Exploring Teacher Trainees’ Perspectives on Integrating Artificial Intelligence (AI) Into Primary School Science Education: A Case Study

The integration of Artificial Intelligence (AI) in education has become a significant area of research due to its potential to transform teaching and learning (T&L) processes. However, little is known about the perspectives of teacher trainees regarding AI integration in primary school science education. This study addresses this gap by exploring the attitudes, beliefs and concerns of teacher trainees toward AI implementation. The primary objective is to identify the possibility, challenges and effectiveness of AI in primary school science teaching. This study is grounded in the Technology Acceptance Model (TAM), which assess users’ acceptance of new technologies. A qualitative case study design is employed using structured interviews with four purposively selected teacher trainees. The collected data undergo thematic analysis to uncover patterns and themes related to AI integration. The findings provided that AI has the potential to transform science teaching by offering personalised learning experiences and making abstract concepts more accessible through visualisations and simulations. However, significant challenges remain including inadequate teacher training and unequal access to AI tools especially in rural areas. The study concludes that while AI presents great opportunities for enhancing primary science education, address barriers like training and access is critical for its successful integration.

Authors

Publication Details

Journal
International Journal of Research and Innovation in Social Science
Published
2025-01-01
DOI
https://doi.org/10.47772/ijriss.2025.90300120
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

Exploring Teacher Trainees’ Perspectives on Integrating Artificial Intelligence (AI) Into Primary School Science Education: A Case Study

Samri Chongo, Lee Er
International Journal of Research and Innovation in Social Science
Online Learning and Analytics
article

Exploring Teacher Trainees’ Perspectives on Integrating Artificial Intelligence (AI) Into Primary School Science Education: A Case Study

Samri Chongo, Lee Er
article en

Abstract

The integration of Artificial Intelligence (AI) in education has become a significant area of research due to its potential to transform teaching and learning (T&L) processes. However, little is known about the perspectives of teacher trainees regarding AI integration in primary school science education. This study addresses this gap by exploring the attitudes, beliefs and concerns of teacher trainees toward AI implementation. The primary objective is to identify the possibility, challenges and effectiveness of AI in primary school science teaching. This study is grounded in the Technology Acceptance Model (TAM), which assess users’ acceptance of new technologies. A qualitative case study design is employed using structured interviews with four purposively selected teacher trainees. The collected data undergo thematic analysis to uncover patterns and themes related to AI integration. The findings provided that AI has the potential to transform science teaching by offering personalised learning experiences and making abstract concepts more accessible through visualisations and simulations. However, significant challenges remain including inadequate teacher training and unequal access to AI tools especially in rural areas. The study concludes that while AI presents great opportunities for enhancing primary science education, address barriers like training and access is critical for its successful integration.

International Journal of Research and Innovation in Social ScienceVol. IX(III)
Openalex Percentile: Top 94%
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.