NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 4 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Sole, Marla A. – Mathematics Teacher, 2016
Every day, students collect, organize, and analyze data to make decisions. In this data-driven world, people need to assess how much trust they can place in summary statistics. The results of every survey and the safety of every drug that undergoes a clinical trial depend on the correct application of appropriate statistics. Recognizing the…
Descriptors: Statistics, Mathematics Instruction, Data Collection, Teaching Methods
Peer reviewed Peer reviewed
Direct linkDirect link
Raju, Dheeraj; Schumacker, Randall – Journal of College Student Retention: Research, Theory & Practice, 2015
The study used earliest available student data from a flagship university in the southeast United States to build data mining models like logistic regression with different variable selection methods, decision trees, and neural networks to explore important student characteristics associated with retention leading to graduation. The decision tree…
Descriptors: Student Characteristics, Higher Education, Graduation Rate, Academic Persistence
Peer reviewed Peer reviewed
Direct linkDirect link
Martínez Abad, Fernando; Chaparro Caso López, Alicia A. – School Effectiveness and School Improvement, 2017
In light of the emergence of statistical analysis techniques based on data mining in education sciences, and the potential they offer to detect non-trivial information in large databases, this paper presents a procedure used to detect factors linked to academic achievement in large-scale assessments. The study is based on a non-experimental,…
Descriptors: Foreign Countries, Data Collection, Statistical Analysis, Evaluation Methods
Peer reviewed Peer reviewed
Direct linkDirect link
Carpenter, Dick M., II; Robertson, Jenifer Walsh; Johnson, Michele E.; Blum, Scott – Journal of School Public Relations, 2014
This study measured the salience of, sentiment of, and topics about schools in social media. Based on a mixed-methods approach, results indicated that school districts do not appear to be discussed often or widely, but the small numbers of people who communicate about districts do so repeatedly, positively, and in concentration. Larger and…
Descriptors: Social Networks, Internet, Educational Research, Information Sources