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Integrating infrared technologies in science learning: An evidence-based reasoning perspective

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Abstract

Infrared (IR) technologies have been universally acknowledged as a valuable pedagogical tool for exploring novel and abstract scientific subjects in science education. This study explores the roles of IR images played in middle school students’ Evidence-based Reasoning (EBR) process in support of the understanding of the heat radiation process. Specifically, we implement image processing algorithms explicitly for the visual artifacts mentioned in students’ descriptions of the radiation phenomenon to obtain the numeric representations of their corresponding features. Meanwhile, the quality of those descriptions is further coded with the guidance of the EBR framework for indicating students’ understanding levels of the phenomenon. Finally, the associations between the numerical image features and the quality of descriptions are analyzed to examine the effectiveness of the IR visual artifacts in helping students understand the heat radiation process. The analytical results found that the image features are further positively correlated with the quality of the descriptions generated by students for the heat radiation. The results further suggest the IR images have the potential of driving students to think proactively and explore detailed procedural changes in learning the heat radiation process. Finally, our study calls for the integration of interdisciplinary instructional approaches in science education to reduce students’ cognitive load and guide learning attention, for example, incorporating visualization and relevant processing approaches to present and analyze the otherwise invisible abstract process to help students make sense related knowledge more easily.

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Data Availability

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

References

  • Abdelrahman, Y., Velloso, E., Dingler, T., Schmidt, A., & Vetere, F. (2017). Cognitive Heat: Exploring the Usage of Thermal Imaging to Unobtrusively Estimate Cognitive Load. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 1(3), 1–20. https://doi.org/10.1145/3130898

    Article  Google Scholar 

  • Bohrmann-Linde, C., & Kleefeld, S. (2019). Can you see the heat? – using a thermal imaging camera in the chemistry classroom. World Journal of Chemical Education, 7(2), 179–184. https://doi.org/10.12691/wjce-7-2-18

  • Brown, N. J. S., Furtak, E. M., Timms, M., Nagashima, S. O., & Wilson, M. (2010). The Evidence-Based Reasoning Framework: Assessing Scientific Reasoning. Educational Assessment, 15(3–4), 123–141. https://doi.org/10.1080/10627197.2010.530551

    Article  Google Scholar 

  • Ebadi, S., Ashtarian, S., & Zamani, G. (2020). Exploring arguments presented in predatory journals using toulmin’s model of argumentation. Journal of Academic Ethics. https://doi.org/10.1007/s10805-019-09346-0

    Article  Google Scholar 

  • Evagorou, M., Erduran, S., & Mäntylä, T. (2015). The role of visual representations in scientific practices: from conceptual understanding and knowledge generation to ‘seeing’ how science works. International Journal of STEM Education, 2(1), 1–13. https://doi.org/10.1186/s40594-015-0024-x

  • Fiaidhi, J. (2014). The next step for learning analytics. IT Professional, 16(5), 4–8. https://doi.org/10.1109/MITP.2014.78

    Article  Google Scholar 

  • Furtak, E. M., Hardy, I., Beinbrech, C., Shavelson, R. J., & Shemwell, J. T. (2010). A Framework for Analyzing Evidence-Based Reasoning in Science Classroom Discourse. Educational Assessment, 15(3–4), 175–196. https://doi.org/10.1080/10627197.2010.530553

    Article  Google Scholar 

  • Giri, V., & Paily, M. U. (2020). Effect of scientific argumentation on the development of critical thinking. Science & Education. https://doi.org/10.1007/s11191-020-00120-y

    Article  Google Scholar 

  • Gooding, D. C. (2006). From phenomenology to field theory: Faraday’s visual reasoning. Perspectives on Science, 14(1), 40–65. https://doi.org/10.1162/posc.2006.14.1.40

    Article  Google Scholar 

  • Haglund, J., Jeppsson, F., Hedberg, D., & Schönborn, K. J. (2015a). Thermal cameras in school laboratory activities. Physics Education, 50(4), 424–430. https://doi.org/10.1088/0031-9120/50/4/424

    Article  Google Scholar 

  • Haglund, J., Jeppsson, F., Hedberg, D., & Schönborn, K. J. (2015b). Students’ framing of laboratory exercises using infrared cameras. Physical Review Special Topics - Physics Education Research, 11(2), 020127. https://doi.org/10.1103/PhysRevSTPER.11.020127

    Article  Google Scholar 

  • Haglund, J., Jeppsson, F., & Schönborn, K. J. (2016). Taking on the heat—a narrative account of how infrared cameras invite instant inquiry. Research in Science Education, 46(5), 685–713. https://doi.org/10.1007/s11165-015-9476-8

    Article  Google Scholar 

  • Kácovský, P. (2018). Thermal Imaging Experiments as an Inspiration for Problem-based Learning. The Physics Teacher, 56(9), 596–599. https://doi.org/10.1119/1.5080571

    Article  Google Scholar 

  • Liew, C. W., & Treagust D. F. (1998). The effectiveness of predictobserve-explain tasks in diagnosing students’ understanding of science and in identifying their levels of achievement. Paper presented at the annual meeting of the American Educational Research Association, San Diego, USA.

  • Melander, E., Haglund, J., Weiszflog, M., & Andersson, S. (2016). More than Meets the Eye – Infrared Cameras in Open-Ended University Thermodynamics Labs. The Physics Teacher, 54(9), 528–531. https://doi.org/10.1119/1.4967889

    Article  Google Scholar 

  • Osborne, J., Erduran, S., & Simon, S. (2004). Enhancing the quality of argumentation in school science. Journal of Research in Science Teaching, 41(10), 994–1020. https://doi.org/10.1002/tea.20035

    Article  Google Scholar 

  • Pei, B., Zhao, H., Xing, W., & Lee, H. S. (2019a). The exploration of automated image processing techniques in the study of scientific argumentation. In Cognitive computing in technology-enhanced learning (pp. 175–190). IGI Global.

  • Pei, B., Xing, W., & Lee, H. S. (2019b). Using automatic image processing to analyze visual artifacts created by students in scientific argumentation. British Journal of Educational Technology, 50(6), 3391–3404. https://doi.org/10.1111/bjet.12741

    Article  Google Scholar 

  • Probosari, R., Widyastuti, F., Sajidan, P., Suranto, M., & Prayitno, B. (2017, October 7). Tracing the development of student’s argumentation in science classroom: knowledge acquisition and motivation. Proceedings of the International Conference on Teacher Training and Education 2017 (ICTTE 2017). International Conference on Teacher Training and Education 2017 (ICTTE 2017), Paris, France. https://doi.org/10.2991/ictte-17.2017.68.

  • Vollmer, M., & Möllmann, K.-P. (2017). Teaching physics and understanding infrared thermal imaging. In Education and training in optics and photonics (p. 104522C). Optical Society of America.

  • Wade, S., & Kidd, C. (2019). The role of prior knowledge and curiosity in learning. Psychonomic Bulletin & Review, 26(4), 1377–1387. https://doi.org/10.3758/s13423-019-01598-6

    Article  Google Scholar 

  • Xie, C., & Hazzard, E. (2011). Infrared Imaging for Inquiry-Based Learning. The Physics Teacher, 49, 368–372. https://doi.org/10.1119/1.3628268

    Article  Google Scholar 

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Correspondence to Wanli Xing.

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Pei, B., Xing, W., Zhu, G. et al. Integrating infrared technologies in science learning: An evidence-based reasoning perspective. Educ Inf Technol 28, 8423–8443 (2023). https://doi.org/10.1007/s10639-022-11538-y

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