ABSTRACT Background Learning analytics (LA) aim to support informed decision making based on educational data but often fail to align with students' realities, especially when designed to be used across multiple courses (e.g., interactions with feedback from multiple educators). The notion of human‐centred learning analytics addresses this in part by encouraging the involvement of stakeholders in the design process to incorporate lived experiences and enhance technical and pedagogical interactions. Design Thinking, an iterative, human‐centred approach, is particularly relevant as LA tools must not only process data but also support students' evolving needs. Its non‐linear nature allows continuous refinement through user feedback, yet its systematic, full application in LA tool development remains under‐explored. Objectives This paper illustrates the non‐linear iterative use of design thinking phases to conceptualise, design, develop, deploy and evaluate a LA tool, to be used across various courses, with continuous involvement of students. This is to ensure the tool effectively addresses their evolving needs and real‐world learning contexts. Design thinking is applied within the context of the well documented educational challenge of capturing students' interactions with feedback ( traceability ), specifically to capture, analyse and visualise students' interactions with feedback (i.e., feedback traceability). Methods Throughout the design process of the tool, various design thinking phases were conducted, revisited or repeated, involving a total of 86 higher education students across various phases through a participatory approach. A range of design and research activities were employed at each phase, including focus group discussions, design sprints, prototype validation and interviews. Results and Conclusions This paper contributes to human‐centred learning analytics by providing a detailed account of the application of design thinking in the development of an LA tool. It illustrates the non‐linear use of various design phases to identify and translate six key student requirements to 8 design decisions for tool development. Students perceived the tool as helpful in consolidating and analysing feedback, planning next steps and improving grades by understanding common strengths and weaknesses. Additionally, the paper presents the resulting LA tool, which enables feedback traceability and documents its journey from ideation to full deployment and evaluation in an authentic learning environment. The paper concludes with key recommendations for managing student and research needs in LA tool development, along with strategies for balancing research and design tensions and offers insights to guide other researchers and designers.
Maheshi et al. (Thu,) studied this question.