Teaching Integration Testing using VARK-based activities

Software testing is an essential aspect of software development, ensuring the reliability, functionality, and overall quality of software products. Integration testing, a critical phase in the testing hierarchy, verifies interactions between software components. However, teaching integration testing presents challenges due to its complexity and abstract nature. To address these issues, this study explores the use of the VARK learning model - Visual, Auditory, Reading/Writing, and Kinesthetic - to design and implement multimodal activities that cater to diverse learning styles. A cohort of students engaged in VARK-based activities aimed at improving their understanding of integration testing concepts. The results indicated improved student engagement and comprehension, with participants demonstrating a greater ability to apply theoretical knowledge in practical testing scenarios (increase correctness from 80% to 93% and from 50% to 70% for several testing concepts). Around 60% of students agreed that VARK learning created a better understanding of how to use and apply integration testing. This paper discusses the implementation of these activities, their outcomes, and the potential of VARK-based approaches to advance technical education, especially in software engineering. These findings provide insights for educators looking for innovative methods to teach complex technical concepts effectively.

Authors

Institutions

Publication Details

Journal
Procedia Computer Science
Published
2025-01-01
DOI
https://doi.org/10.1016/j.procs.2025.09.270
Primary Topic
Software Testing and Debugging Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Teaching Integration Testing using VARK-based activities

Nadejde Camelia-Petrina, Gaceanu Radu, Vescan Andreea
Procedia Computer Science
Software Testing and Debugging Techniques
article

Teaching Integration Testing using VARK-based activities

Nadejde Camelia-Petrina, Gaceanu Radu, Vescan Andreea
article en

Abstract

Software testing is an essential aspect of software development, ensuring the reliability, functionality, and overall quality of software products. Integration testing, a critical phase in the testing hierarchy, verifies interactions between software components. However, teaching integration testing presents challenges due to its complexity and abstract nature. To address these issues, this study explores the use of the VARK learning model - Visual, Auditory, Reading/Writing, and Kinesthetic - to design and implement multimodal activities that cater to diverse learning styles. A cohort of students engaged in VARK-based activities aimed at improving their understanding of integration testing concepts. The results indicated improved student engagement and comprehension, with participants demonstrating a greater ability to apply theoretical knowledge in practical testing scenarios (increase correctness from 80% to 93% and from 50% to 70% for several testing concepts). Around 60% of students agreed that VARK learning created a better understanding of how to use and apply integration testing. This paper discusses the implementation of these activities, their outcomes, and the potential of VARK-based approaches to advance technical education, especially in software engineering. These findings provide insights for educators looking for innovative methods to teach complex technical concepts effectively.

Procedia Computer ScienceVol. 270
Babeș-Bolyai University (RO)
Openalex Percentile: Top 66%
Software Testing and Debugging Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.