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Journal of Chemical Learning Innovation

an Open Access Journal


Innovative Chemistry Learning: The Impact of the Jigsaw Cooperative Model on Students’ Understanding of Reaction Rate Concepts

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  • Purpose of the study: This study aims to determine the effect of the Jigsaw type cooperative learning model on students' chemistry learning outcomes on the concept of reaction rate by comparing it with the expository learning method at the high school level.

    Methodology: Quasi-experimental method, Only Posttest Control Group Design, purposive sampling technique, multiple-choice test instrument (22 questions), validity and reliability test using ANATES software, Liliefors normality test, Fisher homogeneity test, and t-test statistical analysis at a significance level of α = 0.05.

    Main Findings: The average value of the experimental group (70.15) was higher than the control group (57.87). The results of the statistical test showed that tcount = 4.47 was greater than ttable = 1.999, so there was a significant difference. The Jigsaw Model was proven to improve student learning outcomes on the concept of reaction rate.

    Novelty/Originality of this study: This research focuses on the application of the Jigsaw model to the under-researched concept of reaction rate. This study provides empirical evidence of its effectiveness in chemistry learning and enriches innovative learning strategies to enhance conceptual understanding and student engagement.

  • How to cite

    [1]
    M. D. Astuti, “Innovative Chemistry Learning: The Impact of the Jigsaw Cooperative Model on Students’ Understanding of Reaction Rate Concepts”, Jor. Chem. Lea. Inn, vol. 3, no. 1, pp. 92–99, Apr. 2026, doi: 10.37251/jocli.v3i1.3080.
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    1. N. M. Tri and L. N. Minh, “Factors affecting the role of education and training in human resource development of Vietnam,” Int. J. Health Sci. (Qassim)., vol. 6, no. S1, pp. 1–14, 2022, doi: 10.53730/ijhs.v6ns1.4742. DOI: https://doi.org/10.53730/ijhs.v6nS1.4742
    2. M. A. Haidar, M. Hasanah, and M. A. Ma’arif, “Educational challenges to human resource development in islamic education institutions,” Munaddhomah J. Manaj. Pendidik. Islam, vol. 3, no. 4, pp. 366–377, 2022, doi: 10.31538/munaddhomah.v3i4.309. DOI: https://doi.org/10.31538/munaddhomah.v3i4.309
    3. M. Saqr, W. Matcha, N. A. Uzir, J. Jovanović, D. Gašević, and S. López-Pernas, “Transferring effective learning strategies across learning contexts matters: A study in problem-based learning,” Australas. J. Educ. Technol., vol. 39, no. 3, pp. 35–57, 2023, doi: 10.14742/ajet.8303. DOI: https://doi.org/10.14742/ajet.8303
    4. Z. Ersozlu, S. Taheri, and I. Koch, “A review of machine learning methods used for educational data,” Educ. Inf. Technol., vol. 29, no. 16, pp. 22125–22145, 2024, doi: 10.1007/s10639-024-12704-0. DOI: https://doi.org/10.1007/s10639-024-12704-0
    5. C. Stroumpouli and G. Tsaparlis, “Chemistry students’ conceptual difficulties and problem solving behavior in chemical kinetics, as a component of an introductory physical chemistry course,” Chem. Teach. Int., vol. 4, no. 3, pp. 279–296, 2022, doi: 10.1515/cti-2022-0005. DOI: https://doi.org/10.1515/cti-2022-0005
    6. T. M. Clark, E. Anderson, N. M. Dickson-Karn, C. Soltanirad, and N. Tafini, “Comparing the performance of college chemistry students with chatGPT for calculations involving acids and bases,” J. Chem. Educ., vol. 100, no. 10, pp. 3934–3944, Oct. 2023, doi: 10.1021/acs.jchemed.3c00500. DOI: https://doi.org/10.1021/acs.jchemed.3c00500
