Generating Knowlede Structures from Data

This app follows a very straightforward way to generate knowledge structures from data. Subsets of the item set Q whose frequency within the set of response patterns is higher than a certain threshold are taken as knowledge states. Initially, the threshold is set to "# response patterns" / 2^|Q|.

Please note, however, that this approach requires a number of response patterns multiply larger than 2^|Q|.

This App was created within the TquanT project.
TquanT was co-funded by the Erasmus+ Programme of the European Commission.

Example Spaces

As example data, knowledge spaces provided by the R package pks (Heller & Wickelmaier, 2013; Wickelmaier et al., 2016) are used. Concretely, the following spaces are used:

Density: Taagepera et al. (1997) applied knowledge space theory to specific science problems. The density test was administered to 2060 students, a sub structure of five items is included here.
Matter: Taagepera et al. (1997) applied knowledge space theory to specific science problems. The conservation of matter test was administered to 1620 students, a sub structure of five items is included here.
Doignon & Falmagne: Fictitious data set from Doignon and Falmagne (1999, chap. 7).

References

Doignon, J.-P., & Falmagne, J.-C. (1999). Knowledge spaces. Berlin: Springer.

Heller, J. & Wickelmaier, F. (2013). Minimum discrepancy estimation in probabilistic knowledge structures. Electronic Notes in Discrete Mathematics, 42, 49-56.

Schrepp, M., Held, T., & Albert, D. (1999). Component-based construction of surmise relations for chess problems. In D. Albert & J. Lukas (Eds.), Knowledge spaces: Theories, empirical research, and applications (pp. 41--66). Mahwah, NJ: Erlbaum.

Taagepera, M., Potter, F., Miller, G.E., & Lakshminarayan, K. (1997). Mapping students' thinking patterns by the use of knowledge space theory. International Journal of Science Education, 19, 283--302.

Wickelmaier, F., Heller, J., & Anselmi, P. (2016). pks: Probabilistic Knowledge Structures. R package version 0.4-0. https://CRAN.R-project.org/package=kst