This study examined the predictive power of students' demographic characteristics, reading attitudes, school characteristics, and teacher-informed reading activities on three metacognitive reading skills: understanding and remembering, summarizing, and assessing credibility and their influence on 15-year-old students' reading scores. The dataset…

Determining which students are at risk of poorer outcomes -- such as dropping out, failing classes, or decreasing standardized examination scores -- has become an important area of research and practice in both K-12 and higher education. The detectors produced from this type of predictive modeling research are increasingly used in early warning…

This Innovative Practice Category Work In Progress paper presents an application of machine learning and data mining to student performance data in an undergraduate electrical engineering program. We are developing an analytical approach to enhance retention in the program especially among underrepresented groups. Our approach will provide…

Completion rates for massive open online classes (MOOCs) are notoriously low, but learner intent is an important factor. By studying students who drop out despite their intent to complete the MOOC, it may be possible to develop interventions to improve retention and learning outcomes. Previous research into predicting MOOC completion has focused…

An underlying theme of this paper is that it can be easier and more efficient to conduct valid and effective research studies in online environments than in traditional classrooms. Taking advantage of the "big data" available in an online university, we conducted a study in which a massive online database was used to predict student…

Childhood is the crucial period for early children's reading ability building. Former research (Hanson & Farrell, 1995) found that early reading experience had a positive and long-term effect on reading competence for high school seniors in the future. Therefore, it is of great importance for researchers to understand children's initial reading…

This paper identifies specific problems with stepwise regression, notes criticisms of stepwise methods by statisticians, suggests appropriate ways in which stepwise procedures can be used, and gives examples of how this can be done. Although the stepwise method has been routinely criticized by statisticians, it is still frequently used in the…

Most of the emphasis on mining online assessment logs has been to identify content-specific errors. However, the pattern of general "consistency" is domain independent, strongly related to performance, and can itself be a target of educational data mining. We demonstrate that simple consistency indicators are related to student outcomes,…

The Comparing Options in Secondary Mathematics: Investigating Curriculum (COSMIC) project is a longitudinal study of student learning from two types of mathematics curricula: integrated and subject-specific. Previous large-scale research studies such as the National Assessment of Educational Progress (NAEP) indicate that numerous variables are…

The ability to predict a student's performance could be useful in a great number of different ways associated with university-level learning. In this paper, a grammar guided genetic programming algorithm, G3P-MI, has been applied to predict if the student will fail or pass a certain course and identifies activities to promote learning in a…

The utility of a non-linear transformation of the criterion is established. The Pythagorean Theorem is used as the example to demonstrate the point. The functional relationships may be such (as in the Pythagorean Theorem) that an R-squared of 1.00 cannot be found without making a non-linear transformation of the criterion. The goal of…

The value of variance is emphasized, and the element of design, frequently not adequately understood, is clarified to underscore the importance of variance to the researcher. Two analytic methods, analysis of variance (ANOVA) and multiple regression, are discussed in terms of how each uses/applies variance. Advantages and major difficulties with…

The Goodman technique of log linear analysis is ideal for family research, because it is designed for categorical (non-quantitative) variables. Variables are dichotomized (for example, married/divorced, childless/with children) or otherwise categorized (for example, level of permissiveness, life cycle stage). Contingency tables are then…

Guidelines for articulation of a framework for practical application of proportional-hazards models (PHMs) to professional survival analysis are provided. Focus is on data analysis fitting the PHMs with the semi-parametric methods of partial likelihood; this strategy is available in the BMDP2L and SAS PROC PHGLM computer programs. Areas in which…

The issues and some proposed solutions regarding Follow Through (FT) site variability are examined with a review of developments in FT evaluation. The role of adjusted site means with differences within sponsors and between sponsors and background characteristics is discussed to determine whether adjusted means are the preferred measures of model…