Date of Award

5-7-2026

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Computer Science

First Advisor

Aryabrata Basu

Abstract

Extended Reality (XR) environments are increasingly used for training, simulation, and skill development. However, conventional feedback mechanisms such as summary performance scores or first-person video recordings often lack the spatial and contextual detail necessary to support effective reflective learning. As a result, users may observe what occurred during an immersive task without fully understanding how their movement strategies and navigation decisions influenced performance outcomes. This work presents DataEcho, a telemetry-driven replay framework designed to capture, store, and reconstruct structured XR session data for interactive performance review and behavioral analysis. The system records frame-level telemetry from Unity-based XR applications, including object transformations, input device states, and task events, and streams this data to a backend ingestion service for storage and processing. Recorded sessions are reconstructed in a web-based 3D interface that allows temporal playback, trajectory visualization, and multi-perspective exploration of user behavior. The architecture emphasizes structured data modeling, replay fidelity, and scalable telemetry management while maintaining minimal runtime overhead during immersive tasks. To evaluate the effectiveness of reflective telemetry replay, a controlled user study (n = 25) was conducted using a virtual office navigation task across two sessions separated by one day. Participants were randomly assigned to either a replay-review condition or a no-review control condition. Behavioral changes between sessions were analyzed using telemetry-derived navigation metrics capturing path efficiency, route reversals, decisiveness of movement, and head-orientation stability. Participants who accessed interactive replay demonstrated significantly greater improvements in decisiveness during navigation compared to the control group, with additional directional trends suggesting reduced hesitation and more stable route commitment. These findings support the effectiveness of structured telemetry replay as a mechanism for enhancing performance analysis and reflective learning in XR environments.

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