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Designing guidance for interpreting dynamic visualizations: Generating versus reading explanations
Author(s) -
Ryoo Kihyun,
Linn Marcia C.
Publication year - 2014
Publication title -
journal of research in science teaching
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.067
H-Index - 131
eISSN - 1098-2736
pISSN - 0022-4308
DOI - 10.1002/tea.21128
Subject(s) - visualization , reading (process) , computer science , process (computing) , mathematics education , energy (signal processing) , salient , data visualization , psychology , artificial intelligence , linguistics , statistics , mathematics , operating system , philosophy
We compared designs of guidance to support students while interacting with dynamic visualizations of complex scientific phenomena in inquiry instruction. Three hundred thirty‐two 7th‐grade students were randomly assigned to either a reading or a generating condition and completed a web‐based inquiry unit focusing on energy concepts in photosynthesis. When students interacted with a dynamic visualization of energy transformation, typical guidance provided text explanations while inquiry‐oriented guidance asked students to generate their own explanations about three key energy transformation concepts. The results showed that both reading and generating explanations helped students interpret the visualization, but generating explanations was more beneficial. Students who generated explanations were better able to extract salient information and distinguish among multiple ideas. In particular, they made more connections between their understanding of energy transformation learned from the visualization to other energy concepts to articulate the process of photosynthesis than those who read instructional explanations. Analyses of log data revealed that students in each condition spent similar amounts of time learning from the visualization but navigated the activities in distinct ways and engaged in different kinds of collaborative discourse. This study builds on previous research showing the value of prompting students to generate explanations by clarifying the effective timing for such guidance and characterizing how it helps students make sense of visualizations. These results show that well‐designed guidance enables students working in pairs to generate useful explanations for learning from visualizations and suggest promising designs for online instruction featuring dynamic visualizations. © 2013 Wiley Periodicals, Inc. J Res Sci Teach 51: 147–174, 2014