Complex interactions characterise lessons. This presents classroom research with a methodological challenge if researchers want to capture this dynamic. So far, analyses of lessons often use methods that aim at global assessments of teaching, whereby statements about dynamic processes are missing. One approach to solving this problem is the State Space Grids (SSG) developed by Hollenstein (2007), which relate the temporal course of the expression of two teaching characteristics to each other. However, in SSGs, there is no possibility of recording the relationship between two indicators numerically.
The Advanced State Space Grids (ASSG) method aims to expand SSGs into Advanced State Space Grids (ASSG) using mathematically based concepts. In the process, we add numerical and graphical elements. These include new n-dimensional relation strengths between the recorded indicators, error estimations, chi-square tests, and parameters for densities and deviations. We define and proof these parameters in the following document.
Using the Advanced State Space Grid method, it is possible to differentiate combinations of indicators into four different categories of dynamic behaviours:
