The acquisition of scientific knowledge through problem solving offers the possibility to consider different requirements for inclusive chemistry lessons. We will present and discuss on empirical data a theoretical model that differentiates between low achievers and high performers and, in addition to domain-specific characteristics, also takes up general criteria for good teaching. The architecture of the "model for inclusive chemistry teaching" (MiC) is designed so that teachers can derive concrete, planning-guiding assistance from it. As part of the evaluation of our model for inclusive chemistry teaching (MiC), a learning environment on the topic of “fire & flame” was designed and evaluated [1]. The orchestration of the learning environment with real experiments, an interactive Multitouch Learning Book – a dynamic, web-based platform that allows the instructor to combine e.g. texts, videos or learning games –, and a paper-based workbook leads to a realistic design of features for problem solving, motivational aspects, self-regulated learning with digital media, the teaching and learning sequence, type of experiments, and the use of prompts. In addition to individualized learning paths, linear and branched procedures can be designed. Digital learning environments create scope for open and inclusive teaching, but traditional teaching concepts need to be reoriented in order to make the potential of digital learning environments effective. The teaching unit was quantitatively tested (N = 165) with school students at the age of 12 and 13years from different school types. Questionnaires and video recordings were used to record the perceived fit of the teaching offer with the individual performance of students, supplemented by questionnaires and observation forms from teachers. The first results regarding the pre-post analysis showed positive, significant changes for the students' self-assessment regarding the “fire and flame” content knowledge (high school N = 51, elementary school (N = 43), comprehensive school (N = 71), 23 items, Expertise pre: α = 0.927, post: α = 0.846, p <.001). We showed that even students with a low interest in natural sciences answered all tasks in the knowledge test at a very high level.
Keywords: Science Education, Inclusion, Professional Development, Chemistry.