Article Sidebar

Download
PDF
Statistic
Read Counter : 54 Download : 34

Downloads

Download data is not yet available.

Main Article Content

Abstract

This research was motivated by the low ability of students to apply mathematical solution methods to thermodynamic functions. Thermodynamic functions are functions that consist of pressure, temperature, volume and enthalpy functions where changes in one function can occur due to changes in other functions. The aim of this research was to show the implementation of chain rules in thermodynamic function problems by relying on a process technique to improve students' cognitive awareness of thermodynamic functions. The place of this research was at the TD Pardede Institute of Science and Technology. The process of understanding chain rules is very impactful for understanding thermodynamic state functions. Differential decomposition of functions within functions is also described in the chain rule method. Thermodynamic functions which consist of pressure, temperature, volume and enthalpy functions can depend on each other so that the chain rule analysis method can be clearly used. With this method students will also be given the opportunity to connect one concept with other thermodynamic concepts. Apart from that, this method can be used anywhere. This shows a cognitive increase in terms of cognitive elements, cognitive structure and cognitive function.

Keywords

Cognitive Improvement Thermodynamic Functions Chain Rule

Article Details

License

Copyright (c) 2024 Sumihar Simangunsong

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

The journal allows the author(s) to hold the copyright without restrictions.


Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

How to Cite
Simangunsong, S. (2024). Cognitive Improvement in Thermodynamic Functions With Calculus Chain Rule. PENDIPA Journal of Science Education, 8(1), 50–56. https://doi.org/10.33369/pendipa.8.1.50-56
Download Citation
Endnote/Zotero/Mendeley (RIS)
BibTeX

References

  1. Anisa, A., Medriati, R., & Putri, D. H. (2019). Pengaruh Model Quantum Learning Terhadap Pemahaman Konsep Dan Hasil Belajar Siswa Kelas X. Jurnal Kumparan Fisika, 2(3), 201–208. https://doi.org/10.33369/jkf.2.3.201-208
  2. Antera, S. (2021). Professional Competence of Vocational Teachers: a Conceptual Review. Vocations and Learning, 14(3), 459–479. https://doi.org/10.1007/s12186-021-09271-7.
  3. Bawa, R. K., & Kanpur-india, I. I. T. (2006). Value Problems. 23(2), 0–3.
  4. Brookes, D. T., & Etkina, E. (2015). The Importance of Language in Students’ Reasoning AboutHeat in Thermodynamic Processes. International Journal of Science Education
  5. Chen, H. (2006). A power series expansion and its applications. International Journal of Mathematical Education in Science and Technology, 37(3), 362–368. https://doi.org/10.1080/00207390500433384.
  6. Chen, P., Villa, U., & Ghattas, O. (2019). Taylor approximation and variance reduction for PDE-constrained optimal control under uncertainty. Journal of Computational Physics, 385, 163–186. https://doi.org/10.1016/j.jcp.2019.01.047.
  7. Christensen, W. M., Meltzer, D. E., & Ogilvie, C. S. (2009). Student ideas regarding entropy and the second law of thermodynamics in an introductory physics course, Am. J. Phys. 77, 907.
  8. Clark John Craig. (1997). Microsoft Visual Basic 4.0 Developer's Workshop, Dinastindo, Jakarta.
  9. Cleopatra, Maria.(2015)“Pengaruh Gaya Hidup Dan Motivasi Belajar Terhadap Prestasi Belajara Matematika.” Formatif Jurnal Ilmiah Pendidikan MIPA 5, no. 2
  10. Cochran, M. J., & Heron, P. R. L. (2006). Development and assessment of research-based tutorials on heat engines and the second law of thermodynamics, Am. J. Phys. 74, 734.
  11. Georgiou, H., & Sharma, M.D. (2012) University students’ understanding of thermal physics in everyday contexts. International Journal of Science and Mathematics Education, 10, 1119-1142. https://doi.org/10.1007/s10763-011-9320-1
  12. Goudsmit, S. A. (1929). Quantum mechanics. Journal of the Franklin Institute, 207(4), 523–524. https://doi.org/10.1016/S0016-0032(29)91835-4
  13. Mazzolani, A., Macdonald, C. M., & Munro, P. R. T. (2022). Application of a Taylor series approximation to the Debye–Wolf integral in time-domain numerical electromagnetic simulations. Journal of the Optical Society of America A, 39(5), 927. https://doi.org/10.1364/josaa.448797
  14. Novák, L., & Novák, D. (2020). On taylor series expansion for statistical moments of functions of correlated random variables. Symmetry, 12(8). https://doi.org/10.3390/SYM12081379
  15. Rostikawati, D. A., & Saefullah, A. (2022). Analysis of the needs basic physics teaching materials in industrial engineering major. Gravity: Jurnal Ilmiah Penelitian Dan Pembelajaran Fisika, 8(1), 34–40. https://doi.org/10.30870/gravity.v8i1.14865
  16. Satek, V., Veigend, P., & Necasova, G. (2019). Taylor series based integration in electric circuits simulations. Advances in Electrical and Electronic Engineering, 17(3), 352–359. https://doi.org/10.15598/aeee.v17i3.3369
  17. Simangunsong, S. (2022). Student ’ s professional competence development using the blended learning. 08(02), 70–77. https://doi.org/10.30870/gravity.v8i2.15932.
  18. Simangunsong, S., & Trisna, I. (2021). Analisa Kognitif Model Blended Learning Dengan Pendekatan Kalkulus Dasar. Jurnal Pendidikan Fisika Dan Teknologi, 7(1), 11–16. https://doi.org/10.29303/jpft.v7i1.2580.
  19. Skoumios, M., & Xatzinikita, B. (2000). Student models of heat, temperature, and thermal effects. Physics Review, 31, 58-71.
  20. Sokrat, H., Tamani, S., Moutaabbid, M., & Radid, M. (2014). Difficulties of Students from the Faculty of Science with Regard to Understanding the Concepts of Chemical Thermodynamics. Procedia - Social and Behavioral Sciences, 116, 368–372. https://doi.org/10.1016/j.sbspro.2014.01.223
  21. Syukri, M., Putri, E. S., Halim, L., Kuala, U. S., & Mekah, U. S. (2023). Analysis of Solving Physics Problems Using The Minnesota Model for Mechanics Concepts. 8(3), 296–303.
  22. Wattanakasiwich, P., Taleab, P., Sharma, M. D., & Johnston, I. D. (2013). Development and Implementation of a Conceptual Survey in Thermodynamics. International Journal of Innovation in Science and Mathematics Education, 21(1), 29–53.