Validating metacognitive awareness inventory (MAI) in chemistry learning for senior high school: A rasch model analysis
DOI:
10.29303/jpm.v16i4.2603Published:
2021-09-04Downloads
Abstract
This study aims to validate metacognitive instruments, which include eight indicators of declarative knowledge, procedural knowledge, conditional knowledge, planning, information management, monitoring, debugging, and evaluation. The validation method uses Rasch modeling (Item Response Theory), namely Map analysis Wright (Person-item Map), Measure DIFF, Validity (Fit Statistics for The Draft Questionnaire), Reliability Cronbach Alpha (Summary statistics). Results map analysis wright shows the distribution of items and the power of discrimination are categorized as good with the logit value around 1.0. The curve Measure DIFF and the probability value indicate that the thing does not have an element of distinguishing gender characteristics if the probability value is above 0.05. The assessment instrument's validation showed an infit-outfit of 0.5 MNSQ 1.5, an infit-outfit value of 0.5 ZSTD 1.5, and a value of 0.4 PTMEA 0.85. Furthermore, the reliability of the instrument category is excellent, with a Cronbach alpha of 0.94. In conclusion, the MAI instrument in chemistry learning was feasible to measure the metacognitive abilities of high school students.Keywords:
validation Rasch model metacognitive awareness inventory (MAI)References
Hodson, D. (2014). Learning science, learning about science, doing science: Different goals demand different learning methods. International Journal of Science Education, 36(15), 2534-2553.
Astuti, A. P., Aziz, A., Sumarti, S. S., & Bharati, D. A. L. (2019, June). Preparing 21st century teachers: implementation of 4C characterââ¬â¢s pre-service teacher through teaching practice. In Journal of Physics: Conference Series (Vol. 1233, No. 1, p. 012109). IOP Publishing.
Mahanani, P. (2018, December). Analysis of Challenges and Needs of Generation Behavior in 21st Century. In International Conference on Education and Technology (ICET 2018) (pp. 146-149). Atlantis Press.
Oktapiani, N., & Hamdu, G. (2020). Desain Pembelajaran STEM berdasarkan Kemampuan 4C di Sekolah Dasar. Jurnal Ilmiah Pendidikan Dasar, 7(2), 99-108.
Danial, M. (2016). Kesadaran metakognitif, keterampilan metakognitif, dan penguasaan konsep kimia dasar. Jurnal Ilmu Pendidikan, 17(3).
Schraw, G., Olafson, L., Weibel, M., & Sewing, D. (2012). Metacognitive knowledge and field-based science learning in an outdoor environmental education program. In Metacognition in science education (pp. 57-77). Springer, Dordrecht.
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.
Asy'ari, M., Ikhsan, M., & Muhali, M. (2018). Validitas instrumen karakterisasi kemampuan metakognitif mahasiswa calon guru fisika. Prisma Sains: Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram, 6(1), 18-26.
Hadwin, A. F., Järvelä, S., & Miller, M. (2011). Self-regulated, co-regulated, and socially shared regulation of learning. Handbook of self-regulation of learning and performance, 30, 65-84.
Sitzmann, T., & Ely, K. (2011). A meta-analysis of self-regulated learning in work-related training and educational attainment: what we know and where we need to go. Psychological bulletin, 137(3), 421.
Anderson, T., & Kanuka, H. (1999). Using constructivism in technology-mediated learning: Constructing order out of the chaos in the literature.
Anggo, M. (2011). Pemecahan masalah matematika kontekstual untuk meningkatkan kemampuan metakognitif siswa. Edumatica: Jurnal Pendidikan Matematika.
Lestari, F., SARYANTONO, B., Syazali, M., Saregar, A., MADIYO, M., JAUHARIYAH, D., & Rofiqul, U. M. A. M. (2019). Cooperative Learning Application with the Method of" Network Tree Concept Map": Based on Japanese Learning System Approach. Journal for the Education of Gifted Young Scientists, 7(1), 15-32.
Sumintono, B. (2018, February). Rasch Model Measurements as Tools in Assesment for Learning. In 1st International Conference on Education Innovation (ICEI 2017) (pp. 38-42). Atlantis Press.
Pasquali, L., & Primi, R. (2003). Basic theory of Item Response Theory: IRT. Avaliação Psicológica, 2(2), 99-110.
Abdullah, R., & Soemantri, D. (2018). Validasi Metacognitive Awareness Inventory pada Pendidikan Dokter Tahap Akademik. Jurnal eJKI, 6(1), 15-23.
Sumintono, B., & Widhiarso, W. (2015). Aplikasi pemodelan rasch pada assessment pendidikan. Trim komunikata.
Sumintono, B. (2017). Rasch Model Measurement as Tools in Assessment for Learning.
Saefi, M., Fauzi, A., Kristiana, E., Adi, W. C., Muchson, M., Setiawan, M., ... & Ramadhani, M. (2020). Validating of Knowledge, Attitudes, and Practices Questionnaire for Prevention of COVID-19 Infections among Undergraduate Students: A RASCH and Factor Analysis. EURASIA Journal of Mathematics, Science and Technology Education, 16(12).
Vitasari, S. D. (2018). Assessment Instrument of Scientific Literacy Skills Based on Nature of Science For Middle School. Journal of Development Research, 2(2), 59-65.
Whitmore, M. L., & Schumacker, R. E. (1999). A comparison of logistic regression and analysis of variance differential item functioning detection methods. Educational and Psychological Measurement, 59(6), 910-927.
SE, CES-D. Item Calibration Logit Real, Infit MNSQ Infit ZSTD Outfit MNSQ, and Outfit ZSTD. "Evaluation of the CES-D in Six Countries Using Rasch Item Response Theory (IRT) Analysis." Education 11: 2-7.
Heo, M., Kim, N., & Faith, M. S. (2015). Statistical power as a function of Cronbach alpha of instrument questionnaire items. BMC medical research methodology, 15(1), 1-9.
License
The following terms apply to authors who publish in this journal:
1. Authors retain copyright and grant the journal first publication rights, with the work simultaneously licensed under a Creative Commons Attribution License 4.0 International License (CC-BY License) that allows others to share the work with an acknowledgment of the work's authorship and first publication in this journal.
2. Authors may enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., posting it to an institutional repository or publishing it in a book), acknowledging its initial publication in this journal.
3. Before and during the submission process, authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website), as this can lead to productive exchanges as well as earlier and greater citation of published work (See The Effect of Open Access).
Downloads
How to Cite
