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Student perspectives of the spatial thinking components embedded in a topographic map activity using an augmented-reality sandbox

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posted on 14.09.2021, 20:40 by Elijah T. Johnson, Karen S. McNeal

Spatial thinking skills are crucial for success in any of the STEM (science, technology, engineering, and mathematics) domains, and they are malleable. One approach to support the development of student spatial skills is through the use of innovative technologies, like the augmented reality (AR) sandbox, that can also effectively teach geoscience content in the process. In this study, we aimed to create a student-informed spatial topographic map activity designed to emphasize mental rotation, spatial orientation, and spatial visualization skills using the AR sandbox that incorporated elements such as drawing topographic profiles and recognizing stream flow direction. Furthermore, this study explored the spatial reasoning beliefs and challenges of undergraduate students at a large-enrollment Southeastern US university. Both quantitative and qualitative measures were employed to better understand student performance on and challenges with the topographic map and spatial tasks. Overall, the students found spatial visualization tasks in the activity to be the most challenging, and they were least confident in their spatial visualization skills. However, they believed that their spatial visualization skills were most improved after completing the topographic map activity, and those activities were reported to be the most effective at getting them to think in spatial terms. These results highlight that multi-step mental manipulations required to perform spatial visualization tasks are of great interest to instructors when developing topographic map activities using the AR sandbox. With more investigation, the AR sandbox has the potential to aid in the development of students’ spatial visualization skills while simultaneously teaching geological content.

Supplemental data for this article is available online at https://doi.org/10.1080/10899995.2021.1969862


This material is based upon work supported by the National Science Foundation Graduate Research Fellowship Program under Grant No. DGE-1414475. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.