Evaluating Students' Academic Resilience in Chemistry Learning: Insights from a Rasch Model Analysis

Desfi Annisa(1*), Hari Sutrisno(2), Endang Widjajanti Laksono(3), Sri Novita Yanda(4)

(1) Faculty of Mathematics and Natural Sciences, Universitas Negeri Yogyakarta
(2) Faculty of Mathematics and Natural Sciences, Universitas Negeri Yogyakarta
(3) Faculty of Mathematics and Natural Sciences, Universitas Negeri Yogyakarta
(4) Department of Educational Research, Evaluation, and Assessment, Northern Illinois University
(*) Corresponding Author

Abstract

Teaching chemistry is a complex subject that requires a certain level of knowledge and skills to understand. Students must overcome this challenge because teaching chemistry involves abstract ideas (atoms, molecules, and electrons) and principles, laws, reaction equations, and mathematical operations. Increasing academic resilience is important in enhancing students' understanding and well-being in learning. This research aimed to test the validity and reliability of students' chemistry academic resilience tests using the Rasch model. Data collection was conducted using Google Forms. Data analysis utilized the Rasch model, assisted by the Winstep application, to reveal various aspects of the assessment. Based on the research findings, a Cronbach's alpha coefficient of 0.78 indicates strong internal consistency. In addition, item reliability reached a significant value of 0.99, while person reliability of 0.78 confirmed the consistency of respondents in providing accurate answers in the assessed categories. Furthermore, the OUTFIT and INFIT MNSQ (persons) have average values of +1.02 and +1.01, respectively (the closer to 1, the better). In contrast, the INFIT and OUTFIT ZSTD values are 0.1 and 0.3, respectively (the closer to 0, the better). The most difficult question is coded ra11 with a logit score of 0.61, and the easiest is coded ra4 with a logit score of -0.05. Therefore, the student academic resilience instrument is an effective measuring tool. In the future, chemistry educators and researchers can benefit from the potential impact of this research on Indonesian education.

Keywords

academic resilience; chemistry learning; rasch model

Full Text:

PDF

References

Alkan, F., & Yucel, A. S. (2019). An analysis of achievement goal orientations and chemistry motivations of students within the structural equation modeling and an evaluation of the influencing factors. New Trends and Issues Proceedings on Humanities and Social Sciences, 6(2), 01–08. https://doi.org/10.18844/prosoc.v6i2.4276.

Allan, J. F., McKenna, J., & Dominey, S. (2014). Degrees of resilience: profiling psychological resilience and prospective academic achievement in university inductees. British Journal of Guidance and Counselling, 42(1), 9–25. https://doi.org/10.1080/03069885.2013.793784

Almubarak, A., Saadi, P., Prayogi, R., & Maldini, P. P. (2023). Assessing Students' Understanding of Chemical Bonds Material by Rasch Modeling. Indonesian Journal on Learning and Advanced Education (IJOLAE), 5(3), 217–232. https://doi.org/10.23917/ijolae.v5i3.22242

Angel, M., Cevallos, S., Alexander, C., Rosado, Z., Viviana, O., & Terán, T. (2019). The Procedure Used on Diagnostic Evaluation Process. 3, 1–10.

Angriani, A. D., Nursalam, N., Fuadah, N., & Baharuddin, B. (2018). Pengembangan Instrumen Tes Untuk Mengukur Kemampuan Pemecahan Masalah Matematika Siswa. AULADUNA: Jurnal Pendidikan Dasar Islam, 5(2), 211. https://doi.org/10.24252/auladuna.v5i2a9.2018

Annisa, D., Sutrisno, H., & Widjajanti, E. (2023). Academic Resilience in Chemistry during Covid-19: A Systematic Review. Jurnal Penelitian Pendidikan IPA, 9(11), 1111–1119. https://doi.org/10.29303/jppipa.v9i11.4354

Ariffin, S. R., Omar, B., Isa, A., & Sharif, S. (2010). Validity and reliability multiple intelligent item using rasch measurement model. Procedia Social and Behavioral Sciences, 9, 729–733. https:// doi.org/10.1016/j.sbspro.2010.12.225

Baghaei, P. (2013). Development and psychometric evaluation of a multidimensional scale of willingness to communicate in a foreign language. European Journal of Psychology of Education, 28(3), 1087–1103. https://doi.org/10.1007/s10212-012-0157-y

Baghaei, P., & Aryadoust, V. (2015). Modeling Local Item Dependence Due to Common Test Format With a Multidimensional Rasch Model. International Journal of Testing, 15(1), 71–87. https://doi.org/10.1080/15305058.2014.941108

Beale, J. (2020). Academic Resilience and its Importance in Education after Covid-19. Eton Journal for Innovation and Research in Education, 4, 1–6.

