Research Questions (130) The “Rocard Report” on science education examines current initiatives in Europe to renew activities in this field (2007). A key recommendation of the expert group is to foster inquiry-based science education (IBSE). According to Linn, Davis and Bell (2004), this method can be described as an intentional process of analysing problems, planning investigations, researching conjectures, searching for information and discussing and communicating the results. Also in the OECD Programme for International Student Assessment (PISA), problem solving competence is one of the important cross curricular competencies (OECD, 2004). Like competence in general, it is contextualised, and to follow the recommendation of the European experts, this project consequently deals with the question of modelling and assessing problem solving competence in chemistry contexts. Objectives (130) The design of a valid and outcome oriented model of problem solving competence makes it necessary to take the domain-specific and contextualised character of this competence as well as methods and results of empirical based research in science education, especially in chemistry education, into account. Hence the project aim was the development and the empirical evaluation of a theory driven competence model for problem solving regarding domain specific topics of chemistry (ester and chemical equilibrium). Furthermore the assessment of complex problem solving should be based on a computer tool, useful for larger sample sizes. Additionally to the theory driven development of this tool, the user friendliness as well as the data management and the evaluation of the data are practical oriented objectives of this project. Theoretical Framework (130) During the last 10 years the focus of the current discussions on problem solving is shifted towards more complex situations, dealing with real-life situations and complex competencies (e.g. Funke & Frensch, 2007). According to the OECD (2004, p.27) the problem solver has to pass different steps: (1) understanding the problem, (2) characterizing the problem, (3) representing the problem, (4) solving the problem, (5) reflecting on the solution and (6) communicating the solution. Using these steps for a domain-specific topic, we could only separate four steps. So finally our model describes four problem solving steps: (1) understanding and characterizing the problem PUC, (2) representing the problem PR, (3) solving the problem PS and (4) reflecting on and communicating the solution SRC on three proficiency levels (Koppelt & Tiemann, 2009).

As an assessment tool a computer-adaptive testing laboratory environment was designed for the dynamic testing of the solving process (e.g., van der Linden, 2005; Wirth, 2004). It was designed for students at the age of 14, 16 and 18. In this virtual laboratory the different steps of the problem solving process are built up by a number of small independent tasks. Independent variables like e.g. the familiarity with computers or the domain-specific prior knowledge are assessed by well elaborated and evaluated questionnaires and short tasks (paper & pencil tests). Especially the changes in learning during the solving process were taken into account (e.g., Koeppen, Hartig, Klieme et al., 2008). The investigations were carried out on two days (each 90min.) for each class with students at the age of 14 to 18 from secondary schools in Berlin (Germany). Each sample (class 8, 10 and 12) consisted of ca. 350 students.

The measurement procedure allows e.g. the analysis of solution paths or strengths and weaknesses on an individual level. This formative evaluation offers conclusions with regard to domain-specific characteristics of the curricular content. It could be answered whether a student has attained a certain competence level after a specific chemistry unit. As an example, we found for 10 years old students only a small group of successful problem solvers (7.1%), but a much bigger group of “beginning” problem solvers (13.8%). 38.3% of the students achieved level 2 and 40.8% level 1. By vertical scaling the person parameters of the 14 years and the 18 years old students at the scale of the 10 years old ones we could describe the development of complex problem competence. First results will be presented at the conference.