Cyberbullying has garnered growing attention, yet existing research lacks nuanced insights into the dynamics of students' cyberbullying profiles and the associated risk factors across multiple domains. This study aims to (1) investigate K-12 students' cyberbullying profiles, (2) develop an AI predictive model for cyberbullying roles, and (3)…

This study presents a data mining approach to predict academic success of the first-year students. A dataset of 10 academic years for first-year bachelor's degrees from a Portuguese Higher Institution (N = 9652) has been analysed. Features' selection resulted in a characterising set of 68 features, encompassing socio-demographic, social origin,…

This study attempts to predict secondary school students' performance in English and Mathematics subjects using data mining (DM) techniques. It aims to provide insights into predictors of students' performance in English and Mathematics, characteristics of students with different levels of performance, the most effective DM technique for students'…

Recent trends in "educational technology" have led to emergence of methods such as teaching analytics (TA) in understanding and management of the teaching-learning processes. Didactically, "teaching analytics" is one of the promising and emerging methods within the Education domain that have proved to be useful, towards…

The main drive for this study is to look into potential predictors of educational achievement using OECD's original Pisa 2018 dataset. This paper explores (i) access to ICT, (ii) physical characteristics of learning environment at school, (iii) quality of teaching staff and educational material, (iv) student characteristics and learning climate,…