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Ricardo Matheus; Stuti Saxena; Charalampos Alexopoulos – International Journal of Information and Learning Technology, 2024
Purpose: The purpose of the study is to understand the moderating impact of perceived technological innovativeness (PTI) in terms of gender differences as far as adoption and usage of Open Government Data (OGD) is concerned. Design/methodology/approach: Partial least squares-structural equation modelling (PLS-SEM) methodological approach is used…
Descriptors: Gender Differences, Technological Advancement, Data Use, Foreign Countries
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Ean Teng Khor; Dave Darshan – International Journal of Information and Learning Technology, 2024
Purpose: This study leverages social network analysis (SNA) to visualise the way students interacted with online resources and uses the data obtained from SNA as features for supervised machine learning algorithms to predict whether a student will successfully complete a course. Design/methodology/approach: The exploration and visualisation of the…
Descriptors: Prediction, Academic Achievement, Electronic Learning, Artificial Intelligence
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Hui, Bowen – International Journal of Information and Learning Technology, 2022
Purpose: The purpose of this work is to illustrate the processes involved in managing teams in order to assist designers and developers to build software that support teamwork. A deeper investigation into the role of team analytics is discussed in this article. Design/methodology/approach: Many researchers over the past several decades studied the…
Descriptors: Design, Guidelines, Research Needs, Teamwork
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Mason, Claire M.; Chen, Haohui; Evans, David; Walker, Gavin – International Journal of Information and Learning Technology, 2023
Purpose: This paper aims to demonstrate how skills taxonomies can be used in combination with machine learning to integrate diverse online datasets and reveal skills gaps. The purpose of this study is then to show how the skills gaps revealed by the integrated datasets can be used to achieve better labour market alignment, keep educational…
Descriptors: Taxonomy, Artificial Intelligence, Data Collection, Data Analysis