Beri, N., & Kumar, D. (2018). Predictors of Academic Resilience Among Students: a Meta-Analysis. I-Manager’s Journal on Educational Psychology, 11(4), 37. https://doi.org/10.26634/jpsy.11.4.14220

Bond, T. G, Fox, C. M. (2015). Applying the rasch model: Fundamental measurement in the human sciences:Third Edition. In Andrew’s Disease of the Skin Clinical Dermatology. Routledge Taylor & Francis Group.

Bond, T. G., & Fox, C. M. (2007). Applying the Rasch Model : Fundamental Measurement. Lawrence Erlbaum Associates

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

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

Briggs, D. C. (2019). Interpreting and visualizing the unit of measurement in the Rasch Model. Measurement: Journal of the International Measurement Confederation, 146(July), 961–971. https://doi.org/10.1016/j.measurement.2019.07.035

Cassidy, S. (2016). The Academic Resilience Scale (ARS-30): A new multidimensional construct measure. Frontiers in Psychology, 7(NOV), 1–11. https://doi.org/10.3389/fpsyg.2016.01787

Cheung, F. M., van de Vijver, F. J. R., & Leong, F. T. L. (2011). Toward a new approach to the study of personality in culture. American Psychologist, 66(7), 593–603. https://doi.org/10.1037/a0022389

Chiang, W.-W. (2015). Ninth Grade Student’ Self-assessment in Science: A Rasch Analysis Approach. Procedia - Social and Behavioral Sciences, 176, 200–210. https://doi.org/10.1016/j.sbspro.2015.01.462

Chow, J., Tse, A., & Armatas, C. (2018). Comparing trained and untrained teachers on their use of LMS tools using the Rasch analysis. Computers and Education, 123, 124–137. https://doi.org/10.1016/j.compedu.2018.04.009

Fiorilli, C., Farina, E., Buonomo, I., Costa, S., Romano, L., Larcan, R., & Petrides, K. V. (2020). Trait emotional intelligence and school burnout: The mediating role of resilience and academic anxiety in high school. International Journal of Environmental Research and Public Health, 17(9). https://doi.org/10.3390/ijerph17093058

Fitri. (2017). Analisis Validitas dan Reliabilitas Instrumen Kinerja Akuntan Menggunakan Pendekatan Rasch Model. Jurnal Ilmiah Akuntansi Peradaban, 3(1), 34–45.

Gul, Y. E. (2023). A Theoretical Perspective On Survey Method From Quantitative Research Methods. Universum, 4(106),64-68. https://doi.org/10.32743/UniPsy.2023.106.4.15254.

Hermita, N., Putra, Z., Alim, J., Wijaya, T., Anggoro, S., & Diniya, D. (2021). Elementary Teachers' Perceptions on Genially Learning Media Using Item Response Theory (IRT). Indonesian Journal on Learning and Advanced Education (IJOLAE), 4(1), 1-20. doi:https://doi.org/10.23917/ijolae.v4i1.14757

Herwin, & Nurhayati, R. (2021). Measuring students’ curiosity character using confirmatory factor analysis. European Journal of Educational Research, 10(2), 773–783. https://doi.org/10.12973/EU-JER.10.2.773

Hinton, P., McMurray, I., & Brownlow, C. (2014). SPSS Explained. In SPSS Explained. https://doi.org/10.4324/9781315797298

Honra, J. R. (2022). Development and Validation of Filipino Learners’ Academic Resilience Scale (FLARS). American Journal of Education and Technology, 1(2), 107–113. https://doi.org/10.54536/ajet.v1i2.664

Ibrahem Ayasrah, J., & Nawaf Albalawi, K. (2022). Academic resilience and its relationship with academic achievement of the first-year students of university. Journal of Positive School Psychology, 6(11), 2647–2666.

