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Download full textSciarra, Daniel T.; Seirup, Holly J.; Sposato, Elizabeth – Professional Counselor, 2016
This study investigated factors from high school that might predict college persistence. The sample consisted of 7,271 participants in three waves of data collection (2002, 2004 and 2006) who participated in the Educational Longitudinal Study (ELS; U.S. Department of Education, 2008). A multinomial logistic regression mode was employed to…
Descriptors: Predictor Variables, Academic Persistence, High School Graduates, Longitudinal Studies
Direct linkLu, Jiamei; Li, Daqi; Stevens, Carla; Ye, Renmin – Journal of Educational Computing Research, 2016
Using Program for International Student Assessment (PISA) 2012, an international education database, this study analyzed the evaluations of computer use for academic learning by 15-year-old students from seven Edu-systems (unit in PISA) in Eastern Asia. Six variables were identified in association with students' evaluations of computer use…
Descriptors: Foreign Countries, College Students, Computer Attitudes, Computer Uses in Education
Barnes, Tiffany, Ed.; Chi, Min, Ed.; Feng, Mingyu, Ed. – International Educational Data Mining Society, 2016
The 9th International Conference on Educational Data Mining (EDM 2016) is held under the auspices of the International Educational Data Mining Society at the Sheraton Raleigh Hotel, in downtown Raleigh, North Carolina, in the USA. The conference, held June 29-July 2, 2016, follows the eight previous editions (Madrid 2015, London 2014, Memphis…
Descriptors: Data Analysis, Evidence Based Practice, Inquiry, Science Instruction
