Measuring self-regulated learning in the STEM framework: A confirmatory factor analysis

Abstract

Within the context of Self-Regulated Learning (SRL), a process of directing oneself to facilitate individual learning more effectively, the SRL instrument development is deemed necessary to measure students’ self-reliance in learning mathematics in the science, technology, engineering, and mathematics (STEM) framework. The research aims to develop and test the validity and reliability of an SRL instrument, namely a 14-item SRL questionnaire accommodating four aspects, namely planning, self-monitoring, self-controlling, and evaluation. The study involved 420 junior high school students in East Java, Central Java, and Yogyakarta Special Region. The results show that the questionnaire was developed as planned and that planning, monitoring, controlling, and evaluating aspects can reflect the SRL variable in a valid, reliable, and significant way supported by each aspect's behavior indicator. The SRL variable theoretical model corresponds (good fit) with the empirical data, and all of the items are likely valid and reliable to assess student's mathematics SRL in the STEM framework. The SRL questionnaire was also found suitable for use by teachers to measure junior high school students’ self-reliance in SRL. © 2021 The Author(s).

Keywords

Author Keywords

STEM validity Self-regulated learning confirmatory factor analysis reliability

Index Keywords

Author Affiliations

Universitas Negeri Yogyakarta, Yogyakarta, Yogyakarta, Indonesia

Funding & Acknowledgements

Direktorat Jenderal Pendidikan Tinggi, DIKTI

This work is supported by the Directorate General of Higher Education of the Ministry of Education, Culture, Research, and Technology for their support to this research. The researchers also would like to extend their gratitude to the entire participants and to mathematics teachers who supported us distributing the questionnaire to the students.

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Measuring self-regulated learning in the STEM framework: A confirmatory factor analysis

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