logo logo European Journal of Educational Research

EU-JER is is a, peer reviewed, online academic research journal.

Subscribe to

Receive Email Alerts

for special events, calls for papers, and professional development opportunities.

Subscribe

Publisher (HQ)

Eurasian Society of Educational Research
Eurasian Society of Educational Research
7321 Parkway Drive South, Hanover, MD 21076, USA
Eurasian Society of Educational Research
Headquarters
7321 Parkway Drive South, Hanover, MD 21076, USA
confirmatory factor analysis physics metacognition inventory psychometric evaluation rasch model scale adaptation

The Indonesian Version of the Physics Metacognition Inventory: Confirmatory Factor Analysis and Rasch Model

Moh. Irma Sukarelawan , Jumadi , Heru Kuswanto , M. Anas Thohir

Metacognition inventory supports increased awareness and self-control to improve student’s academic success, including physics. However, there a.

M

Metacognition inventory supports increased awareness and self-control to improve student’s academic success, including physics. However, there are limitations to revealing the Physics Metacognition Inventory (PMI), especially in Indonesia. This study aims to explore and evaluate the psychometric properties of PMI. This survey research has involved 479 students from three high schools in Indonesia. The psychometric properties of the I-PMI were evaluated using a Confirmatory Factor Analysis and Rasch Model approach. The results show that the Indonesian Physics Metacognition Inventory (I-PMI) is collected in 6 constructs from 26 items. The validity, reliability, and compatibility tests have also been analyzed with good results. The five rating scales used have adequate functionality. This research has also presented more comprehensive information about the Physics Metacognition Inventory in the context of Indonesian culture. This study has implications for using I-PMI to assess students’ metacognition at the high school level in Indonesia and recommendations for future research.

Keywords: Confirmatory factor analysis, Physics Metacognition Inventory, psychometric evaluation, Rasch model, scale adaptation.

cloud_download PDF
Cite
Article Metrics
Views
497
Download
463
Citations
Crossref
2

Scopus
1

References

Akben, N. (2020). Effects of the problem-posing approach on students’ problem solving skills and metacognitive awareness in science education. Research in Science Education, 50(3), 1143–1165. https://doi.org/10.1007/s11165-018-9726-7

Ali, M., Surif, J., Abdullah, A. H., Ibrahim, N. H., Talib, C. A., Shukor, N. A., Halim, N. D. A., Ali, D. F., & Suhairom, N. (2018). The pattern of physics problem solving between more successful and less successful from metacognitive perspective. Advanced Science Letters, 24(11), 8476–8479. https://doi.org/10.1166/asl.2018.12592

Asy’ari, M., Ikhsan, M., & Muhali. (2019). The effectiveness of inquiry learning model in improving prospective teachers’ metacognition knowledge and metacognition awareness. International Journal of Instruction, 12(2), 455–470. https://doi.org/10.29333/iji.2019.12229a

Bond, T., & Fox, C. M. (2015). Applying the rasch model: Fundamental measurement in the human sciences (3rd ed.). Routledge.

Boone, W. J., Staver, J. R., & Yale, M. S. (2014). Rasch analysis in the human sciences. Springer. https://doi.org/10.1007/978-94-007-6857-4

Byrne, B. M. (2013). Structural equation modeling with AMOS: Basic concepts, applications, and programming (2nd ed). Routledge. https://doi.org/10.4324/9781410600219

Çetin, B. (2017). Metacognition and self-regulated learning in predicting university students’ academic achievement in Turkey. Journal of Education and Training Studies, 5(4), 132–138. https://doi.org/10.11114/jets.v5i4.2233

Coşkun, Y. (2018). A study on metacognitive thinking skills of university students. Journal of Education and Training Studies, 6(3), 38–46. https://doi.org/10.11114/jets.v6i3.2931

Cubukcu, F. (2009). Metacognition in the classroom. Procedia - Social and Behavioral Sciences, 1(1), 559–563. https://doi.org/10.1016/j.sbspro.2009.01.101

Dafik, Sucianto, B., Irvan, M., & Rohim, M. A. (2019). The analysis of student metacognition skill in solving rainbow connection problem under the implementation of research-based learning model. International Journal of Instruction, 12(4), 593–610. https://doi.org/10.29333/iji.2019.12438a

Flavell, J. H. (1976). Metacognitive aspects of problem solving. In L. R. Resnick (Ed.), The Nature of Intelligence. Lawrence Erlbaum Associates.

