ANALYSIS OF SCIENTIFIC HABITS OF MIND ENERGY ISSUES INVENTORY (SHOMEII) INSTRUMENT: RASCH MODEL
Abstract
ANALYSIS OF SCIENTIFIC HABITS OF MIND ENERGY ISSUES INVENTORY (SHOMEII) INSTRUMENT: RASCH MODEL
Abstract
Scientific Habits of Mind (SHOM) is a thinking characteristic that individuals have in solving problems and making decisions. SHOM can be accomplished in learning such as physics education through discussion, debate, and issue-based learning. However, the instrument for measuring SHOM in physics education is still immature. The purpose of this research is to develop and identify the quality of the SHOM instrument with energy problems analyzed using Model Rasch. This instrument is known as the Scientific Habits of Mind Energy Issue Inventory (SHOMEII). The development was carried out with the 3D+1I model (defining, designing, developing and implementing), involving 280 high school students with an average age of 17 years and came from West Java, Indonesia. The instruments used were a validation sheet and a SHOMEII consisting of 22 items with 4 answer choices based on the level of confidence. The results of the analysis show that SHOMEII has excellent reliability, good validity, and varying levels of difficulty. Therefore, SHOMEII can be implication as an instrument to measure students' SHOM abilities in physics education.
Abstrak
Scientific Habits of Mind (SHOM) merupakan karakteristik berpikir seperti ilmuwan dalam melakukan sesuatu, memecahkan masalah dan mengambil keputusan. SHOM dapat dilatihkan dengan diskusi, debat dan pembelajaran berbasis isu. Akan tetapi, instrumen untuk mengukur SHOM dalam pendidikan fisika kurang berkembang. Tujuan penelitian ini adalah untuk mengembangkan dan mengidentifikasi kualitas instrumen SHOM dengan isu energi yang dianalisis Model Rasch, dikenal dengan Scientific Habits of Mind Energy Issues Inventory (SHOMEII). Metode penelitian ini adalah pengembangan dengan model 3D+1I (defining, designing, developing dan implementing) yang melibatkan 280 peserta didik SMA berasal dari Jawa Barat, Indonesia. Instrumen yang digunakan adalah lembar validasi dan SHOMEII terdiri dari 22 item dengan 4 pilihan jawaban berdasarkan tingkat kepercayaan. Hasil analisis, SHOMEII memiliki reliabilitas yang sangat baik, validitas yang baik dan tingkat kesukaran yang beragam. Oleh karena itu, SHOMEII dapat diimplikasikan sebagai instrumen untuk kemampuan SHOM peserta didik pada pendidikan fisika.
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Adams, D., Sumintono, B., Mohamed, A., & Noor, N. S. M. (2018). E-learning readiness among students of diverse backgrounds in a leading Malaysian higher education institution. Malaysian Journal of Learning and Instruction.
Adimayuda, R., Aminudin, A. H., Kaniawati, I., Suhendi, E., & Samsudin, A. (2020). A multitier open-ended momentum and impulse (MOMI) instrument: Developing and assessing quality of conception of 11th grade sundanese students with rasch analysis. International Journal of Scientific and Technology Research.
Arsad, N., Kamal, N., Ayob, A., Sarbani, N., Tsuey, C. S., Misran, N., & Husain, H. (2013). Rasch model analysis on the effectiveness of early evaluation questions as a benchmark for new students ability. International Education Studies.
