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Download full textKutlu, Ömer; Babadogan, Mustafa Cem; Kumandas-Öztürk, Hatice; Altintas, Özge – Turkish Journal of Education, 2018
The purpose of this study is to improve students' knowledge and awareness regarding the scale of pollution that has engulfed the Istanbul Strait as well as the general threats faced by the ecosystem. Towards this end, 2310 1-12 grade students were sampled from schools in Istanbul to serve as study participants. To collect the research data, two…
Descriptors: Foreign Countries, Pollution, Program Effectiveness, Consciousness Raising
Direct linkPlasman, Jay Stratte; Gottfried, Michael A. – Educational Policy, 2018
Applied science, technology, engineering, and math (STEM) coursetaking is becoming more commonplace in traditional high school settings to help students reinforce their learning in academic STEM courses. Throughout U.S. educational history, vocational education has been a consistent focus for schools to keep students on the school-to-career…
Descriptors: STEM Education, High School Students, Learning Disabilities, Dropout Rate
Rozek, Christopher S.; Svoboda, Ryan C.; Harackiewicz, Judith M.; Hulleman, Christopher S.; Hyde, Janet S. – Grantee Submission, 2017
During high school, developing competence in science, technology, engineering, and mathematics (STEM) is critically important as preparation to pursue STEM careers, yet students in the United States lag behind other countries, ranking 35th in mathematics and 27th in science achievement internationally. Given the importance of STEM careers as…
Descriptors: STEM Education, Career Readiness, College Readiness, High School Students
Brown, J.; Schiller, K.; Roey, S.; Perkins, R.; Schmidt, W.; Houang, R. – National Center for Education Statistics, 2013
The 2005 National Assessment of Educational Progress (NAEP) High School Transcript Study (HSTS) found that high school graduates in 2005 earned more mathematics credits, took higher level mathematics courses, and obtained higher grades in mathematics courses than in 1990. The report also noted that these improvements in students' academic records…
Descriptors: Difficulty Level, Mathematics Achievement, Academic Records, Credits
Mac Iver, Martha Abele – Journal of Education for Students Placed at Risk, 2011
This 5-year longitudinal randomized study focused on the effects of a dropout prevention program implemented at two urban high schools. The program incorporated the characteristics of personalization found in previous research to have some positive effects, and typical of the type of programs implemented in many high schools nationwide. The…
Descriptors: Longitudinal Studies, Urban Schools, High Schools, Dropout Programs
Pazera, Carol – Online Submission, 2010
This report compares characteristics of AISD students who had taken career and technical education (CTE) courses or a sequence of such courses, to those of students who had not. The role of CTE in postsecondary employment and enrollment is also examined.
Descriptors: Vocational Education, School Districts, Student Characteristics, Academic Achievement
Harkreader, Steve; Hughes, John; Tozzi, Melanie Hicks; Vanlandingham, Gary – Journal of Student Financial Aid, 2008
Florida's Bright Futures program is one of the nation's largest merit-based scholarship initiatives. This study used high school transcript and college enrollment data to examine the program's impact on high school course-taking patterns, school grades, college entrance exam scores, and rates of college attendance over time. The study indicates…
Descriptors: High Schools, Course Selection (Students), College Attendance, Scholarships
Lynch, Collin F., Ed.; Merceron, Agathe, Ed.; Desmarais, Michel, Ed.; Nkambou, Roger, Ed. – International Educational Data Mining Society, 2019
The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…
Descriptors: Data Collection, Data Analysis, Information Retrieval, Content Analysis
