The Development of Instrument of Emotional Climate and Attitude Measurement on Science Learning Environment

Authors

Hasna Rashifah , Yuli Rahmawati , Riyadi

DOI:

10.29303/jppipa.v9i11.5029

Published:

2023-11-25

Issue:

Vol. 9 No. 11 (2023): November

Keywords:

Attitude, Emotional climate, Learning environment, Science

Research Articles

Downloads

How to Cite

Rashifah, H., Rahmawati, Y., & Riyadi. (2023). The Development of Instrument of Emotional Climate and Attitude Measurement on Science Learning Environment . Jurnal Penelitian Pendidikan IPA, 9(11), 9313–9323. https://doi.org/10.29303/jppipa.v9i11.5029
Crossref
Scopus
Google Scholar
Europe PMC

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

Abstract

The purpose of this research is to enrich the discussion of the component of developing instrument as a realization of student reflection on their learning environment, and as an evaluation by researchers, teachers, and principals to increase students’ motivation and achievement. The approach of the research is a quantitative research with developing the instrument method. The research is conduct on 1.067 students of public middle school in Jakarta. The result demonstrate that the instrument that developed and validated from the instrument of Classroom Emotional Climate (CEC) and the instrument of Test Of Science-Related Attitudes (TOSRA) have eight dimensions are, collaboration, motivation, care, clarity, attitude to scientific inquiry, enjoyment of lessons, adoption of scientific attitudes, and sosial implications of science, used LISREL to test Confirmatory Factor Analysis are 37 items. The further analysis use Rasch Fit Item value is 36 items and 589 person, have five items level of difficulty and person abilities are also clustered into five levels. Besides that, Cronbach's alpha value is 0.92, Person reliability is 0.88 and item reliability is 0.99, shows that the instrument results is reliabel, therefore able to use.

References

Adi, N. R. M., Amaruddin, H., Adi, H. M. M., & A`yun, L. Q. (2022). Validity and Reliability Analysis Using the Rasch Model to Measure the Quality of Mathematics Test Items of Vocational High Schools. Journal of Educational Research and Evaluation, 11(2), 103–113. Retrieved from http://journal.unnes.ac.id/sju/index.php/jere

Agency, C. I. (2007). The world fact book: Indonesia. The World Fact Book: Indonesia. Retrieved from https://www.cia.gov/cia/publications/factbook/print/id.html.

Alarcon, L. A. G., Trapaga, J. A. B., & Navarro, R. E. (2017). A photovoice study of older adults’ conceptualizations of risk. Journal of Aging Studies, 26(4), 448–458. Retrieved from http://www.embase.com/search/results?subaction=viewrecord&from=export&id=L52096536%0Ahttp://dx.doi.org/10.1016/j.jaging.2012.06.004

Andrich, D. (2011). Rating scales and Rasch measurement.

Antonietti, C., Schmitz, M. L., Consoli, T., Cattaneo, A., Gonon, P., & Petko, D. (2023). “Development and validation of the ICAP Technology Scale to measure how teachers integrate technology into learning activities.†Computers and Education, 192(August 2022), 104648. https://doi.org/10.1016/j.compedu.2022.104648

Balparda, K., Herrera-Chalarca, T., Silva-Quintero, L. A., Torres-Soto, S. A., & Vanegas-Ramírez, C. M. (2020). Development and validation of the “Keratoconus end-points assessment questionnaire†(KEPAQ), a disease-specific instrument for evaluating subjective emotional distress and visual function through rasch analysis. Clinical Ophthalmology, 14, 1287–1296. https://doi.org/10.2147/OPTH.S254370

Barr, J. J. (2016). Developing a positive classroom climate. The IDEA Center, 61(October), 1–9. Retrieved from http://files.eric.ed.gov/fulltext/ED573643.pdf

Blegur, J., Rajagukguk, C. P. M., Sjioen, A. E., & Souisa, M. (2023). Innovation of Analytical Thinking Skills Instrument for Throwing and Catching Game Activities for Elementary School Students. International Journal of Instruction, 16(1), 723–740. https://doi.org/10.29333/iji.2023.16140a

Bond, T. G., & Fox, C. M. (2015). Applying the Rasch Model: Fundamental Measurement in the Human Sciences, Third Edition 3rd Edition. In Maternal & Child Nutrition (Vol. 11, Issue supplement S2). Routledge.