https://doi.org/10.5539/ies.v6n6p185
Boone, W. J. (2016). Rasch analysis for instrument development: Why,when,and how? CBE Life Sciences Education. https://doi.org/10.1187/cbe.16-04-0148
Çalik, M., & Coll, R. K. (2012). Investigating Socioscientific Issues via Scientific Habits of Mind: Development and validation of the Scientific Habits of Mind Survey. International Journal of Science Education. https://doi.org/10.1080/09500693.2012.685197
Çalik, M., & Karataş, F. Ö. (2019). Does a “Science, Technology and Social Change” course improve scientific habits of mind and attitudes towards socioscientific issues? Australian Journal of Teacher Education. https://doi.org/10.14221/ajte.2018v44n6.3
Clements, D. H., Sarama, J. H., & Liu, X. H. (2008). Development of a measure of early mathematics achievement using the Rasch model: The Research-Based Early Maths Assessment. Educational Psychology. https://doi.org/10.1080/01443410701777272
Coll, R. K., Taylor, N., & Lay, M. C. (2009). Scientists’ habits of mind as evidenced by the interaction between their science training and religious beliefs. International Journal of Science Education. https://doi.org/10.1080/09500690701762621
Costa, A. L., & Kallick, B. (2008). Learning and Leading with Habits of Mind : 16 Essential Characteristics for Success. In Association for Supervision and Curriculum Development.
Crick, B. (1998). Education for citizenship and the teaching of democracy in schools: Final report of the advisory group on citizenship. In Qualifications and Curriculum Authority, London.
DeMars, C. E. (2010). Item Theory Response. In Oxford University Press, Inc. (Vol. 66).
Ding, L. (2014). Seeking missing pieces in science concept assessments: Reevaluating the Brief Electricity and Magnetism Assessment through Rasch analysis. Physical Review Special Topics - Physics Education Research.
https://doi.org/10.1103/PhysRevSTPER.10.010105
Ding, L., Wei, X., & Mollohan, K. (2016). Does Higher Education Improve Student Scientific Reasoning Skills? International Journal of Science and Mathematics Education. https://doi.org/10.1007/s10763-014-9597-y
Fisher, W. P. (2007). Rating Scale Instrument Quality Criteria. Rasch Measurement Transactions.
Galili, I. (2019). Towards a Refined Depiction of Nature of Science. Science & Education. https://doi.org/10.1007/s11191-019-00042-4
Gauld, C. (1982). The scientific attitude and science education: A critical reappraisal. Science Education. https://doi.org/10.1002/sce.3730660113
Gauld, C. F. (2005). Habits of mind, scholarship and decision making in science and religion. Science and Education. https://doi.org/10.1007/s11191-004-1997-x
Ghulman, H. A., & Mas’odi, M. S. (2009). Modern measurement paradigm in engineering education: Easier to read and better analysis using rasch-based approach. 2009 International Conference on Engineering Education, ICEED2009 - Embracing New Challenges in Engineering Education. https://doi.org/10.1109/ICEED.2009.5490624
Griffin, P., McGaw, B., & Care, E. (2012). Assessment and teaching of 21st century skills. Spinger. https://doi.org/10.1007/978-94-007-2324-5
Hayat, M. S., Rustaman, N. Y., Rahmat, A., & Redjeki, S. (2019). Profile of life-long learning of prospective teacher in learning biology. Journal of Physics: Conference Series. https://doi.org/10.1088/1742-6596/1157/2/022083
Herrmann-Abell, C. F., & DeBoer, G. E. (2011). Using distractor-driven standards-based multiple-choice assessments and Rasch modeling to investigate hierarchies of chemistry misconceptions and detect structural problems with individual items. Chemistry Education Research and Practice. https://doi.org/10.1039/c1rp90023d
Hizqiyah, I. Ya. N., Nurhadi, M., Widodo, A., & Riandi, R. (2019). Developing Habits of Mind through Web Based Learning Approach. 253(Aes 2018), 312–316. https://download.atlantis-press.com/proceedings/aes-18/55917366
Hodson, D. (2006). Why we should prioritize learning about science. Canadian Journal of Science, Mathematics and Technology Education. https://doi.org/10.1080/14926150609556703
Idris, Tengku, Sriyati, Siti, Rahmat, A. (2014). Pengaruh Asesmen Portofolio Terhadap Habits of Mind Dan Penguasaan Konsep Biologi Siswa Kelas Xi. Jurnal Pendidikan Biologi Universitas Negeri Malang.
Kassim, N. L. A. (2011). Judging behaviour and rater errors: An application of the many-facet rasch model. GEMA Online Journal of Language Studies, 3, 179–197.
