Big Data, Analytics and Education: Challenges, Opportunities and an Example from a Large University Unit

Abstract

<p>The challenge in educational technology (EdTech) is to apply modern analytics to educational data in order to derive information. Information quality (InfoQ) has been proposed by Kenett and Shmueli as a framework for assessing the quality of information generated by empirical studies by using specific empirical methods such as regression models, analysis of variance or predictive analytics. InfoQ is determined by eight dimensions: 1) Data Resolution, 2) Data Structure, 3) Data Integration 4) Temporal Relevance, 5) Chronology of Data and Goal, 6) Generalizability, 7) Operationalization and 8) Communication.</p><p> The chapter considers, with an example, opportunities and challenges of analytics in education. Among other topics, it discusses how the InfoQ framework can be applied in order to achieve conceptual understanding and other learning outcomes, and applies the framework to an example concerning academic performance of university students pursuing a Bachelor and Master Degree Programme in Education. The rationale is to provide information regarding the students' performance and their actions on the online learning platform. It investigates how the day of assignment submission affect the grade of the students and we predicted the day of the week for assignment submission, by each student. The results revealed that students received highest grades on Wednesdays and Thursdays and lowest grades on Sunday. It is predicted that when students submit assignments on Sunday, their grades are lower. Days with the highest grades were Thursday, for the first assignment, and Tuesday for the second assignment and final score. The results of the case study provided the unit coordinator with feedback to evaluate and review the unit through the lens of best practices.</p>