Data Interrogation: Using Complementary and Opposing Lenses for Un-and Dis-covering

Friday, November 15, 2019
11:30 a.m.–12:30 p.m.

This presentation examined the role of biases and downfalls in using linear regression analyses and presented alternate analysis methods used in research that may allow for emergent patterns and categories from the data. The presentation included an overview of multiple machine-learning analytic models, including classification and regression trees (CART) and cluster analysis, that can be applied to student college placements in the Pacific Region and other contexts in which researchers need to examine emergent data structures that may be invisible with traditional analyses.

The presentation was grounded in REL Pacific's contextual approach to conducting research in the Pacific Region, included current proposed studies on Using High School and College Data to Predict Teacher Candidates' Performance on the Praxis Core^® Exam at the Unibetsedaåt Guaåhan (University of Guam) and Factors Associated with Third Grade Reading Outcomes of Students in the Commonwealth of Northern Marianas Islands Public School System), and shared information about methodologies and reporting structures that are easily accessible to practitioners and that may foster their understanding of findings within diverse contexts and in turn facilitate changes in practice.

Location

Minneapolis Convention Center, Hilton Minneapolis, Minnesota

Speakers

Dr. Bradley Rentz, REL Pacific at McREL International
Dr. Sheila A. Arens, REL Pacific at McREL International

More Information

  Agenda (306 KB)