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Kelli A. Bird; Benjamin L. Castleman; Zachary Mabel; Yifeng Song – Annenberg Institute for School Reform at Brown University, 2021
Colleges have increasingly turned to predictive analytics to target at-risk students for additional support. Most of the predictive analytic applications in higher education are proprietary, with private companies offering little transparency about their underlying models. We address this lack of transparency by systematically comparing two…
Descriptors: At Risk Students, Higher Education, Predictive Measurement, Models
Aiken, John M.; Henderson, Rachel; Caballero, Marcos D. – Physical Review Physics Education Research, 2019
Physics education research (PER) has used quantitative modeling techniques to explore learning, affect, and other aspects of physics education. However, these studies have rarely examined the predictive output of the models, instead focusing on the inferences or causal relationships observed in various data sets. This research introduces a modern…
Descriptors: Physics, Bachelors Degrees, College Science, Student Records
The Complex Route to Success: Complex Problem-Solving Skills in the Prediction of University Success
Stadler, Matthias J.; Becker, Nicolas; Greiff, Samuel; Spinath, Frank M. – Higher Education Research and Development, 2016
Successful completion of a university degree is a complex matter. Based on considerations regarding the demands of acquiring a university degree, the aim of this paper was to investigate the utility of complex problem-solving (CPS) skills in the prediction of objective and subjective university success (SUS). The key finding of this study was that…
Descriptors: Success, Predictive Validity, Predictor Variables, Problem Solving
Conijn, Rianne; Snijders, Chris; Kleingeld, Ad; Matzat, Uwe – IEEE Transactions on Learning Technologies, 2017
With the adoption of Learning Management Systems (LMSs) in educational institutions, a lot of data has become available describing students' online behavior. Many researchers have used these data to predict student performance. This has led to a rather diverse set of findings, possibly related to the diversity in courses and predictor variables…
Descriptors: Blended Learning, Predictor Variables, Predictive Validity, Predictive Measurement
Riofrio-Luzcando, Diego; Ramirez, Jaime; Berrocal-Lobo, Marta – IEEE Transactions on Learning Technologies, 2017
Data mining is known to have a potential for predicting user performance. However, there are few studies that explore its potential for predicting student behavior in a procedural training environment. This paper presents a collective student model, which is built from past student logs. These logs are first grouped into clusters. Then, an…
Descriptors: Student Behavior, Predictive Validity, Predictor Variables, Predictive Measurement
Jensen, Philip A.; Barron, James N. – Journal of College Science Teaching, 2014
Students routinely ignore negative feedback regarding their performances early in college science courses. In this study we analyzed the extent to which two standard forms of feedback, midterm and first-exam grades, correlated with final grades in several biology courses. The courses ranged from an introductory course for nonmajors to upper…
Descriptors: Biology, Predictive Validity, Grade Prediction, Feedback (Response)
Crouch, Suzanne J. – Journal of College Teaching & Learning, 2015
The purpose of this study was to assess the merit of the Watson-Glaser Critical Thinking Appraisal as a pre-admission criterion in conjunction with the frequently utilized admission criteria of the college prerequisite grade point average and the National League of Nursing pre-admission test. Data were collected from 192 first-year nursing…
Descriptors: Nursing Education, Success, Predictor Variables, Admission Criteria
Pacheco, Wendy I.; Noel, Richard J., Jr.; Porter, James T.; Appleyard, Caroline B. – CBE - Life Sciences Education, 2015
The use and validity of the Graduate Record Examination General Test (GRE) to predict the success of graduate school applicants is heavily debated, especially for its possible impact on the selection of underrepresented minorities into science, technology, engineering, and math fields. To better identify candidates who would succeed in our program…
Descriptors: Puerto Ricans, Predictor Variables, Success, Doctoral Programs
Slanger, William D.; Berg, Emily A.; Fisk, Paul S.; Hanson, Mark G. – Journal of College Student Retention: Research, Theory & Practice, 2015
Ten years of College Student Inventory (CSI) data from one Midwestern public land-grant university were used to study the role of motivational factors in predicting academic success and college student retention. Academic success was defined as cumulative grade point average (GPA), cumulative course load capacity (i.e., the number of credits…
Descriptors: Longitudinal Studies, Cohort Analysis, Student Motivation, Academic Achievement
Bozick, Robert; Gonzalez, Gabriella; Engberg, John – Journal of Student Financial Aid, 2015
The Pittsburgh Promise is a scholarship program that provides $5,000 per year toward college tuition for public high school graduates in Pittsburgh, Pennsylvania who earned a 2.5 GPA and a 90% attendance record. This study used a difference-in-difference design to assess whether the introduction of the Promise scholarship program directly…
Descriptors: Merit Scholarships, College Bound Students, Enrollment Influences, Enrollment Management
Cavallo, Fernando – ProQuest LLC, 2012
The current study was completed through a retrospective analysis of school records of elementary school students in the Northeast Region of the Philadelphia School District (PSD) who have participated in the Fast ForWord (FFW) Language program. The data requested from student records included: demographic information (e.g., gender, grade, age,…
Descriptors: Student Records, Program Effectiveness, Intervention, Reading Programs
Kotamraju, Pradeep; Blackman, Orville – Community College Journal of Research and Practice, 2011
The paper uses the Integrated Postsecondary Education Data system (IPEDS) data to simulate the 2020 American Graduation Initiative (AGI) goal introduced by President Obama in the summer of 2009. We estimate community college graduation rates and completion numbers under different scenarios that include the following sets of variables: (a) internal…
Descriptors: Community Colleges, Graduation Rate, Educational Attainment, Predictor Variables
Pascopella, Angela – District Administration, 2012
Predicting the future is now in the hands of K12 administrators. While for years districts have collected thousands of pieces of student data, educators have been using them only for data-driven decision-making or formative assessments, which give a "rear-view" perspective only. Now, using predictive analysis--the pulling together of data over…
Descriptors: Expertise, Prediction, Decision Making, Data
Smith, Wade; Droddy, Jason; Guarino, A. J. – Current Issues in Education, 2011
Schools across America are being ranked for their effectiveness on a number of student criteria, among them preparation of students for a successful college experience. This study investigates the relationship between graduating seniors, their successful first year retention in college and several personal and school related factors. The study…
Descriptors: Academic Achievement, Accountability, School Holding Power, Effect Size
Marnewick, Carl – Educational Studies, 2012
First-year students are still failing at an alarming rate. This is an international issue that universities face and there is currently no clear indication of the cause of the problem as universities move from being elite to providing mass education. This article examines the possible correlation between students' high school performance and…
Descriptors: Academic Achievement, Admission Criteria, Correlation, Mathematics Achievement

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