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Forma mentis networks reconstruct how Italian high schoolers and international STEM experts perceive teachers, students, scientists, and school (2001.02596v1)

Published 6 Jan 2020 in physics.ed-ph and physics.soc-ph

Abstract: This study investigates how students and researchers shape their knowledge and perception of educational topics. The mindset or forma mentis of 159 Italian high school students and of 59 international researchers in STEM are reconstructed through forma mentis networks, i.e., cognitive networks of concepts connected by free associations and enriched with sentiment labels. The layout of conceptual associations between positively/negatively/neutrally perceived concepts is informative on how people build their own mental constructs or beliefs about specific topics. Researchers displayed mixed positive/neutral mental representations of teacher'',student'' and, scientist''. Students' conceptual associations ofscientist'' were highly positive and largely non-stereotypical, although links about the mad scientist'' stereotype persisted. Students perceivedteacher'' as a complex figure, associated with positive aspects like mentoring/knowledge transmission but also to negative sides revolving around testing and grading. School'' elicited stronger differences between the two groups. In the students' mindset,school'' was surrounded by a negative emotional aura or set of associations, indicating an anxious perception of the school setting, mixing scholastic concepts, anxiety-eliciting words, STEM disciplines like maths and physics, and exam-related notions. Researchers' positive stance of ``school'' included concepts of fun, friendship, and personal growth instead. Along the perspective of Education Research, the above results are discussed as quantitative evidence for test- and STEM anxiety co-occurring in the way Italian students perceive education places and their actors. Detecting these patterns in student populations through forma mentis networks offers new, simple to gather yet detailed knowledge for future data-informed intervention policies and action research.

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