With the inclusion of computational modelling within the acceptable list of internal assessments (I find it a big struggle to call them IA’s) for the Group 4 sciences I have become intrigued by the possibilities they provide.
I have also read read in some quarters of a certain resistance to their inclusion within student internal assessments as they feel there is a lack of complexity and sophistication in their use. I have continued to explore the possibilities that include sufficient rigor to be comparable with the classroom experiments.
Through a recent search I came across the following (HERE) and further exploration got me to find these. From a colleague I was shown this which focuses on population genetics. And the one below looks at the impact of tobacco on mortality rates.
Compared to those simulations in a previous post on NetLogo based simulations (which are referred to as agent-based models AB) the above computational models are referred to as System Dynamic SD models.
These represent the two main types of computational modelling systems available and you can read more of the differences between the two if you click HERE.
At the OETC conference in February, Jon Darkow will be leading a session that looks at best practices in implementing simulations in the classroom.
Computational modelling represents an exciting and new direction for the Group 4 sciences. As with many of the changes that have occurred with the new syllabus, wash back into the lower grades greatly supports the shift that has taken place that further embraces technological advancement. As schools embrace code as a necessary skill for the future, creating and working with models either in the diploma years or below represents an excellent opportunity to develop scientific understanding.
And lastly check out the following article [BRINGING SYSTEM DYNAMICS TO A SCHOOL NEAR YOU Suggestions for Introducing and Sustaining System Dynamics in K-12 Education]