Development of a logarithmic module equipped with a jigsaw cooperative model

Authors

DOI:

https://doi.org/10.29408/jel.v9i2.17520

Keywords:

cooperative jigsaw model, developmental research, logarithmic module

Abstract

The teacher's task is to compile lesson plans, books, or modules assess and evaluate. However, the fact is that the low learning outcomes are due to the difficulty level of the book. The results of the 2022 study show that students' scores are below 75, which is 74.80. Urgency, there is a difference between teacher assignments, expectations, and learning outcomes. The research aims to design practical and effective modules. The research method used is Research and Development (R&D): Determination, Design, Development, Implementation, and Evaluation. The subject is high school, and the subject is 32 students. They are collecting data with assessment instruments from material experts, teachers, and students. Modules are measured by practicality through instruments, and tests measure effectiveness. Analysis technique with validation. Average values and interpretations. As a result, the logarithmic module is practical, effective, and can increase value. The validation of material experts and math teachers assessed 92.35% and 91.45% in the very good category. Student assessment of the module is 95.81%, a very good category. Post-test learning outcomes use the 90.28 module, and those that do not use the 68.40 module.

References

Albeshree, F., Al-Manasia, M., Lemckert, C., Liu, S., & Tran, D. (2022). Mathematics teaching pedagogies to tertiary engineering and information technology students: a literature review. International Journal of Mathematical Education in Science and Technology, 53(6), 1609–1628. https://doi.org/10.1080/0020739X.2020.1837399

Bilal, H. S. M., Amin, M. B., Hussain, J., Ali, S. I., Hussain, S., Sadiq, M., Razzaq, M. A., Abbas, A., Choi, C., & Lee, S. (2020). On computing critical factors based healthy behavior index for behavior assessment. International Journal of Medical Informatics, 141(March 2019), 1-13. https://doi.org/10.1016/j.ijmedinf.2020.104181

Codreanu, E., Sommerhoff, D., Huber, S., Ufer, S., & Seidel, T. (2020). Between authenticity and cognitive demand: Finding a balance in designing a video-based simulation in the context of mathematics teacher education. Teaching and Teacher Education, 95(October), 103146.1-12. https://doi.org/10.1016/j.tate.2020.103146

Dosta, M., Litster, J. D., & Heinrich, S. (2020). Flowsheet simulation of solids processes: Current status and future trends. Advanced Powder Technology, 31(3), 947–953. https://doi.org/10.1016/j.apt.2019.12.015

Hainora Hamzah, Mohd Isa Hamzah, & Hafizhah Zulkifli. (2022). Systematic Literature Review on the Elements of Metacognition-Based Higher Order Thinking Skills (HOTS) Teaching and Learning Modules. Sustainability (Switzerland), 14(2), 1-15. https://doi.org/https://doi.org/10.3390/su14020813

Halomoan, J. H. L. (2022). Difficulty of Mathematics teacher competence in applying curriculum online. Asian Journal of Educational Technology, 1(1), 44–54. https://doi.org/10.53402/ajet.v1i2.16

Haser, Ç., Doğan, O., & Kurt Erhan, G. (2022). Tracing students’ mathematics learning loss during school closures in teachers’ self-reported practices. International Journal of Educational Development, 88(no 1. November 2021), 1–2. https://doi.org/10.1016/j.ijedudev.2021.102536

Jebeile, J., & Crucifix, M. (2020). Multi-model ensembles in climate science: Mathematical structures and expert judgements. Studies in History and Philosophy of Science Part A, 83(June 2019), 44–52. https://doi.org/10.1016/j.shpsa.2020.03.001

Jerrim, J., Oliver, M., & Sims, S. (2022). Erratum: The relationship between inquiry-based teaching and students’ achievement. New evidence from a longitudinal PISA study in England (Learning and Instruction (2019) 61 (35–44), (S095947521830361X), (10.1016/j.learninstruc.2018.12.004)). Learning and Instruction, 80(March 2020), 101310.1-10. https://doi.org/10.1016/j.learninstruc.2020.101310

Liu, M., Gorgievski, M. J., Qi, J., & Paas, F. (2022). Increasing teaching effectiveness in entrepreneurship education: Course characteristics and student needs differences. Learning and Individual Differences, 96(August 2021), 102147.1-10. https://doi.org/10.1016/j.lindif.2022.102147

Lumbantoruan, J. H. (2022a). Further insight into Student Learning Outcomes of Derivative Materials: Numbered Head Together and Expository Learning Model. Utamax : Journal of Ultimate Research and Trends in Education, 4(2), 135–145. https://doi.org/10.31849/utamax.v4i2.9918

