Pedagogical Data Production as the Generative Foundation of Meaningful Learning Analytics

Learner-centred and distributed higher education increases the need for information that makes learning visible beyond system-generated traces. While learning analytics has advanced methods for analysing learning processes, less attention has been paid to how learning design generates data on which such analytics depend. Drawing on a multi-year, design-oriented and practice-based research process, this process paper introduces a model that conceptualises pedagogical data production as a configuration of interconnected learning design dimensions. It specifies how the learning-related data, defined by its interpretive function, is produced through the alignment of learning design elements, which structure how such data is generated, becomes visible, and is interpreted, making learners’ engagement, reasoning, and competence development visible. The proposed model positions learning analytics as a practice emerging from pedagogically structured learning processes and defines learning design as the generative condition of pedagogically meaningful learning-related data, through which learner agency and pedagogical action can be supported.