Next-Level Learning: Classifying Self-Regulated Learning in Mathematical Problem-Solving

Background/purpose. Learning mathematics often presents challenges for students, particularly in problem-solving and establishing mathematical connections. Self-regulated learning allows students to direct, adjust, and control their learning processes. This approach is essential in encouraging students to manage their learning strategies effectively when solving mathematical problems. This study introduces a new classification of self-regulated learning in mathematical problem-solving, which is aligned with the three key aspects of self-regulated learning.

Materials/methods. A qualitative descriptive approach was employed in this research, utilizing purposive sampling to select 20 students from three different islands in Indonesia, all of whom engaged in self-regulated learning while solving mathematical problems. Data collection was carried out through tests, observations, and interviews. The collected data were analyzed through three stages: data reduction, data presentation, conclusion drawing, and verification.

Results. The results of the study reveal three classifications of self-regulated learning in mathematical problem-solving: connective, visualization, and direct.

Conclusion. These findings provide new insights into how students manage their learning in the context of mathematics and offer practical implications for mathematics education in Indonesia. The study highlights the importance of understanding how self-regulated learning can be categorized and applied to improve mathematical problem-solving skills.

Keywords: Self-regulated learning, classification, problem-solving, mathematics problems

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