Rafki Nasuha Ismail, Ahmad Fauzan, Yerizon
The goal of this study was to describe of motivation and students' self-regulation profiles in online mathematics learning. This research uses descriptive qualitative method involving respondents who had attended online learning at SMPN 8 Padang, SMPN 25 Padang, and SMP DEK Padang. The method of data collection was used in the analysis of the question, semi-structured interviews, distributed via Google Form and WhatsApp. From link to measure learning motivation towards online learning mathematics. Use optimal data analysis to determine cluster analyses was performed to identify the profiles showing patterns of motivation in an online course. and the Miles & Hubert analysis model which consists of three stages, namely data reduction, data and image analysis, and final analysis. Overall, the study results revealed that motivation profiles related with the students' self-regulation in online mathematics learning divided by five cluster, ie. Cluster 1 = High motivation, Cluster 2 = A bit of Average motivation, Cluster 3 = Average motivation, Cluster 4 = A bit of Low motivation, Cluster 5 = Low motivation. So it can be concluded that the motivational profile and SRL show that students' motivation to learn online, explained by clusters, predicts their self-regulation; and that the level of predictability of self-regulation in affective learning outcomes differs, depending on the student's motivational profile © 2023 Author(s).
Department of Mathematics, Universitas Negeri Padang, Padang, Indonesia
