Skip to main content
SpringerLink
Log in

Unpacking Students’ Modeling Practices During a Modeling-Based STEM Curriculum on Highway Route Selection: Comparing Between High- and Low-Spatial Ability Students

  • Published:
International Journal of Science and Mathematics Education Aims and scope Submit manuscript

Abstract

The intersection of modeling and STEM practices offers a promising avenue for creating an integrated STEM curriculum. However, research on designing modeling-based STEM (m-STEM) curricula is limited, particularly concerning how the curriculum affects the learning of students with different spatial abilities. This study developed a four-round modeling cycle using highway route selection as the topic to support the development of modeling practices for learners with diverse spatial abilities. Using a mixed-method research approach, this study collected and analyzed the modeling practices of 24 Taiwanese upper elementary school students with different spatial abilities by modeling practice worksheets. Further analysis of the modeling practices was conducted on students in the top third and bottom third of spatial abilities. Qualitative data, including interviews, classroom observations, and teacher reflections, were also analyzed to identify the curriculum factors influencing learning in students with different spatial abilities. Results revealed that all students increased their modeling practices from level 1 (single factor) to level 3 (relation) as the model complexity increased, indicating the effectiveness of the m-STEM curriculum. Additionally, the curriculum improved the equity of spatial ability in modeling practices. Low-spatial ability students benefited from hands-on practices and digital tools during the modeling selection phase. In contrast, high-spatial ability students benefited from analogies and experimental thinking during the model construction phase. This study highlights the potential for m-STEM curricula to promote learning equity and provides insights into effective and inclusive design practices for STEM educators.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Data Availability

The data collected during this study are available upon request. For inquiries regarding data access, please contact Jing-Wen Lin at jwlin@mail.ntue.edu.tw. We prioritize the maintenance of participant confidentiality and adhere to ethical and privacy regulations when granting data access.

References

  • Baharin, N., Kamarudin, N., & Manaf, U. K. A. (2018). Integrating STEM education approach in enhancing higher order thinking skills. International Journal of Academic Research in Business and Social Sciences, 8(7), 810–822. https://doi.org/10.6007/IJARBSS/v8-i7/4421

    Article  Google Scholar 

  • Biggs, J. B., & Tang, C. (2007). Teaching for quality learning at university (3rd ed.). McGraw Hill Education & Open University Press.

  • Birchall, D. (2015). Spatial ability in radiologists: A necessary prerequisite? British Journal of Radiology, 88(1049), 20140511. https://doi.org/10.1259/bjr.20140511

    Article  Google Scholar 

  • Buckley, J., Seery, N., & Canty, D. (2018). A heuristic framework of spatial ability: A review and synthesis of spatial factor literature to support its translation into STEM education. Educational Psychology Review, 30, 947–972. https://doi.org/10.1007/s10648-018-9432-z

    Article  Google Scholar 

  • Chang, C. K., & Chiu, M. H. (2009). The development and application of modeling ability analytic index-Take electrochemistry as an example. Chinese Journal of Science Education, 17(4), 319–342.

    Google Scholar 

  • English, L. D. (2009). Promoting interdisciplinarity through mathematical modelling. ZDM Mathematics Education, 41, 161–181. https://doi.org/10.1007/s11858-008-0106-z

    Article  Google Scholar 

  • Epler-Ruths, C. M., McDonald, S., Pallant, A., & Lee, H. S. (2020). Focus on the notice: Evidence of spatial skills’ effect on middle school learning from a computer simulation. Cognitive Research: Principles and Implications, 5, Article 61. https://doi.org/10.1186/s41235-020-00263-0

    Article  Google Scholar 

  • Halloun, I. (1996). Schematic modeling for meaningful learning of physics. Journal of Research in Science Teaching, 33(9), 1019–1041.

    Article  Google Scholar 

  • Hallström, J., & Schönborn, K. J. (2019). Models and modelling for authentic STEM education: Reinforcing the argument. International Journal of STEM Education, 6, Article 22. https://doi.org/10.1186/s40594-019-0178-z

    Article  Google Scholar 

  • Hempel, C. G. (1952). Fundamentals of concept formation in empirical science. University of Chicago Press.

    Google Scholar 

  • Hockett, J. A. (2009). Curriculum for highly able learners that conforms to general education and gifted education quality indicators. Journal for the Education of the Gifted, 32(3), 394–440. https://doi.org/10.4219/jeg-2009-857

    Article  Google Scholar 

  • Hjalmarson, M. A., Holincheck, N., Baker, C. K., & Galanti, T. M. (2020). Learning models and modeling across the STEM disciplines. In C. C. Johnson, M. J. Mohr-Schroeder, T. J. Moore, & L. D. English (Eds.), Handbook of research on STEM education (pp. 223–233). Routledge.

    Chapter  Google Scholar 

  • Hsu, Y. T. (2013). An across-grade study of validating the conceptual evolution tree in earth and its relationship with spatial ability [Master’s thesis]. The University of Taipei. Retrieved 3 March 2022 from http://lib.utaipei.edu.tw/webpac/bookDetail.do?id=283318

  • Huang, T. C., & Lin, C. Y. (2017). From 3D modeling to 3D printing: Development of a differentiated spatial ability teaching model. Telematics and Informatics, 34(2), 604–613. https://doi.org/10.1016/j.tele.2016.10.005

    Article  Google Scholar 

  • Huk, T. (2006). Who benefits from learning with 3D models? The case of spatial ability. Journal of Computer Assisted Learning, 22(6), 392–404. https://doi.org/10.1111/j.1365-2729.2006.00180.x

