Simulation modeling is an effective tool for solving problems that cannot be explained analytically or when data cannot be collected. This is done by simulating the observed behavior of a problem under study using a computer program. In math education, this can develop knowledge and fundamental competencies of simulation modeling at a higher level…

With the continuous development of education, personalized learning has attracted great attention. How to evaluate students' learning effects has become increasingly important. In information technology courses, the traditional academic evaluation focuses on the student's learning outcomes, such as "scores" or "right/wrong,"…

The present study examines bias in parameter estimates and standard error in cross-classified random effect modeling (CCREM) caused by omitting the random interaction effects of the cross-classified factors, focusing on the effect of a sample size within cells and ratio of a small cell. A Monte Carlo simulation study was conducted to compare the…

Background: Different studies reveal an association between parent involvement, metacognition, and academic achievement; however, the majority analyse the developmental process of acquisition in experimental or quasi-experimental designs with students enrolled in child education. Adolescence is an important stage in personal and academic…

Mathematical modeling is an open-ended research subject where no definite answers exist for any problem. Math modeling enables thinking outside the box to connect different fields of studies together including statistics, algebra, calculus, matrices, programming and scientific writing. As an integral part of society, it is the foundation for many…

In recent years, a principal supply shortage crisis has emerged in the USA. This problem has been exacerbated by an increase in principal departures, which has been found to be negatively related to school outcomes. While research exists on several determinants of principal turnover, any examination of the relationship between principals'…

This study examined the mediating role of student school motivation in linking student victimization experiences and academic achievement among a nationally representative sample of students in 10th grade. Structural equation modeling supported that there were significant associations between student victimization and academic achievement for high…

The present study reports on the first investigation of the generalizability of the psychometric properties of the Student Subjective Wellbeing Questionnaire (SSWQ) beyond the original development and replication studies. Previous studies tested an English version of the SSWQ with urban, mostly Black/African American, low socioeconomic status,…

An important, yet largely unstudied problem in student data analysis is to detect "misconceptions" from students' responses to "open-response" questions. Misconception detection enables instructors to deliver more targeted feedback on the misconceptions exhibited by many students in their class, thus improving the quality of…

In this article, I introduce a novel applet ("module") for exploring probability distributions, their samples, and various related statistical concepts. The module is primarily designed to be used by the instructor in the introductory course, but it can be used far beyond it as well. It is a free, cross-platform, stand-alone interactive…

Family Rewards was an innovative approach to poverty reduction in the United States that was modelled on the conditional cash transfer (CCT) programs common in lower- and middle-income countries. The program offered cash assistance to poor families to reduce immediate hardship, provided they met certain criteria related to family health care,…

Interactive learning environments can provide learners with opportunities to explore rich, real-world problem spaces, but the nature of these problem spaces can make assessing learner progress difficult. Such assessment can be useful for providing formative and summative feedback to the learners, to educators, and to the designers of the…

The short-term emphasis engendered by No Child Left Behind (NCLB) has focused research predominantly on unraveling the complexities and uncertainties in assessing short-term results, rather than developing methods and assessing results over the longer term. In this paper we focus on estimating long-term gains and address questions important to…

The persistently low college attainment rates of youth from poor families are partly attributable to their uncertainty about college affordability. The current federal financial aid system does not provide specific information about college costs until just before college enrollment and the information is only available to students completing a…

Monte Carlo methods can be used in data analytic situations (e.g., validity studies) to make decisions about sample size and to estimate power. The purpose of using Monte Carlo methods in a validity study is to improve the methodological approach within a study where the primary focus is on construct validity issues and not on advancing…