Idris, I., Khairani, A. Z., & Shamsuddin, H. (2019). The influence of resilience on psychological well-being of Malaysian University undergraduates. International Journal of Higher Education, 8(4), 153–163. https://doi.org/10.5430/ijhe.v8n4p153

Indihadi, D., Suryana, D., & Ahmad, A. B. (2022). the Analysis of Construct Validity of Indonesian Creativity Scale Using Rasch Model. Creativity Studies, 15(2), 560–576. https://doi.org/10.3846/cs.2022.15182

Kumalasari, D., & Akmal, S. Z. (2020). Resiliensi akademik dan kepuasan belajar daring di masa pandemi COVID-19: Peran mediasi kesiapan belajar daring. Persona:Jurnal Psikologi Indonesia, 9(2), 353–368. https://doi.org/10.30996/persona.v9i2.4139

Lakhan, G. R., Ullah, M., Channa, A., Siddique, M., & Gul, S. (2020). The Effect Of Academic Resilience And Attitude On Managerial Performance. 19(3), 3326–3340. http://ilkogretim-online.org

Le, L. T. (2009). Investigating Gender Differential Item Functioning Across Countries and Test Languages for PISA Science Items. International Journal of Testing, 9(2), 122–133. https://doi.org/10.1080/15305050902880769

Lin, C., Education, T., & District, G. S. (2015). Impact Of Gratitude On Resource Development And Emotional Well-Being. Social Behavior And Personality, 43(3), 493–504. http://dx.doi.org/10.2224/sbp.2015.43.3.493

Linacre, J.M. (2002). What do infit and outfit mean-square and standardized mean? Rasch Measurement Transaction, 16, 878.

Linacre, J. M. (2009). Local independence and residual covariance: A study of olympic figure skating ratings. Journal of Applied Measurement, 10(2), 157–169.

Linacre, J. M. (2011). Winsteps Help for Rasch Analysis. http://homes.jcu.edu.au/~edtgb/%5Cnpapers3://publication/uuid/D56B724A-62FF-4D00-84E1-ECC888298B70

Livana, Mubin, & Basthomi, Y. (2020). Penyebab Stres Mahasiswa Selama Pandemi Covid-19. Jurnsl Ilmu Keperawatan Jiwa, 3(2), 203–208.

Mahato, D., Gayen, P., Mahato, R. C. (2023). Relationship Between Academic Resilience and Internet Addiction Of Undergraduate Students of Purulia District of West Bengal: A Study. EPRA International Journal of Multidisciplinary Research (IJMR)-Peer Reviewed Journal, 9(3), 103–106. https://doi.org/10.36713/epra2013

Mahmudah, U., Lola, M. S., Fatimah, S., & Suryandari, K. C. (2022). Academic Resilience and Science Academic Emotion in Numeration Under Online Learning: Predictive Capacity of an Artificial Neural Network. Jurnal Pendidikan IPA Indonesia, 11(4), 542–551. https://doi.org/10.15294/jpii.v11i4.39091

Masten, A. S., Lucke, C. M., Nelson, K. M., & Stallworthy, I. C. (2021). Resilience in Development and Psychopathology: Multisystem Perspectives. Annual Review of Clinical Psychology, 17, 521–549. https://doi.org/10.1146/annurev-clinpsy-081219-120307

Ngadi, I. (2023). Analisis Model Rasch Untuk Mengukur Kompetensi Pengetahuan Siswa Smkn 1 Kalianget Pada Mata Pelajaran Perawatan Sistem Kelistrikan Sepeda Motor. Jurnal Pendidikan Vokasi Otomotif, 6(1).

Misbach, I. H., & Sumintono, B. (2014). Pengembangan dan Validasi Instrumen “Persepsi Siswa tehadap Karakter Moral Guru” di Indonesia dengan Model Rasch. PROCEEDING Seminar Nasional Psikometri, May, 148–162.

Muntazhimah, M. (2019). Pengembangan Instrumen Kemampuan Berpikir Reflektif Matematis siswa Kelas 8 SMP. Imajiner: Jurnal Matematika Dan Pendidikan Matematika, 1(5), 237–242. https://doi.org/10.26877/imajiner.v1i5.4551

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

Nicoll, W. G. (2014). Developing Transformative Schools: A Resilience-Focused Paradigm for Education. International Journal of Emotional Education, 6(1), 47–65. http://search.ebscohost.com/login.aspx?direct=true&db=eric&AN=EJ1085706&site=ehost-live

Noben, I., Maulana, R., Deinum, J. F., & Hofman, W. H. A. (2021). Measuring university teachers’ teaching quality: a Rasch modelling approach. Learning Environments Research, 24(1), 87–107. https://doi.org/10.1007/s10984-020-09319-w

Oladejo, A. I., Ademola, I. A., Ayanwale, M. A., & Tobih, D. (2023). Concept Difficulty in Secondary School Chemistry – an Intra-Play of Gender, School Location and School Type. Journal of Technology and Science Education, 13(1), 255–275. https://doi.org/10.3926/jotse.1902

