14 research outputs found
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How Misconceptions Affect Formal Physics Problem Solving: Model-Based Predictions and Empirical Observations
One important finding in physics education is that very often
students enter physics courses with misconceptions about the
domain. A n often raised, but hardly ever thoroughly investigated question is whether and how students' misconceptions
in physics come into play in solving formal textbook problems
which ask for a precise quantitative solution. W e developed a
cognitive computer model of the role qualitative physics
knowledge plays in formal physics problem solving. O n the
basis of the model it cannot only be hypothesized where misconceptions might come into play during formal physics problem solving, but also which correct qualitative physics
knowledge should be applied instead in order to guide the use
of quantitative physics knowledge efficiently and successfully.
In particular, the model predicts that the application of misconceptions prevents the results of qualitative problem analyses from being exploited to construct additionally required
formal, quantitative physics knowledge. A n empirical investigation confirmed that misconceptions frequently affect formal
physics problem solving in the way predicted by the model.
Commonly, subjects who applied misconceptions during problem solving reached an impasse when they tried to express the
results of their qualitative problem analyses in quantitative
terms. Most of the subjects were not able to resolve such an
impasse successfully
Collaborative inquiry learning: models, tools, and challenges
Collaborative inquiry learning is one of the most challenging and exciting ventures for today’s schools. It aims at bringing a new and promising culture of teaching and learning into the classroom where students in groups engage in self-regulated learning activities supported by the teacher. It is expected that this way of learning fosters students’ motivation and interest in science, that they learn to perform steps of inquiry similar to scientists and that they gain knowledge on scientific processes. Starting from general pedagogical reflections and science standards the article reviews some prominent models of inquiry learning. This comparison results in a set of inquiry processes being the basis for cooperation in the scientific network NetCoIL. Inquiry learning is conceived in several ways with emphasis on different processes. For an illustration of the spectrum, some main conceptions of inquiry and their focuses are described. In the next step, the article describes exemplary computer tools and environments from within and outside the NetCoIL network that were designed to support processes of collaborative inquiry learning. These tools are analysed by describing their functionalities as well as effects on student learning known from the literature. The article closes with challenges for further developments elaborated by the NetCoIL network
Encouraging the Active Integration of Information During Learning with Multiple and Interactive
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Steps Towards the Acquisition of Expertise: Shifting the Focus from Quantitative to Qualitative Problem Prepresentations During Collaborative Problem Solving
Three important findings of research on expertise in formal sciences such as physics are that novices and experts differ with respect to (1) how they structure their domain knowledge, (2) how they mentally represent problems and (3) how they approach problems. Though first attempts have been made to account for the acquisition of knowledge structures as possessed by experts, the reconstruction of the involved learning mechanisms in a psychologically plausible and instructionally fruitful way still remains a challenge. In an experimental study, we investigated how tenth graders acquire and successively relate qualitative and quantitative problem representations in classical mechanics. Initially, subjects were taught either qualitative or quantitative aspects of classical mechanics. Afterwards, two subjects, who were taught differently, collaborated on problems which were beyond the competence of each of them separately. Before and after the collaboration subjects had to work on multi-component tests. In addition, protocols were taken of the subjects' verbal exchange of information during collaborative problem solving. An analysis of variance of the multi-component tests revealed that the subjects successfully learned to interrelate qualitative and quantitative problem representations. A protocol analysis further indicated that subjects gradually shifted their focus from quantitative problem representations to qualitative problem representations during collaborative problem solving
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Teaching and Supporting the Use of Qualitative and Quantitative Concepts in Classical Mechanics
A systematic characterisation of expository animations
Despite the rapid and widespread adoption of animations in education, there is still no systematic account of the main characteristics of expository animations that have been targeted by educational research. A literature search and analysis was conducted to address this deficiency. First, overviews, reviews, and meta-analyses were analysed to extract an initial set of dimensions to characterise expository animations. Next, a representative set of descriptions of expository animations used in past research on learning from animation was retrieved from the research literature. The animations employed in the 44 investigations analysed covered 30 different topics in 14 different domains. The characterisation developed distinguishes attributes that are inherent characteristics of animations from attributes that are external supplements to animations. The potential advantages of the characterisation developed as a framework for future research on learning from animation are discussed
When Learning from Animations is More Successful than Learning from Static Pictures
Data of an experimental study that compared learning from one picture, four pictures, and an animation