Perceptions of pre-service teachers toward Artificial Intelligence integration in education

This study examines the perceptions of pre-service teachers regarding the integration of Artificial Intelligence (AI) into educational practices. As AI technologies increasingly permeate educational settings, understanding the perspectives of future educators is critical for effective implementation. This research investigates pre-service teachers’ readiness to adopt AI, the challenges they encounter, and the influence of demographic factors such as gender, academic discipline, and prior technological exposure on their perceptions. A sample of 60 pre-service teachers from the District Institute of Education and Training (DIET) in Guntur district, India, participated in the study. Data were collected using a validated questionnaire and analyzed through statistical methods to identify perceptual differences across groups. Results reveal significant individual variations in perceptions but no statistically significant differences based on gender, academic discipline, or technological exposure. The findings underscore the necessity for targeted AI training within teacher education curricula to prepare future educators for seamless AI integration. This research offers critical insights for policymakers and educators aiming to foster AI adoption in education.

Authors

Publication Details

Journal
International Journal of Science and Research Archive
Published
2025-06-27
DOI
https://doi.org/10.30574/ijsra.2025.15.3.1908
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Perceptions of pre-service teachers toward Artificial Intelligence integration in education

Sandeep Talluri
International Journal of Science and Research Archive
Online Learning and Analytics
article

Perceptions of pre-service teachers toward Artificial Intelligence integration in education

Sandeep Talluri
article en

Abstract

This study examines the perceptions of pre-service teachers regarding the integration of Artificial Intelligence (AI) into educational practices. As AI technologies increasingly permeate educational settings, understanding the perspectives of future educators is critical for effective implementation. This research investigates pre-service teachers’ readiness to adopt AI, the challenges they encounter, and the influence of demographic factors such as gender, academic discipline, and prior technological exposure on their perceptions. A sample of 60 pre-service teachers from the District Institute of Education and Training (DIET) in Guntur district, India, participated in the study. Data were collected using a validated questionnaire and analyzed through statistical methods to identify perceptual differences across groups. Results reveal significant individual variations in perceptions but no statistically significant differences based on gender, academic discipline, or technological exposure. The findings underscore the necessity for targeted AI training within teacher education curricula to prepare future educators for seamless AI integration. This research offers critical insights for policymakers and educators aiming to foster AI adoption in education.

International Journal of Science and Research ArchiveVol. 15(3)
Openalex Percentile: Top 85%
Online Learning and Analytics
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.

Perceptions of pre-service teachers toward Artificial Intelligence integration in education — Sandeep Talluri · International Journal of Science and Research Archive (2025) | TGRS Research Map | TGRS