Visual understanding of divergence and curl : Visual cues promote better learning
Klein, P., Viiri, J., & Kuhn, J. (2018). Visual understanding of divergence and curl : Visual cues promote better learning. In A. Traxler, Y. Cao, & S. Wolf (Eds.), PERC 2018 : Physics Education Research Conference 2018 Proceedings. American Association of Physics Teachers. PERC Proceedings. https://doi.org/10.1119/perc.2018.pr.Klein
Published inPERC Proceedings
© The Authors
Prior research has shown that students struggle to indicate whether vector field plots have zero or non-zero curl or divergence. In an instruction-based eye-tracking study, we investigated whether visual cues (VC) provided in the vector field plot can foster students’ understanding of these concepts. The VC were only present during instruction and highlighted conceptual information about vector decomposition and partial derivatives. Thirty-two physics majors were assigned to two groups, one was instructed with VC about the problemsolving strategy, and one without. The results show that students in VC-condition performed better, responded with higher confidence, experienced less mental effort, and rated the instructional quality better than students instructed without cues. All results were statistically significant. Furthermore, VC-students performed better on a transfer task about the curl concept. The superior performance of students in VC-condition can be attributed to saccadic eye-movements which are in line by correct application of the visual strategy and which were supported by the visual cues. The outcomes strongly confirm multimedia design principles and reveal a direct link between processing explicit instructions and its application in subsequent tasks in the domain of problem solving. ...
PublisherAmerican Association of Physics Teachers
ConferencePhysics Education Research Conference
Is part of publicationPERC 2018 : Physics Education Research Conference 2018 Proceedings
Publication in research information system
MetadataShow full item record
Showing items with similar title or keywords.
Poincaré Type Inequalities for Vector Functions with Zero Mean Normal Traces on the Boundary and Applications to Interpolation Methods Repin, Sergey (Springer, 2019)We consider inequalities of the Poincaré–Steklov type for subspaces of H1 -functions defined in a bounded domain Ω∈Rd with Lipschitz boundary ∂Ω . For scalar valued functions, the subspaces are defined by zero mean ...
A Surrogate-assisted Reference Vector Guided Evolutionary Algorithm for Computationally Expensive Many-objective Optimization Chugh, Tinkle; Jin, Yaochu; Miettinen, Kaisa; Hakanen, Jussi; Sindhya, Karthik (Institute of Electrical and Electronics Engineers, 2018)We propose a surrogate-assisted reference vector guided evolutionary algorithm (EA) for computationally expensive optimization problems with more than three objectives. The proposed algorithm is based on a recently developed ...
From monitoring to sharing of attention in dyadic interaction : The affordances of gaze data to better understand social aspects of remote collaborative problem solving Pöysä-Tarhonen, Johanna; Awwal, Nafisa; Häkkinen, Päivi; Otieno, Suzanne (Asia-Pacific Society for Computers in Education, 2020)This paper aims to better understand the social aspects of collaborative problem solving (CPS) through studying joint attention behaviour (JAB) in an online game–like environment. To capture these behaviours and exemplify ...
Visual cues improve students’ understanding of divergence and curl : Evidence from eye movements during reading and problem solving Klein, Pascal; Viiri, Jouni; Kuhn, Jochen (American Physical Society, 2019)The coordination of multiple external representations is important for learning, but yet a difficult task for students, requiring instructional support. The subject in this study covers a typical relation in physics between ...
Fieldsend, Jonathan E.; Chugh, Tinkle; Allmendinger, Richard; Miettinen, Kaisa (Institute of Electrical and Electronics Engineers (IEEE), 2022)Visualizing the search behavior of a series of points or populations in their native domain is critical in understanding biases and attractors in an optimization process. Distancebased many-objective optimization test ...