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Educational Data Mining: An Application of a Predictive Model of Online Student Enrollment Decisions
Cody Gene Singer – ProQuest LLC, 2023
College and university enrollment has decreased nationwide every year for more than a decade as educational consumers increasingly question the value of higher education and discover alternatives to the traditional university system. Enrollment professionals seeking growth are tasked to develop and implement innovative solutions to address…
Descriptors: Data Collection, Predictor Variables, Electronic Learning, Enrollment
National Forum on Education Statistics, 2018
The Forum Guide to Early Warning Systems provides information and best practices to help education agencies plan, develop, implement, and use an early warning system in their agency to inform interventions that improve student outcomes. The document includes a review of early warning systems and their use in education agencies and explains the…
Descriptors: Educational Indicators, Best Practices, Elementary Secondary Education, Data Collection
Lido, Catherine; Osborne, Michael; Livingston, Mark; Thakuriah, Piyushimita; Sila-Nowicka, Katarzyna – International Journal of Lifelong Education, 2016
This research employs novel techniques to examine older learners' journeys, educationally and physically, in order to gain a "three-dimensional" picture of lifelong learning in the modern urban context of Glasgow. The data offers preliminary analyses of an ongoing 1,500 household survey by the Urban Big Data Centre (UBDC). A sample of…
Descriptors: Older Adults, Adult Learning, Lifelong Learning, Urban Areas
Skelly, JoAnne; Hill, George; Singletary, Loretta – Journal of Extension, 2014
Extension professionals often assess community needs to determine programs and target audiences. Data can be collected through surveys, focus group and individual interviews, meta-analysis, systematic observation, and other methods. Knowledge gaps are identified, and programs are designed to resolve the deficiencies. However, do Extension…
Descriptors: Needs Assessment, Data Analysis, Community Needs, Extension Education
Test, David W.; Richter, Sharon; Knight, Victoria; Spooner, Fred – Focus on Autism and Other Developmental Disabilities, 2011
This comprehensive review of Social Story[TM} literature included (a) a descriptive review, (b) an analysis of research quality, and (c) a meta-analysis using percentage of nonoverlapping data. In the review, 28 studies were included; 18 were included in the meta-analysis. Descriptive results highlighted information on participants, dependent…
Descriptors: Research Design, Meta Analysis, Literature Reviews, Alignment (Education)
Lee, In Heok – Career and Technical Education Research, 2012
Researchers in career and technical education often ignore more effective ways of reporting and treating missing data and instead implement traditional, but ineffective, missing data methods (Gemici, Rojewski, & Lee, 2012). The recent methodological, and even the non-methodological, literature has increasingly emphasized the importance of…
Descriptors: Vocational Education, Data Collection, Maximum Likelihood Statistics, Educational Research
VanderLaan, Ski R. – ProQuest LLC, 2010
This mixed methods study (Creswell, 2008) was designed to test the influence of collaborative testing on learning using a quasi-experimental approach. This study used a modified embedded mixed method design in which the qualitative and quantitative data, associated with the secondary questions, provided a supportive role in a study based primarily…
Descriptors: Formative Evaluation, Testing, Predictor Variables, Program Effectiveness
Alverson, Charlotte Y.; Naranjo, Jason M.; Yamamoto, Scott; Unruh, Deanne K. – Career Development for Exceptional Individuals, 2010
The current U.S. federal mandate for educational accountability requires state departments of education to collect data on the postschool employment and postsecondary school and/or training enrollment of young adults with disabilities. To examine how these data have been collected, we conducted a literature synthesis of follow-up and follow-along…
Descriptors: Disabilities, Young Adults, State Departments of Education, Accountability
Boyer, Kristy Elizabeth, Ed.; Yudelson, Michael, Ed. – International Educational Data Mining Society, 2018
The 11th International Conference on Educational Data Mining (EDM 2018) is held under the auspices of the International Educational Data Mining Society at the Templeton Landing in Buffalo, New York. This year's EDM conference was highly competitive, with 145 long and short paper submissions. Of these, 23 were accepted as full papers and 37…
Descriptors: Data Collection, Data Analysis, Computer Science Education, Program Proposals
Alverson, Charlotte Y.; Bayliss, Camilla; Naranjo, Jason M.; Yamamoto, Scott H.; Unruh, Deanne – National Post-School Outcomes Center, 2006
The purpose of this brief is to summarize the methodologies and outcome measures used in Post-School Outcomes follow-up and follow-along studies of adolescents with disabilities. As a requisite in the Request for Proposal for funding of the National Post-School Outcomes Center (NPSO), knowledge development activities were to include: "Conducting a…
Descriptors: Disabilities, Literature Reviews, Followup Studies, Outcomes of Education
Barnes, Tiffany, Ed.; Desmarais, Michel, Ed.; Romero, Cristobal, Ed.; Ventura, Sebastian, Ed. – International Working Group on Educational Data Mining, 2009
The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…
Descriptors: Data Analysis, Educational Research, Conferences (Gatherings), Foreign Countries