SLADE: A method for designing human-centred Learning Analytics Systems

There is a growing interest in creating Learning Analytics (LA) systems that incorporate student perspectives. Yet, many LA systems still lean towards a technology-centric approach, potentially overlooking human values and the necessity of human oversight in automation. Although some recent LA studies have adopted a human-centred design stance, there is still limited research on establishing safe, reliable, and trustworthy systems during the early stages of LA design. Drawing from a newly proposed framework for human-centred artificial intelligence, we introduce SLADE, a method for ideating and identifying features of human-centred LA systems that balance human control and computer automation. We illustrate SLADE's application in designing LA systems to support collaborative learning in healthcare. Twenty-one third-year students participated in design sessions through SLADE's four steps: i) identifying challenges and corresponding LA systems; ii) prioritising these LA systems; iii) ideating human control and automation features; and iv) refining features emphasising safety, reliability, and trustworthiness. Our results demonstrate SLADE's potential to assist researchers and designers in: 1) aligning authentic student challenges with LA systems through both divergent ideation and convergent prioritisation; 2) understanding students' perspectives on personal agency and delegation to teachers; and 3) fostering discussions about the safety, reliability, and trustworthiness of LA solutions.