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#edge computing Open access

Design and Deployment of an Open-Source LMS Architecture for Hybrid Pre-Laboratory Instruction: An Open edX Implementation Case Study

Sep 2026 · international journal of engineering trends and technology · 0 citations

TL;DR

An open-source Learning Management System architecture supporting hybrid pre-laboratory instruction in a resource-constrained university setting is reported, together with a quantified account of its capacity envelope and its limits.

Abstract

This paper reports the design, implementation and deployment of an open-source Learning Management System (LMS) architecture supporting hybrid pre-laboratory instruction in a resource-constrained university setting. The platform was deployed with Tutor, the Docker-based distribution of Open edX, on a single virtual private server with four virtual CPU cores and 4 GB of RAM, with DNS and TLS resolution provided by Cloudflare. The architecture is layered across infrastructure, platform, course content and data processing. Two pre-laboratory modules were delivered through short instructional videos, auto-graded formative quizzes and an embedded interactive serious game, and the engineering trade-offs of third-party tool integration without a Learning Tools Interoperability bridge are analysed. A four-stage learning analytics pipeline extracts learner activity from the LMS gradebook, selects valid engagement signals and computes a composite engagement index. Operational validation over a continuous 58-day production period shows a mean edge response time of 67.3 ms (SD 14.0 ms, n = 20), an application-tier saturation throughput of approximately 74 requests per second, and zero failed requests across 1,600 load-test requests at concurrency levels from 5 to 50. Across the deployed cohort, 82.4% of learners in Module CS101 (n = 17) and 77.3% in Module CS102 (n = 22) attempted at least one formative quiz, and the composite engagement index (n = 17) reached a mean of 76.5% (SD 33.8%, median 88.9%). The result is a low-cost, reproducible blueprint for hybrid digital instruction, together with a quantified account of its capacity envelope and its limits.

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