Deep learning readiness, self-regulated learning, and numeracy literacy in mathematics education: A PLS-SEM mediation study
Sherly Mayfana Panglipur Yekti, Agustin Patmaningrum, Eny Dwi Utami, Nayla Sasti Ifadza, Aditya Ramadhan
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Source: Crossref
Published: Aug 17, 2026
DOI: 10.58524/jasme.v6i3.1498
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Background: Improving numeracy literacy requires mathematics learning environments that support meaningful engagement while enabling students to regulate their learning processes. However, the mechanism linking Deep Learning Readiness (DLR), Self-Regulated Learning (SRL), and Numeracy Literacy (NL) remains insufficiently understood. Aims: This study investigated the structural relationships among DLR, SRL, and NL and examined the mediating role of SRL in the DLR–NL relationship. Method: A cross-sectional survey involved 144 Grade VIII students from three junior secondary schools in Nganjuk Regency, East Java, Indonesia. Data were collected using a PISA-aligned Numeracy Literacy Test (α = .905), a 51-item SRL questionnaire (α = .980) based on Zimmerman’s three-phase model, and a Deep Learning Readiness Scale. Data were analyzed using PLS-SEM with 5,000 bootstrap resamples. Results: DLR was positively associated with SRL (β = .512, p < .001) and NL (β = .287, p < .001), while SRL was positively associated with NL (β = .483, p < .001). The model explained 26.2% of SRL variance and 48.7% of NL variance. SRL partially mediated the DLR–NL relationship (β = .247, VAF = 46.3%). Conclusion: SRL serves as an important mechanism connecting deep learning readiness with numeracy literacy, highlighting the importance of integrating self-regulatory practices into mathematics learning environments.
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