Learning styles and academic performance in engineering students: A pre- and pos-pandemic bibliometric study

Introduction: The relationship between learning styles and academic performance has gained significant attention, particularly in engineering education, as it plays an important role in enhancing the quality of the learning process. This study aims to provide a comprehensive bibliometric analysis of research trends in this field, focusing on pre- and post-pandemic periods. Methods: A total of 1397 articles from the Scopus database were analyzed using VOSviewer software to map the scientific production until 2023. The analysis was divided into two periods: 2016-2019 and 2020-2023, identifying clústers of research focused on learning styles, academic performance, and the growing importance of e-learning post-pandemic.Results: Five main clústers were identified between 2016-2019, including learning styles, the development of evaluation instruments, psychological aspects, curricular development, and general learning. In the post-pandemic period, three dominant clústers emerged, focused on learning styles, academic performance, and e-learning. Co-authorship analysis revealed changes in collaboration patterns, with increased global cooperation, particularly in the United States, China, and Spain during the 2020-2023 period. Conclusions: The study highlights the increasing relevance of research on learning styles and the shift toward remote learning triggered by the pandemic. These findings underscore the need for further exploration of adaptive teaching strategies to diverse learning preferences in the evolving educational landscape.

Authors

Institutions

Publication Details

Journal
Data & Metadata
Published
2025-02-13
DOI
https://doi.org/10.56294/dm2025197
Primary Topic
Learning Styles and Cognitive Differences
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Learning styles and academic performance in engineering students: A pre- and pos-pandemic bibliometric study

Fernando Ramírez-Paredes, José Jácome, Silvia Arciniega, Stefany Flores et al.
Data & Metadata
Learning Styles and Cognitive Differences
article

Learning styles and academic performance in engineering students: A pre- and pos-pandemic bibliometric study

Fernando Ramírez-Paredes, José Jácome, Silvia Arciniega, Stefany Flores, Mateo Chancosi
article en

Abstract

Introduction: The relationship between learning styles and academic performance has gained significant attention, particularly in engineering education, as it plays an important role in enhancing the quality of the learning process. This study aims to provide a comprehensive bibliometric analysis of research trends in this field, focusing on pre- and post-pandemic periods. Methods: A total of 1397 articles from the Scopus database were analyzed using VOSviewer software to map the scientific production until 2023. The analysis was divided into two periods: 2016-2019 and 2020-2023, identifying clústers of research focused on learning styles, academic performance, and the growing importance of e-learning post-pandemic.Results: Five main clústers were identified between 2016-2019, including learning styles, the development of evaluation instruments, psychological aspects, curricular development, and general learning. In the post-pandemic period, three dominant clústers emerged, focused on learning styles, academic performance, and e-learning. Co-authorship analysis revealed changes in collaboration patterns, with increased global cooperation, particularly in the United States, China, and Spain during the 2020-2023 period. Conclusions: The study highlights the increasing relevance of research on learning styles and the shift toward remote learning triggered by the pandemic. These findings underscore the need for further exploration of adaptive teaching strategies to diverse learning preferences in the evolving educational landscape.

Data & MetadataVol. 4
Universidad Técnica del Norte (EC)
Openalex Percentile: Top 94%
Learning Styles and Cognitive Differences
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.