Detecting Innovators in the Field: Teachers’ Perceptions and Adoption of Generative AI in Education

The adoption of Generative Artificial Intelligence (GenAI) has gained popularity since late 2022, sparking discussions about its role in education. An important issue is understanding teachers' perceptions of this technology, given that teachers are seen as key actors in integrating GenAI into teaching and learning processes. This qualitative research explores secondary school teachers' perceptions of GenAI, using an adapted Technology Acceptance Model (TAM) and Rogers' Diffusion of Innovation Model. TAM, known for assessing user acceptance of technology, was employed to gauge perceptions, while Rogers' model provided insights into how teachers distribute across GenAI adoption stages, from innovators to late adopters. Data was collected through semi-structured interviews and an online survey with 20 in-service teachers from Flanders, Belgium. Findings reveal mixed attitudes among teachers towards GenAI, as participants express enthusiasm about its potential for time-saving and personalized learning benefits, while also voicing significant concerns about plagiarism, GenAI’s trustworthiness, and its possible negative impact on students’ cognitive abilities. The study also highlights the current lack of sufficient training and support for teachers integrating GenAI.

Authors

Institutions

Publication Details

Journal
The Open/Technology in Education Society and Scholarship Association Journal
Published
2025-05-20
DOI
https://doi.org/10.18357/otessaj.2025.5.1.89
Citations
1
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
1.69
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Detecting Innovators in the Field: Teachers’ Perceptions and Adoption of Generative AI in Education

Annelies Raes, Kristina Krushinskaia, Alanur Ahsen Dalyanci, Lobke Mast
1 citations
The Open/Technology in Education Society and Scholarship Association Journal
Online Learning and Analytics
1.69
article

Detecting Innovators in the Field: Teachers’ Perceptions and Adoption of Generative AI in Education

Annelies Raes, Kristina Krushinskaia, Alanur Ahsen Dalyanci, Lobke Mast
article en
1 citations

Abstract

The adoption of Generative Artificial Intelligence (GenAI) has gained popularity since late 2022, sparking discussions about its role in education. An important issue is understanding teachers' perceptions of this technology, given that teachers are seen as key actors in integrating GenAI into teaching and learning processes. This qualitative research explores secondary school teachers' perceptions of GenAI, using an adapted Technology Acceptance Model (TAM) and Rogers' Diffusion of Innovation Model. TAM, known for assessing user acceptance of technology, was employed to gauge perceptions, while Rogers' model provided insights into how teachers distribute across GenAI adoption stages, from innovators to late adopters. Data was collected through semi-structured interviews and an online survey with 20 in-service teachers from Flanders, Belgium. Findings reveal mixed attitudes among teachers towards GenAI, as participants express enthusiasm about its potential for time-saving and personalized learning benefits, while also voicing significant concerns about plagiarism, GenAI’s trustworthiness, and its possible negative impact on students’ cognitive abilities. The study also highlights the current lack of sufficient training and support for teachers integrating GenAI.

The Open/Technology in Education Society and Scholarship Association JournalVol. 5(1)
KU Leuven (BE)
Openalex Percentile: Top 10%
Online Learning and Analytics
1.69
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.