Learning Analytics-Driven Student Monitoring: Design and Evaluation of a Real-Time Feedback Toolkit

This study explores the user experience of the Traffic Signals Toolkit, a teaching innovation designed for Data and Information Visualization, an undergraduate elective course. Using the intuitive red–yellow–green metaphor, the toolkit supports both student self-regulation and instructor monitoring by signaling levels of understanding in real time. Data were collected from 75 students across two semesters through entrance surveys, an interactive exercise, and exit surveys. Results show significant gains in conceptual understanding, technical skills, independence, and error-handling, with survey comparisons confirming improvements across all five measured dimensions. Toolkit signals further demonstrated a clear progression from confusion to mastery. Students valued its clarity and reflective prompts, while instructors benefited from actionable insights. The findings suggest that this scalable, low-barrier approach has broader potential for enhancing pedagogy in data-intensive learning contexts.

Learning tool, real-time feedback, information visualization, learning analytics

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