Commentary: Deep analysis of epistemic frames and passive participants around argumentation and learning in informal learning spaces |
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| Affiliation: | 2. Department of Radiology, Kyungpook National University School of Medicine, Daegu, Korea;3. Department of Radiology, Gyeongsang National University School of Medicine, Jinju, Korea;1. Department of Psychology, University of Bologna, Bologna, Italy;2. Life, Health and Environmental Science Department, L’Aquila University, L’Aquila, Italy;3. Neuropsychology Unit, IRCCS Santa Lucia Foundation, Rome, Italy;4. CINECA, Consorzio Universitario, Bologna, Italy;1. School of Energy and Power Engineering, Beihang University, Beijing 100191, PR China;2. Collaborative Innovation Center of Advanced Aero-Engine, Beihang University, Beijing 100083, PR China |
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| Abstract: | Our commentary first discusses three points of interest highlighted by the current studies in terms of breadth of measured behaviors and characteristics, the commensurability of designs, and the importance and challenge of analyzing learning by passive participants. We then discuss how datamining strategies might be organized to support future research building on these points of interest. |
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| Keywords: | Argumentation Datamining |
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