    Article  Google Scholar 

  • Jackson, C., Mohr-Schroeder, M. J., Bush, S. B., Maiorca, C., Roberts, T., Yost, C., & Fowler, A. (2021). Equity-oriented conceptual framework for K-12 STEM literacy. International Journal of STEM Education, 8(1), 1–16. https://doi.org/10.1186/s40594-021-00294-z

    Article  Google Scholar 

  • Jiang, H., Qin, S., Fu, J., Zhang, J., & Ding, G. (2021). How to model and implement connections between physical and virtual models for digital twin application. Journal of Manufacturing Systems, 58, 36–51. https://doi.org/10.1016/j.jmsy.2020.05.012

    Article  Google Scholar 

  • Li, X., & Wang, W. (2021). Exploring spatial cognitive process among STEM students and its role in STEM education. Science & Education, 30, 121–145. https://doi.org/10.1007/s11191-020-00167-x

    Article  Google Scholar 

  • Lin, J. W. & Yu, R. C. (2022). Examining modelling ability before educational reforms: Findings of cross-country comparisons of grade 8 data from TIMSS 2011. Asia Pacific Journal of Education, 42(4), 744–759. https://doi.org/10.1080/02188791.2020.1798740

  • Lin, J. W., Cheng, T. S., & Linn, G. (2023). The impacts of modelling-based SSI teaching module on preservice teachers’ decision making – A case of Dongfeng Highway route selection. International Journal of Science Education, 45(1), 65–85. https://doi.org/10.1080/09500693.2022.2151329

  • MacFarlane, B. (2016). Infrastructure of comprehensive STEM programming for advanced learners. In B. MacFarlane (Ed.), STEM education for high-ability learners designing and implementing programming (pp. 139–160). Routledge.

    Google Scholar 

  • Ministry of Education Taiwan. (2018a). Curriculum guidelines of 12-year basic education for elementary school, junior high and general senior high schools―the domain of natural sciences.

  • Ministry of Education Taiwan. (2018b). Curriculum guidelines of 12-year basic education for elementary school, junior high and general senior high schools―the domain of social studies.

  • Motulsky, H. J. (2007). Prism 5 statistics guide. GraphPad Software.

    Google Scholar 

  • National Research Council. (2012). A framework for K–12 science education: Practices, crosscutting concepts, and core ideas. National Academies Press.

    Google Scholar 

  • National Science Board. (2007). A national action plan for addressing the critical needs of the U.S. science, technology, engineering, and mathematics education system. National Science Foundation.

  • New Jersey Department of Transportation. (2015). Roadway design manual. Author.

  • Pan, K. L. (2019). Engineering geology. Wu-nan.

  • Pellegrino, J. W., & Kail, R. (1982). Process analyses of spatial aptitude. In R. J. Sternberg (Ed.), Advances in the psychology of human intelligence (pp. 311–366). Erlbaum.

    Google Scholar 

  • Rich, K., & Brendefur, J. L. (2019). The importance of spatial reasoning in early childhood mathematics. In D. Farland-Smith (Ed.), Early childhood education (pp. 113–132). IntechOpen. https://doi.org/10.5772/intechopen.81564

    Chapter  Google Scholar 

  • Richland, L. E., & Simms, N. (2015). Analogy, higher order thinking, and education. Wiley Interdisciplinary Reviews: Cognitive Science, 6(2), 177–192. https://doi.org/10.1002/wcs.1336

    Article  Google Scholar 

  • Šafhalter, A., Vukman, K. B., & Glodež, S. (2015). The effect of 3D-modeling training on students’ spatial reasoning relative to gender and grade. Journal of Educational Computing Research, 54(3), 395–406. https://doi.org/10.1177/0735633115620430

    Article  Google Scholar 

  • Schwarz, C. V., & Gwekwerere, Y. (2007). Using a guided inquiry and modeling instructional framework (EIMA) to support pre-service K-8 science teaching. Science Education, 91(1), 158–186. https://doi.org/10.1002/sce.20177

    Article  Google Scholar 

  • Schwarz, C. V., Ke, L., Salgado, M., & Manz, E. (2022). Beyond assessing knowledge about models and modeling: Moving toward expansive, meaningful, and equitable modeling practice. Journal of Research in Science Teaching, 59(6), 1086–1096. https://doi.org/10.1002/tea.21770

    Article  Google Scholar 

  • Uttal, D. H., Meadow, N. G., Tipton, E., Hand, L. L., Alden, A. R., Warren, C., & Newcombe, N. S. (2013). The malleability of spatial skills: A meta-analysis of training studies. Psychological Bulletin, 139(2), 352–402. https://doi.org/10.1037/a0028446

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Science Education, National Taipei University of Education, Taipei, Taiwan

    Jing-Wen Lin

  2. Keelung Municipal Du Nan Elementary School, Keelung, Taiwan

    Yi-Min Chen

Authors
  1. Jing-Wen Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yi-Min Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jing-Wen Lin.

Ethics declarations

Ethics Approval and Consent to Participate

This study was reviewed and granted by the Anonymity Institution. The review concluded that this study did not require submission to further review by the Human Ethics Committee. All participants were grades 5 and 6 students and gave written informed consent to participate, and their parents and received study results as feedback. All personally identifiable data were anonymized during data collection and publication.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lin, JW., Chen, YM. Unpacking Students’ Modeling Practices During a Modeling-Based STEM Curriculum on Highway Route Selection: Comparing Between High- and Low-Spatial Ability Students. Int J of Sci and Math Educ 21 (Suppl 1), 67–86 (2023). https://doi.org/10.1007/s10763-023-10384-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10763-023-10384-9

Keywords

Search

Navigation