Role of Indian Print and Digital Media in Learning Analytics: A Tool to Sustain Education in the New Normal

Introduction

Education is one of the most important aspects of human civilization. It not only imparts knowledge and skills, but also nurtures healthy habits and values. It shapes the overall personality. It transforms the mere biological existence of a man into a more meaningful existence of human being. Importance of education can be best understood in the present time. The lifestyle adapted by the society so far, has become severely disrupted due to a pandemic---NOVEL CORONA VIRUS or COVID 19, as it is popularly known. The concept of social distancing has arisen from the need to prevent the disease. Educational system is essentially an interactive process which requires a face-to-face interaction. It has impeded since the outbreak of pandemic. Need for social distancing has compelled the teaching-learning process to take technological assistance to fulfill the gap.

From the turn of the last century, technology was becoming an inseparable part of human life style. It is gradually extending its application in all the walks of life. Education is no exception. Due to different needs and demands of teachers and learners, online learning has emerged. Since digital system saves every kind of information generated from the human interaction, it is possible to organize, analyze and use those data. Purpose of such analysis is to assist, improve and evaluate student performance. This is a continuous process, as there is always room for improvement. Additionally, those analysis build predictive models from the perspective of user-learners.

Learning Analytics is a growing field in educational technology. While interacting and using information from digital media, students often leave data trail in the system. Learning Analytics helps the educators and the researchers to collect, organize and analyze those data. The aim is to improve students’ performance and education system as a whole. The term ‘analytics’ in education is used from various angles. Since early 1990s, researches were emerging in this respect (Kozma, 1994; Salomon, 1991). However, the concept was underutilized in e-learning research. The use of this automatically-captured data is now termed learning analytics. This term includes and answers the queries like which records who accessed what and when to study student behaviour (Goldstein & Katz, 2005; Oblinger & Campbell, 2007).

Learning Analytics can be described as process, where information about learners and learning environments is used to “access, elicit, and analyse them for modelling, prediction, and optimization of learning processes” (Mah, 2016, p. 288).

Learning Analytics adapts and uses different analysis techniques from related fields and disciplines like data mining, data visualization, machine learning, learning sciences, psychology, social network analysis, semantics, artificial intelligence, e-learning, and social aspects (Bienkowski et al., 2012; Dawson & Siemens, 2014). It is an integration of data science and science of learning (Gašević, Dawson, & Siemens, 2015).

There is difference among researchers about the definition of Learning Analytics. According to some of them, Learning Analytics is the use of student-generated data which helps in the prediction of educational outcomes and customize according to needs of individual student (Junco & Clem, 2015; Xing, Guo, Petakovic, & Goggins, 2015).

Other group of researchers views Learning Analytics as a means to analyse and comprehend students’ study behaviour and change their learning environment (Drachsler & Kalz, 2012; Rubel & Jones, 2016).