Planinic, M., Boone, W. J., Susac, A., & Ivanjek, L. (2019). Rasch analysis in physics education research: Why measurement matters. Physical Review Physics Education Research, 15(2), 20111. https://doi.org/10.1103/PhysRevPhysEducRes.15.020111

Rachman, T., & Napitupulu, D. B. (2017). Rasch Model for Validation a User Acceptance Instrument for Evaluating E-learning System. CommIT (Communication and Information Technology) Journal, 11(1), 9. https://doi.org/10.21512/commit.v11i1.2042

Ramdani, R., Hanurawan, F., Ramli, M., Lasan, B. B., & Afdal, A. (2020). Development and Validation of Indonesian Academic Resilience Scale Using Rasch Models. International Journal of Instruction, 14(1), 105–120. https://doi.org/10.29333/IJI.2021.1417A

Ramirez-Granizo, I. A., Sánchez-Zafra, M., Zurita-Ortega, F., Puertas-Molero, P., González-Valero, G., & Ubago-Jiménez, J. L. (2020). Multidimensional self-concept depending on levels of resilience and the motivational climate directed towards sport in schoolchildren. International Journal of Environmental Research and Public Health, 17(2). https://doi.org/10.3390/ijerph17020534

Reeve, J., Cheon, S. H., & Yu, T. H. (2020). An autonomy-supportive intervention to develop students’ resilience by boosting agentic engagement. International Journal of Behavioral Development, 44(4), 325–338. https://doi.org/10.1177/0165025420911103

Rao, P. S., & Krishnamurthy, A. R. (2018). Impact of Academic Resilience on the Scholastic Performance of High School Students. Indian Journal of Mental Health, 5(July), 453–462.

Reise, S. P. (1990). A Comparison of Item- and Person-Fit Methods of Assessing Model-Data Fit in IRT. Applied Psychological Measurement, 14(2), 127–137. https://doi.org/10.1177/014662169001400202

Rodriguez, E. (2018). Google Forms in Library Instruction: Creating an Active Learning Space and Communicating with Students. Innovative Pedagogy, 1(7), 69–82.

Rojas F., L. F. (2015). Factors Affecting Academic Resilience in Middle School Students: A Case Study. GiST Education and Learning Research Journal, 11(11), 63–78. https://doi.org/10.26817/16925777.286

Romano, L., Angelini, G., Consiglio, P., & Fiorilli, C. (2021). Academic resilience and engagement in high school students: The mediating role of perceived teacher emotional support. European Journal of Investigation in Health, Psychology and Education, 11(2), 334–344. https://doi.org/10.3390/ejihpe11020025

Sariati, Kadek, N., Suardana, Nyoman, I., Wiratini, & Made, N. (2020). Analisis Kesulitan Belajar Kimia Siswa Kelas Xi Pada Materi Larutan Penyangga. Jurnal Imiah Pendidikan Dan Pembelajaran P-ISSN : 1858-4543 e-ISSN : 2615-6091, 4(1), 86–97. https://doi.org/10.23887/jipp.v4i1.15469.

Senocak, E., & Baloglu, M. (2014). The adaptation and preliminary psychometric properties of the Derived Chemistry Anxiety Rating Scale. Chemistry Education Research and Practice, 15(4), 800–806. https://doi.org/10.1039/c4rp00073k

Sivakumar Ramaraj. (2019). Google Forms in Education. Journal of Contemporary Educational Research and Innovations, 9(1), 35–39.

Sumintono, B. (2018). Rasch Model Measurements as Tools in Assesment for Learning. 173(Icei 2017), 38–42. https://doi.org/10.2991/icei-17.2018.11

Sumintono, B., Islam, U., Indonesia, I., Widhiarso, W., & Mada, U. G. (2014). untuk Penelitian Ilmu-Ilmu Sosial. November.

Sumintono, B., Islam, U., Indonesia, I., Widhiarso, W., & Mada, U. G. (2015). RascH. September.

Sumintono, B., & Widhiarso, W. (2015). Penilaian Pendidikan dan Ujian. AplikAsi RascH PemodelAn Pada Assessment Pendidikan, September, 1–24.

Suud, F. M, Uyun, M, Na’imah, T. (2023). Development of achievement motivation training module to improve Islamic student academic resilience in disaster areas. Psikis: Jurnal Psikologi Islami, 9(2), 312–323.

