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…

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,…

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 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.…

Learning analytics (LA) has emerged as a field that offers promising new ways to prevent drop-out and aid retention. However, other research suggests that large datasets of learner activity can be used to understand online learning behaviour and improve pedagogy. While the use of LA in language learning has received little attention to date,…

In this study, we applied decision trees (DT) to extract a compact set of pedagogical decision-making rules from an original "full" set of 3,702 Reinforcement Learning (RL)- induced rules, referred to as the DT-RL rules and Full-RL rules respectively. We then evaluated the effectiveness of the two rule sets against a baseline Random…

Blended learning combines online digital resources with traditional classroom activities and enables students to attain higher learning performance through well-defined interactive strategies involving online and traditional learning activities. Learning analytics is a conceptual framework and is a part of our Precision education used to analyze…

This is an exploratory study about engaging students in mathematics learning both inside and outside of the classroom of an introductory proof course. The author utilized the framework of scholarship of teaching and learning as a guide to ensure the research process was carried out systematically. This study was conducted through one cycle of…

The article illustrates how statistical content and pedagogical reasoning were taught in tandem in an undergraduate course. A typical day in the course is described. It is also suggested that practising teachers can benefit from strategies used in the course. (Contains 1 table and 3 figures.)

The "2015 NMC Technology Outlook for Higher Education in Ireland: A Horizon Project Regional Report" is a collaborative research effort between the New Media Consortium (NMC), National Institute for Digital Learning (NIDL) at Dublin City University, and the Irish Learning Technology Association (ILTA) to inform Irish higher education…

The "2015 NMC Technology Outlook for Brazilian Universities" is a collaborative research effort between the New Media Consortium and Saraiva to inform Brazilian higher education leaders and decision-makers about important developments in technologies supporting teaching, learning, and creative inquiry in higher education across the…

The New Media Consortium (NMC) and the National Institute for Staff and Organizational Development (NISOD), with the generous support of Dell and Intel, have jointly released the "Technology Outlook for Community, Technical, and Junior Colleges 2013-2018: An NMC Horizon Project Sector Analysis." This report applies the process developed…