Learning Analytics in Reading Comprehension

Abstract

Emerging technologies enable the acquisition of substantial volumes of data produced through user engagement with Internet-connected learning platforms. Hence, it is feasible to analyze and convert such data into valuable insights to maximize the effectiveness of any instruction, be it for children, adolescents, or adults. Using Learning Analytics in this context enables the derivation of conclusions from the data, the identification of new variables that may assist an academic institution in responding more effectively to the various situations that students encounter, and the formulation of decisions based on the information analysis. By leveraging Learning Analytics, numerous benefits can be realized, including but not limited to obtaining vital student data, generating predictions, reducing attrition, increasing revenue, and enhancing course offerings. This chapter of the book explores the utilization of Learning Analytics in the context of reading comprehension to quantify various learning-related behaviors. The primary graphs utilized in Learning Analytics are delineated, accompanied by a case study on reading comprehension.