Open AccessA Preliminary Investigation of the Technology Acceptance Model (TAM) in Early Childhood Education and Care
Author(s) -
Dana Rad,
Anca Egerău,
Alina Felicia Roman,
Tiberiu Dughi,
Evelina Balaș,
Roxana Maier,
Sonia Ignat,
Gavril Rad
Publication year - 2022
Publication title -
broad research in artificial intelligence neuroscience
Language(s) - English
Resource type - Journals
eISSN - 2067-3957
pISSN - 2068-0473
DOI - 10.18662/brain/13.1/297
Subject(s) - technology acceptance model , theory of planned behavior , construct (python library) , psychology , variance (accounting) , psychological intervention , information technology , perspective (graphical) , knowledge management , applied psychology , computer science , business , usability , control (management) , operating system , accounting , human–computer interaction , artificial intelligence , psychiatry , programming language
The technology acceptance model (TAM) is a well-known postmodern idea that explains how humans adopt and use new technologies. The model focuses on variables that impact behavioral intention to use new technology from the perspective of the end user. The purpose of this study was to construct a viable questionnaire for assessing preschool teachers' technology acceptability in online instruction in ECEC, based on data collected from 182 Romanian preschool instructors, using the theory of planned behavior framework. Our application of theory of planned behavior in technology adoption in ECEC is extraordinarily good, with 66 percent explained variance of actual usage of technology in class. The research literature supports the findings that the intention to use technology and a good attitude toward technology are the most significant determinants of actual technology usage. Although more research is needed in larger and more complex samples to confirm these findings, there is compelling evidence that the prediction methodology can be used to predict preschool teachers' level of technology acceptance and assist educational decision-makers in designing timely interventions that improve the chances of success. The study's major findings point to crucial variables that might help national educational decision-makers improve technology adoption in ECEC.