Designing for data: the crucial role of the educator in learning analytics
Authors: Kitchenham, A., Holley, D. and Biggins, D.
Conference: INTED 2026
Dates: 2-4 March 2026
Abstract:Learning analytics literature in higher education is framed by two dominant perspectives: the institutional need to monitor performance and optimise systems, and the learner’s need for feedback, support, and personalised pathways. This work positions a third stakeholder as equally essential within this landscape: the educator. As both subject expert and pedagogical designer, the educator sits at the intersection of institutional expectations and student learning needs, shaping the everyday experiences that generate the data on which learning analytics relies.
Using a topological perspective to map the core components of learning analytics—data, analytical methods, use cases, technologies, stakeholders, governance, outcomes and evaluation—the centrality of data is an essential for informing teaching and learning processes. Yet much of the data currently produced in higher education emerges incidentally as a by-product of administrative or instructional activity. Thus, a ‘one size fits all’ compilation of macro-level institutional datasets fails to recognise the nuances of learning context, are unable to capture discipline specific pedagogic differences and provides minimal contribution to the enhancement of student learning gain.
As a result, the potential for analytics to enhance learning and teaching is limited by the absence of intentional, pedagogically grounded data design.
In this presentation the case is made for repositioning learning analytics as an integral element of learning design. Moving to the micro-level where educators can conceive data generation as a purposeful component of curriculum planning, opportunities emerge to embed real-time, meaningful, and actionable information directly into teaching and learning activities. Such an approach supports continuous improvement, enriches the educator’s capacity to personalise learning, and contributes to more coherent and effective analytics practices across the institution. To enable educators to conceptualise the three perspectives informing the debate and potentiality of this theoretical approach, a model is offered framing the options for educator-led data design. Application of the principles will, it is argued, facilitate the creation of more impactful learning experiences and foster stronger alignment between institutional aims, teaching practice, and student success.
Source: Manual