Open AccessSelf-regulated learning skill as a predictor of mathematics achievement: a focus on ability levels
Author(s) -
Darlington Chibueze Duru,
Sam O. C. Okeke
Publication year - 2021
Publication title -
malikussaleh journal of mathematics learning
Language(s) - English
Resource type - Journals
eISSN - 2620-6323
pISSN - 2620-6315
DOI - 10.29103/mjml.v4i2.5708
Subject(s) - cronbach's alpha , mathematics education , simple random sample , reliability (semiconductor) , regression analysis , variance (accounting) , academic achievement , psychology , mathematics , statistics , medicine , psychometrics , population , power (physics) , physics , environmental health , accounting , quantum mechanics , business
This paper investigated self-regulated learning skills as a predictor of students’ achievement in mathematics based on ability level. The study is prediction-design research of correlational type. The subjects were 882 SSII students from the secondary schools in Owerri Education Zone of Imo State. The researchers adopted the multi-stage but simple random sampling technique to draw the sample. Two instruments were used to collect data for this study. They are the Self-regulated Learning Questionnaire (SRLQ) and Mathematics Achievement Proforma. The validity of the instruments was ensured through experts’ suggestions and guidance. Single-administration reliability and Cronbach Alpha ensured the reliability of SRLQ (0.89). The data collected were analyzed using regression analysis and coefficient of determination at 0.05 alpha level with the aid of Statistical Package for Social Sciences (SPSS) version 20. The results of the study revealed that self-regulated learning skill predicts 6.0% and 4.3% respectively to the variance observed in high and low achieving students in mathematics. This prediction is significant as attested to by the regression analysis carried out (p < 0.05). Therefore, secondary school students should regulate their learning to increase their mathematics achievement.