Boone, W. J., & Noltemeyer, A. (2017). Rasch analysis: A primer for school psychology researchers and practitioners. Cogent Education, 4(1), 1–13. https://doi.org/10.1080/2331186X.2017.1416898

Creswell, W. J., & Creswell, J. D. (2018). Research Design: Qualitative, Quantitative adn Mixed Methods Approaches. In Journal of Chemical Information and Modeling (Vol. 53, Issue 9). SAGE. Retrieved from http://www.ceil-conicet.gov.ar/wp-content/uploads/2015/10/Creswell-Cap-10.pdf

Damanik, E. (2014). Science and Mathematics Education Centre Principal Leadership Style and Its Impact on School Climate and Teacher Self-Efficacy in Indonesian Schools Enceria Damanik (Issue February). Curtin University of Technology. Retrieved from https://espace.curtin.edu.au/bitstream/handle/20.500.11937/391/200089_Damanik 2014.pdf?sequence=2

DiStefano, C., & Morgan, G. B. (2010). Evaluation of the BESS TRS-CA Using the Rasch Rating Scale Model. School Psychology Quarterly, 25(4), 202–212. https://doi.org/10.1037/a0021509

dos Santos, P. M., & Cirillo, M. Â. (2023). Construction of the average variance extracted index for construct validation in structural equation models with adaptive regressions. Communications in Statistics: Simulation and Computation, 52(4), 1639–1650. https://doi.org/10.1080/03610918.2021.1888122

Embretson, S. E., & Reise, S. P. (2000). Item Response Theory For Psychologists. In Item Response Theory. Lawrence Erlbaum Associates, Inc. https://doi.org/10.4324/9781410605269-13

Fernández-Gómez, E., Martín-Salvador, A., Luque-Vara, T., Sánchez-Ojeda, M. A., Navarro-Prado, S., & Enrique-Mirón, C. (2020). Content validation through expert judgement of an instrument on the nutritional knowledge, beliefs, and habits of pregnant women. Nutrients, 12(4). https://doi.org/10.3390/nu12041136

Fisher, W. P. (2007). Rating scale instrument quality criteria. Rasch Measurement Transactions, 21(1), 1095.

Fornell, C., & Larcker F., D. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, XVIII(February), 39–50. https://doi.org/10.1177/002224378101800313

Fraser, B. J. (1981). Test of science-related attitudes.

Fraser, B. J., McLure, F. I., & Koul, R. B. (2021). Assessing Classroom Emotional Climate in STEM classrooms: developing and validating a questionnaire. Learning Environments Research, 24(1). https://doi.org/10.1007/s10984-020-09316-z

Giguère, G., Brouillette-Alarie, S., & Bourassa, C. (2023). A Look at the Difficulty and Predictive Validity of LS/CMI Items With Rasch Modeling. Criminal Justice and Behavior, 50(1), 118–138. https://doi.org/10.1177/00938548221131956

Hair.Jr, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2018). Multivariate Data Analysis. Cengage. https://doi.org/10.1002/9781119409137.ch4

Hanrahan, M. (1998). The effect of learning environment factors on students’ motivation and learning. International Journal of Science Education, 20(6), 737–753. https://doi.org/10.1080/0950069980200609

Henderson, D., Fisher, D., & Fraser, B. (2000). Interpersonal behavior, laboratory learning environments, and student outcomes in senior biology classes. Journal of Research in Science Teaching, 37(1), 26–43. https://doi.org/10.1002/(SICI)1098-2736(200001)37:1<26::AID-TEA3>3.0.CO;2-I

Hoyle, R. H. (2023). Handbook of Structural Equation Modeling (Second edi). The Guilford Publications.

