This contribution deals with effect measures for covariates in ordinal data models to address the interpretation of the results on the extreme categories of the scales, evaluate possible response styles, and motivate collapsing of extreme categories. It provides a simpler interpretation of the influence of the covariates on the probability of the…

We consider the ability to complete an investigative cycle as an indicator of the robustness of students' statistical knowledge. From this standpoint, we analyzed the written reports of primary education student teachers when they developed an investigative cycle in a Chilean and a Spanish university. In their development of the stages of the…

Curriculum-Based Measurement of Reading (CBM-R) is frequently used to monitor instructional effects and evaluate response to instruction. Educators often view the data graphically on a time-series graph that might include a variety of statistical and visual aids, which are intended to facilitate the interpretation. This study evaluated the effects…

Researchers use many different metrics for evaluation of performance of student models. The aim of this paper is to provide an overview of commonly used metrics, to discuss properties, advantages, and disadvantages of different metrics, to summarize current practice in educational data mining, and to provide guidance for evaluation of student…

Statistics and probability have become an integral part of mathematics education. Therefore it is important to understand whether curricular materials adequately represent statistical ideas. The "Guidelines for Assessment and Instruction in Statistics Education" (GAISE) report (Franklin, Kader, Mewborn, Moreno, Peck, Perry, & Scheaffer, 2007),…

Experimental data are analysed statistically to allow researchers to draw conclusions from a limited set of measurements. The hard fact is that researchers can never be certain that measurements from a sample will exactly reflect the properties of the entire group of possible candidates available to be studied (although using a sample is often the…

In the modern world, higher education is transitioning from enrollment mode to recruitment mode. This shift paved the way for institutional research and policy making from historical data perspective. More and more universities in the U.S. are implementing and using enterprise resource planning (ERP) systems, which collect vast amounts of data.…

We live in an era where IC&T generates numerous transformations to the classic way of learning. The most known results of these transformations concretise in two means of learning through IC&T: e-learning and computer assisted learning. Just like the classical ones, these models assume the existence of an efficient learning process based…

This paper focuses on model interpretation issues and employs a geometric approach to compare the potential value of using the Grade of Membership (GoM) model in representing population heterogeneity. We consider population heterogeneity manifolds generated by letting subject specific parameters vary over their natural range, while keeping other…

Presents an activity to analyze the data from the Challenger explosion to help students understand the critical role of statistics in decision making and the importance of considering all available data. (MKR)

Demonstrates a statistically valid method allowing students to explore randomization. Described are two examples: counting techniques for a small set of data and simulation for a large sample. (YP)

Too few researchers understand what statistical significance testing does and does not do, and consequently their results are misinterpreted. This Digest explains the concept of statistical significance testing and discusses the meaning of probabilities, the concept of statistical significance, arguments against significance testing,…