González, A., Fernández, M.-V. C., & Paoloni, P.-V. (2017). Hope and anxiety in physics class: Exploring their motivational antecedents and influence on metacognition and performance. Journal of Research in Science Teaching, 54(5), 558–585. https://doi.org/10.1002/tea.21377

Graesser, A. C., Fiore, S. M., Greiff, S., Andrews-Todd, J., Foltz, P. W., & Hesse, F. W. (2018). Advancing the science of collaborative problem solving. Psychological Science in the Public Interest, 19(2), 59–92. https://doi.org/10.1177/1529100618808244

Habibi, H., Jumadi, J., & Mundilarto, M. (2019). The rasch-rating scale model to identify learning difficulties of physics students based on self-regulation skills. International Journal of Evaluation and Research in Education, 8(4), 659–665. https://doi.org/10.11591/ijere.v8i4.20292

Haeruddin, Prasetyo, Z. K., Supahar, Sesa, E., & Lembah, G. (2020). Psychometric and structural evaluation of the physics metacognition inventory instrument. European Journal of Educational Research, 9(1), 215–225. https://doi.org/10.12973/eu-jer.9.1.215

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014). Multivariate data analysis (7th ed). Pearson Education Limited.

Harrison, G. M., & Vallin, L. M. (2018). Evaluating the metacognitive awareness inventory using empirical factor-structure evidence. Metacognition and Learning, 13(1), 15–38. https://doi.org/10.1007/s11409-017-9176-z

Hikmah, F. N., Sukarelawan, M. I., Nurjannah, T., & Djumati, J. (2021). Elaboration of high school student’s metacognition awareness on heat and temperature material: Wright map in Rasch model. Indonesian Journal of Science and Mathematics Education, 4(2), 172–182. https://doi.org/10.24042/ijsme.v4i2.9488

Kallio, H., Virta, K., Kallio, M., Virta, A., Hjardemaal, F. R., & Sandven, J. (2017). The Utility of the metacognitive awareness inventory for teachers among in-service teachers. Journal of Education and Learning, 6(4), 78–91. https://doi.org/10.5539/jel.v6n4p78

Kim, B., Zyromski, B., Mariani, M., Lee, S. M., & Carey, J. C. (2017). Establishing the factor structure of the 18-item version of the junior metacognitive awareness inventory. Measurement and Evaluation in Counseling and Development, 50(1–2), 48–57. https://doi.org/10.1177/0748175616671366

Koyunlu Ünlü, Z., & Dökme, İ. (2019). Adaptation of physics metacognition inventory to Turkish. International Journal of Assessment Tools in Education, 6(1), 125–137. https://doi.org/10.21449/ijate.483104

Kyriazos, T. A. (2018). Applied psychometrics: Sample size and sample power considerations in factor analysis (EFA, CFA) and SEM in general. Psychology, 9(8), 2207–2230. https://doi.org/10.4236/psych.2018.98126

Lee, Y. M., Song, J.-E., Park, C., & Son, Y.-J. (2018). Psychometric evaluation of the korean version of Patient-Centered care scale for hospital nurses. Evaluation & the Health Professions, 42(3), 344–365. https://doi.org/10.1177/0163278718805244

Ling Lee, W., Chinna, K., & Sumintono, B. (2020). Psychometrics assessment of HeartQoL questionnaire: A rasch analysis. European Journal of Preventive Cardiology, 2047487320902322. https://doi.org/10.1177/2047487320902322

Livingston, J. A. (2003). Metacognition: An overview. ERIC. https://files.eric.ed.gov/fulltext/ED474273.pdf

Mahdavi, M. (2014). An overview: Metacognition in education. International Journal of Multidisciplinary and Current Research, 2(6), 529–535.

Mirzaei, F., Phang, F. A., Sulaiman, S., Kashefi, H., & Ismail, Z. (2012). Mastery goals, performance goals, students’ beliefs and academic success: Metacognition as a mediator. Procedia - Social and Behavioral Sciences, 46, 3603–3608. https://doi.org/10.1016/j.sbspro.2012.06.113

Myers, N. D., Wolfe, E. W., Feltz, D. L., & Penfield, R. D. (2006). Identifying differential item functioning of rating scale items with the rasch model: An introduction and an application. Measurement in Physical Education and Exercise Science, 10(4), 215–240. https://doi.org/10.1207/s15327841mpee1004_1

Ning, H. K. (2018). A rasch analysis of the junior metacognitive awareness inventory with singapore students. Measurement and Evaluation in Counseling and Development, 51(2), 84–91. https://doi.org/10.1080/07481756.2017.1358061

