Research from cognitive science and geoscience education has shown that sketching can improve spatial thinking skills and facilitate solving spatially complex problems. Yet sketching is rarely implemented in introductory geosciences courses, due to time needed to grade sketches and lack of materials that incorporate cognitive science research. Here, we report a design-centered, collaborative effort, between geoscientists, cognitive scientists, and artificial intelligence researchers, to characterize spatial learning challenges in geoscience and to design sketch activities that use a sketch-understanding program, CogSketch. We (...) developed 26 CogSketch worksheets that use cognitive science–based principles to scaffold problem solving of spatially complex geoscience problems and report observations of an implementation in an introductory geoscience course where students used CogSketch or human-graded paper worksheets. Overall, this research highlights the principles of interdisciplinary design between cognitive scientists, geoscientists, and AI researchers that can inform the collaborative design process for others aiming to develop effective educational materials. (shrink)

Science, technology, engineering, and mathematics disciplines commonly illustrate 3D relationships in diagrams, yet these are often challenging for students. Failing to understand diagrams can hinder success in STEM because scientific practice requires understanding and creating diagrammatic representations. We explore a new approach to improving student understanding of diagrams that convey 3D relations that is based on students generating their own predictive diagrams. Participants’ comprehension of 3D spatial diagrams was measured in a pre- and post-design where students selected the correct 2D (...) slice through 3D geologic block diagrams. Generating sketches that predicated the internal structure of a model led to greater improvement in diagram understanding than visualizing the interior of the model without sketching, or sketching the model without attempting to predict unseen spatial relations. In addition, we found a positive correlation between sketched diagram accuracy and improvement on the diagram comprehension measure. Results suggest that generating a predictive diagram facilitates students’ abilities to make inferences about spatial relationships in diagrams. Implications for use of sketching in supporting STEM learning are discussed. (shrink)

Memory for spatial location is typically biased, with errors trending toward the center of a surrounding region. According to the category adjustment model, this bias reflects the optimal, Bayesian combination of fine-grained and categorical representations of a location. However, there is disagreement about whether categories are malleable. For instance, can categories be redefined based on expert-level conceptual knowledge? Furthermore, if expert knowledge is used, does it dominate other information sources, or is it used adaptively so as to minimize overall error, (...) as predicted by a Bayesian framework? We address these questions using images of geological interest. The participants were experts in structural geology, organic chemistry, or English literature. Our data indicate that expertise-based categories influence estimates of location memory—particularly when these categories better constrain errors than alternative categories. Results are discussed with respect to the CAM. (shrink)

Findings in dynamic unit formation suggest that completion processes reflect the optics of our world. Dynamic unit formation may depend on patterns of motion signals that are consistent with the causes of optical changes. In addition, dynamic completion conforms to a local curvature minimization constraint. Such relational aspects of vision are important to consider in linking perceptual experience and neural activity.