Background: Parents are often involved in their child's homework with the goal of improving their child's academic achievement. However, mixed findings were observed for the role of parental involvement in homework in shaping students' learning outcomes. Aims: The present study examined whether and how the effect of parental involvement in…

The online homework system WeBWorK has been successfully used at several hundred colleges and universities. Despite its popularity, the WeBWorK system does not provide detailed metrics of student performance to instructors. In this article, we illustrate how an analysis of the log files of the WeBWorK system can provide information such as the…

We propose a novel model, Wide & Deep Item Response Theory (Wide & Deep IRT), to predict the correctness of students' responses to questions using historical clickstream data. This model combines the strengths of conventional Item Response Theory (IRT) models and Wide & Deep Learning for Recommender Systems. By leveraging clickstream…

This study presents a model for the early identification of students who are likely to fail in an academic course. To enhance predictive accuracy, sentiment analysis is used to identify affective information from text-based self-evaluated comments written by students. Experimental results demonstrated that adding extracted sentiment information…

Prediction of student performance is one of the most important subjects of educational data mining. Artificial neural networks are seen to be an effective tool in predicting student performance in e-learning environments. In the studies carried out with artificial neural networks, performance predictions based on student scores are generally made,…

This paper discusses ethical issues surrounding Netnography, an innovative methodology, relatively unusual in Education research. It explores the ethical approach developed for a study of UK mother perspectives on primary school homework found on open-access parenting websites, reviewing issues considered at the project's outset and examining…

Although the advent and popularization of the "flipped classroom" tends to center around at-home video lectures, teachers are increasingly turning to at-home labs for enhanced student engagement. This paper describes two simple at-home experiments that can be accomplished in the kitchen. The first experiment analyzes the density of four…

Traditionally, statistical computing courses have taught the syntax of a particular programming language or specific statistical computation methods. Since Nolan and Temple Lang's seminal paper, we have seen a greater emphasis on data wrangling, reproducible research, and visualization. This shift better prepares students for careers working with…

The use of machine learning and data mining techniques across many disciplines has exploded in recent years with the field of educational data mining growing significantly in the past 15 years. In this study, random forest and logistic regression models were used to construct early warning models of student success in introductory calculus-based…

The demand for in-depth studies on educational data presupposes the application of technologies that allow data analysis of vast quantities, and subsequently, drawing relevant information and knowledge. The research objective herein is to employ data mining techniques on PISA databases to identify potential patterns that may explain the…

The purpose is to improve insights and educational results by applying analytic methods. The focus is on the mathematics applied to learn from the kind of data available to most classes such as final examination marks or homework grades. The sample is 249 students learning introductory college statistics. The result is a predictive model for…

There is a long history of research efforts aimed at understanding the relationship between homework activity and academic achievement. While some self-report inventories involving homework activity have been useful for predicting academic performance, self-reported measures may be limited or even problematic. Here, we employ a novel method for…

Over the course of one semester, six empirical assignments that utilize FRED are used to introduce students of money and banking courses to the economic analysis required for the conduct of monetary policy. The first five assignments cover the following topics: inflation, bonds and stocks, monetary aggregates, the Taylor rule, and employment.…

Adaptive Learning Technologies (ALT) and Learning Analytics (LA) are expected to contribute to the customisation and personalisation of pupil learning by continually calibrating and adjusting pupils' learning activities towards their skill and competence levels. The overall aim of the study presented in this paper was to obtain a comprehensive…

In this article, we examine the ways in which an ESL instructor constructs contextually relevant meanings through the synchronization of speech and gesture during unplanned vocabulary explanations. Video recorded data are analysed, with focus on an in-class homework review in which students demonstrated difficulty in comprehending several key…