Publication Date
In 2025 | 0 |
Since 2024 | 1 |
Since 2021 (last 5 years) | 3 |
Since 2016 (last 10 years) | 21 |
Since 2006 (last 20 years) | 76 |
Descriptor
Academic Achievement | 83 |
Data Analysis | 83 |
Student Records | 83 |
Predictor Variables | 27 |
Student Characteristics | 20 |
Foreign Countries | 18 |
Data Collection | 15 |
Grade Point Average | 15 |
Achievement Gains | 14 |
Gender Differences | 13 |
Correlation | 12 |
More ▼ |
Source
Author
Ice, Phil | 2 |
Adzima, Kerry | 1 |
Akers, Cindy | 1 |
Algozzine, Bob | 1 |
Anderson, Pamela | 1 |
Anthony, Peter | 1 |
Aom Perkash | 1 |
Arrambide, Teresa | 1 |
Atchley, Wayne | 1 |
Bailey, Clare | 1 |
Bartik, Timothy J. | 1 |
More ▼ |
Publication Type
Education Level
Higher Education | 37 |
Postsecondary Education | 33 |
High Schools | 18 |
Secondary Education | 18 |
Elementary Secondary Education | 17 |
Elementary Education | 6 |
Middle Schools | 6 |
Grade 6 | 5 |
Grade 8 | 5 |
Junior High Schools | 5 |
Grade 4 | 4 |
More ▼ |
Location
United Kingdom | 4 |
Illinois | 3 |
Texas | 3 |
Virginia | 3 |
Belgium | 2 |
California | 2 |
Florida | 2 |
Michigan | 2 |
Ohio | 2 |
Alabama | 1 |
Australia | 1 |
More ▼ |
Laws, Policies, & Programs
No Child Left Behind Act 2001 | 3 |
Family Educational Rights and… | 1 |
Goals 2000 | 1 |
Assessments and Surveys
ACT Assessment | 3 |
SAT (College Admission Test) | 3 |
Florida Comprehensive… | 1 |
Motivated Strategies for… | 1 |
Schools and Staffing Survey… | 1 |
Test of English as a Foreign… | 1 |
What Works Clearinghouse Rating
Does not meet standards | 1 |
Aom Perkash; Qaisar Shaheen; Robina Saleem; Furqan Rustam; Monica Gracia Villar; Eduardo Silva Alvarado; Isabel de la Torre Diez; Imran Ashraf – Education and Information Technologies, 2024
Developing tools to support students, educators, intuitions, and government in the educational environment has become an important task to improve the quality of education and learning outcomes. Information and communication technology (ICT) is adopted by educational institutions; one such instance is video interaction in flipped teaching.…
Descriptors: Academic Achievement, Colleges, Artificial Intelligence, Predictor Variables
Zualkernan, Imran – International Association for Development of the Information Society, 2021
A significant amount of research has gone into predicting student performance and many studies have been conducted to predict why students drop out. A variety of data including digital footprints, socio-economic data, financial data, and psychological aspects have been used to predict student performance at the test, course, or program level.…
Descriptors: Prediction, Engineering Education, Academic Achievement, Dropouts
Broos, Tom; Pinxten, Maarten; Delporte, Margaux; Verbert, Katrien; De Laet, Tinne – Assessment & Evaluation in Higher Education, 2020
In this study, we present a case study involving two self-service dashboards providing feedback on learning and study skills and on academic achievement. These dashboards were offered to first-year university students in several study programmes in Flanders, Belgium. Data for this study were collected using usage tracking (N = 2875) and a survey…
Descriptors: Data Analysis, Learning Analytics, Dropout Prevention, Student Experience
Khan, Anupam; Ghosh, Soumya K. – Education and Information Technologies, 2018
Analysing the behaviour of student performance in classroom education is an active area in educational research. Early prediction of student performance may be helpful for both teacher and the student. However, the influencing factors of the student performance need to be identified first to build up such early prediction model. The existing data…
Descriptors: Data Collection, Data Analysis, Educational Research, Performance
Jeon, Byungsoo; Shafran, Eyal; Breitfeller, Luke; Levin, Jason; Rosé, Carolyn P. – International Educational Data Mining Society, 2019
This paper addresses a key challenge in Educational Data Mining, namely to model student behavioral trajectories in order to provide a means for identifying students most at risk, with the goal of providing supportive interventions. While many forms of data including clickstream data or data from sensors have been used extensively in time series…
Descriptors: Online Courses, At Risk Students, Academic Achievement, Academic Failure
Qazdar, Aimad; Er-Raha, Brahim; Cherkaoui, Chihab; Mammass, Driss – Education and Information Technologies, 2019
The use of machine learning with educational data mining (EDM) to predict learner performance has always been an important research area. Predicting academic results is one of the solutions that aims to monitor the progress of students and anticipates students at risk of failing the academic pathways. In this paper, we present a framework for…