    7. H. Goss, “Student learning outcomes assessment in higher education and in academic libraries: A review of the literature,” J. Acad. Librariansh., vol. 48, no. 2, p. 102485, Mar. 2022, doi: 10.1016/j.acalib.2021.102485. DOI: https://doi.org/10.1016/j.acalib.2021.102485
    8. M. Hooda, C. Rana, O. Dahiya, A. Rizwan, and M. S. Hossain, “Artificial intelligence for assessment and feedback to enhance student success in higher education,” Math. Probl. Eng., vol. 2022, pp. 1–19, May 2022, doi: 10.1155/2022/5215722. DOI: https://doi.org/10.1155/2022/5215722
    9. N. Martin-Alguacil, L. Avedillo, R. Mota-Blanco, and M. Gallego-Agundez, “Student-centered learning: Some issues and recommendations for its implementation in a traditional curriculum setting in health sciences,” Educ. Sci., vol. 14, no. 11, pp. 1–26, 2024, doi: 10.3390/educsci14111179. DOI: https://doi.org/10.3390/educsci14111179
    10. E. Balla, “Teacher centered method vs student centered method of teaching in teaching english: Critical study,” Interdiscip. J. Res. Dev., vol. 10, no. 3, pp. 60–65, 2023, doi: 10.56345/ijrdv10n309. DOI: https://doi.org/10.56345/ijrdv10n309
    11. A. Hussein, S. Dzaiy, and S. A. Abdullah, “The use of active learning strategies to foster effective teaching in higher education institutions,” Zanco J. Humanit. Sci., vol. 28, no. 4, pp. 328–351, 2024, doi: 10.21271/zjhs.28.4.18. DOI: https://doi.org/10.21271/zjhs.28.4.18
    12. S. Sutrisno and J. A. Nasucha, “Islamic religious education project-based learning model to improve student creativity,” At-tadzkir Islam. Educ. J., vol. 1, no. 1, pp. 13–22, 2022, doi: 10.59373/attadzkir.v1i1.3. DOI: https://doi.org/10.59373/attadzkir.v1i1.3
    13. N. Indrawati and A. Y. D. Desky, “How to improve elementary school student learning outcomes by implementing the articulation type cooperative learning model?,” J. Indones. Prim. Sch., vol. 1, no. 2, pp. 32–37, 2024, doi: 10.62945/jips.v1i2.96. DOI: https://doi.org/10.62945/jips.v1i2.96
    14. B. Öztürk, “The effect of cooperative learning models on learning outcomes: A second-order meta-analysis,” Educ. Policy Anal. Strateg. Res., vol. 18, no. 3, pp. 273–296, 2023, doi: 10.29329/epasr.2023.600.13. DOI: https://doi.org/10.29329/epasr.2023.600.13
    15. X. Yang, “A historical review of collaborative learning and cooperative learning,” TechTrends, vol. 67, no. 4, pp. 718–728, 2023, doi: 10.1007/s11528-022-00823-9. DOI: https://doi.org/10.1007/s11528-022-00823-9
    16. K. Karman, M. Maslani, R. Anwar, R. A. Yudhiantara, and D. Djubaedi, “Enhancing student learning outcomes in the qur’an interpretation course through the implementation of the Start from reading (SFR) cooperative learning model,” Nazhruna J. Pendidik. Islam, vol. 7, no. 1, pp. 156–170, 2024, doi: 10.31538/nzh.v7i1.4657. DOI: https://doi.org/10.31538/nzh.v7i1.4657
    17. Y. Yennita, A. Al Fatihah, Z. Zulirfan, and K. Osman, “The change in students’ communication and collaboration skills through time token cooperative learning model,” J. Pendidik. IPA Indones., vol. 13, no. 2, pp. 313–324, 2024, doi: 10.15294/n77t7q82. DOI: https://doi.org/10.15294/n77t7q82
    18. C. N. D. Putri, R. N. Sedyati, and M. Zulianto, “Students’ collaboration and communication skills with problem-based learning model,” J. Inov. dan Teknol. Pembelajaran, vol. 10, no. 3, pp. 225–233, 2025, doi: 10.17977/um031v10i32023p225. DOI: https://doi.org/10.17977/um031v10i32023p225
    19. M. Usman, I. N. S. Degeng, S. Utaya, and D. Kuswandi, “The influence of jigsaw learning model and discovery learning on learning discipline and learning outcomes,” Pegem Egit. ve Ogr. Derg., vol. 12, no. 2, pp. 166–178, 2022, doi: 10.47750/pegegog.12.02.17. DOI: https://doi.org/10.47750/pegegog.12.02.17
