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Students’ progress during an assignment in computational physics: mental models and code development
Umeå University, Faculty of Science and Technology, Department of Physics.
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Solving physics problems in university physics education using a numerical approach requires knowledge and skills in several domains, for example, physics, mathematics, programming, and modeling. In this study students' mental models are monitored using interviews at several occasions during an assignment in computational physics. The interview data was analysed using a network analysis approach. Interview transcripts were coded according to the context dependent concepts that were used to define the particular context and situation of this assignment. The adjacency of concepts in the transcripts was assumed to reflect the associations between them made by students, and thus representing students' mental models of the problem solving situation at the time of the interview. For each student a network was built where the concepts were nodes and their adjacency formed the links between them. The changes in students' mental models between the interview occasions gave important information about what the students were focusing on at different stages of the solution process. What students focused on at the different interview occasions was assumed to be an indication of what they believed was useful in solving the task. The visualization of the mental models showed that at the beginning students were concerned about how to deal with writing the Matlab code that was needed to model the problem. As students got more comfortable with the coding process, the physics needed to assure that their simulation was following physics principles, such as energy conservation, became more and more central in their narratives. This study gives important contribution to how networks can be used to model students' thinking in a particular context and provides important knowledge about students' progress in a task in computational physics.

Keyword [en]
computational physics, mental models, network analysis, content analysis
National Category
Didactics
Research subject
didactics of physics
Identifiers
URN: urn:nbn:se:umu:diva-53281OAI: oai:DiVA.org:umu-53281DiVA: diva2:510997
Note
Manuscript submitted for publication in: Research in science education, ISSN 0157-244X, EISSN 1573-1898Available from: 2012-03-20 Created: 2012-03-19 Last updated: 2012-03-20Bibliographically approved
In thesis
1. Computational problem solving in university physics education: Students’ beliefs, knowledge, and motivation
Open this publication in new window or tab >>Computational problem solving in university physics education: Students’ beliefs, knowledge, and motivation
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Solving physics problem in university physics education with a computational approach requires knowledge and skills in several domains, for example, physics, mathematics, programming, and modelling. These competences are in turn related to students' beliefs about these domains as well as about learning, and their motivation to learn. The purpose of this thesis was to investigate the role of university physics students' knowledge, beliefs and motivation when solving and visualizing a physics problem using a computational approach. The results showed that expert-like beliefs about physics and learning physics together with prior knowledge were important predictors of the quality of performance. Feelings corresponding to control and concentration, i.e., emotions that are expected to be good indicators of students' motivation were also good predictors of performance. However, intrinsic motivation, as indicated by enjoyment and interest, together with beliefs expressing students' personal interest and utility value, did not predict performance to any higher extent. Instead, my results indicate that integration and identification of expert-like beliefs about learning and concentration and control emotions during learning are more influential on the quality of performance. Thus, the results suggest that the development of students' epistemological beliefs is important for students' ability to learn from realistic problem-solving situations with many degrees of freedom in physics education. In order to investigate knowledge and beliefs structures network modeling has been applied as a novel tool for analysis. Students' epistemic frames are analyzed before and after the task in computational physics using a network analysis approach on interview transcripts, producing visual representations of mental models. The results show that students change their epistemic framing from a modelling task, with expectancies about learning programming, to a physics task, in which they are challenged to use physics principles and conservation laws in order to troubleshoot and understand their simulations. This implies that the task, even though it is not introducing any new physics, helped the students to develop a more consistent view of the importance of using physics principles in problem solving. When comparing students' framing with teachers,' it is shown that although teachers and students agree on the main features of simulation competence in physics, differences in their epistemic networks can be distinguished. For example, while teachers believe that numerical problem solving facilitates fundamental understanding of physics and mathematics, this is not obvious to students. This implies that university teachers need to be aware of these differences as well as students' beliefs in order to challenge students' expectations and to give support concerning the learning objectives of the assignment. 

Place, publisher, year, edition, pages
Umeå: Umeå universitet, 2012. 60 p.
Series
Studies in Science and Technology Education, ISSN 1652-5051 ; 54
Keyword
physics education, computational physics, simulation, beliefs, motivation, mental models, network analysis
National Category
Didactics
Research subject
didactics of physics
Identifiers
urn:nbn:se:umu:diva-53317 (URN)978-91-7459-398-3 (ISBN)
Public defence
2012-04-16, KBC-huset, KB3A9, Umeå universitet, Umeå, 13:00 (English)
Opponent
Supervisors
Available from: 2012-03-26 Created: 2012-03-20 Last updated: 2012-03-22Bibliographically approved

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Citation style
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