Lumbantoruan, J. H. (2022b). Mathematics Module Development Derivative Materials Christian University of Indonesia, Jakarta, Indonesia E-Mail: Abstract Introduction in Purwaningsih's Research, (2016) It Was Seen That There Was an Increase In Student Activity In Learning Assisted By Modul. Aksioma: Journal of the Mathematics Education Study Program 11(4), 2593–2609. https://doi.org/http://dx.doi.org/10.24127/ajpm.v11i4.5716

Mavrotas, G., & Makryvelios, E. (2021). Combining multiple criteria analysis, mathematical programming and Monte Carlo simulation to tackle uncertainty in Research and Development project portfolio selection: A case study from Greece. European Journal of Operational Research, 291(2), 794–806. https://doi.org/10.1016/j.ejor.2020.09.051

Mishra, L., Gupta, T., & Shree, A. (2020). Online teaching-learning in higher education during lockdown period of COVID-19 pandemic. International Journal of Educational Research Open, 1(August), 100012.1-8. https://doi.org/10.1016/j.ijedro.2020.100012

Moons, F., Vandervieren, E., & Colpaert, J. (2022). Atomic, reusable feedback: a semi-automated solution for assessing handwritten tasks? A crossover experiment with mathematics teachers. Computers and Education Open, 3(July 2021), 100086.1-17. https://doi.org/10.1016/j.caeo.2022.100086

Ndaïrou, F., Area, I., Nieto, J. J., & Torres, D. F. M. (2020). Mathematical modeling of COVID-19 transmission dynamics with a case study of Wuhan. Chaos, Solitons and Fractals, 135(June), 1-6. https://doi.org/10.1016/j.chaos.2020.109846

Pinheiro, H., Vignola-Gagné, E., & Campbell, D. (2021). A large-scale validation of the relationship between cross-disciplinary research and its uptake in policy-related documents, using the novel overton altmetrics database. Quantitative Science Studies, 2(2), 616–642. https://doi.org/10.1162/qss_a_00137

Rahman, T., & Lewis, S. E. (2020). Evaluating the evidence base for evidence-based instructional practices in chemistry through meta-analysis. Journal of Research in Science Teaching, 57(5), 765–793. https://doi.org/10.1002/tea.21610

Sanaat, A., Shooli, H., Ferdowsi, S., Shiri, I., Arabi, H., & Zaidi, H. (2021). DeepTOFSino: A deep learning model for synthesizing full-dose time-of-flight bin sinograms from their corresponding low-dose sinograms. NeuroImage, 245(July), 118697.1-9. https://doi.org/10.1016/j.neuroimage.2021.118697

Sihwail, R., Said Solaiman, O., & Zainol Ariffin, K. A. (2022). New robust hybrid Jarratt-Butterfly optimization algorithm for nonlinear models. Journal of King Saud University - Computer and Information Sciences, 34(10), 8207-8220.1-14. https://doi.org/10.1016/j.jksuci.2022.08.004

Staddon, R. V. (2022). A supported flipped learning model for mathematics gives safety nets for online and blended learning. Computers and Education Open, 3(1. December), 100106.1-11. https://doi.org/10.1016/j.caeo.2022.100106

Suherman, S., & Vidákovich, T. (2022). Assessment of mathematical creative thinking: A systematic review. Thinking Skills and Creativity, 44(2. June), 1-13. https://doi.org/10.1016/j.tsc.2022.101019

Sun, Z., Xie, K., & Anderman, L. H. (2018). The role of self-regulated learning in students’ success in flipped undergraduate math courses. Internet and Higher Education, 36(1), 41–53. https://doi.org/10.1016/j.iheduc.2017.09.003

Vogel, F., Kollar, I., Fischer, F., Reiss, K., & Ufer, S. (2022). Adaptable scaffolding of mathematical argumentation skills: The role of self-regulation when scaffolded with CSCL scripts and heuristic worked examples. International Journal of Computer-Supported Collaborative Learning, 17(1), 39–64. https://doi.org/10.1007/s11412-022-09363-z

Wijaya, T. T., Cao, Y., Weinhandl, R., & Tamur, M. (2022). A meta-analysis of the effects of E-books on students’ mathematics achievement. Heliyon, 8(6), e09432.1-9. https://doi.org/10.1016/j.heliyon.2022.e09432

Wildeman, E., Koopman, M., & Beijaard, D. (2022). Fostering subject teachers’ integrated language teaching in technical vocational education: Results of a professional development program. Teaching and Teacher Education, 112(4), 103626.1-14. https://doi.org/10.1016/j.tate.2021.103626

Downloads

Published

31-07-2023

How to Cite

Lumbantoruan, J. H., & Deliviana, E. (2023). Development of a logarithmic module equipped with a jigsaw cooperative model. Jurnal Elemen, 9(2), 616–629. https://doi.org/10.29408/jel.v9i2.17520

Issue

Section

Articles

Similar Articles

<< < 19 20 21 22 23 24 

You may also start an advanced similarity search for this article.