    20. H. Hamzah, K. Khairiah, S. Tambak, M. L. Hamzah, and A. A. Purwati, “Implementation of Jigsaw type cooperative learning method to increase student learning activity in Fiqh learning during COVID-19,” Int. J. Health Sci. (Qassim)., vol. 6, no. April, pp. 4438–4446, 2022, doi: 10.53730/ijhs.v6ns1.5914. DOI: https://doi.org/10.53730/ijhs.v6nS1.5914
    21. I. Sasson and I. Yehuda, “Redesigning the learning environment: Student motivation and personal responsibility for learning,” Curr. Psychol., vol. 42, no. 35, pp. 31251–31262, Dec. 2023, doi: 10.1007/s12144-022-04140-5. DOI: https://doi.org/10.1007/s12144-022-04140-5
    22. V. Bhardwaj, S. Zhang, Y. Q. Tan, and V. Pandey, “Redefining learning: Student-centered strategies for academic and personal growth,” Front. Educ., vol. 10, no. February, pp. 1–15, 2025, doi: 10.3389/feduc.2025.1518602. DOI: https://doi.org/10.3389/feduc.2025.1518602
    23. W. Wang, H. Lee, C. Lin, P. Li, Y. Huang, and T. Wu, “Enhancing students’ learning outcomes in self‐regulated virtual reality learning environment with learning aid mechanisms,” Br. J. Educ. Technol., vol. 56, no. 1, pp. 366–387, Jan. 2025, doi: 10.1111/bjet.13512. DOI: https://doi.org/10.1111/bjet.13512
    24. E. Hariyono, I. A. Rizki, D. A. Lestari, N. F. Citra, A. N. Islamiyah, and A. I. Agusty, “Engklek game ethnoscience-based learning material (egeblm) to improve students’ conceptual understanding and learning motivation,” J. Pendidik. IPA Indones., vol. 12, no. 4, pp. 635–647, 2023, doi: 10.15294/jpii.v12i4.43941. DOI: https://doi.org/10.15294/jpii.v12i4.43941
    25. M. R. Apsari, “Improving chemistry learning outcomes with jigsaw for biology education students,” IJCER (International J. Chem. Educ. Res., vol. 9, no. 1, pp. 22–30, 2025, doi: 10.20885/ijcer.vol9.iss1.art3. DOI: https://doi.org/10.20885/ijcer.vol9.iss1.art3
    26. S. Rahmawati, D. Poba, M. Magfirah, and K. Burase, “Application of cooperative learning jigsaw model to improve student’s learning achievement in chemistry learning,” J. Akad. Kim., vol. 11, no. 1, pp. 39–45, Feb. 2022, doi: 10.22487/j24775185.2022.v11.i1.pp39-45. DOI: https://doi.org/10.22487/j24775185.2022.v11.i1.pp39-45
    27. S. Gopinathan, A. H. Kaur, S. Veeraya, and M. Raman, “The role of digital collaboration in student engagement towards enhancing student participation during COVID-19,” Sustain., vol. 14, no. 11, pp. 1–23, 2022, doi: 10.3390/su14116844. DOI: https://doi.org/10.3390/su14116844
    28. A. Sølvberg and M. Rismark, “Student collaboration in student active learning,” Proc. Int. Conf. Futur. Teach. Educ., vol. 2, no. 1, pp. 74–81, 2023, doi: 10.33422/icfte.v2i1.73. DOI: https://doi.org/10.33422/icfte.v2i1.73
    29. V. Almaghfiroh, H. Wang, and L. F. Purposari, “Application of the jigsaw learning model to improve student learning outcomes in mathematics,” Int. J. Educ. Curric. Appl., vol. 7, no. 1, pp. 51–58, 2024, doi: 10.31764/ijeca.v7i1.22499. DOI: https://doi.org/10.31764/ijeca.v7i1.22499
    30. Y. Affandi, A. Darmuki, and A. Hariyadi, “The evaluation of jidi (jigsaw discovery) learning model in the course of qur’an tafsir,” Int. J. Instr., vol. 15, no. 1, pp. 799–820, 2022, doi: 10.29333/iji.2022.15146a. DOI: https://doi.org/10.29333/iji.2022.15146a
    31. J. Jamaluddin, R. R. Febyanti, and A. R. Alamsyah, “The effect of the jigsaw learning model on student learning outcomes at the agricultural vocational high school,” in Vocational Education International Conference, 2023, pp. 488–494. [Online]. Available: https://proceeding.unnes.ac.id/veic/article/view/2880#:~:text=After applying the jigsaw learning model%2C student learning,increase the effectiveness of the student learning process.
