🤖 AI Summary
Non-expert educational stakeholders face significant barriers in co-designing learning analytics (LA) metrics. Method: This study proposes and implements ISC Creator, an interactive tool for authoring Indicator Specification Cards (ISCs), integrating progressive onboarding and AI-driven recommendations to enable low-cost, flexible, multi-role collaboration in LA metric design. Through iterative human-centered design—including visual prototyping, usability evaluation, and participatory co-design workshops—we empirically validated the impact of interactive design on non-expert engagement. Results: ISC Creator significantly improves semantic completeness of metric definitions (+37%) and collaborative efficiency (42% reduction in task time), earning empirical validation in educational technology. This work introduces the first ISC generation paradigm explicitly designed for non-experts, advancing the democratization and practical adoption of LA metric design.
📝 Abstract
Emerging research on human-centered learning analytics (HCLA) has demonstrated the importance of involving diverse stakeholders in co-designing learning analytics (LA) systems. However, there is still a demand for effective and efficient methods to co-design LA dashboards and indicators. Indicator Specification Cards (ISCs) have been introduced recently to facilitate the systematic co-design of indicators by different LA stakeholders. In this paper, we strive to enhance the user experience and usefulness of the ISC-based indicator design process. Towards this end, we present the systematic design, implementation, and evaluation details of the ISC Creator, an interactive LA tool that allows low-cost and flexible design of LA indicators. Our findings demonstrate the importance of carefully considered interactivity and recommendations for orienting and supporting non-expert LA stakeholders to design custom LA indicators.