The Difference between Evaluating and Understanding Students' Visual Representations of Scientists and Engineers

The Difference between Evaluating and Understanding Students' Visual Representations of Scientists and Engineers

Donna Farland-Smith (The Ohio State University, USA) and Kevin D. Finson (Bradley University, USA)
Copyright: © 2016 |Pages: 15
DOI: 10.4018/978-1-5225-0480-1.ch013
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This chapter is a discussion of multiple tools for analyzing children's representations of scientists and engineers. Draw-A-Scientist and Draw-An-Engineer protocols have been utilized by science education researchers to investigate learners' perceptions of scientists and engineers. The chapter discusses the methods for analyzing students' perceptions of scientists and engineers how aspects of analysis lead to deeper understanding of the visual data. The discussion presented here is framed in the context in which refined protocols and rubrics are tools that uncover ranges of conceptions, and sometimes visual data are best examined by simple evaluation methods and sometimes by a qualitative rubric. The overarching question of this section is how can researchers use analysis of visual data to further what they already know about conceptions of scientists and engineers.
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Evaluating Visual Data From Students About Scientists And Engineers

Well before children are able to express and verbalize which careers may be interesting to them, they are forming opinions and impressions from the world in which they live. Children collect and store ideas about scientists and in some cases engineers as well based on their experiences. For this reason, asking children to complete what science educators frequently term the Draw-A-Scientist Test (DAST) became a popular method for providing insight into how children represent and identify with those in the science fields. In its many forms, visual information and visual data within these illustrations have an important role to play with respect to learning and career choice. These assumptions might exhibit themselves in multiple ways, such as influencing someone’s conceptions or even serving as tools that enable educators to investigate, collect information, and utilize that information to improve their instruction and student learning. The focus of this portion of the chapter is to discuss the analysis of this form of visual data and provide multiple means of evaluation as a way to understand these visual representations.

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