Descriptors: Data Analysis, Academic Achievement, At Risk Students, High School Students
Data Quality Campaign, 2021
The 2020 election brought about legislative change across the country. New and veteran policymakers need information about the schools in their state. What programs are the most cost effective and work best for students? How can states attract and retain great teachers? What information do parents need to ensure that their kids are on track to…
Descriptors: Educational Policy, Policy Formation, Data Collection, Data Analysis
Sanderson, Heather; DeRousie, Jason; Guistwite, Nicole – Journal of Student Affairs Research and Practice, 2018
This study examined the impact of collegiate recreation participation on academic success as measured by grade point average, course credit completion, and persistence or graduation. Logistic and multiple regressions were run to explore the relationship between total recreation contact hours and outcome variables. Results indicated a positive and…
Descriptors: College Athletics, Recreational Activities, Academic Achievement, Success
Moore, Colleen; Bracco, Kathy Reeves – Education Insights Center, 2018
California's education data, at least as they currently are collected, managed, and made available, are not sufficient for understanding and addressing the needs of California's students. That's the conclusion of the first three reports in the series "California Education Policy, Student Data, and the Quest to Improve Student Progress,"…
Descriptors: Information Needs, Longitudinal Studies, Educational Policy, Educational Improvement
Data Quality Campaign, 2014
Regular attendance is essential to succeeding in school, and chronic absence--missing excessive amounts of school for any reason--can cause students to be off track academically. Developed in partnership with Attendance Works, this fact sheet analyzes data from the "Data for Action 2013" survey to discuss how states use data to monitor…
Descriptors: Attendance, Success, Academic Achievement, State Action
Bird, Kelli; Castleman, Benjamin L. – Research in Higher Education, 2016
College affordability continues to be a top concern among prospective students, their families, and policy makers. Prior work has demonstrated that a significant share of prospective students forgo financial aid because they did not complete the Free Application for Federal Student Aid (FAFSA); recent federal policy efforts have focused on…
Descriptors: College Freshmen, Student Financial Aid, Longitudinal Studies, Academic Achievement
Data Quality Campaign, 2015
If our destination is improved student achievement, we cannot get there without valuing and effectively using data in education. Central to reaching this goal is building trust among all those who have a stake in education that individual student data, such as attendance, course taking, grades, and test scores, are being collected for meaningful…
Descriptors: Data Collection, Data Analysis, Academic Achievement, State Departments of Education
Henry, Philip – College and University, 2019
Phillip Henry is a semi-retired former U.K. Registrar and Secretary with almost 40 years' experience in higher education. He has been active in staff development in the United Kingdom (Association of University Administrators, Academic Registrars Council, and Association of Heads of University Administration), in the United States (AACRAO and a…
Descriptors: Academic Achievement, Administrator Attitudes, Educational Experience, College Students
Cho, Moon-Heum; Yoo, Jin Soung – Interactive Learning Environments, 2017
Many researchers who are interested in studying students' online self-regulated learning (SRL) have heavily relied on self-reported surveys. Data mining is an alternative technique that can be used to discover students' SRL patterns from large data logs saved on a course management system. The purpose of this study was to identify students' online…
Descriptors: Online Courses, Self Management, Active Learning, Data Analysis
Vanwynsberghe, Griet; Vanlaar, Gudrun; Van Damme, Jan; De Fraine, Bieke – School Effectiveness and School Improvement, 2017
Although the importance of primary schools in the long term is of interest in educational effectiveness research, few studies have examined the long-term effects of schools over the past decades. In the present study, long-term effects of primary schools on the educational positions of students 2 and 4 years after starting secondary education are…
Descriptors: Secondary Education, School Effectiveness, Elementary Secondary Education, Followup Studies