Journal of Smart Education and Emerging Technology
Vol 1 No 2 (2026) : January

Development and Evaluation of an Interactive E-Module for Virtualization and Cloud Technology Learning in Computer Engineering Education

Rhesky Annisa Basri (Universitas Negeri Makassar)
Jumadi Mabe Parenreng (Universitas Negeri Makassar)
Mustari S. Lamada (Universitas Negeri Makassar)



Article Info

Publish Date
25 Jan 2026

Abstract

Background/Context: The transformation of learning in higher education requires the availability of structured and interactive digital teaching materials that support independent and practice-based learning. In the Virtualisation and Cloud Technology course, the limited availability of standardised learning modules has resulted in suboptimal learning processes and inconsistencies in students’ learning outcomes. Objective/Purpose: his study aimed to develop an electronic module (e-module) for the Virtualisation and Cloud Technology course in the Computer Engineering Study Programme at Makassar State University to enhance learning effectiveness, conceptual understanding, and students practical skills. Method: This study employed a research and development approach using the 4D model, which consists of the define, design, develop, and disseminate stages. The e-module was validated by subject matter experts and media experts, followed by small-group and large-group trials. Its effectiveness was evaluated through pre-test and post-test assessments. Results: The validation results indicated that the e-module demonstrated very high quality in terms of content and media design. Student responses showed that the e-module was practical to use and supported the learning process. Furthermore, the implementation of the e-module significantly improved students’ learning outcomes and promoted independent learning as well as deeper conceptual understanding. Conclusion: The developed Virtualisation and Cloud Technology e-module was found to be valid, practical, and effective as a digital learning resource. Its use contributes positively to improving learning outcomes and the overall quality of instruction, making it suitable for implementation in higher education, particularly in technology- and practice-oriented courses.

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Journal Info

Abbrev

JSEET

Publisher

Subject

Computer Science & IT Education

Description

Artificial Intelligence in Education (AIED), exploring intelligent and adaptive educational applications that support learning and teaching. Machine Learning in Education, focusing on predictive and adaptive models for learning support, personalization, and educational decision-making. Deep Learning ...