This report examines the extent to which student characteristics, achievement, and postsecondary plans can predict the likelihood of college attendance. The report compares students' self-reported plans in Spring 2019 with subsequent college attendance through the 2019-2020 school year. The postsecondary plans used in this report are obtained from…

Effectively predicting academic success is essential for providing students with the resources they need to succeed in their careers and for matching individuals to postsecondary institutions that suit their needs. Despite evidence for ACT scores as meaningful predictors of both first-year grade point average (FYGPA) and degree completion, little…

Few studies have used exploratory factor analysis (EFA) and exploratory bifactor factor analysis (EBFA) to define a baseline factor structure model checking the construct-relevant psychometric multidimensionality of student engagement. This study was conducted on a sample of 3,374 students in France, Wallonia-Brussels Federation, and Luxembourg by…

In this study, we analyse the predictive power of home and school environment-related factors for determining pupils' aggression. The multiple regression analyses are performed for fourth- and eighth-grade pupils based on the Trends in Mathematics and Science Study (TIMSS) 2007 (N = 8394) and TIMSS 2011 (N = 9415) databases for Slovenia. At the…

Data-mined models often achieve good predictive power, but sometimes at the cost of interpretability. We investigate here if selecting features to increase a model's construct validity and interpretability also can improve the model's ability to predict the desired constructs. We do this by taking existing models and reducing the feature set to…

Students conducted inquiry using simulations within a rich learning environment for 4 science topics. By applying educational data mining to students' log data, assessment metrics were generated for two key inquiry skills, testing stated hypotheses and designing controlled experiments. Three models were then developed to analyze the transfer of…

The purpose of the study was to investigate how grading in primary school affected students' achievement measured by grades in 7th, 8th and 9th Grade and educational attainment in upper secondary school (12th Grade), and how the effect varied as a function of students' cognitive ability, gender and socio-economic status. The data derived from the…

This article proposes a model of student school engagement, comprising aspirations, belonging, and productivity. From this model, items for the Student School Engagement Measure (SSEM) were developed. The SSEM was validated with data from 396 eighth graders in an urban school district. Utilizing structural equation modeling, the second-order…

Factors associated with motivation and satisfaction aid in understanding the processes that enhance achievement and productivity. Siegle and McCoach (2005) proposed a motivational model for understanding student achievement and underachievement that included self-perceptions in three areas (meaningfulness [goal valuation], self-efficacy, and…

Building on Shulruf, Hattie and Tumen (2008), this work examines the capacity of various National Certificate in Educational Achievement (NCEA)-derived models to predict first-year performance in Biological Sciences at a New Zealand university. We compared three models: (1) the "best-80" indicator as used by several New Zealand…

Amotivation refers to a state in which individuals cannot perceive a relationship between their behavior and that behavior's subsequent outcome. With the belief that considering amotivation as a multidimensional construct could reflect the complexity of motivational deficits in physical education, we developed this study to validate an amotivation…

Virtual schooling has the potential to offer K-12 students increased access to educational opportunities not available locally, but comparatively high dropout rates continue to be a problem, especially for the underserved students most in need of these opportunities. Creating and using prediction models to identify at-risk virtual learners, long a…