Visual literacy among students and its relationship with interpreting infographics and decision-making within a learning management system

Objectives This study investigated visual literacy levels among students in the “Introduction to Educational Technology” course at the College of Basic Education, PAAET in Kuwait and examined their relationships with infographic interpretation and decision-making within a Learning Management System (LMS). It also tested the effect of an integrated intelligent learning assistant. Methodology A descriptive–correlational approach with a quasi-experimental pre-test/post-test design was used. Data were collected from N = 168 students (2023–2024). Visual literacy was measured using a researcher-developed Visual Literacy Test validated for this study. Validity evidence included expert content review (S-CVI = .92), exploratory and confirmatory factor analysis supporting a three-factor structure ( χ 2 /df = 1.55; CFI = .91; TLI = .90; RMSEA = .057; SRMR = .068), and acceptable internal consistency (Cronbach's α = .89; McDonald's ω = .90). Infographic interpretation and decision-making were assessed through practical Moodle tasks. Within-group changes were examined using paired-samples t-tests. Between-group differences were examined primarily using ANCOVA, with pre-test scores as covariates, supplemented by independent-samples t-tests of unadjusted post-test scores. Additional analyses included Pearson correlations, multiple linear regression, and ANOVA. Results Visual literacy correlated positively with infographic interpretation ( r = .71, p < .01) and decision-making ( r = .68, p < .01). After adjusting for pre-test scores, the experimental group outperformed the control group on visual literacy, infographic interpretation, and decision-making (all p < .001), with large effects. Unadjusted post-test scores also favored the experimental group over the control group (visual literacy: M = 82.1 vs. 70.9; p < .001), with large effects (Cohen's d ≈ 1.03–1.34). The assistant was associated with improvements of about 34% (infographic interpretation) and 29% (decision-making). Conclusion Developing visual literacy is essential in the digital age. Intelligent learning assistants may support these competencies when embedded in LMS-supported coursework. The study recommends systematic integration of visual-literacy training and policies that support evidence-based investment in smart educational technologies. Given the quasi-experimental design, findings should be interpreted as group differences and associations rather than definitive causal effects.

Authors

Institutions

Publication Details

Journal
Frontiers in Education
Published
2026-11-04
DOI
https://doi.org/10.3389/feduc.2026.1943596
Primary Topic
Literacy, Media, and Education
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Visual literacy among students and its relationship with interpreting infographics and decision-making within a learning management system

Ahmad Alfailakawi, Abdulaziz Alenizi
Frontiers in Education
Literacy, Media, and Education
article

Visual literacy among students and its relationship with interpreting infographics and decision-making within a learning management system

Ahmad Alfailakawi, Abdulaziz Alenizi
article en

Abstract

Objectives This study investigated visual literacy levels among students in the “Introduction to Educational Technology” course at the College of Basic Education, PAAET in Kuwait and examined their relationships with infographic interpretation and decision-making within a Learning Management System (LMS). It also tested the effect of an integrated intelligent learning assistant. Methodology A descriptive–correlational approach with a quasi-experimental pre-test/post-test design was used. Data were collected from N = 168 students (2023–2024). Visual literacy was measured using a researcher-developed Visual Literacy Test validated for this study. Validity evidence included expert content review (S-CVI = .92), exploratory and confirmatory factor analysis supporting a three-factor structure ( χ 2 /df = 1.55; CFI = .91; TLI = .90; RMSEA = .057; SRMR = .068), and acceptable internal consistency (Cronbach's α = .89; McDonald's ω = .90). Infographic interpretation and decision-making were assessed through practical Moodle tasks. Within-group changes were examined using paired-samples t-tests. Between-group differences were examined primarily using ANCOVA, with pre-test scores as covariates, supplemented by independent-samples t-tests of unadjusted post-test scores. Additional analyses included Pearson correlations, multiple linear regression, and ANOVA. Results Visual literacy correlated positively with infographic interpretation ( r = .71, p < .01) and decision-making ( r = .68, p < .01). After adjusting for pre-test scores, the experimental group outperformed the control group on visual literacy, infographic interpretation, and decision-making (all p < .001), with large effects. Unadjusted post-test scores also favored the experimental group over the control group (visual literacy: M = 82.1 vs. 70.9; p < .001), with large effects (Cohen's d ≈ 1.03–1.34). The assistant was associated with improvements of about 34% (infographic interpretation) and 29% (decision-making). Conclusion Developing visual literacy is essential in the digital age. Intelligent learning assistants may support these competencies when embedded in LMS-supported coursework. The study recommends systematic integration of visual-literacy training and policies that support evidence-based investment in smart educational technologies. Given the quasi-experimental design, findings should be interpreted as group differences and associations rather than definitive causal effects.

Frontiers in EducationVol. 11
Public Authority for Applied Education and Training (KW), Basic Education College (KW)
Openalex Percentile: Top 3%
Literacy, Media, and Education
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.

Laika access coming soon