Implementation of Rasch Model for Mapping Students’ Metacognitive Awareness

M I Sukarelawan; J Jumadi; H Kuswanto; T Nurjannah; F N Hikmah; M F Ramadhan

doi:10.15294/jpfi.v17i2.27172

Implementation of Rasch Model for Mapping Students’ Metacognitive Awareness

M I Sukarelawan⁽¹⁾, J Jumadi⁽²⁾, H Kuswanto⁽³⁾, T Nurjannah⁽⁴⁾, F N Hikmah⁽⁵⁾, M F Ramadhan⁽⁶⁾,

DOI: https://doi.org/10.15294/jpfi.v17i2.27172

(1) Postgraduate Program of Physics Education, Universitas Ahmad Dahlan Postgraduate Program of Physics Education, Universitas Negeri Yogyakarta
(2) Postgraduate Program of Physics Education, Universitas Negeri Yogyakarta
(3) Postgraduate Program of Physics Education, Universitas Negeri Yogyakarta
(4) SMA Negeri 1 Bantarsari
(5) Department of Physics Education, Universitas Islam Negeri Antasari
(6) Department of Physics Education, Universitas Muhammadiyah Mataram

Abstract

This study aim is to map students’ metacognitive awareness in physics subjects. This research was conducted at SMAN 1 Bantarsari in 2020. A total of 112 respondents (male = 17% and female = 83%) from class XI and XII were selected using a combination of snowball techniques and convenience sampling. Students’ metacognitive physics awareness was administrated using the Physics Metacognition Inventory (PMI) and analyzed using the Rasch model. The PMI inventory consists of 26 items and uses a Likert scale of 5 ratings ranging from 1 (never) to 5 (always). Mapping students’ physics metacognitive awareness based on the Logit Value of Person. Metacognitive awareness is classified into four levels, namely: low, medium, high, and very high levels. The results showed that more than 80% of students had metacognitive awareness at moderate and high levels. Dominant female students have metacognitive awareness at a high level and male students at a moderate level. The students’ metacognitive awareness in class XI and XII were at very high and moderate levels, respectively. The 15-16 year age group was dominant at a moderate level and the 17-18 year age group at a high level.

Keywords

mapping metacognition; metacognitive awareness; rasch model

Full Text:

PDF

References

Abdellah, R. (2015). Metacognitive Awareness and its Relation to Academic Achievement and Teaching Performance of Pre-service Female Teachers in Ajman University in UAE. Procedia - Social and Behavioral Sciences, 174, 560–567. https://doi.org/10.1016/j.sbspro.2015.01.707.

Abdelrahman, R. M. (2020). Metacognitive awareness and academic motivation and their impact on academic achievement of Ajman University students. Heliyon, 6(9), e04192. https://doi.org/10.

/j.heliyon.2020.e04192.

Ahmed, N., Senam, & Wiyarsi, A. (2019). Comparison of Students’ Metacognitive Skills by Gender in Chemistry. Journal Pendidikan Sains, 7(2).

Alghamdi, A., Karpinski, A. C., Lepp, A., & Barkley, J. (2020). Online and face-to-face classroom multitasking and academic performance: Moderated mediation with self-efficacy for self-regulated learning and gender. Computers in Human Behavior, 102, 214–222. https://doi.org/10.

/j.chb.2019.08.018.

Alkadrie, R. P., Mirza, A., & Hamdani. (2015). Faktor-Faktor yang Mempengaruhi Level Metakognisi dalam Pemecahan Masalah Pertidaksamaan Kuadrat di SMA. Jurnal Pendidikan Dan Pembelajaran Khatulistiwa, 4(12), 1–13.

Bond, T. G., & Fox, C. M. (2015). Applying the Rasch Model: Fundamental Measurement in the Human Sciences (3rd ed.). Routledge.

Canbulat, M., Direkci, B., Çorapçıgil, A., Şimşek, E. E., Asma, B., Tezci, İ. H., Akbulut, S., & Şimşek, B. (2020). The psychometric properties of school belonging scale for primary school students: A validity and reliability study. Elementary Education Online, 19(3), 1422–1438. https://doi.org/10.17051

/ilkonline.2020.730754.

Craig, K., Hale, D., Grainger, C., & Stewart, M. E. (2020). Evaluating metacognitive self-reports: systematic reviews of the value of self-report in metacognitive research. Metacognition and Learning, 15(2), 155–213. https://doi.org/10.1007/

s11409-020-09222-y.

Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297–334. https://doi.org/10.1007/BF02310555.

Desoete, A., & De Craene, B. (2019). Metacognition and mathematics education: an overview. ZDM - Mathematics Education, 51(4), 565–575. https://doi.org/10.1007/s11858-019-01060-w.

Didino, D., Taran, E. A., Barysheva, G. A., & Casati, F. (2019). Psychometric evaluation of the Russian version of the flourishing scale in a sample of older adults living in Siberia. Health and Quality of Life Outcomes, 17(1), 34. https://doi.org/10.1186/s

-019-1100-6.

Eichmann, B., Goldhammer, F., Greiff, S., Pucite, L., & Naumann, J. (2019). The role of planning in complex problem solving. Computers & Education, 128(January), 1–12. https://doi.org/10.1016/j.comp

edu.2018.08.004.

