Completion of remedial mathematics has been identified as one of the keys to college success. However, completion rates in remedial mathematics have been low and are of much debate across America. This study leverages machine learning techniques in trying to predict and understand completion rates in remedial mathematics. The purpose of this study…

Much research shows academic self-concept and achievement are reciprocally related over time, based on traditional longitudinal data cross-lag-panel models (CLPM) supporting a reciprocal effects model (REM). However, recent research has challenged CLPM's appropriateness, arguing that CLPMs with random intercepts (RI-CLPMs) provide a more robust…

In this exploratory study, a theoretical model proposed by Sriraman (2005) consisting of five theoretical principles for optimizing creativity in a K-12 setting was investigated empirically. This was accomplished in two steps. In the first study, the five principles were operationalized by generating a questionnaire consisting of 45 items intended…

Metacognition is a powerful predictor for learning performance, and for problem-solving. But how metacognition works for cognitive strategies and learning performance is not clear. The present study was designed to explore how metacognition affected the cognition (learning strategies and problem solving strategies) and different kinds of learning…

Low success rates in developmental mathematics courses have caused a growing concern for many institutions including moderately selective four-year universities. As a result, institutions have adopted various course redesign models, such as the emporium and replacement models, which take advantage of interactive online learning tools. Though these…

If we wish to embed assessment for accountability within instruction, we need to better understand the relative contribution of different types of learner data to statistical models that predict scores and discrete achievement levels on assessments used for accountability purposes. The present work scales up and extends predictive models of math…

This three-article dissertation considers the pedagogical practices for developing statistically literate students and teaching data-driven decision-making with the goal of preparing students for civic engagement and improving student achievement. The first article discusses a critical review of the literature on data-driven decision-making…

This multilevel study examined the effects of socioeconomic status (SES) and student perceptions of school climate on academic achievement at the student and school levels. Data used were from the Education Longitudinal Study of 2002. The sample included 9,518 students enrolled in 584 public high schools. The results revealed that student-level…

Data mining has been successfully used by financial and retail companies since the mid-1960's to create predictive models and reveal unexpected relationships. However, it remains underutilized as a tool in educational research. Large-scale standardized assessment programs such as the Trends in International Mathematics and Science Study (TIMSS)…

This study compared the direct, indirect, and total effects of information, communication, and technology (ICT) variables on math achievement for second-generation immigrant, first-generation immigrant, and nonimmigrant students. A path model was used to analyze U.S. nationally representative data from the Program for International Student…

This study aims to analyse the relationship between students' mathematics achievement in Programme for International Student Assessment (PISA) 2012 and the instructional climate-related factors in the index of principals' perceptions (learning hindrance, teacher morale and teacher intention). As preliminary analysis procedure, the chi-squared…

The internal/external frame of reference model (I/E model) posits that individuals' achievement-related self-concepts are formed through social comparisons (e.g., self vs. peers) within academic domains and dimensional comparisons (e.g., math vs. verbal) between distinct domains. A large body of research has supported the theorized pattern of…

Few studies have examined the relation between maternal caloric intake during pregnancy and growth in child academic achievement while controlling for important confounding influences. Using data from the National Longitudinal Survey of Youth, the current study examined the effects of reduced prenatal caloric intake on growth in scores on the…

In this study, we conducted binary logistic regression on survey data collected from 244 past participants of a Talent Search program who attended regular high schools but supplemented their regular high school education with enriched or accelerated math and science learning activities. The participants completed an online survey 4 to 6 years…

The Fullerton Longitudinal Study offers a unique opportunity to model the stability of intelligence and achievement and their relations from elementary through secondary school. Using latent variable modeling, we fit a cross-lagged panel model to examine the relations between intelligence and achievement in two academic domains: mathematics and…