<![CDATA[This study examined the measurement and calibration of learning independence among PGSD students in digital learning using the Rasch Model. Motivated by the need for validated tools that capture readiness for autonomous learning in higher education, a survey of 40 students from the 2023 and 2024 cohorts employed a Learning Independence Test. Rasch analysis estimated item difficulty and person ability and assessed reliability and model fit. Most items showed acceptable fit and internal consistency. Item and person distributions indicated generally moderate to high independence, with meaningful individual variation. These findings suggest the instrument functions adequately and can yield actionable diagnostics for curriculum design and targeted supports that strengthen autonomy in digital environments. Psychometrically sound measurement is therefore valuable for understanding learner characteristics and informing teacher preparation, since prospective teachers must foster independence in their future pupils. The small sample limits generalization. Future research should use larger and more diverse samples and adopt longitudinal designs to track changes in learning independence over time. ]]>
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