DIGITAL LIBRARY
MODELLING TEACHERS’ INTENTION TO RE-USE DIGITAL EDUCATIONAL CONTENT
University of Zagreb, Faculty of Organization and Informatics (CROATIA)
About this paper:
Appears in: EDULEARN22 Proceedings
Publication year: 2022
Pages: 5543-5550
ISBN: 978-84-09-42484-9
ISSN: 2340-1117
doi: 10.21125/edulearn.2022.1306
Conference name: 14th International Conference on Education and New Learning Technologies
Dates: 4-6 July, 2022
Location: Palma, Spain
Abstract:
The “e-Schools: Development of the System of Digitally Mature Schools” project is carried out in Croatia with the aim to increase information and communication technology (ICT) usage in primary and secondary schools by developing ICT educational tools and services schools. Digital educational contents (DEC) are one of the tools developed for the needs of contemporary learning processes and are primarily focused on the students. In this paper we focus on teachers` intention to re-use DEC. While many researchers have highlighted the importance of continuance towards using an information technology, not many studies exist that focus on the continuation of the intention to use the same educational material. Our research fills the gap by examining teachers` intentions to re-use DEC. The objectives of this study are twofold:
(i) to measure the influence of teacher’s perception on intention to re-use DEC;
(ii) to study the effect of control variables (e.g. gender and school level) on the relationship between perception and intention.

To achieve the research objectives data was collected by questionnaire which investigated teachers' perceptions about the quality and satisfaction with DECs. The total of 1653 teachers participated in the online questionnaire after their students used DEC for a period of time in respected school subjects.

For development of teachers` intention predictive model, data mining was applied. CRISP DM process is used consisting of six steps:
(i) domain understanding,
(ii) data understanding,
(iii) data preparation,
(iv) modelling,
(v) evaluation and
(vi) deployment.

In the modelling phase, machine learning algorithm decision tree is applied. Sensitivity analysis of the predictive model indicated most important variables for intention prediction. Research results contribute to the understanding of continuation intention to use information technology.
Keywords:
Digital educational content, e-Schools, data mining, decision tree.