Linacre, J. M. (1994). Sample Size and Item Calibration or Person Measure Stability. Rasch Measurement Transactions.
Long, C., Wendt, H., & Dunne, T. (2011). Applying Rasch measurement in mathematics education research: Steps towards a triangulated investigation into proficiency in the multiplicative conceptual field. Educational Research and Evaluation. https://doi.org/10.1080/13803611.2011.632661
Marzano, R. J., Pickering, D., & McTighe, J. (1993). Assessing Student Outcomes: Performance Assessment Using the Dimensions of Learning Model. Association for Supervision and Curriculum Development. https://files.eric.ed.gov/fulltext/ED461665.pdf
Mešić, V., Neumann, K., Aviani, I., Hasović, E., Boone, W. J., Erceg, N., Grubelnik, V., Sušac, A., Glamočić, D. S., Karuza, M., Vidak, A., AlihodŽić, A., & Repnik, R. (2019). Measuring students’ conceptual understanding of wave optics: A Rasch modeling approach. Physical Review Physics Education Research. https://doi.org/10.1103/PhysRevPhysEducRes.15.010115
Nahadi, Firman, H., & Farina, J. (2015). Effect of feedback in formative assessment in the student learning activities on chemical course to the formation of habits of mind. Jurnal Pendidikan IPA Indonesia. https://doi.org/10.15294/jpii.v4i1.3499
Park, M., & Liu, X. (2019). An Investigation of Item Difficulties in Energy Aspects Across Biology, Chemistry, Environmental Science, and Physics. Research in Science Education. https://doi.org/10.1007/s11165-019-9819-y
Peter, J. P. (1981). Construct Validity: A Review of Basic Issues and Marketing Practices. Journal of Marketing Research. https://doi.org/10.2307/3150948
Planinic, M., Boone, W. J., Susac, A., & Ivanjek, L. (2019). Rasch analysis in physics education research: Why measurement matters. Physical Review Physics Education Research. https://doi.org/10.1103/PhysRevPhysEducRes.15.020111
Planinic, M., Ivanjek, L., & Susac, A. (2010). Rasch model based analysis of the Force Concept Inventory. Physical Review Special Topics - Physics Education Research. https://doi.org/10.1103/PhysRevSTPER.6.010103
Purwanto, M. G., Suhandi, A., Coştu, B., Samsudin, A., & Nurtanto, M. (2020). Static fluid concept inventory (SFCI): A gender gap analysis using rasch model to promote a diagnostic test instrument on students’ conception. International Journal of Advanced Science and Technology.
Rasch, G. (1960). Studies in mathematical psychology: I. Probabilistic models for some intelligence and attainment tests.
Rashid, R. A., & Abdullah, R. (2008). Application of Rasch-based ESPEGS Model in Measuring Generic Skills of Engineering Students : A New Paradigm. Advances in Engineering Education.
Reise, S. P., Ainsworth, A. T., & Haviland, M. G. (2005). Item response theory: Fundamentals, applications, and promise in psychological research. Current Directions in Psychological Science. https://doi.org/10.1111/j.0963-7214.2005.00342.x
Romine, W. L., & Sadler, T. D. (2016). Measuring Changes in Interest in Science and Technology at the College Level in Response to Two Instructional Interventions. Research in Science Education. https://doi.org/10.1007/s11165-014-9452-8
Sadler, T. D. (2004). Informal reasoning regarding socioscientific issues: A critical review of research. In Journal of Research in Science Teaching. https://doi.org/10.1002/tea.20009
Saidfudin, M., Azrilah, A. A., Rodzo’An, N. A., Omar, M. Z., Zaharim, A., & Basri, H. (2010). Easier learning outcomes analysis using rasch model in engineering education research. International Conference on Engineering Education and International Conference on Education and Educational Technologies - Proceedings.
