A comparative analysis of pre-service teachers’ readiness for AI integration

Artificial Intelligence (AI) is impacting the way we teach and learn. However, there are still substantial barriers to the integration of AI in educational settings, as teachers often lack the necessary competences to understand and use AI for pedagogical purposes. Therefore, in the early stages of teacher preparation, it is essential to assess the readiness of pre-service teachers for this transition in different initial teacher education (ITE) contexts. This study aims to investigate the readiness of pre-service teachers in Portugal and Spain to integrate AI into future teaching practices. To this end, a study was conducted with 203 pre-service teachers from both countries that compared results regarding different dimensions: trust in AI, knowledge of AI, digital competence and ITE training for AI. The study further examined the relations between these dimensions. The results showed no significant differences between the two countries for trust in AI, knowledge of AI and digital competence. Significant differences were observed for ITE training for AI, with the Spanish sample scoring higher. However, these differences were limited to the distinction between disagreement and neutrality, suggesting that pre-service teachers in both countries are not fully ready to integrate AI into their future teaching practices. The results also showed that ITE training for AI had almost no significant influence on both samples’ trust in AI, knowledge of AI and digital competence, suggesting that ITE in both countries are not integrating AI into their programmes. The study identifies aspects within ITE programmes that need to be reviewed to adequately qualify future teachers for AI readiness and provides practitioners, ITE providers and policy makers with insights to consider when updating ITE programmes. • Pre-service teachers' readiness may present an obstacle to AI integration in schools. • There is a pressing need to understand how ITE is preparing them to do so. • Spanish pre-service teachers score slightly higher in ITE training for AI. • Results show both samples are not fully ready to integrate AI into their future teaching. • ITE providers and policymakers in Portugal and Spain should consider the revision of ITE programmes.

Authors

Institutions

Publication Details

Journal
Computers and Education Artificial Intelligence
Published
2025-03-15
DOI
https://doi.org/10.1016/j.caeai.2025.100396
Citations
13
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
22.02

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A comparative analysis of pre-service teachers’ readiness for AI integration

Antonio Palacios‐Rodríguez, Pedro Bem‐Haja, Margarida Lucas, María del Carmen Llorente Cejudo et al.
13 citations
Computers and Education Artificial Intelligence
Online Learning and Analytics
22.02
article

A comparative analysis of pre-service teachers’ readiness for AI integration

Antonio Palacios‐Rodríguez, Pedro Bem‐Haja, Margarida Lucas, María del Carmen Llorente Cejudo, Yidi Zhang
article en
13 citations

Abstract

Artificial Intelligence (AI) is impacting the way we teach and learn. However, there are still substantial barriers to the integration of AI in educational settings, as teachers often lack the necessary competences to understand and use AI for pedagogical purposes. Therefore, in the early stages of teacher preparation, it is essential to assess the readiness of pre-service teachers for this transition in different initial teacher education (ITE) contexts. This study aims to investigate the readiness of pre-service teachers in Portugal and Spain to integrate AI into future teaching practices. To this end, a study was conducted with 203 pre-service teachers from both countries that compared results regarding different dimensions: trust in AI, knowledge of AI, digital competence and ITE training for AI. The study further examined the relations between these dimensions. The results showed no significant differences between the two countries for trust in AI, knowledge of AI and digital competence. Significant differences were observed for ITE training for AI, with the Spanish sample scoring higher. However, these differences were limited to the distinction between disagreement and neutrality, suggesting that pre-service teachers in both countries are not fully ready to integrate AI into their future teaching practices. The results also showed that ITE training for AI had almost no significant influence on both samples’ trust in AI, knowledge of AI and digital competence, suggesting that ITE in both countries are not integrating AI into their programmes. The study identifies aspects within ITE programmes that need to be reviewed to adequately qualify future teachers for AI readiness and provides practitioners, ITE providers and policy makers with insights to consider when updating ITE programmes. • Pre-service teachers' readiness may present an obstacle to AI integration in schools. • There is a pressing need to understand how ITE is preparing them to do so. • Spanish pre-service teachers score slightly higher in ITE training for AI. • Results show both samples are not fully ready to integrate AI into their future teaching. • ITE providers and policymakers in Portugal and Spain should consider the revision of ITE programmes.

Computers and Education Artificial IntelligenceVol. 8
Centre for Health Technology and Services Research (PT), University of Aveiro (PT), Universidad de Sevilla (ES)
Fundação para a Ciência e a Tecnologia
Quality Education
Openalex Percentile: Top 1%
Online Learning and Analytics
22.02
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.