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Evaluating learning of motion graphs with a LiDAR-based smartphone application
written by Colleen Megowan-Romanowicz, Daniel J. O’Brien, Rebecca E. Vieyra, Chrystian Vieyra Cortés, and Mina C. Johnson-Glenberg
Data modeling and graphing skill sets are foundational to science learning and careers, yet students regularly struggle to master these basic competencies. Further, although educational researchers have uncovered numerous approaches to support sense-making with mathematical models of motion, teachers sometimes struggle to enact them due to a variety of reasons, including limited time and materials for lab-based teaching opportunities and a lack of awareness of student learning difficulties. In this paper, we introduce a free smartphone application that uses LiDAR data to support motion-based physics learning with an emphasis on graphing and mathematical modeling. We tested the embodied technology, called LiDAR Motion, with 106 students in a non-major, undergraduate physics classroom at a mid-sized, private university on the U.S. East Coast. In identical learning assessments issued both before and after the study, students working with LiDAR Motion improved their scores by a more significant margin than those using standard issue sonic rangers. Further, per a voluntary survey, students who used both technologies expressed a preference for LiDAR Motion. This mobile application holds potential for improving student learning in the classroom, at home, and in alternative learning environments.
Physics Education Research Conference 2023
Part of the PER Conference series
Sacramento, CA: July 19-20, 2023
Pages 224-229
Subjects Levels Resource Types
Education - Applied Research
- Curriculum Development
= Laboratory
- Instructional Material Design
= Activity
- Technology
Education - Basic Research
- Assessment
= Conceptual Assessment
- Lower Undergraduate
- Reference Material
= Research study
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Format:
application/pdf
Mirror:
https://doi.org/10.1119/perc.2023…
Access Rights:
Free access
License:
This material is released under a Creative Commons Attribution 4.0 license. Further distribution of this work must maintain attribution to the published article's author(s), title, proceedings citation, and DOI.
Rights Holder:
American Association of Physics Teachers
DOI:
10.1119/perc.2023.pr.Megowan-Romanowicz
NSF Number:
2114586
Keyword:
PERC 2023
Record Creator:
Metadata instance created September 20, 2023 by Lyle Barbato
Record Updated:
October 8, 2023 by Lyle Barbato
Last Update
when Cataloged:
October 15, 2023
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Record Link
AIP Format
C. Megowan-Romanowicz, D. O’Brien, R. Vieyra, C. Vieyra Cortés, and M. Johnson-Glenberg, , presented at the Physics Education Research Conference 2023, Sacramento, CA, 2023, WWW Document, (https://www.compadre.org/Repository/document/ServeFile.cfm?ID=16587&DocID=5767).
AJP/PRST-PER
C. Megowan-Romanowicz, D. O’Brien, R. Vieyra, C. Vieyra Cortés, and M. Johnson-Glenberg, Evaluating learning of motion graphs with a LiDAR-based smartphone application, presented at the Physics Education Research Conference 2023, Sacramento, CA, 2023, <https://www.compadre.org/Repository/document/ServeFile.cfm?ID=16587&DocID=5767>.
APA Format
Megowan-Romanowicz, C., O’Brien, D., Vieyra, R., Vieyra Cortés, C., & Johnson-Glenberg, M. (2023, July 19-20). Evaluating learning of motion graphs with a LiDAR-based smartphone application. Paper presented at Physics Education Research Conference 2023, Sacramento, CA. Retrieved June 16, 2025, from https://www.compadre.org/Repository/document/ServeFile.cfm?ID=16587&DocID=5767
Chicago Format
Megowan-Romanowicz, C, D. O’Brien, R. Vieyra, C. Vieyra Cortés, and M. Johnson-Glenberg. "Evaluating learning of motion graphs with a LiDAR-based smartphone application." Paper presented at the Physics Education Research Conference 2023, Sacramento, CA, July 19-20, 2023. https://www.compadre.org/Repository/document/ServeFile.cfm?ID=16587&DocID=5767 (accessed 16 June 2025).
MLA Format
Megowan-Romanowicz, Colleen, Daniel J. O’Brien, Rebecca E. Vieyra, Chrystian Vieyra Cortés, and Mina C. Johnson-Glenberg. "Evaluating learning of motion graphs with a LiDAR-based smartphone application." Physics Education Research Conference 2023. Sacramento, CA: 2023. 224-229 of PER Conference. 16 June 2025 <https://www.compadre.org/Repository/document/ServeFile.cfm?ID=16587&DocID=5767>.
BibTeX Export Format
@inproceedings{ Author = "Colleen Megowan-Romanowicz and Daniel J. O’Brien and Rebecca E. Vieyra and Chrystian Vieyra Cortés and Mina C. Johnson-Glenberg", Title = {Evaluating learning of motion graphs with a LiDAR-based smartphone application}, BookTitle = {Physics Education Research Conference 2023}, Pages = {224-229}, Address = {Sacramento, CA}, Series = {PER Conference}, Month = {July 19-20}, Year = {2023} }
Refer Export Format

%A Colleen Megowan-Romanowicz %A Daniel J. O'Brien %A Rebecca E. Vieyra %A Chrystian Vieyra Cortés %A Mina C. Johnson-Glenberg %T Evaluating learning of motion graphs with a LiDAR-based smartphone application %S PER Conference %D July 19-20 2023 %P 224-229 %C Sacramento, CA %U https://www.compadre.org/Repository/document/ServeFile.cfm?ID=16587&DocID=5767 %O Physics Education Research Conference 2023 %O July 19-20 %O application/pdf

EndNote Export Format

%0 Conference Proceedings %A Megowan-Romanowicz, Colleen %A O'Brien, Daniel J. %A Vieyra, Rebecca E. %A Vieyra Cortés, Chrystian %A Johnson-Glenberg, Mina C. %D July 19-20 2023 %T Evaluating learning of motion graphs with a LiDAR-based smartphone application %B Physics Education Research Conference 2023 %C Sacramento, CA %P 224-229 %S PER Conference %8 July 19-20 %U https://www.compadre.org/Repository/document/ServeFile.cfm?ID=16587&DocID=5767


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