The components of spatial thinking: empirical evidence

• Autor(a) principal: Bednarz, Robert S.
• Data de Publicação: 2018
• Outros Autores: Lee, Jongwon
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Boletim Paulista de Geografia
• Texto Completo: https://publicacoes.agb.org.br/boletim-paulista/article/view/1473
• topic: Spatial thinking; visualization; spatial relations; orientation; spatial thinking ability test.

This paper begins with a short discussion of concepts of spatial thinking skills and the instruments available to measure them. Next, the paper briefly describes the development of the Spatial Thinking Ability Test (STAT). Differences in the performance of 446 junior high, high school, and university students are explored and tested for statistical significance. In addition, the test scores are analyzed using factor analysis to identify underlying spatial thinking components and to determine if the identified components support the structure of spatial thinking proposed by other researchers. Students at all levels displayed similar performance patters; scores for all students were uniformly higher for some questions than others, offering some support for the argument that spatial thinking is composed of more than one skill or ability (in addition to the widely accepted spatial visualization and orientation abilities). We hypothesized that factor analysis would identify independent components of spatial thinking by generating factors that reflected the eight components of previous researchers’ spatial thinking conceptualizations that were represented by questions in the STAT. Our analysis of STAT scores, however, offers relatively little support for the existence of the independent spatial thinking components hypothesized in the literature. The analysis does suggest that spatial thinking is almost certainly not a single ability but comprised of a collection of different skills. Based on the clusters indentified by the analysis, the following spatial thinking components emerge: map visualization and overlay, identification and classification of map symbols (point, line, area), generalized or abstract Boolean operations, map navigation or way-finding, and recognition of positive spatial correlation.