PAR Framework Releases Results of Groundbreaking Research Predicting Transfer Student Success With Community College Data.

This study replicated research conducted over several years by UMUC that had considered factors and behaviors among community college students to identify variables predicting academic success at the students’ 4-year transfer institution. The ability to apply results from one research study based on a local sample to a larger, national population has traditionally been compromised by limited generalizability. Thanks to the PAR Framework Common Data Definitions and massive student outcomes level dataset, PAR can serve as vehicle for validating the results of research conducted at one institution with results achieved using a single institution, multiple institutions or a national dataset. Thanks to PAR partner institutions UMUC ( working with Drs. Karen Vignare and Denise Nadasen) and U of Hawaii (working with Drs. Hae Okimoto and Pearl Iboshi) to use community college student outcomes data to predict success in their 4 year transfer programs. To read the original press release please click here