Machine learning methods for predictive analytics have great potential for uncovering trends in educational data. However, simple linear models still appear to be most widely used, in part, because of their interpretability. This study aims to address the issues of interpretability of complex machine learning classifiers by conducting feature…

In institutional research, modern data mining approaches are seldom considered to address predictive analytics problems. The goal of this paper is to highlight the advantages of tree-based machine learning algorithms over classic (logistic) regression methods for data-informed decision making in higher education problems, and stress the success of…

Recent reforms emphasize a shift in how students should learn and demonstrate knowledge of science. These reforms call for students to learn content knowledge using science and engineering practices, creating integrated science knowledge. While there is existing literature about the development of integrated science knowledge assessments, few…

Predicting the future is now in the hands of K12 administrators. While for years districts have collected thousands of pieces of student data, educators have been using them only for data-driven decision-making or formative assessments, which give a "rear-view" perspective only. Now, using predictive analysis--the pulling together of data over…

Although behavior analysis relies primarily on visual inspection for interpreting data, previous research shows that the method of display can influence the judgments. In the current study, 26 Board-Certified Behavior Analysts reviewed two data sets displayed on each of three methods--equal-interval graphs, tables, and Standard Celeration…

The purpose of this study was to examine the variable of estimated earnings in order to determine how forecasts might be utilized to develop a securities portfolio strategy. The hypothesis stated that there is an inverse relationship between projected change in earnings per share and security performance. Ninety-one New York Stock Exchange…

Data-mining technology's predictive modeling was applied to enhance the prediction of enrollment behaviors of admitted applicants at a large state university. (Contains 4 tables and 6 figures.)

Proposes three types of supplementary problems to develop students' skill in interpretation of graphically represented data. Eleven examples are presented and solved for the following types of problems: comparison of one quantity to another, comparison of two quantities that each depend on a common parameter, and reasonable data prediction. (MDH)