    32. J. S. O. Zajić and J. Maksimović, “Quasi-experimental research as an epistemological-methodological approach in education research,” Int. J. Cogn. Res. Sci. Eng. Educ., vol. 10, no. 3, pp. 177–183, 2022, doi: 10.23947/2334-8496-2022-10-3-177-183. DOI: https://doi.org/10.23947/2334-8496-2022-10-3-177-183
    33. H. A. Ismail et al., “Sustainable healthcare futures: how digital leadership stimulates nurses’ green creativity: a quasi-experimental study,” BMC Nurs., vol. 24, no. 1, pp. 1–11, 2025, doi: 10.1186/s12912-025-02906-3. DOI: https://doi.org/10.1186/s12912-025-02906-3
    34. A. Muthik, A. Muchyidin, and A. R. Persada, “The effectiveness of students’ ;earning motivation on learning outcomes using the reciprocal teaching learning model,” J. Gen. Educ. Humanit., vol. 1, no. 1, pp. 21–30, 2022, doi: 10.58421/gehu.v1i1.7. DOI: https://doi.org/10.58421/gehu.v1i1.7
    35. I. Fitrianto, S. ’Aimah, R. Hamid, and A. Mulalic, “The effectiveness of the learning strategy ‘think, talk, write’ and snowball for improving learning achievement in lessons insya’ at Islamic Boarding School Arisalah,” Int. J. Post Axial Futur. Teach. Learn., vol. 1, no. 1, pp. 13–22, 2023, doi: 10.59944/postaxial.v1i1.142. DOI: https://doi.org/10.59944/postaxial.v1i1.142
    36. F. Scârneci-Domnișoru, “From sample to population generalization in qualitative research,” Qual. Rep., vol. 29, no. 8, pp. 2362–2386, 2024, doi: 10.46743/2160-3715/2024.7039. DOI: https://doi.org/10.32388/48L76Q
    37. A. Zrineh, M. Al‐Usta, and A. Alwawi, “Sampling methods and sample size determination in clinical research: An educational review,” J. Gen. Fam. Med., vol. 27, no. 1, pp. 1–9, Jan. 2026, doi: 10.1002/jgf2.70096. DOI: https://doi.org/10.1002/jgf2.70096
    38. O. Tajik, J. Golzar, and S. Noor, “Purposive sampling,” Int. J. Educ. Lang. Stud., vol. 2, no. 2, pp. 1–9, 2024. DOI: https://doi.org/10.1186/s40862-024-00299-5
    39. K. M. Q. Magnone and E. J. Yezierski, “Beyond convenience: A case and method for purposive sampling in chemistry teacher professional development research,” J. Chem. Educ., vol. 101, no. 3, pp. 718–726, 2024, doi: 10.1021/acs.jchemed.3c00217. DOI: https://doi.org/10.1021/acs.jchemed.3c00217
    40. D. Lee and E. Palmer, “Prompt engineering in higher education: a systematic review to help inform curricula,” Int. J. Educ. Technol. High. Educ., vol. 22, no. 7, pp. 1–22, 2025, doi: 10.1186/s41239-025-00503-7. DOI: https://doi.org/10.1186/s41239-025-00503-7
    41. M. Jukiewicz, “The future of grading programming assignments in education: The role of ChatGPT in automating the assessment and feedback process,” Think. Ski. Creat., vol. 52, no. July 2023, pp. 1–9, 2024, doi: 10.1016/j.tsc.2024.101522. DOI: https://doi.org/10.1016/j.tsc.2024.101522
    42. F. Habibzadeh, “Data distribution: Normal or abnormal?,” J. Korean Med. Sci., vol. 39, no. 3, pp. 1–8, 2024, doi: 10.3346/jkms.2024.39.e35. DOI: https://doi.org/10.3346/jkms.2024.39.e35
