This study proposes a knowledge graph-based big data analysis model for course quality evaluation, aiming to address issues in online education course evaluations such as semantic bias, grammatical deficiencies, vocabulary limitations, false evaluations, information distortion, and imbalanced evaluation categories. The model incorporates three…

Temporality-driven covariate classification had limited impact on: the specification of directed acyclic graphs (DAGs) by 85 novice analysts (medical undergraduates); or the risk of bias in DAG-informed multivariable models designed to generate causal inference from observational data. Only 71 students (83.5%) managed to complete the…

Online learning has attracted a large number of participants and is increasingly becoming very popular. However, the completion rates for online learning are notoriously low. Further, unlike traditional education systems, teachers, if any, are unable to comprehensively evaluate the learning gain of each student through the online learning…

We have investigated whether and how a categorization of responses to questions on linear distance-time graphs, based on a study of Irish students enrolled in an algebra-based course, could be adopted and adapted to responses from students enrolled in calculus-based physics courses at universities in Flanders, Belgium (KU Leuven) and the Basque…

Much research on higher education has discussed the positional competition induced by global rankings and the complementary concept of "world-class" universities. This paper investigates the network of social media communication between globally ranked universities. Specifically, it examines whether universities seek to preserve and…

Literature on global international student mobility (ISM) highlights the uneven nature of student flows--from the developing to the developed world--however, studies have yet to address whether this pattern is replicated within expanding regional networks. Utilizing social network analysis, UNESCO ISM data, and World Bank income classifications,…

Direct Behavior Rating (DBR) is a repeatable and efficient method of behavior assessment that is used to document teacher perceptions of student behavior in the classroom. Time-series data can be graphically plotted and visually analyzed to evaluate patterns of behavior or intervention effects. This study evaluated the decision accuracy of novice…

Detailed logs of students' computer use, during independent study sessions, were captured in an open-access computer laboratory. Each log consisted of a chronological sequence of tasks representing either the application or the Internet domain displayed in the workstation's active window. Each task was classified using a three-tier schema…

We have investigated the various approaches taken by first-year university students (n[image omitted]550) when asked to determine the direction of motion, the constancy of speed, and a numerical value of the speed of an object at a point on a numerical linear distance-time graph. We investigated the prevalence of various well-known general…

One critical aspect that hinders the systematic use of concept mapping in everyday classrooms is the difficulty of providing high-quality feedback to students so as to keep improving and revising their concept maps (Cmaps). The development of an innovative way to analyse, at a glance, students' Cmaps is presented to allow a diagnostic assessment…

The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…

The 9th International Conference on Educational Data Mining (EDM 2016) is held under the auspices of the International Educational Data Mining Society at the Sheraton Raleigh Hotel, in downtown Raleigh, North Carolina, in the USA. The conference, held June 29-July 2, 2016, follows the eight previous editions (Madrid 2015, London 2014, Memphis…

The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…

Introduction: The strategies that people use to browse Websites are difficult to analyse and understand: quantitative data can lack information about what a user actually intends to do, while qualitative data tends to be localised and is impractical to gather for large samples. Method: This paper describes a novel approach that combines data from…

The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…