Idris, M., Izmaimusah, D., & Ahmad. (2021). Instrument Development of Mathematics Learning Outcomes By the Rasch Model in Elementary School To Support the Implementation of the 2013 Curriculum. JISAE: Journal of Indonesian Student Assessment and Evaluation, 7(2), 88–102. https://doi.org/10.21009/jisae.v7i2.21830

Jonsdottir, G., Haraldsdottir, E., Sigurdardottir, V., Thoroddsen, A., Vilhjalmsson, R., Tryggvadottir, G. B., & Jonsdottir, H. (2023). Developing and testing inter-rater reliability of a data collection tool for patient health records on end-of-life care of neurological patients in an acute hospital ward. Nursing Open, July 2021, 1–9. https://doi.org/10.1002/nop2.1789

JR, H. J. F., Black, W. C., J.Babin, B., & Anderson, R. E. (2010). Multivariate Data Analysis (p. 161).

Kemendikbud. (2019). Hasil PISA Indonesia 2018: Akses Makin Meluas, Saatnya Tingkatkan Kualitas. Siaran Pers. Nomor: 397/Sipres/A5.3/XII/2019. Fraser, B. J. (1981). Test of science-related attitudes. https://www.kemdikbud.go.id/main/blog/2019/12/hasil-pisa-indonesia-2018-akses-makin-meluas-saatnya-tingkatkan-kualitas

Landis, J. R., & Koch, G. G. (1977). Landis amd Koch1977_agreement of categorical data. Biometrics, 33(1), 159–174. https://doi.org/10.2307/2529310

Lederman, N. G., & Sandra, A. K. (2014). Handbook of Research on Science Education. In Handbook of Research on Science Education (Vol. 2). Routledge. https://doi.org/10.1097/00003465-199001000-00018

Leyva, E. M. (2023). A Review of the Kentucky Inventory of Mindfulness Skills under Rasch Modeling for Unidimensionality Based on Difficulty. Research Square, 1–18. https://doi.org/10.21203/rs.3.rs-2034570/v1

Muslihin, H. Y., Suryana, D., Ahman, Suherman, U., & Dahlan, T. H. (2022). Analysis of the Reliability and Validity of the Self-Determination Questionnaire Using Rasch Model. International Journal of Instruction, 15(2), 207–222. https://doi.org/10.29333/iji.2022.15212a

Ng, C. (2021). What kind of students persist in science learning in the face of academic challenges? Journal of Research in Science Teaching, 58(2), 195–224. https://doi.org/10.1002/tea.21652

Perera, C. J., Sumintono, B., & Jiang, N. (2018). The Psychometric Validation Of The Principal Practices Questionnaire Based On Item Response Theory. International Online Journal of Educational Leadership, 2(1), 21–38. https://doi.org/10.22452/iojel.vol2no1.3

Pratama, H., Maduretno, T. W., & Yusro, A. C. (2021). Online Learning Solution: Ice Breaking Application to Increase Student Motivation. Journal of Educational Science and Technology (EST), 7(1), 117–125. https://doi.org/10.26858/est.v7i1.19289

Rahmawati, Y., Ridwan, A., Faustine, S., Syarah, S., Ibrahim, I., & Mawarni, P. C. (2020). Pengembangan Literasi Sains Dan Identitas Budaya Siswa Melalui Pendekatan Etno-Pedagogi Dalam Pembelajaran Sains. Edusains, 12(1), 54–63. https://doi.org/10.15408/es.v12i1.12428

Recker, J., & Rosemann, M. (2010). A Measurement Instrument for Process Modeling Research. Scandinavian Journal of Information Systems, 22(2), 3–30. Retrieved from https://eprints.qut.edu.au/39834/1/c39834.pdf

Rosli, M. S., Saleh, N. S., Alshammari, S. H., Ibrahim, M. M., Atan, A. S., & Atan, N. A. (2021). Improving Questionnaire Reliability using Construct Reliability for Researches in Educational Technology. International Journal of Interactive Mobile Technologies, 15(4), 109–116. https://doi.org/10.3991/IJIM.V15I04.20199

Salta, K., & Koulougliotis, D. (2015). Research and Practice Assessing motivation to learn chemistry : adaptation and validation of Science Motivation Questionnaire II with Greek secondary school students. Chemistry Education Research and Practice. https://doi.org/10.1039/C4RP00196F

