From Configuration to Cognition: A Computational Thinking Approach to Computing Infrastructure Education

Authors

  • S. Thiruchadai Pandeeswari Assistant Professor, Thiagarajar College of Engineering, Madurai-15
  • G. Vennila Department of Information Technology, Thiagarajar College of Engineering, Madurai-15

DOI:

https://doi.org/10.16920/jeet/2026/v39is2/26048

Keywords:

Computational Thinking, Algorithmic Thinking, IT Infrastructure, Computing Infrastructure, Infrastructure Studies.

Abstract

AI innovations have led to unprecedented demand and growth in computing infrastructure domain, creating promising avenue of employment for role-ready Engineering graduates. In this context, computing infrastructure studies garner special focus. Though there are several studies on integrating CT skills in K-12 and Engineering Education, thre are few to none on integrating CT skills into Computing Infrastructure education. This study aims at proposing a unified framework for integration of Computational Thinking (CT) skills into the course design, delivery and assessment of computing infrastructure studies targeting undergraduate Engineering students of IT discipline. The proposed approach is implemented for a foundational course on IT Infrastructure, with a focus on enhancing student cognition and problem-solving capabilities. A structured pedagogical approach is employed to map course activities to core CT components—Decomposition, Pattern Recognition, Abstraction, and Algorithmic Thinking—using Bloom’s taxonomy for skill-level alignment. A carefully planned Assessment framework to evaluate the attainment of CT skills through guided activities is also proposed. Quantitative evaluation of the proposed approach was conducted by considering the performance of 120 students across eight assessment items, with correlation mapping and Cronbach’s alpha used to validate the reliability of the skill measurement. Results indicated strong correlations among Pattern Recognition, Abstraction, and Algorithmic Thinking, with Cronbach’s alpha values for Decomposition and Algorithmic Thinking approaching the benchmark of 0.7, confirming acceptable consistency. Performance distributions showed high class averages, narrow interquartile ranges, and minimal outliers, suggesting effective learning outcomes. Perception-based evaluation using a Likert-scale survey revealed uniformly positive student feedback, with average ratings between 4.27 and 4.54, indicating a strong sense of CT skill acquisition. The findings demonstrate that integrating CT skills into course pedagogy can significantly improve technical proficiency, cognitive engagement, and student confidence in solving computing infrastructure-related problems.

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Published

2026-02-17

How to Cite

Thiruchadai Pandeeswari, S., & Vennila, G. (2026). From Configuration to Cognition: A Computational Thinking Approach to Computing Infrastructure Education. Journal of Engineering Education Transformations, 39(Special Issue 2), 397–406. https://doi.org/10.16920/jeet/2026/v39is2/26048

Issue

Volume 39, Special Issue 2, January 2026

Section

Articles
Crossref
Scopus
Google Scholar
Europe PMC

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