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The block design test (BDT) has been used for over a century in research and clinical contexts as a measure of spatial cognition, both as a singular ability and as part of more comprehensive intelligence assessment. Traditionally, the BDT has been scored using methods that do not reflect the full potential of individual differences that could be measured by the test. Recent advancements in technology, including eye-tracking, embedded sensor systems, and artificial intelligence, have provided new opportunities to measure and analyze data from the BDT. In this methodological review, we outline the information that BDT can assess, review several recent advancements in measurement and analytic methods, discuss potential future uses of these methods, and advocate for further research using these methods. 

Language can affect cognition, but through what mechanism? Substantial past research has focused on how labeling can elicit categorical representation during online processing. We focus here on a particularly powerful type of language—relational language—and show that relational language can enhance relational representation in children through an embodied attention mechanism. Four-year-old children were given a color-location conjunction task, in which they were asked to encode a two-color square, split either vertically or horizontally (e.g., red on the left, blue on the right), and later recall the same configuration from its mirror reflection. During the encoding phase, children in the experimental condition heard relational language (e.g., “Red is on the left of blue”), while those in the control condition heard generic non-relational language (e.g., “Look at this one, look at it closely”). At recall, children in the experimental condition were more successful at choosing the correct relational representation between the two colors compared to the control group. Moreover, they exhibited different attention patterns as predicted by the attention shift account of relational representation (Franconeri et al., 2012). To test the sustained effect of language and the role of attention, during the second half of the study, the experimental condition was given generic non-relational language. There was a sustained advantage in the experimental condition for both behavioral accuracies and signature attention patterns. Overall, our findings suggest that relational language enhances relational representation by guiding learners’ attention, and this facilitative effect persists over time even in the absence of language. Implications for the mechanism of how relational language can enhance the learning of relational systems (e.g., mathematics, spatial cognition) by guiding attention will be discussed. 

Experience with geographic information systems (GIS) can improve students’ spatial skills and provide a foundation for success in STEM (Jant et al., 2019). Researchers and educators co-designed a GIS unit in which high school students learned to use ArcGIS software by exploring geospatial patterns in their local communities. Across three teachers, 134 students participated in the unit and completed a geospatial problem-solving assessment. Students’ performance on the assessment significantly increased from pre- to post-test. Students whose teachers had more GIS experience and completed graded GIS assessments scored higher on geospatial assessments and used more spatial language than students whose teachers had less GIS experience and graded on participation. Students’ expectancy, value, and cost of computer science varied across teachers, and may be linked to students’ ability to devote time to mapbuilding and their engagement with a GIS careers guide. We discuss the impacts of teacher training and lesson implementation on students’ geospatial thinking. 

Spatial thinking skills are associated with performance, persistence, and achievement in science, technology, engineering, and mathematics (STEM) school subjects. Because STEM knowledge and skills are integral to developing a well-trained workforce within and beyond STEM, spatial skills have become a major focus of cognitive, developmental, and educational research. However, these efforts are greatly hampered by the current lack of access to reliable, valid, and well-normed spatial tests. Although there are hundreds of spatial tests, they are often hard to access and use, and information about their psychometric properties is frequently lacking. Additional problems include (1) substantial disagreement about what different spatial tests measure—even two tests with similar names may measure very different constructs; (2) the inability to measure some STEM-relevant spatial skills by any existing tests; and (3) many tests only being available for specific age groups. The first part of this report delineates these problems, as documented in a series of structured and open-ended interviews and surveys with colleagues. The second part outlines a roadmap for addressing the problems. We present possibilities for developing shared testing systems that would allow researchers to test many participants through the internet. We discuss technological innovations, such as virtual reality, which could facilitate the testing of navigation and other spatial skills. Developing a bank of testing resources will empower researchers and educators to explore and support spatial thinking in their disciplines, as well as drive the development of a comprehensive and coherent theoretical understanding of spatial thinking. 

Students’ engagement with geographic information systems (GIS) can improve spatial skills, which are predictors of STEM success (Jant et al., 2019). We used a survey motivated by Eccles’s (2009) expectancy-value-cost framework to assess students’ perceptions of their computer science (CS) courses before and after participation in a GIS unit. The unit provided opportunities to apply GIS to inquiry-based projects focused on solving problems in their own communities. Across four teachers, 158 students participated in the GIS unit and completed the survey. We found that students’ reports of classroom equity predicted their expectancy for success in CS and their desire to take additional CS courses or major in CS. We also examined students’ performance on a geospatial problem-solving assessment to investigate their understanding of GIS and their spatial reasoning. 

A spatial cognition–based curriculum in schools improved verbal reasoning, and neural changes outpredicted tests and grades. 

This work is part of an ongoing partnership that seeks to create a sustainable infrastructure to support GIS-infused instruction in a large urban school district. In this paper, we report an illustrative cross-case comparison of two teachers’ approaches to infusing GIS in their courses. The goal of this analysis is to examine how GIS-infused instruction is adapted in different contexts and to consider the affordances of divergent approaches. Findings illustrate the relationships among organizational context, individual and collective context, particularly teacher identity, and instructional practice in the work of spreading GIS-infused instruction. We also discuss key lessons learned in our partnership thus far and implications for district-level partnerships focused on spread and scale.