Active Learning Observation Networks
ORAL
Abstract
Classroom observations protocols have been used to gauge the types of actions made by students and teachers in classrooms [e.g. 1]. Analyses based on protocol observations have been used in middle and high school settings [2] as well as university settings to identify different ways of teaching in physics [3]. We argue that encoding and portraying observations of student and teacher actions in networks, may expand the use of observation protocols to capture the dynamics of teaching [4].
We illustrate how we encode video observations to Active Learning Observation Networks (ALONs) via our adapted version of the Classroom Observation Protocol for Undergraduate STEM (COPUS) [1]. Second, we show examples of ALONs, which illustrate how observation networks may be used to analyse video/audio recordings of physics lessons. We find that different classrooms yielded different dynamical structures as displayed in ALONs, and we then used these structures to identify episodes in the original video/audio recordings for further analyses. These analyses showed different fine-grained student-teacher interactional patterns, which may influence learning in the classroom.
DOI-based references
1. Smith, Michelle K., et al. (2013): https://doi.org/10.1187/cbe.13-08-0154
2. Gitomer, D., et al. (2014): https://doi.org/10.1177/016146811411600607
3. Stains, Marilyne, et al (2018): https://doi.org/10.1126/science.aap8892
4. Bruun, J. & Andersen, I.V. (2017): https://doi.org/10.48550/arXiv.1708.01389"
We illustrate how we encode video observations to Active Learning Observation Networks (ALONs) via our adapted version of the Classroom Observation Protocol for Undergraduate STEM (COPUS) [1]. Second, we show examples of ALONs, which illustrate how observation networks may be used to analyse video/audio recordings of physics lessons. We find that different classrooms yielded different dynamical structures as displayed in ALONs, and we then used these structures to identify episodes in the original video/audio recordings for further analyses. These analyses showed different fine-grained student-teacher interactional patterns, which may influence learning in the classroom.
DOI-based references
1. Smith, Michelle K., et al. (2013): https://doi.org/10.1187/cbe.13-08-0154
2. Gitomer, D., et al. (2014): https://doi.org/10.1177/016146811411600607
3. Stains, Marilyne, et al (2018): https://doi.org/10.1126/science.aap8892
4. Bruun, J. & Andersen, I.V. (2017): https://doi.org/10.48550/arXiv.1708.01389"
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Presenters
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Jesper Bruun
University of Copenhagen, Department of Science Education
Authors
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Jesper Bruun
University of Copenhagen, Department of Science Education
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Karen A Voigt
University of Copenhagen
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Viktor H Janas
University of Copenhagen