Learning style recognition is an indispensable part of achieving personalized learning in online learning systems. The traditional inventory method for learning style identification faces the limitations such as subject and static characteristics. Therefore, an automatic and reliable learning style recognition mechanism is designed in this…

There is a small window of opportunity at the beginning of semester for a university to provide commencing students with timely and targeted support. However, there is limited information available on interventions that identify and support disengaged students from equity groups without using equity group status as the basis for the contact. The…

The dropout of students is one of the major obstacles that ruin the improvement of higher education quality. To facilitate the study of students' dropout in Moroccan universities, this paper aims to establish a clustering approach model based on machine learning algorithms to determine Moroccan universities categories. Our objective in this…

This paper reports on teachers developing their own data literacy and then acting as data coaches for colleagues in their schools. The 13 teachers from 7 schools in the study analysed standardised data using a data conversation protocol to identify students with significant mathematical misconceptions. They then took data-informed action with…

The quality of the data and the amount of correct information available is key to informed decision-making. Higher education institutions (HEIs) often employ various decision support systems (DSSs) to make better choices. However, there is a lack of systems to assist with decision-making to promote innovation in teaching and learning. In this…

Evidence based decision making is essential for enabling improved student learning. Teacher motivations and beliefs about the types and use of data are critical determinants of decision making. Our research explored the types of data teachers use and consider valuable when measuring improvement in student learning. Findings from 294 teachers from…

Learning analytics have the potential to improve teaching and learning in K-12 education, but as student data is increasingly being collected and transferred for the purpose of analysis, it is important to take measures that will protect student privacy. A common approach to achieve this goal is the de-identification of the data, meaning the…

The purpose of this paper is to share insights gained from the discovery, design, and delivery phases of creating a three-tiered model of non-academic learning support in open, distance, and flexible learning (ODFL): "Learner Engagement and Success Services (LESS)", at Open Polytechnic | Te Pukenga, New Zealand. Presented as a case…

Background: Small private online courses (SPOCs) are one of the strategies to introduce the massive open online courses (MOOCs) within the university environment and to have these courses validates for academic credit. However, numerous researchers have highlighted that academic dishonesty is greatly facilitated by the online context in which…

Massive Open Online Massive Open Online Courses (MOOCs) have been transitioning slowly from being completely open and without clear recognition in universities or industry, to private settings through the emergence of Small and Massive Private Online Courses (SPOCs and MPOCs). Courses in these new formats are often for credit and have clear market…

The identification of predictor variables for students at-risk of dropping out of university has received increased attention in higher education settings internationally concerning the context of origin in which they are developed and the different academic context in which they are introduced, often lacking schema-theoretic perspectives to offer…

Rural teachers and educators are increasingly called upon to build partnerships with families who use languages other than English in the home (US DOE, 2016). This is equally true for rural schools, where the number of multilingual families is small, and the language and cultural backgrounds of students differs from those of school. This article…

E-learning platforms and processes face several challenges, among which is the idea of personalizing the e-learning experience and to keep students motivated and engaged. This work is part of a larger study that aims to tackle these two challenges using a variety of machine learning techniques. To that end, this paper proposes the use of k-means…

Over the last decade, there has been great research interest in the application of artificial intelligence (AI) in various fields, such as medicine, finance, and law. Recently, there has been a research focus on the application of AI in education, where it has great potential. Therefore, a systematic review of the literature on AI in education is…

Student success and drop-out predictions have gained increased attention in recent years, connected to the hope that by identifying struggling students, it is possible to intervene and provide early help and design programs based on patterns discovered by the models. Though by now many models exist achieving remarkable accuracy-values, models…