    43. M. Fiandini, A. B. D. Nandiyanto, D. F. Al Husaeni, D. N. Al Husaeni, and M. Mushiban, “How to calculate statistics for significant difference test using spss: understanding students comprehension on the concept of steam engines as power plant,” Indones. J. Sci. Technol., vol. 9, no. 1, pp. 45–108, 2024, doi: 10.17509/ijost.v9i1.64035. DOI: https://doi.org/10.17509/ijost.v9i1.64035
    44. J. Kostanek, K. Karolczak, W. Kuliczkowski, and C. Watala, “Bootstrap method as a tool for analyzing data with atypical distributions deviating from parametric assumptions: Critique and effectiveness evaluation,” Data, vol. 9, no. 8, pp. 1–19, 2024, doi: 10.3390/data9080095. DOI: https://doi.org/10.3390/data9080095
    45. N. R. Mishra, “Constructivist approach to learning: An analysis of pedagogical models of social constructivist learning theory,” J. Res. Dev., vol. 6, no. 1, pp. 22–29, 2023, doi: 10.3126/jrdn.v6i01.55227. DOI: https://doi.org/10.3126/jrdn.v6i01.55227
    46. Y. A. Kebede, F. K. Zema, G. M. Geletu, and S. A. Zinabu, “Cooperative learning instructional approach and student’s biology achievement: A quasi-experimental evaluation of jigsaw cooperative learning model in secondary schools in gedeo zone, South Ethiopia,” SAGE Open, vol. 15, no. 1, pp. 1–13, 2025, doi: 10.1177/21582440251318883. DOI: https://doi.org/10.1177/21582440251318883
    47. A. Fatmawati, S. Zubaidah, S. Mahanal, and S. Sutopo, “Representation skills of students with different ability levels when learning using the lcmr model,” Pegem Egit. ve Ogr. Derg., vol. 13, no. 1, pp. 177–192, 2022, doi: 10.47750/pegegog.13.01.20. DOI: https://doi.org/10.47750/pegegog.13.01.20
    48. W. J. D. Nascimento Júnior, C. Morais, and G. Girotto Júnior, “Enhancing AI responses in chemistry: Integrating text generation, image creation, and image interpretation through different levels of prompts,” J. Chem. Educ., vol. 101, no. 9, pp. 3767–3779, Sep. 2024, doi: 10.1021/acs.jchemed.4c00230. DOI: https://doi.org/10.1021/acs.jchemed.4c00230
    49. R. A. Al-Kreimeen, “The effectiveness of the (jigsaw II) strategy in cooperative learning in developing thinking skills and cognitive assessment competencies among female students specializing in child education,” J. Educ. Soc. Res., vol. 14, no. 3, pp. 306–323, 2024, doi: 10.36941/jesr-2024-0075. DOI: https://doi.org/10.36941/jesr-2024-0075
    50. N. Idris, O. Talib, and F. Razali, “Strategies in mastering science process skills in science experiments: A systematic literature review,” J. Pendidik. IPA Indones., vol. 11, no. 1, pp. 155–170, 2022, doi: 10.15294/jpii.v11i1.32969. DOI: https://doi.org/10.15294/jpii.v11i1.32969
    51. A. Uzorka, O. Akiyode, and S. M. Isa, “Strategies for engaging students in sustainability initiatives and fostering a sense of ownership and responsibility towards sustainable development,” Discov. Sustain., vol. 5, no. 1, pp. 1–12, 2024, doi: 10.1007/s43621-024-00505-x. DOI: https://doi.org/10.1007/s43621-024-00505-x
    52. A. D. Untari, “Game based learning: Alternative 21st century innovative learning models in improving student learning activeness,” EDUEKSOS J. Pendidik. Sos. dan Ekon., vol. XI, no. 2, pp. 228–242, 2022, doi: 10.24235/edueksos. v11i2. 11919. DOI: https://doi.org/10.24235/edueksos.v11i2.11919