- Falmagne, J.-C., Koppen, M., Villano, M., Doignon, J.-P., & Johannesen, L. (1990). Introduction to knowledge spaces:
How to build, test and search them.
*Psychological Review, 97,*201-224 - Heller, J., Hockemeyer, C., & Stefanutti, L. (2017).
*Knowledge Space Theory*. Moodle course.

- Chess
- Held, Schrepp and Fries (1995) derive several knowledge structures for the representation of 92 responses to 16 chess problems. See Schrepp, Held and Albert (1999) for a detailed description of these problems. This app uses the projection of their DST1-structure reduced to the first five items.
- 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).

Held, T., Schrepp, M., & Fries, S. (1995). Methoden zur Bestimmung von Wissensstrukturen — Eine Vergleichsstudie [Methods for determining knowledge structures — a comparing study]. Zeitschrift für Experimentelle Psychologie, XLII (2) ,205–236.

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

If you do not know knowledge space theory, you should best start with the short introduction.

On the right side, you see a Hasse diagram of the knowledge space where the states of the learning path are marked.

The above Hasse diagram shows the knowledge space
with automatically changing learning paths
marked in blue
#### List of All Learning Paths:

TquanT was co-funded by the Erasmus+ Programme of the European Commission.

© 2018 Cord Hockemeyer, University of Graz, Austria