The second CSEDM data challenge aimed at finding innovative methods to use students' programming traces to model their learning. The main challenge of this task is how to decide which past problems are relevant for predicting performance on a future problem. This paper proposes a set of weighting schemes to address this challenge. Specifically,…

Logistic regression is one of the most fundamental tools in predictive analytics. Graduate business analytics students are often familiarized with implementation of logistic regression using Python, R, SPSS, or other software packages. However, an understanding of the underlying maximum likelihood model and the mechanics of estimation are often…

As vast amounts of data have become available in business in recent years, the demand for data scientists has been rising. The author of this article provides a tutorial on how one entry-level machine learning competition from Kaggle, an online community for data scientists, can be integrated into an undergraduate econometrics course as an…

This study investigates whether information saved in the log files of a computer-based tutor can be used to predict the problem solving performance of students. The log files of a computer-based physics tutoring environment called Andes Physics Tutor was analyzed to build a logistic regression model that predicted success and failure of students'…

Student models for adaptive systems may not model collaborative learning optimally. Past research has either focused on modeling individual learning or for collaboration, has focused on group dynamics or group processes without predicting learning. In the current paper, we adjust the Additive Factors Model (AFM), a standard logistic regression…

Student models for adaptive systems may not model collaborative learning optimally. Past research has either focused on modeling individual learning or for collaboration, has focused on group dynamics or group processes without predicting learning. In the current paper, we adjust the Additive Factors Model (AFM), a standard logistic regression…

Although ITSs are supposed to adapt to differences among learners, so far, little attention has been paid to how they might adapt to differences in how students learn from help. When students study with an Intelligent Tutoring System, they may receive multiple types of help, but may not comprehend and make use of this help in the same way. To…

The purpose of this study is to analyze of university students' perceived social support and social problem solving. The participants were 827 (474 female and 353 male) university students. Data were collected Perceived Social Support Scale-Revised (Yildirim, 2004) and Social Problem Solving (Maydeu-Olivares and D'Zurilla, 1996) translated and…

This study examines the role of salient external factors (family, peer and school caring relations) and internal factors (goals and aspirations, problem solving and self-efficacy, empathy, and self-awareness) in protecting adolescents experiencing interpersonal problems and academic pressure from depression. A total of 1,297 eighth and ninth grade…

Fourteen children with autism spectrum disorders (ASD) and fourteen age-matched typically-developing (TD) controls were tested on an adapted version of the Twenty Questions Task (Mosher and Hornsby in Studies in cognitive growth. Wiley, New York, pp 86-102, "1966") to examine effects of content, executive and verbal IQ factors on category use in…

The study examined the incremental validity of thinking styles in predicting academic achievement after controlling for personality and achievement motivation in the hypermedia-based learning environment. Seventy-two Chinese college students from Shanghai, the People's Republic of China, took part in this instructional experiment. The…

In the early 1990s, the National Science Foundation funded many research projects for improving statistical education. Many of these stressed the need for classroom activities that illustrate important issues of designing experiments, generating quality data, fitting models, and performing statistical tests. Our paper describes such an activity on…

This paper proposes a learning based method that can automatically determine how likely a student is to give a correct answer to a problem in an intelligent tutoring system. Only log files that record students' actions with the system are used to train the model, therefore the modeling process doesn't require expert knowledge for identifying…