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Showcase November 2014: Distributed Spatial Sensemaking in Middle School Engineering Learning

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Distributed Spatial Sensemaking in Middle School Engineering Learning

Kay E. Ramey & David H. Uttal

Northwestern University

Interest in engineering education programs and curricula for K-12 students has increased substantially in recent years (NAE & NRC, 2009). Students in these programs engage in a wide variety of spatially-rich activities, ranging from construction kits, like Lego® Mindstorms or Snap Circuits®, to focused engineering design projects, to open-ended tinkering activities (e.g. Kolodner et al., 2003; Resnick & Rosenbaum, 2013).

With all of these options to choose from, it is important for educators and researchers to understand what types of skills these various activities facilitate. Our research attempts to answer this question for one important subset of engineering-relevant skills, spatial thinking skills.

Spatial thinking and spatial representations are ubiquitous in professional engineering practice and engineering learning. Both engineers and engineering students must routinely work from maps, models, and diagrams, create spatial representations, such as sketches and models, and tinker with physical or digital objects to solve problems (Christensen & Schunn, 2007; Johri & Olds, 2011; Sorby, 1999; Tseng & Yang, 2011; Wetzel & Forbus, 2010).

Most research on spatial thinking in education has been conducted from a cognitive or psychometric perspective. This research has shown that psychometrically-assessed spatial skills strongly and uniquely predict both performance in college engineering courses (e.g. Hsi, Linn & Bell, 1997; Sorby, 1999; Sorby & Baartmans, 2000; Tseng & Yang, 2011) and entry into STEM professions, including (but not limited to) engineering (e.g. Humphreys, Lubinski, & Yao, 1993; Shea, Lubinski, & Benbow, 2001; Wai, Lubinski, & Benbow, 2009). We also know that there are various subtypes of spatial thinking and that some, such as spatial visualization are more predictive of engineering success than others (e.g. Hsi, Linn & Bell, 1997; Newcombe, Uttal & Sauter, 2013; Sorby, 1999; Sorby & Baartmans, 2000).

Our research augments the cognitive and psychometric perspective by also thinking of spatial thinking as situated (e.g. Brown, Collins & Duguid, 1989; Lave & Wenger, 1991) and distributed (e.g. Hutchins, 1995a; 1995b). We want to know how spatial thinking is used in rich, real-world contexts. We are studying the influence of contextual factors on visual-spatial learning. These factors include other people, external representations, material resources, and the structure of activities. Our research goals were to determine when and why different types of spatial thinking mattered in the context of a middle school summer engineering camp, how students made sense of spatial information, and the role that different aspects of context played in facilitating this sensemaking.

Using multilevel and multimodal analysis of video recordings from learners' activities in the engineering camp, we identified a number of episodes of socially and materially distributed spatial sensemaking, which played an integral role in engineering learning in this context. For example, in Figure 1, we see Kristin, Gabrielle and Miss Alexis, the assistant instructor (all names are pseudonyms), engaging in distributed spatial sensemaking to solve a design problem. The girls are trying to design roofs for model houses, meant to withstand an arctic climate, when they become confused about the constraint that their houses must withstand two pounds of metal discs placed on the roof (representing snow). They work through this confusion collaboratively, manipulating objects to represent static spatial relations (e.g. proposed angle of the roof), using gesture to demonstrate dynamic spatial processes (e.g. snow sliding off the roof), and drawing analogies (e.g. between the metal discs and snow or between their model home and homes they’ve seen in Chicago, an “arctic” climate).

Figure 1a
Figure 1b

The girls often used strategies that align with SILC-identified tools for spatial instruction, such as gesture, analogy and spatial language. They also used other strategies, such as manipulating objects to facilitate spatial thinking and engineering problem solving.

We also found that the different types of engineering activities facilitated different types of spatial sensemaking, spatial skills, and problem solving practices. For example, episodes of spatial sensemaking during the design activities involved more talk about categorizing space and translating between 2D and 3D representations than did episodes during construction kit activities. Design activities also facilitated more sketching and gesture about spatial ideas. Conversely, episodes during construction kit activities involved more talk about spatial relations between objects, more working from diagrams and more object manipulation. Finally, both types of activities facilitated talk about scale or magnitude, rotation, spatial visualization and perspective taking, as well as spatial relational or analogical comparison.

These findings provide a starting point for researchers and educators to design engineering learning activities for this age group that scaffold specific spatial, representational, and problem solving skills. They also provide additional insight into which tools for spatial instruction are likely to be helpful in which types of activities and how they might be used by learners to make sense of spatial problems.

References

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  • ♦ Christensen, B. T. & Schunn, C. D. (2007). The relationship of analogical distance to analogical function and preinventive structure: The case of engineering design. Memory & Cognition, 35(1), 29-38.
  • ♦ Hsi, S., Linn, M. C., & Bell, J. E. (1997). The role of spatial reasoning in engineering and the design of spatial instruction. Journal of Engineering Education, 151-158. DOI
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  • ♦ National Academy of Engineering (NAE) and National Research Council (NRC) (2009). Engineering in K-12 education: Understanding the status and improving the prospects. National Academies Press: Washington DC.
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  • ♦ Resnick, M., & Rosenbaum, E. (2013). Designing for Tinkerability. In Honey, M., & Kanter, D. (Eds.), Design, Make, Play: Growing the Next Generation of STEM Innovators (pp. 163-181). Routledge.
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  • ♦ Sorby, S., & Baartmans, B. (2000). The development and assessment of a course for enhancing the 3-D spatial visualization skills of first-year engineering students. Journal of Engineering Education, 301-307.
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  • ♦ Uttal, D. H., Meadow, N. G., Tipton, E., Hand, L. L., Alden, A. R., Warren, C., & Newcombe, N. S. (2012). The Malleability of Spatial Skills: A Meta-Analysis of Training Studies. Psychological Bulletin. Advance online publication. doi: 10.1037/a0028446
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  • ♦ Wetzel, J. & Forbus, K. (2010). Design Buddy: Providing feedback for sketched multi-modal causal explanations. Proceedings of the 24th International Workshop on Qualitative Reasoning (QR2010).
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