The Interaction between Chatbot Pattern and learning style to Develop English Vocabulary Skills for intermediate School Students in the UAE

This research investigates the interaction between chatbot patterns (linguistic and voice) and learning styles (visual and auditory) in developing English vocabulary skills among intermediate school students in the UAE. A quasi-experimental design was employed with four groups of male and female Grade 8 students (N = 72), categorized based on their learning styles (visual vs. auditory) and chatbot interaction patterns (linguistic-based vs. voice-based). The participants were randomly assigned to the following groups: Visual-Linguistic, Visual-Voice, Auditory-Linguistic, and Auditory-Voice. To achieve the research objectives, several instruments were utilized, including a Learning Style Questionnaire (based on the VARK model), an English Vocabulary Skills Checklist, and a Vocabulary Knowledge Skills Test (pre- and post-tests). The chatbot was implemented through a web-based platform and integrated within Teams, the school's official Learning Management System (LMS). Quantitative results revealed significant differences in vocabulary acquisition between pre-test and post-test scores across all groups, with the greatest improvements observed in the Visual-Linguistic group, followed by the Auditory-Voice, Auditory-Linguistic, and Visual-Voice groups. The results also showed significant differences between the linguistic and voice groups in favor of the linguistic chatbot, with a high impact, while no significant differences were found between visual and auditory groups, with only a low impact. These findings underscore the effectiveness of chatbot-based interventions in enhancing English vocabulary skills, particularly when chatbot interaction types are aligned with students' learning styles. The research recommends integrating chatbot technologies tailored to students' learning styles into English language curricula to improve vocabulary acquisition and overall language proficiency.

Authors

Publication Details

Journal
Technium Romanian Journal of Applied Sciences and Technology
Published
2025-04-23
DOI
https://doi.org/10.47577/technium.v29i.12741
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Interaction between Chatbot Pattern and learning style to Develop English Vocabulary Skills for intermediate School Students in the UAE

Mohamed Elsayed Elnaggar, Ahmed Adel Nouri Jumaa, Haggag Mohamed Haggag
Technium Romanian Journal of Applied Sciences and Technology
AI in Service Interactions
article

The Interaction between Chatbot Pattern and learning style to Develop English Vocabulary Skills for intermediate School Students in the UAE

Mohamed Elsayed Elnaggar, Ahmed Adel Nouri Jumaa, Haggag Mohamed Haggag
article en

Abstract

This research investigates the interaction between chatbot patterns (linguistic and voice) and learning styles (visual and auditory) in developing English vocabulary skills among intermediate school students in the UAE. A quasi-experimental design was employed with four groups of male and female Grade 8 students (N = 72), categorized based on their learning styles (visual vs. auditory) and chatbot interaction patterns (linguistic-based vs. voice-based). The participants were randomly assigned to the following groups: Visual-Linguistic, Visual-Voice, Auditory-Linguistic, and Auditory-Voice. To achieve the research objectives, several instruments were utilized, including a Learning Style Questionnaire (based on the VARK model), an English Vocabulary Skills Checklist, and a Vocabulary Knowledge Skills Test (pre- and post-tests). The chatbot was implemented through a web-based platform and integrated within Teams, the school's official Learning Management System (LMS). Quantitative results revealed significant differences in vocabulary acquisition between pre-test and post-test scores across all groups, with the greatest improvements observed in the Visual-Linguistic group, followed by the Auditory-Voice, Auditory-Linguistic, and Visual-Voice groups. The results also showed significant differences between the linguistic and voice groups in favor of the linguistic chatbot, with a high impact, while no significant differences were found between visual and auditory groups, with only a low impact. These findings underscore the effectiveness of chatbot-based interventions in enhancing English vocabulary skills, particularly when chatbot interaction types are aligned with students' learning styles. The research recommends integrating chatbot technologies tailored to students' learning styles into English language curricula to improve vocabulary acquisition and overall language proficiency.

Technium Romanian Journal of Applied Sciences and TechnologyVol. 29
Openalex Percentile: Top 96%
AI in Service Interactions
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.