New Perspectives in Science Education

Edition 13

Accepted Abstracts

The Cognitive Development of Visual Literacy for Scientific Symbolic Problem Solving

Michael Taber, Colorado College (United States)

Elizabeth Benedict, Colorado College (United States)

Elizabeth Waterman, Colorado College (United States)


In many scientific interpretational situations, the available information inputs (i.e., plurality of data) are often expressed to the user in symbolic representations. To what extent does the novice scientist, a student just learning science, have the capacity to holistically interpret the data? Where is the science learner in the development of visual literacy in terms of spatial thinking, re-representations of information in visual format(s), and communication of complex patterns? Learners with more developed linguistic skills, both verbal and phonological, should be better equipped to understand and solve visual problems. Also, would science learners in individual vs. group settings fair worse or better in visual literacy expression? This study attempts to answer two key questions: 1) what visual literacy skills do science learners utilize in solving a symbolically driven problem, and 2) do group settings lead to enhanced opportunities to both utilize and develop visual literacy skills? Participants in the study were students in graded seven through graduate school (U.S.A). Participants were asked to solve an unseen sixth face on a cube, record observations and answers and provide evidence to support answers. Results showed that older participants did indeed possess higher linguistic fortitude through more detailed pictures and notes, but did not necessarily communicate complex patterns more effectively, concluding that age does not determine improved visual literacy and that visual literacy is a cognitive developmental process. Moreover, participants in group settings were able to provide more opportunity for enhanced visual literacy than participants in individual settings, suggesting that visual literacy learning is best performed in social-constructivist scenarios.


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