Experimentation as a process of gaining scientific knowledge has become increasingly important in educational politics and public interest within the last years. Although this approach to gaining scientific knowledge has belonged to the core of scientific education for a long time, further areas are being researched and developed. These include introducing pre-school children to science and technology in a playful way and a conceptional reprocessing of experimentation as a supporting competence as well as a central and competent method (especially for primary and secondary education) for scientific instruction. The work of the doctoral programme ExMNU contributes a share to this effect.

The central issue in the third PISA study from 2006 was science. The conceptional focus of the survey was oriented on the “scientific literacy” of basic scientific education. Under scientific literacy three sub-skills are distinguished:

(a)    are students able to recognise a scientific question (differentiation between scientific and non-scientific interrogations),

(b)   are students able to explain scientific phenomena (describe, explain and predict phenomena),

(c)    are students able to use scientific evidence (dealing with empirical evidence and scientific conclusions).

PISA and other international achievement studies attribute only moderate performance to German students when it comes to independent problem solving tasks in a mathematical-scientific context (see Baumert & Lehmann; (TIMSS), 1997, Rost et al., 2004). Two problem solving types are differentiated: “analytic” and “dynamic” problem solving (Klieme, Leutner & Wirth, 2005). In the framework of the doctoral programme, especially analytic problem solving is of interest, since experimentation uses mainly features from this kind of problem solving.

Experiments or experimental actions in a mathematic and scientific context are understood as a systematically controlled methodological intervention, based on assumption, into a specific natural event/ observed phenomena/ a problem structure. The intention of these procedures is to verify a correlation (in the best case a causal link) between two variables under (controlled) constant conditions and/or variations of state variables (‘parameter’ independent variables).

Following Klahr (2000), an experiment can be grasped as a complex process of problem solving or, to be more precise, as an outstanding element in the process of scientific discovery. In this concept, the experimental approach is designed as a “Dual-Search-Model” which includes a search in two search areas (the hypothesis and experimental search areas) as wells as a phase of data evaluation and interpretation (according Klahr, 2000).

Researching scientific teaching in German schools shows that experiments, on the one hand, are an essential component in scientific education, but on the other hand occur mostly in the form of demonstrative experiments and that explorative learning activities are rarely implemented (Prenzel et al.,  2008, S. 14).

How experiments are employed in the classroom and what implemented forms will show which results cannot be satisfactorily answered at this time from an empirical point of view, since questions on this issue have not yet been treated (Hamann, 2007, Ehmer, 2008). This is hampered by the fact that there exists little knowledge about a) how the competences in scientific experimentation for the various grade levels can be acquired, b) what cognitive structures of experimental competences lie at the base and c) how these competences develop. It is also an open question whether this model can also be carried over to all scientific as well as mathematics subjects and if yes, then which parts.

Altogether the EXMNU course of lectures is orientated on existing models and measurement methods for the topic “experimenting to gaining scientific knowledge” (Hammann, 2004, Klahr, 2000). However, these models are adapted or expanded to the effect that they are structurally adjusted to the conception of course contents which foster experimental competences. Moreover, these existing models are scrutinized for their suitability in the acquisition of a domain comprehensive experimental competence.

Central aims of the doctoral programme are to examine:

i) whether experiments, which are based on subject-didactical knowledge and empiric studies, can be employed to support content learning and competency acquisition in classroom teaching and

ii) whether the experimental competences of students can be diagnosed and specifically promoted.

More about research relevant aims in detail

Reference list:

Baumert, J., Lehmann, R. (Eds.) (1997). TIMSS - Third International Mathematics and Science Study: Dritte Internationale Mathematik- und Naturwissenschaftsstudie: Anlage, Fragestellungen und Durchführung der TIMSS-Studie in der Bundesrepublik Deutschland. Berlin: Max-Planck-Inst. für Bildungsforschung.

Ehmer, M. (2008). Förderung von kognitiven Fähigkeiten beim Experimentieren im Biologieunterricht der 6. Klasse: Eine Untersuchung zur Wirksamkeit von methodischem, epistemologischem und negativem Wissen. Dissertationsschrift an der Christian-Albrechts-Universität zu Kiel.

Hammann, M. (2004). Kompetenzentwicklungsmodelle. Merkmale und ihre Bedeutung – dargestellt anhand von Kompetenzen beim Experimentieren. Der mathematische und naturwissenschaftliche Unterricht. MNU 57/4 (1.6.2004), 196 – 203. Troisdorf: Bildungsverlag E1NS – Dümmler.

Hammann, M., Phan, T. T. H., & Bayrhuber, H. (2007).  Experimentieren als Problemlösen: Lässt sich das SDDS-Modell nutzen, um unterschiedliche Dimensionen beim Experimentieren zu messen?   In: J. Baumert, & al. (Hrsg.),  Zeitschrift für Erziehungswissenschaften. Sonderheft 8: Kompetenzdiagnostik, 33 – 49. Wiesbaden: Verlag für Sozialwissenschaften.

Klahr, D. (2000/02). Exploring Science. The Cognition and Development of Discovery Processes. London: The MIT Press (Massachusetts Institute of Technology).

Klieme, E., Leutner, D. & Wirth, J. (Hrsg.) (2005). Problemlösekompetenz von Schülerinnen und Schülern. Diagnostische Ansätze, theoretische Grundlagen und empirische Befunde der deutschen PISA-2000-Studie. Wiesbaden: VS Verlag.

Rost, J., Prenzel, M., Carstensen, C., Senkbeil, M. & Groß, K. (2004).  Naturwissenschaftliche Bildung in Deutschland. Methoden und Ergebnisse von PISA 2000. Wiesbaden : VS Verlag für Sozialwissenschaften.