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Homer, Gina M. – ProQuest LLC, 2013
This qualitative research study focuses on retention of first-year learners by exploring three variables: academic support, social support, and coping strategies. The research method is grounded theory founded by Glaser, B. and Strauss, A. (1967). The philosophical assumptions of the study are Constructivist and Advocacy/Participatory knowledge…
Descriptors: Qualitative Research, Higher Education, Academic Persistence, College Freshmen
Ogilvie, Gina M. – ProQuest LLC, 2011
Technology usage is increasing important for community college students, but whether nontraditional students differ from traditional students in technology usage and support was unclear. Further, it was not known whether Nontraditional and Traditional community college students feel equally connected to the college when using social networking…
Descriptors: Learner Engagement, Nontraditional Students, Two Year College Students, Community Colleges
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Simonson, Michael, Ed. – Association for Educational Communications and Technology, 2015
For the thirty-eighth time, the Research and Theory Division of the Association for Educational Communications and Technology (AECT) is sponsoring the publication of these Proceedings. Papers published in this volume were presented at the annual AECT Convention in Indianapolis, Indiana. The Proceedings of AECT's Convention are published in two…
Descriptors: Information Technology, Educational Technology, Student Attitudes, Online Courses
Rey, Jason Goering – ProQuest LLC, 2010
Online education is a modality of teaching that has proliferated throughout higher education in such a rapid form and without any guidelines that its quality and merit is largely unknown, hotly debated, and still evolving. Institutions have used online education as a method of reducing costs and increasing enrollments and students have flocked to…
Descriptors: Video Technology, Teacher Effectiveness, Community Colleges, Academic Persistence
Schaffhauser, Dian – Campus Technology, 2009
Using data to track and manage student enrollment is steadily becoming a standard practice on both two-year and four-year campuses. Data mining enables colleges to create predictive models for identifying behaviors that put students at risk for dropping out, flag students who engage in these behaviors, and help identify practices that work in…
Descriptors: Community Colleges, Educational Strategies, Academic Support Services, Attendance Patterns