ReflectEd: Evaluating Reflection-Driven Learning in an AI-Assisted System
Md Nazmus Sakib, Ishika Tarin, Naga Manogna Rayasam, Manas Gaur, Sanorita Dey

TL;DR
ReflectEd is an AI-assisted system designed to enhance reflection between checkpoints in collaborative work, improving engagement, actionability, and coordination, while revealing trade-offs between reflection depth and effort.
Contribution
This paper introduces ReflectEd, a novel AI-supported reflection system with structured prompts and scaffolding, and evaluates its impact on collaboration and reflection quality.
Findings
Deeper reflections increased actionability and planning.
Reflections supported coordination and accountability.
Deeper reflection required more effort and was less sustainable.
Abstract
In collaborative settings, sustaining momentum and engagement between checkpoints (e.g., meetings) can be challenging, often leading to task drift and reduced preparedness. To address this gap, we developed ReflectEd, an AI-assisted system that supports between-checkpoint reflection through theory-driven prompts with progressively structured levels and mechanism-based scaffolding. We evaluated ReflectEd in a mixed-method study comparing two reflection configurations: a regular reflection workflow and a deeper reflection workflow that included an additional transformative reflection activity. Across conditions, participants reported steady engagement early in the week. In the deeper configuration, later reflections tended to exhibit higher actionability and richer forward-looking planning, while also being harder to sustain and more effortful during periods of active work.…
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Taxonomy
TopicsTeam Dynamics and Performance · Personal Information Management and User Behavior · Innovative Human-Technology Interaction
