Melissa Bond

TL;DR: In this article, the authors provide an overview of research on AI applications in higher education through a systematic review, focusing on four areas of AIEd applications in academic support services, and institutional and administrative services: 1. profiling and prediction, 2. assessment and evaluation, adaptive systems and personalisation, and 4. intelligent tutoring systems.

TL;DR: In this paper, the authors present a collaborative reaction that narrates the overall view, reflections from the K-12 and higher educational landscape, lessons learned and suggestions from a total of 31 countries across the world with a representation of 62,7% of the whole world population.

TL;DR: In this article, two datasets were examined regarding the use and perceptions of students and teachers on the use of digital tools, with the Learning Management System being perceived as the most useful tool.

TL;DR: In this paper, the authors systematically map research from 243 studies published between 2007 and 2016, with only limited research undertaken in the Global South, and largely focused on the fields of Arts & Humanities, Education, and Natural Sciences, Mathematics & Statistics.

TL;DR: The results indicate that the majority of research has been undertaken in North American and Asian high schools, heavily focused on student perceptions of flipped learning and achievement within STEM subjects, especially Mathematics, with a slight preference for quantitative methods.