Panggayuh, V. (2017). Pengaruh kemampuan metakognitif terhadap prestasi akademik mahasiswa pada mata kuliah pemrograman dasar [The effect of metacognitive ability on student academic achievement in basic programming courses]. Scientific Journal of Informatics Research and Learning/Jurnal Ilmiah Penelitian dan Pembelajaran Informatika, 2(1), 20–25. https://doi.org/10.29100/jipi.v2i1.228

Papini, N., Kang, M., Ryu, S., Griese, E., Wingert, T., & Herrmann, S. (2020). Rasch calibration of the 25-item Connor-Davidson resilience scale. Journal of Health Psychology, 26(11), 1976–1987. https://doi.org/10.1177/1359105320904769

Pozo Muñoz, C., & Bretones Nieto, B. (2019). Spanish version of the flourishing scale (FS) on the parents of children with cancer: A validation through rasch analysis. Frontiers in Psychology, 10(35), 1–8. https://doi.org/10.3389/fpsyg.2019.00035

Rahmat, I., & Chanunan, S. (2018). Open inquiry in facilitating metacognitive skills on high school biology learning: An inquiry on low and high academic ability. International Journal of Instruction, 11(4), 593–606. https://doi.org/10.12973/iji.2018.11437a

Şahin, S. M., & Kendir, F. (2013). The effect of using metacognitive strategies for solving geometry problems on students’ achievement and attitude. Educational Research and Reviews, 8(19), 1777–1792. https://doi.org/10.5897/ERR2013.1578

Schraw, G., & Dennison, R. S. (1994). Assessing metacognitive awareness. Contemporary Educational Psychology, 19(4), 460–475. https://doi.org/10.1006/ceps.1994.1033

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

Sukarelawan, M. I., & Sriyanto, S. (2019). Mapping of profile students’ metacognitive awareness in yogyakarta, Indonesia. Journal of Research and Physics Education Research/ Jurnal Riset dan Kajian Pendidikan Fisika, 6(2), 56–62. https://doi.org/10.12928/jrkpf.v6i2.14556

Sukarelawan, M. I., Sulisworo, D., Jumadi, J., Kuswanto, H., & Rofiqah, S. A. (2021). Heat and temperature metacognition awareness inventory: A confirmatory factor analysis. International Journal of Evaluation and Research in Education, 10(2), 389–395. https://doi.org/10.11591/ijere.v10i2.20917

Sulaiman, T., Syrene, S., Kai, W., & Subramaniam, P. (2021). Primary science teachers’ perspectives about metacognition in science teaching. European Journal of Educational Research, 10(1), 75–84. https://doi.org/10.12973/eu-jer.10.1.75

Sumintono, B., & Widhiarso, W. (2014). Aplikasi model rasch untuk penelitian ilmu-ilmu sosial [Rasch model application for social sciences research]. Trim Komunikata Publishing House.

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/10.1080/09500693.2015.1104425

Taasoobshirazi, G., & Farley, J. (2013). Construct validation of the physics metacognition inventory. International Journal of Science Education, 35(3), 447–459. https://doi.org/10.1080/09500693.2012.750433

Tachie, S. A. (2019). Meta-cognitive skills and strategies application: How this helps learners in mathematics problem-solving. Eurasia Journal of Mathematics, Science and Technology Education, 15(5), 1–12. https://doi.org/10.29333/ejmste/105364

Uopasai, S., Bunterm, T., Muchimapura, S., & Tang, K. N. (2018). The effect of constructivism, metacognition and neurocognitive-based teaching model to enhance veterinary medicine students’ learning outcomes. Pertanika Journal of Social Sciences and Humanities, 26(4), 2313–2331.

Wijanto,  S. H. (2008). Struktural equation modelling dengan lisrel 8.8: Konsep dan tutorial [Structural equation modeling with LISREL 8.8: Concepts and tutorials]. Graha Ilmu.

Williams, B., Onsman, A., & Brown, T. (2012). A rasch and factor analysis of a paramedic graduate attribute scale. Evaluation and the Health Professions, 35(2), 148–168. https://doi.org/10.1177/0163278711407314

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

Zulherman, Zain, F. M., Napitupulu, D., Sailin, S. N., & Roza, L. (2021). Analyzing Indonesian students’ google classroom acceptance during COVID-19 outbreak: Applying an extended unified theory of acceptance and use of technology model. European Journal of Educational Research, 10(4), 1697–1710. https://doi.org/10.12973/eu-jer.7.3.555

...