Learning Analytics: A Survey

TL;DR

This survey reviews recent research in learning analytics, focusing on frameworks, models, and data mining techniques used to analyze learning data for improving student outcomes.

Contribution

It provides a comprehensive overview of recent developments in learning analytics, including frameworks, models, and applications of data mining techniques.

Findings

Identification of students at risk using data mining techniques

Prediction of student performance through integrated models

Overview of frameworks and applications in learning analytics

Abstract

Learning analytics is a research topic that is gaining increasing popularity in recent time. It analyzes the learning data available in order to make aware or improvise the process itself and/or the outcome such as student performance. In this survey paper, we look at the recent research work that has been conducted around learning analytics, framework and integrated models, and application of various models and data mining techniques to identify students at risk and to predict student performance.