The transformation of higher education in the Industry 4.0 and Society 5.0 eras demands an intelligent learning model capable of dynamically aligning student competencies with the needs of the digital industry. This research develops EduLinkMatch, a web-based intelligent e-learning model integrated with a virtual laboratory using Cisco Packet Tracer in physicalmode. The core technical innovation lies in the Learning Analytics Engine, whichcontinuously collects and processes performance logs from virtual laboratory activities(e.g., configuration errors, task completion status, average completion time, and topologyvalidation results). This data is analyzed through a rule-based diagnostic mechanism andthreshold-based performance indicators, which drive an adaptive feedback module thatrecommends remedial tasks, additional simulations, or targeted resources through acompetency dashboard. This research adopts a Research and Development (R&D) approachusing the ADDIE framework, focusing on the Analysis, Design, and Development phases.System trials with 150 students in the Computer Networks course and validation by 10experts have been conducted. The results showed that all modules functioned correctlybased on Black Box Testing, the success rate of student assignments reached 92%, theaverage completion time was 24 minutes, and student satisfaction scores ranged from 4.3to 4.5 (Likert 1–5). Expert validation yielded an average Aiken V = 0.875 and Fleiss κ =0.91, indicating high interrater validity and reliability. The main contribution of this studyis the presentation of an integrated intelligent e-learning model that combines virtuallaboratories, learning analytics, and adaptive feedback in a single system, which provides atechnical blueprint for competency-based vocational learning systems in developingcountries. © 2025 The authors. This article is published by IIETA and is licensed under the CC BY 4.0 license (http://creativecommons.org/licenses/by/4.0/).
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