Herlanti, Y. (2015). Kesadaran Metakognitif dan Pengetahuan Metakognitif Peserta Didik Sekolah Menengah Atas dalam Mempersiapkan Ketercapaian Standar Kelulusan pada Kurikulum 2013. Cakrawala Pendidikan, 34(3), 357–367.

Inder, R. (1996). Planning and Problem Solving. In Artificial Intelligence (pp. 23–53). Elsevier. https://doi.org/10.1016/B978-012161964-0/50004-2.

Jabrayilov, R., Emons, W. H. M., & Sijtsma, K. (2016). Comparison of Classical Test Theory and Item Response Theory in Individual Change Assessment. Applied Psychological Measurement, 40(8), 559–572. https://doi.org/10.1177/01466216

Liliana, C., & Lavinia, H. (2011). Gender Differences in Metacognitive Skills. A Study of the 8th Grade Pupils in Romania. Procedia - Social and Behavioral Sciences, 29, 396–401. https://doi.org/10.1016/j.sbspro.2011.11.255.

Magno, C. (2009). Demonstrating the Difference between Classical Test Theory and Item Response Theory Using Derived Test Data. The International Journal of Educational and Psychological Assessment, 1(1), 1–11.

Mariati, P. S., Betty, M. T., & Sehat, S. (2017). The Problem Solving Learning Model by Using Video Recording on Experiments of Kinematics and Dynamics to Improve The Students Cognition and Metacognition. Jurnal Pendidikan Fisika Indonesia, 13(1), 25–32. https://doi.org/10.15294/jpfi.v13i1.10154

Nunaki, J. H., Damopolii, I., Kandowangko, N. Y., & Nusantari, E. (2019). The effectiveness of inquiry-based learning to train the students’ metacognitive skills based on gender differences. International Journal of Instruction, 12(2), 505–516. https://doi.org/10.29333/iji.2019.12232a

Sarwer, G., & Govil, P. (2017). Metacognitive awareness as a predicting variable of achievement in english among secondary school students. Nternational Refereed Research Journal, 8(4), 58–66. https://doi.org/10.18843/rwjasc/v8i4/07

Schraw, G., & Moshman, D. (1995). Metacognitive theories. Educational Psychology Review, 7(4), 351–371. https://doi.org/10.1007/BF02212307

Setiawan, B., Panduwangi, M., & Sumintono, B. (2018). A Rasch analysis of the community’s preference for different attributes of Islamic banks in Indonesia. International Journal of Social Economics, 45(12), 1647–1662. https://doi.org/10.1108/IJSE-07-2017-0294

Sriyanto, & Sukarelawan, M. I. (2019). Mapping of Profile Students’ Metacognitive Awareness in Yogyakarta, Indonesia. Jurnal Riset Dan Kajian Pendidikan Fisika, 6(2), 56–62. https://doi.org/10.12928/jrkpf.v6i2.14556

Sumintono, B., & Widhiarso, W. (2014). Aplikasi Model Rasch untuk Penelitian Ilmu-ilmu Sosial. Trim Komunikata.

Taasoobshirazi, G., Bailey, M., & Farley, J. (2015). Physics Metacognition Inventory Part II: Confirmatory factor analysis and Rasch analysis. International Journal of Science Education, 37(17), 2769–2786. https://doi.org/10.1080/09500

2015.1104425.

Taasoobshirazi, G., & Farley, J. (2013). Construct Validation of the Physics Metacognition Inventory. International Journal of Science Education, 35(3), 447–459. https://doi.org/10.1080/09500693.2012.

Tan, O. S. (2004). Enhanching Thinking Problem Based Learning Approached. Thomson.

Thamraksa, C. (2005). Metacognition: A Key to Success for EFL Learners. http://www.bu.ac.th/knowledge-center/epaper/jan_june2005/chutima.pdf

Van Lieshout, E. M. M., Mahabier, K. C., Tuinebreijer, W. E., Verhofstad, M. H. J., Den Hartog, D., Bolhuis, H. W., Bos, P. K., Bronkhorst, M. W. G. A., Bruijninckx, M. M. M., De Haan, J., Deenik, A. R., Den Hoed, P. T., Eversdijk, M. G., Goslings, J. C., Haverlag, R., Heetveld, M. J., Kerver, A. J. H., Kolkman, K. A., Leenhouts, P. A., … Vollbrandt, J. (2020). Rasch analysis of the Disabilities of the Arm, Shoulder and Hand (DASH) instrument in patients with a humeral shaft fracture. Journal of Shoulder and Elbow Surgery, 29(5), 1040–1049. https://doi.org/10.1016/j.jse.2019.09.026

Wolters, C. A. (2003). Regulation of Motivation: Evaluating an Underemphasized Aspect of Self-Regulated Learning. Educational Psychologist, 38(4), 189–205. https://doi.org/10.1207/S1532698

EP3804_1

Zohar, A., & Barzilai, S. (2013). A review of research on metacognition in science education: current and future directions. Studies in Science Education, 49(2), 121–169. https://doi.org/10.1080/03057267

.2013.847261

Refbacks

There are currently no refbacks.

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