The purpose of this dissertation study was twofold. First, this research study examined the role of noncognitive factors on degree completion, academic achievement, and persistence. Second, this research study examined the utility of the Personal Potential Index (PPI) as an avenue to reliably assess noncognitive factors of graduate students that…

In many countries, students are selected into higher education institutions based on their achievement at high school, measured by scores given by their teachers and obtained on final national exams. This paper compares these two measures in terms of their ability to predict students' success in higher education. Accounting for sample selection…

The Motivation for Educational Attainment (MEA) questionnaire, developed to assess facets related to early adolescents' motivation to complete high school, has a bifactor structure with a large general factor and three smaller orthogonal specific factors (teacher expectations, peer aspirations, value of education). This prospective validity study…

We examined the validity of 10 psychosocial factors for predicting retention status (stay, transfer, or drop out) at the start of second year of college by fitting a mixed-effects multinomial logistic regression model. Data consisted of retention records of 9,364 students from 31 four-year institutions. Predictors included commonly used variables…

As online courses become more common, practitioners are in need of clear guidance on how to translate best educational practices into web-based instruction. Moreover, student engagement is a pressing concern in online courses, which often have high levels of dropout. Our goals in this work were to experimentally study routine instructional design…

Metacognition is a good predictor of University students' achievement and should be more systematically considered since it might also help reduce student drop outs. In particular drop out is a dramatic problem for Italian Universities since it may concern more than 40% of students. The identification of factors that lead to academic failure and…

This investigation sought to determine when colleges should conduct assessments to identify first-year students at risk of dropping out. Thirty-five variables were used to predict the persistence of 2,024 first-year students from four universities in the southeastern United States. The predictors were subdivided into groups according to when they…

This paper focuses on predicting drop-outs and school failures when student data has been enriched with data derived from students social behaviour. These data describe social dependencies gathered from e-mail and discussion board conversations, among other sources. We describe an extraction of new features from both student data and behaviour…

Ninth-grade predictors of dropout risk among Austin Independent School District's English language learner students included the following: having an attendance rate below 90%, being 16 years or older, earning less than 5 course credits, attending a Title I campus and scoring beginning or intermediate on the state's English proficiency assessment…

This article reports that several colleges and universities like Purdue University are mining data they have about students to try to improve retention. The institutions analyze years' worth of data on which students did well and which did poorly, and what variables--whether they be SAT scores, financial-aid status, or attendance at the dining…

The 11th International Conference on Educational Data Mining (EDM 2018) is held under the auspices of the International Educational Data Mining Society at the Templeton Landing in Buffalo, New York. This year's EDM conference was highly competitive, with 145 long and short paper submissions. Of these, 23 were accepted as full papers and 37…

Army enlistees with General Educational Development (GED) certificates who completed military service (1,894) were compared with 2,085 GED enlistees who dropped out. Completers had higher GED scores and Armed Services Vocational Aptitude Battery subtest scores. It was recommended that GED scores be an integral part of recruitment screening and a…

Recent research shows that variation in teacher quality has large effects on student performance. However, this research is based entirely on student test scores. Focusing on high-school math teachers, this paper evaluates teacher quality in terms of another educational outcome of great interest--graduation. I use a unique instrumental variables…

Machine Learning algorithms fed with data sets which include information such as attendance data, test scores and other student information can provide tutors with powerful tools for decision-making. Until now, much of the research has been limited to the relation between single variables and student performance. Combining multiple variables as…

This study compared the academic preparation, aspirations, and first-year college performance of first-generation college freshmen with other college freshmen at Indiana State University. It found that first-generation students were more likely to drop out during the first semester and had lower first-semester grades than students with one or more…