Research Article
Expert Judgement of Self-Regulated Learning Questionnaire Quality: A Many-Facet Rasch Model Analysis
@INPROCEEDINGS{10.4108/eai.19-9-2023.2340515, author={Rahmi Ramadhani and Edi Syahputra and Elmanani Simamora}, title={Expert Judgement of Self-Regulated Learning Questionnaire Quality: A Many-Facet Rasch Model Analysis}, proceedings={Proceedings of the 8th Annual International Seminar on Transformative Education and Educational Leadership, AISTEEL 2023, 19 September 2023, Medan, North Sumatera Province, Indonesia}, publisher={EAI}, proceedings_a={AISTEEL}, year={2023}, month={12}, keywords={expert judgement many-facet rasch model self-regulated learning questionnaire}, doi={10.4108/eai.19-9-2023.2340515} }- Rahmi Ramadhani
Edi Syahputra
Elmanani Simamora
Year: 2023
Expert Judgement of Self-Regulated Learning Questionnaire Quality: A Many-Facet Rasch Model Analysis
AISTEEL
EAI
DOI: 10.4108/eai.19-9-2023.2340515
Abstract
Self-regulated learning (SRL) refers to a situation in which students proactively engage in their own learning process, and it is linked to the metacognitive, motivational, and behavioral attributes of students. SRL is an inherent trait among students that enables them to optimize their learning capacity, especially in the realm of mathematics. To assist students in exploring their SRL, SRL questionnaires are required. The objective of this research is to assess and scrutinize the quality of the SRL questionnaire developed in accordance with Zimmerman's stages. The quality of the SRL Questionnaire is evaluated and analyzed according to the following criteria: gender bias, language appropriateness, indicators that correspond to Zimmerman's stages, construction and systematics, relevance and systematics. The Many-Facet Rasch Model was used to assess the quality of the SRL questionnaire. FACETS software was used to collect and code 270 data points. The findings revealed that all 50 statements in the SRL questionnaire were valid and reliable enough to be employed in field research. Other findings revealed that the self-efficacy subscale in the SRL questionnaire was the best. The linguistic appropriateness criterion is the most challenging assessment criterion for experts to evaluate and judge.