Samsudin, A., Fratiwi, N. J., Ramalis, T. R., Aminudin, A. H., Costu, B., & Nurtanto, M. (2020). Using rasch analysis to develop multi-representation of tier instrument on newton’s law (motion). International Journal of Psychosocial Rehabilitation. https://doi.org/10.37200/IJPR/V24I6/PR260865
Sapnas, K. G., & Zeller, R. A. (2002). Minimizing sample size when using exploratory factor analysis for measurement. Journal of Nursing Measurement. https://doi.org/10.1891/jnum.10.2.135.52552
Sriyati, M. S., Rustaman, N. Y., & Zainul, M. A. (2010). KONTRIBUSI ASESMEN FORMATIF TERHADAP HABITS OF MIND MAHASISWA BIOLOGI. Jurnal Pengajaran Matematika Dan Ilmu Pengetahuan Alam. https://doi.org/10.18269/jpmipa.v15i2.283
Steinkuehler, C., & Duncan, S. (2008). Scientific habits of mind in virtual worlds. Journal of Science Education and Technology. https://doi.org/10.1007/s10956-008-9120-8
Sumintono, B. (2017). Perceptions on Influence Tactics among Leaders in the Ministry of Education Malaysia : An Application of The Many Facets Rasch Model. International Conference On Public Policy, Social Computing And Development (ICOPOSDEV).
Sumintono, B., & Widhiarso, W. (2015a). Aplikasi Pemodelan Rasch pada Asesmen Pendidikan. Konferensi Guru Dan Dosen Nasional (KGDN) 2015.
Sumintono, B., & Widhiarso, W. (2015b). Aplikasi Permodelan Rasch Pada Assessment Pendidikan. In Aplikasi Permodelan Rasch Pada Assesment Pendidikan (Issue September).
Sumintono, B., & Widhiarso, W. (2015c). Aplikasi Permodelan Rasch Pada Assessment Pendidikan. In Aplikasi Permodelan Rasch Pada Assesment Pendidikan. Penerbit Trim Komunikata.
Summers, R., Wang, S., Abd-El-Khalick, F., & Said, Z. (2019). Comparing Likert Scale Functionality Across Culturally and Linguistically Diverse Groups in Science Education Research: an Illustration Using Qatari Students’ Responses to an Attitude Toward Science Survey. International Journal of Science and Mathematics Education. https://doi.org/10.1007/s10763-018-9889-8
Susac, A., Planinic, M., Klemencic, D., & Milin Sipus, Z. (2018). Using the Rasch model to analyze the test of understanding of vectors. Physical Review Physics Education Research. https://doi.org/10.1103/PhysRevPhysEducRes.14.023101
Susilowati, E., Hartini, S., Suyidno, Mayasari, T., & Winarno, N. (2018). Profile Habits of Mind Students in Physics Learning. Journal of Physics: Conference Series. https://doi.org/10.1088/1742-6596/1120/1/012055
Taasoobshirazi, G., Bailey, M. L., & Farley, J. (2015). Physics Metacognition Inventory Part II: Confirmatory factor analysis and Rasch analysis. International Journal of Science Education. https://doi.org/10.1080/09500693.2015.1104425
Tesio, L. (2003). Measuring behaviours and perceptions: Rasch analysis as a tool for rehabilitation research. Journal of Rehabilitation Medicine. https://doi.org/10.1080/16501970310010448
Ursachi, G., Horodnic, I. A., & Zait, A. (2015). How Reliable are Measurement Scales? External Factors with Indirect Influence on Reliability Estimators. Procedia Economics and Finance. https://doi.org/10.1016/s2212-5671(15)00123-9
Van Zile-Tamsen, C. (2017). Using Rasch Analysis to Inform Rating Scale Development. Research in Higher Education. https://doi.org/10.1007/s11162-017-9448-0
Wiyarsi, A., & Çalik, M. (2019). Revisiting the scientific habits of mind scale for socio-scientific issues in the Indonesian context. International Journal of Science Education. https://doi.org/10.1080/09500693.2019.1683912
Zeidler, D. L., Sadler, T. D., Simmons, M. L., & Howes, E. V. (2005). Beyond STS: A research-based framework for socioscientific issues education. In Science Education. https://doi.org/10.1002/sce.20048
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