Self-regulated Learning Questionnaire: Differential Item Functioning (DIF) and Calibration using Rasch Model Analysis

Kistantia Elok Mumpuni(1*), Guldana Atymtaevna Begimbetova(2), Heri Retnawati(3)

(1) Universitas Sebelas Maret
(2) Abai Kazakh National Pedagogical University
(3) Universitas Negeri Yogyakarta
(*) Corresponding Author

Abstract

Questionnaires are commonly utilized on educational research. However, studies on Differential Item Functioning (DIF) and calibration using Rasch Models are still limited. Therefore, a Self-regulated Learning questionnaire was developed which aims to determine the ability of students to regulate themselves to achieve learning goals. The instrument consists of twelve items. The involved participants were 300 students who enrolled in first-year to fourth-year. Data were analyzed using Racsh Model Analysis with Winsteps 4.5.2 software. As a result, there are four items that were not fit, so that, therefore should be eliminated or revised. The DIF analysis found that gender bias was unidentified, but long-study bias was detected for items number one and six. The reliability value of the item is categorized as very good (0.99), which indicates that the instrument has sufficient consistency/reliability. While, the function curve showed that the items on the self-regulated learning questionnaire produce optimal information in individuals with moderate (θ) ability. Overall, self-regulated learning questionnaires have to be revised then tested on different sample groups. In addition, longitudinal and cross-sectional research is necessary to determine the level of self-regulated learning of students more comprehensively.

Keywords

Self-regulated learning; bias; DIF; rasch model; item response theory

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References

Gambo, Y., & Shakir, M. Z. (2021). Review on self-regulated learning in smart learning environment. Smart Learning Environments, 8(1). https://doi.org/10.1186/s40561-021-00157-8

Hellebaut, S., Haerens, L., Vanderlinde, R., & Katrien De Cocker. (2023). Burnout, motivation, and (de-)motivating teaching style in different phases of a teaching career. In Teaching and Teacher Education (Vol. 129). Elsevier Ltd. https://doi.org/10.1016/j.tate.2023.104168

Istiyono, E., & Suyoso. (2019). The Developing and Calibration of PhysEDiTHOTS Based on IRT and IQF for Students’ HOTS Diagnostic. Journal of Physics: Conference Series, 1233(1). https://doi.org/10.1088/1742-6596/1233/1/012038

Linacre, J. M. (2020). Winsteps® Rasch measurement computer program (4.5.2). Winsteps.com.

Linacre, M. (2012). Winsteps Tutorial 4: Differential Item Functioning and Dimensionality. June, 1–22. https://www.winsteps.com/a/winsteps-tutorial-4.pdf

Mumpuni, K. E., Sholeha, V., Murni, E. S., & Sidiq, Y. (2022). Parent Understanding to Support Children Science Activity at Home. Proceedings of the International Conference of Learning on Advance Education (ICOLAE 2021), 893–902. https://doi.org/10.2991/assehr.k.220503.096

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

Natanael, Y., Salsabilla, R., Aulia, D., Khoirunnisa, D., Munawar, H. N., Hidayat, N. S., & Firdaus, R. F. (2022). Rasch Rating Scale Model: Bias Detection and Validation Test of Indonesian-Adolescent Life Satisfaction Scale. Psympathic : Jurnal Ilmiah Psikologi, 9(1), 31–44. https://doi.org/10.15575/psy.v9i1.14270

Öz, E., & Şen, H. Ş. (2018). Self Regulated Learning Questionnaire: Reliability and Validity Study. Educational Policy Analysis and Strategic Research, 13(4), 108–123. https://doi.org/10.29329/epasr.2018.178.6

Panadero, E. (2017). A Review of Self-regulated Learning: Six Models and Four Directions for Research. Frontiers in Psychology, 8. https://doi.org/10.3389/fpsyg.2017.00422

Pressley, M., & Harris, K. R. (2009). Cognitive Strategies Instruction: From Basic Research to Classroom Instruction. Journal of Education, 189(1–2), 77–94. https://doi.org/10.1177/0022057409189001-206

Retnawati, H. (2017). Teori Respon Butir dan Penerapannya. Parama Publishing.

Sumintono, B., & Widhiarso, W. (2014). Aplikasi Model RASCH untuk Penelitian Ilmu-ilmu Sosial (B. Trim, Ed.; 1st ed.). Penerbit Trim Komunikata.

Sumintono, B., & Widhiarso, W. (2015). Aplikasi Pemodelan RASCH pada Assessment Pendidikan (B. Trim, Ed.; 1st ed.). Penerbit Trim Komunikata.

Taherdoost, H. (2022). Designing a Questionnaire for a Research Paper: A Comprehensive Guide to Design and Develop an Effective Questionnaire. Asian Journal of Managerial Science, 11(1), 8–16. https://doi.org/10.51983/ajms-2022.11.1.3087ï

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

Xu, J. (2022). A profile analysis of online assignment motivation: Combining achievement goal and expectancy-value perspectives. Computers and Education, 177. https://doi.org/10.1016/j.compedu.2021.104367

Yeşim, Ö., & Baştuğ, Ö. (2016). Educational Research and Reviews A comparison of four differential Item functioning procedures in the presence of multidimensionality. Educational Research and Reviews, 11(13), 1251–1261. https://doi.org/10.5897/ERR2016.2803

Zhang, Y., Tian, Y., Yao, L., Duan, C., Sun, X., & Niu, G. (2022a). Individual differences matter in the effect of teaching presence on perceived learning: From the social cognitive perspective of self-regulated learning. Computers and Education, 179. https://doi.org/10.1016/j.compedu.2021.104427

Zhang, Y., Tian, Y., Yao, L., Duan, C., Sun, X., & Niu, G. (2022b). Teaching presence predicts cyberloafing during online learning: From the perspective of the community of inquiry framework and social learning theory. British Journal of Educational Psychology, 92(4), 1651–1666. https://doi.org/10.1111/bjep.12531

Zhang, Y., Tian, Y., Yao, L., Duan, C., Sun, X., & Niu, G. (2023). Teaching presence promotes learner affective engagement: The roles of cognitive load and need for cognition. Teaching and Teacher Education, 129. https://doi.org/10.1016/j.tate.2023.104167

DOI: 10.23917/varidika.v1i1.22995

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