Local Instructional Theory Topik Dua Tipe Kesalahan dalam Pengujian Hipotesis
Abstract
Two types of errors are one of the important topics in hypothesis testing. Studying the two types of errors is not only studying how the procedure determines the probability of making an error, but it is very important to study the theoretical concepts of the two types of errors. To achieve this goal, a learning design is needed that can facilitate students to construct their own concepts of the two types of errors. The learning design developed is local instructional theory resulting from the cyclic process of hypothetical learning trajectory. The type of research used is design research using the model developed by Gravemeijer and Cobb. The test subjects used in this study were students of the Ma thematics Education Study Program, FMIPA UNP who took the Elementary Statistics Course in the July – December 2019 semester. This research resulted in a very practical local instructional theory used to facilitate students in carrying out horizontal and vertical mathematization processes, so that students are able to construct their own concepts of two types of errors in hypothesis testing.
Downloads
References
Bohamonde, D.C, Joan, J.M.F. & Aymemi. (2017). Mathematical modelling and the learning trajectory: tools to support the teaching of linear algebra. International Journal of Mathematical Education in Science and Tchnology, 48(3). doi: 10. 1080/0020739X.2016.1241436
Batanero, C. (2000). Controversies around the Role of Statistical Tests in Experimental Research. Mathematical Thinking and Learning, 2 (1-2): 75–98. doi: 10.1207/ S15327833MTL0202_4.
Bluman, A. G. (2012). Elementary Statistics: A step by step approach. 8th eds. New York: McGraw Hill.
Brase, C. & Brase, C. (2012). Understanding Basic Statistics. 7th eds. Cengage Learn ing: Australia.
Castro, S. A. E., Vanhoof, S., Noortgate, W. V. den, & Onghena, P. (2007). Students’ misconceptions of statistical inference: A review of the empirical evidence from research on statistics education. Edu cational Research Review, 2(2), 98 – 113. doi: 10.1016/j.edurev.2007.04.001.
Confrey, J., Gianopulos, G., McGowan, W., Shah, M., & Belcher, M. (2017). Sca ffolding learner-centered curricular cohe rence using learning maps and diag nostic assessments designed around mathematics learning trajectories. ZDM Mathematics Education, 49(5), 717-734. doi:10.1007/ s11858-017-0869-1
Daro, P., Mosher, Frederic, A., & Corcoran, T. B. (2011). Learning Trajectories In Mathematics: A Foundation for Standar, Curriculum, Assesment, and Instruction. From 10.12698/cpre.2011.rr68
Fauzan, A., Yerizon, Tasman, F., Yolanda, R. N. (2020). Pengembangan Local Instruc tional Theory Pada Topik Pembagian dengan Pendekatan Matematika Realis tik. Jurnal Eksakta Pendidikan, 4 (1): 1- 9. doi: 10.24036/jep/vol4-iss1/417
Gravemeijer, K. (2004). Local instruction theo ries as a means of support for teachers in reform mathematics education. Mathe matical Thinking and Learning, 6(2), 105–128. doi: 10.1207/s1532833mtl06 02_3
Gravemeijer, K., & Cobb, P. (2013). Design research from the learning design perspective. In Plomp T., & N.
Nieveen (Eds.), Educational Design research. Part A: An introduction (pp. 72-113). Enschede: Netherlands: SLO.
Gravemeijer, K. (2014). Design research on local instruction theories in mathematics education. Development of Mathematics teaching: Design, Scale, Effects. Pro ceedings of MADIF 9 (The Ninth Swe dish Mathematics Education Research Seminar Umeå).
Jacob, B. L. (2013). The Development of Introductory Statistics Students' Infor mal Inferential Reasoning and Its Rela tionship to Formal Inferential Reason ing. Teaching and Leadership – Disserta tions. 245.
Jhonson, A. C. & Drougas, A. M. (2004). Illustrating type i dan type ii errors via spreadsheet simulation in the business statistics course. Decission Sciences Jor nal of Innovative Education, 2 (1): 89-95. doi: 10.1111/j.0011.2004.00024.x
Larson, C.A., Wawro, M. & Zandieh, M. (2017). A hypothetical learning trajec tory for conceptualizing matrices as li near transformations. International Jour nal of Mathematical Education in Scien ce and Technology. doi: 10.1080/ 0020739X. 2016.1276225.
Lemsan, S. C., & House, L. (2012). Improving Mr. Miyagi's Coaching Style: Teaching Data Analytics with Interactive Data Visualizations, CHANCE, 25(2): 4-12. doi:10.1080/09332480.2012.685362.
Muliyardi. (2006). Pengembangan Model Pem belajaran Matematika dengan Menggu nakan Komik di Kelas I Sekolah Dasar. Disertasi. Surabaya: Pascasarjana Uni versitas Surabaya.
Peraturan Presiden Republik Indonesia Nomor 8 Tahun 2012, tentang Kerangka Kualifi kasi Nasional Indonesia. Jakarta: Lem baran Negara Republik Indonesia Tahun 2012 Nomor 24.
Simon, M. (1995). Reconstructing mathematics pedagogy from a constructivist perspec tive. Journal for Research in Mathe matics Education, 26(2), 114-145. doi: 10.2307/749205.
Syafriandi. (2020). Pengembangan local in structional theory berbasis realistic ma thematics education untuk topik pengu jian hipo tesis. Disertasi. Pascasarjana Universitas Negeri Padang.
Syafriandi, S. Fauzan, A., Lufri, L., Armiati, A. (2020). Designing hypothetical learn ing trajectory for learning the impor tance of hypothesis testing. Journal of Physics: Conference Series 1554 (2020) 012045. IOP Publishing. doi:10.1088/ 1742-6596/1554/1/012045.
Sztajn, P., Confrey, J., Wilson, P. H., & Edging ton, C. (2012). Learning trajectory based instruction toward a theory of teaching. Educational Researcher, 41(5), 147-156. doi: 10.3102/0013189x12442801.
Triola, Mario F. (2012). Elementary Statistics Technology, 11th eds. New York: Addison -Wesley.
Van den Heuvel-Panhuizen, M., & Drijvers, P. (2020). Realistic mathematics education. S. Lerman (ed.), Encyclopedia of Mathe matics Education. Doi: 10.1007/978-94-007-4978-8.
Copyright (c) 2021 Syafriandi Syafriandi, Ahmad Fauzan, Lufri Lufri, Armiati Armiati
This work is licensed under a Creative Commons Attribution 4.0 International License.
This work is licensed under a Creative Commons Attribution 4.0 International License.
_(2579-860X).png)
_(2614-1221)1.png)