Tabatabaee-Yazdi, M., Motallebzadeh, K., Ashraf, H., & Baghaei, P. (2018). Development and validation of a teacher success questionnaire using the rasch model. International Journal of Instruction, 11(2), 129–144. https://doi.org/10.12973/iji.2018.11210a

Taufiq, A., Yudha, E. S., Md, Y. H., & Suryana, D. (2021). Examining the Supervision Work Alliance Scale: A Rasch Model Approach. The Open Psychology Journal, 14(1), 179–184. https://doi.org/10.2174/1874350102114010179

Timilsena, N. P., Krishna, ;, Maharjan, B., & Devkota, M. (2022). Teachers’ And Students’ Experiences In Chemistry Learning Difficulties. Journal of Positive School Psychology, 2022(10), 2856–2867. http://journalppw.com

Tjabolo, S. A., & Otaya, L. G. (2019). Quality of school exam tests based on item response theory. Universal Journal of Educational Research, 7(10), 2156–2164. https://doi.org/10.13189/ujer.2019.071013

Ulya, H., & Gumiandari, S. (2023). Efforts to Increase Academic Resilience of IAIN Syekh Nurjati Cirebon Students Through Strengthening Self-Regulation Capabilities. Darussalam: Journal of Psychology and Educational, 2(1) 55-71. https://doi.org/10.55849/djpe.v2i1.43

van de Grift, W. J. C. M., Houtveen, T. A. M., van den Hurk, H. T. G., & Terpstra, O. (2019). Measuring teaching skills in elementary education using the Rasch model. School Effectiveness and School Improvement, 30(4), 455–486. https://doi.org/10.1080/09243453.2019.1577743

Van Zile-Tamsen, C. (2017). Using Rasch Analysis to Inform Rating Scale Development. Research in Higher Education, 58(8), 922–933. https://doi.org/10.1007/s11162-017-9448-0

Wahyuningsih, S. (2021). Using the Rasch’s Partial Credit Model to Analyze the Quality of an Essay Math Test. Proceedings of the 1st International Conference on Mathematics and Mathematics Education (ICMMEd 2020), 550(Icmmed 2020), 257–265. https://doi.org/10.2991/assehr.k.210508.073

Weidlich, J., & Kalz, M. (2021). Exploring predictors of instructional resilience during emergency remote teaching in higher education. International Journal of Educational Technology in Higher Education, 18(1). https://doi.org/10.1186/s41239-021-00278-7

Widana, I. W. (2018). Higher Order Thinking Skills Assessment towards Critical Thinking on Mathematics Lesson. International Journal of Social Sciences and Humanities (IJSSH), 2(1), 24–32. https://doi.org/10.29332/ijssh.v2n1.74

Winarti, A., & Mubarak, A. (2019). Rasch Modeling: A Multiple Choice Chemistry Test. Indonesian Journal on Learning and Advanced Education (IJOLAE), 2(1), 1-9. doi:https://doi.org/10.23917/ijolae.v2i1.8985

Wu, M., Tam, H. P., & Jen, T.-H. (2016). Educational Measurement for Applied Researchers. In Educational Measurement for Applied Researchers. https://doi.org/10.1007/978-981-10-3302-5

Zahro’, S. F., & Ismono, I. (2021). Analisis Kemampuan Multirepresentasi Siswa Pada Materi Kesetimbangan Kimia di Masa Pandemi Covid-19. Chemistry Education Practice, 4(1), 30. https://doi.org/10.29303/cep.v4i1.2338

Zakiyah, Z., Ibnu, S., & Subandi, S. (2018). Analisis Dampak Kesulitan Siswa pada Materi Stoikiometri terhadap Hasil Belajar Termokimia dan Upaya Menguranginya dengan Metode Pemecahan Masalah. EduChemia (Jurnal Kimia Dan Pendidikan), 3(1), 119. https://doi.org/10.30870/educhemia.v3i1.1784

Zamri bin Khairani, A., & Bin Abd. Razak, N. (2015). Modeling a Multiple Choice Mathematics Test with the Rasch Model. Indian Journal of Science and Technology, 8(12). https://doi.org/10.17485/ijst/2015/v8i12/70650

Zubairi, A., & Kassim, A. N. L. (2006). Classical and Rasch analyses of dichotomously scored reading comprehension test items. Malaysian Journal of ELT Research, 2(March), 1–20.

Article Metrics

Abstract view(s): 14 time(s)
PDF: 12 time(s)

Refbacks

  • There are currently no refbacks.