Machine Learning methods for Performance Prediction in Intelligent Tutoring Systems (ITS) have proven their efficacy; specific methods, e.g. Matrix Factorization (MF), however suffer from the lack of available information about new tasks or new students. In this paper we show how this problem could be solved by applying Transfer Learning (TL),…

This paper contributes to the discourse in stochastic education of how young students deal with learning settings that allow a data-based approach to probability. By using the micro-structure of arguments by Toulmin (1958), it explores which arguments students use and which role they play in the learning process. The data stems from design…

The normal curve has long been important in statistics. Most interval variables yield normal or quasi-normal distributions when data are collected from large samples, and the normal "Z" distribution is also used as a test statistic (e.g., to test differences between two means when sample size is large, since "t" approaches…

A unidimensional model for responses to statements that have an unfolding structure was constructed from the cumulative Rasch model for ordered response categories. A joint maximum likelihood estimation procedure was investigated. Analyses of data from a small simulation and a real data set show that the model is readily applicable. (SLD)

Traditional elementary statistics instruction for non-majors has focused on computation. Rarely have students had an opportunity to interact with real data sets or to use questioning to drive data analysis, common activities among professional statisticians. Inclusion of data gathering and analysis into whole class and small group activities…

This paper provides an overview of common sampling methods (both the good and the bad) likely to be used in community college self-evaluations and presents the results from several simulated trials. The report begins by reviewing various survey techniques, discussing the negative and positive aspects of each method. The increased accuracy and…