The complexity of analysing dynamical systems often lies in the difficulty to monitor each of their dynamic properties. In this article, we use qualitative models to present an exhaustive way of representing every possible state of a given system, and combine it with Bayesian networks to integrate quantitative information and reasoning under uncertainty. The result is a combined model able to give explanations relying on expert knowledge to predict the behaviour of a system. We illustrate our approach with a deterministic model to show how the combination is done, then extend this model to integrate uncertainty and demonstrate its benefits
Thinking back and forth between observing physical phenomena and developing scientific ideas, also known as hands-on and minds-on learning, is essential for the development of scientific reasoning in primary science education. In the Netherlands, inquiry-based learning is advocated as the preferred teaching method. However, most teachers lack time and sufficient pedagogical content knowledge to adequately provide the teaching required for this. To address this problem, we designed and evaluated science and technology lessons, consisting of hands-on experiments combined with interactive diagrams, aimed at scaffolding primary school students (9–12 years) in the development of their scientific reasoning. Our proof-of-concept uses an online application, that lets students work through the lessons while alternating hands-on and minds-on activities. A study was carried out (n = 490) showing that most students successfully complete the lessons within a standard lesson timeframe. The approach enables students to effectively apply several types of scientific reasoning and to do so more autonomously than in traditional science classes.
In the Netherlands there is discussion about the best way to teach mathematics, especially in the case of primary school students. Being able to identify and understand pupils’ multiple problem solving strategies is one of the pillars of pedagogy. However, it is very demanding for teachers, since it requires to notice and analyze pupils’ mathematical thinking and to understanding their actions. The skill to notice and analyze a student’s mathematical thinking is usually not emphasized in Dutch primary school teacher training. It is important to find ways to help teacher-students to analyze student mathematical reasoning, and to learn to recognize the importance of such analysis. Sherin and van Es used the concept of video clubs to help teachers in US schools to notice and analyze their students’ mathematical thinking. In such video clubs, students jointly discuss their filmed lessons. This leads to the following research question:How can video clubs be used to teach students who are learning to become primary school teachers to analyze their pupils’ mathematical thinking and to learn to recognize the importance of such analysis?This paper describes a study that monitors a video club with four participants.
