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Showing 1 to 15 of 62 results Save | Export
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Ramesh, Arti; Goldwasser, Dan; Huang, Bert; Daume, Hal; Getoor, Lise – IEEE Transactions on Learning Technologies, 2020
Maintaining and cultivating student engagement is critical for learning. Understanding factors affecting student engagement can help in designing better courses and improving student retention. The large number of participants in massive open online courses (MOOCs) and data collected from their interactions on the MOOC open up avenues for studying…
Descriptors: Online Courses, Learner Engagement, Student Behavior, Success
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Williamson, Ben – Journal of Education Policy, 2016
Educational institutions and governing practices are increasingly augmented with digital database technologies that function as new kinds of policy instruments. This article surveys and maps the landscape of digital policy instrumentation in education and provides two detailed case studies of new digital data systems. The Learning Curve is a…
Descriptors: Visualization, Synchronous Communication, Governance, Data Collection
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Soltaninejad, Mehraneh – Malaysian Online Journal of Educational Sciences, 2015
The purpose of this study is to examine the relationships between achievement goal orientations and Learning Strategies. The sample of study consists of 350 public high school students (135 males and 215 females, mean age: 17 ± 0.65) from two high schools in Kerman province of Iran selected by random multistage cluster sampling method. In this…
Descriptors: Goal Orientation, Learning Strategies, Structural Equation Models, Investigations
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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
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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
Kadhi, T.; Rudley, D.; Holley, D.; Krishna, K.; Ogolla, C.; Rene, E.; Green, T. – Online Submission, 2010
The following report of descriptive statistics addresses the attendance of the 2012 class and the average Actual and Predicted 1L Grade Point Averages (GPAs). Correlational and Inferential statistics are also run on the variables of Attendance (Y/N), Attendance Number of Times, Actual GPA, and Predictive GPA (Predictive GPA is defined as the Index…
Descriptors: Grade Point Average, Law Schools, Statistical Analysis, Databases
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Hartas, Dimitra – British Educational Research Journal, 2012
Using a UK representative sample from the Millennium Cohort Study, the present study examined the unique and cumulative contribution of children's characteristics and attitudes to school, home learning environment and family's socio-economic background to children's language and literacy at the end of Key Stage 1 (age seven-years-old).…
Descriptors: Foreign Countries, Cohort Analysis, Longitudinal Studies, Student Attitudes
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Cox, G. W.; Hughes, W. E., Jr.; Etzkorn, L. H.; Weisskopf, M. E. – IEEE Transactions on Education, 2009
This paper presents the results of an analysis of indicators that can be used to predict whether a student will succeed in a Computer Science Ph.D. program. The analysis was conducted by studying the records of 75 students who have been in the Computer Science Ph.D. program of the University of Alabama in Huntsville. Seventy-seven variables were…
Descriptors: Case Studies, Prediction, Computer Science Education, Doctoral Degrees
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Hunt, Dennis; Randhawa, Bikkar S. – Educational and Psychological Measurement, 1973
Descriptors: Academic Achievement, Cognitive Ability, Computer Science, Measurement Techniques
Tallmadge, G. Kasten – 1988
The question of regression to the mean is discussed in the contexts of the Title I Evaluation and Reporting System (TIERS) and the Bilingual Education Evaluation System (BEES), both of which involve assessing the achievement growth of project students from pre- to post-test. The correction formula recommended for use with TIERS was designed to…
Descriptors: Academic Achievement, Correlation, Predictive Measurement, Pretests Posttests
Weiss, Kenneth P. – Coll Univ, 1970
This study represents an approach to developing a non-linear predictive system by which college applicants may be rank ordered. (IR)
Descriptors: Academic Achievement, Admission (School), Clinical Diagnosis, Higher Education
Black, Hubert P. – 1969
To determine how well certain factors would predict academic achievement, 97 freshmen and 48 sophomores, all full-time 1968-69 students, were tested. The factors were (1) high school GPA, (2) American College Testing (ACT) English test, (3) ACT math portion, (4) ACT social studies portion, (5) ACT natural science portion. The criterion of…
Descriptors: Academic Achievement, Dropout Characteristics, Grade Point Average, Predictive Measurement
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Mack, Faite R-P – Journal of Negro Education, 1974
The research reported contrasted the preregistration characteristics of graduates and non-graduates from the Special Educational Opportunities Program at the University of Illinois at Urbana-Champaign; 62 graduates and 433 non-graduates were included in the study sample. (Author/JM)
Descriptors: Academic Achievement, Academic Aptitude, College Graduates, College Programs
Downes, Beverley – Australian University, 1976
A Model predicts a student's academic performance in his first year in a particular department at a university. It uses an aggregate selection score based on aggregate results obtained at a public examination along with a measure of the student's ability in one or more specific subjects or areas relevant to the department. (LBH)
Descriptors: Academic Achievement, Admission (School), College Freshmen, Foreign Countries
Nolan, Edwin J.
A correlational study was conducted using ACT (American College Test) sub-test scores and actual grades earned in corresponding subject areas in order to determine if the ACT was an effective predictor for student's grades at Southern West Virginia Community College (SWVCC). Study subjects were all students (n= 241) who had ACT test scores on file…
Descriptors: Academic Achievement, Community Colleges, Grade Prediction, Predictive Measurement
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