Reconceptualizing Teacher-Facing Learning Analytics as Experiencing the Educational Data Cycle in Teacher Education

Abstract

Learning Analytics (LA) has been positioned as an infrastructure for datainformed educational improvement. However, in teacher-facing contexts, the availability of dashboards and analytics systems does not necessarily translate into teachers’ instructional judgment or practical action. This challenge has often been discussed in terms of teachers’ data literacy or interface usability, but this paper advances a different account. We argue that stagnation in Teacher-Facing Learning Analytics (TFLA) stems from limited opportunities for teachers to experience, articulate, and discuss the educational data cycle—the connected chain of data generation, representation, interpretation, and action—as a coherent structure grounded in pedagogical questions. From this perspective, we define educational data cycle experience (EDC experience) as opportunities that enable teachers to experience the educational data cycle in relation to pedagogical questions and to articulate and discuss it, and we propose EDC experience as a framing for teacher education. To operationalize this proposal, we present a pilot implementation embedded in a teacher education program, developed in collaboration with the National Institute of Informatics (NII), using a three-layer infrastructure comprising data generation (LMS), representation (dashboard), and interpretation (Python environment). Observations of selected reflective writings suggest that the phases emphasized in the pilot elicited distinct pedagogical questions—what to collect, how to operationalize indicators, and how to interpret under uncertainty—while some reflections also anticipated possible instructional responses. These observations suggest that the central challenge of TFLA lies less in indicator presentation than in how teacher education can design and provide EDC experience.