Siagian, A. F., Ibrahim, M., & Supardi, Z. A. I. (2023). Creative-scientific decision-making skills learning model for training creative thinking skills and student decision making skills. Nurture, 17(1), 10–17. https://doi.org/10.55951/nurture.v17i1.141

Smith, R. M. (1986). Person Fit In The Rasch Model. Hispanic Journal of Behavioral Sciences, 9(2), 183–205. https://doi.org/10.1177/001316448604600210

Sulsilah, H., Hidayat, A., & Ramalis, T. R. (2023). Analysis of Computational Thinking Instrument for High School Student Using Rasch Model. Jurnal Penelitian Pendidikan IPA, 9(3), 1445-1450. https://doi.org/10.29303/jppipa.v9i3.2771

Sumintono, B., & Widhiarso, W. (2015). Aplikasi Pemodelan RASCH Pada Assessment Pendidikan. In AplikAsi RascH pemodelAn Pada Assessment Pendidikan (Issue October). Trim Komunikata.

Sutiani, A., Situmorang, M., & Silalahi, A. (2021). Implementation of an Inquiry Learning Model with Science Literacy to Improve Student Critical Thinking Skills. International Journal of Instruction, 14(2), 117–138. https://doi.org/10.29333/iji.2021.1428a

Talton, E. L., & Simpson, R. D. (1987). Relationships of attitude toward classroom environment with attitude toward and achievement in science among tenth grade biology students. Journal of Research in Science Teaching, 24(6), 507–525. https://doi.org/10.1002/tea.3660240602

Telli, S., Den Brok, P., & Cakiroglu, J. (2007). Students’ perceptions of science teachers’ interpersonal behaviour in secondary schools: Development of a Turkish version of the Questionnaire on Teacher Interaction. Learning Environments Research, 10(2), 115–129. https://doi.org/10.1007/s10984-007-9023-2

Ulumiyah, D., Sumantri, M. S., Rahmawati, Y., & Iasha, V. (2022). An Analysis of Science Literacy Ability Elementary School Students. Jurnal Basicedu, 6(3), 3544–3553. https://doi.org/10.31004/basicedu.v6i3.2623

Vinzi, V. E., Chin, W. M., Hanseler, J., & Wang, H. (2010). Handbook of Partial Least Squares: Concepts, Methods and Applications. In Springer Handbooks of Computational Statistics. Springer. Retrieved from http://www.springer.com/series/7286

Walker, S. L., & Fraser, B. J. (2005). Development and validation of an instrument for assessing distance education learning environments in higher education: The Distance Education Learning Environments Survey (DELES). Phenomenology and the Cognitive Sciences, 4(3), 289–308. https://doi.org/10.1007/s10984-005-1568-3

Widarjono, A. (2010). Analisis Statistika Multivariat Terapan (Ppertama). Unit Penerbit dan Percetakan Sekolah Tinggi Ilmu Manajemen YKPN.

Wijsman, L. A., Saab, N., Schuitema, J., van Driel, J. H., & Westenberg, P. M. (2019). Promoting performance and motivation through a combination of intrinsic motivation stimulation and an extrinsic incentive. Learning Environments Research, 22(1), 65–81. https://doi.org/10.1007/s10984-018-9267-z

Yeung, A. S., & Mclnerney, D. M. (2005). Students’ school motivation and aspiration over high school years. Educational Psychology, 25(5), 537–554. https://doi.org/10.1080/01443410500046804

Author Biographies

Hasna Rashifah, Universitas Negeri Jakarta

Yuli Rahmawati, Universitas Negeri Jakarta

Riyadi, Universitas Negeri Jakarta

License

Copyright (c) 2023 Hasna Rashifah, Yuli Rahmawati, Riyadi

Creative Commons License

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

Authors who publish with Jurnal Penelitian Pendidikan IPA, agree to the following terms:

  1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution 4.0 International License (CC-BY License). This license allows authors to use all articles, data sets, graphics, and appendices in data mining applications, search engines, web sites, blogs, and other platforms by providing an appropriate reference. The journal allows the author(s) to hold the copyright without restrictions and will retain publishing rights without restrictions.
  2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in Jurnal Penelitian Pendidikan IPA.
  3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).