practical Work

Students are required to complete several hours of practical work for IB Environmental Systems and Societies. Practical work in ESS consists of laboratory experiments and investigations, virtual simulations, data visualizations, and – my personal favorite – ecological field work. Over the years, I have developed an extensive program of activities for each topic in the ESS syllabus. You can find some of them below, which I add to this page as I edit them. Editable versions of them are also available at my TPT store by the same name: Mr Kremer Science.

Collaborative Sciences Project

Data and Statistics in ESS

Pearson’s correlation is used to understand the relationship between variables. This brief video provides a nice summary that you can apply to your IA data when you’re dealing with continuous variables like those along an environmental gradient.

I like this video because the examples used are fairly easy to connect to the fieldwork you might do in your ESS IA. It includes p-values, the T-test, chi-squared, and the ANOVA test. The author Greg Martin has a nice stats cheat sheet you can download for free, too.

You may find this video about measures of variability helpful as you write section D of your ESS IA. It goes through the mathematics and the meaning within data sets. You can apply these to the data you collect in your internal assessment.

Happy learning!