Wendy Chu is a rising junior at Macalester College majoring in Psychology. Her background as a first-generation, low-income intellectual has propelled her to seek ways in which she can contribute to the knowledge of psychopathology. She maintains her desire to obtain a Ph.D. in Clinical Science at a renowned university.
As a registered nurse, I will address the ways in which poverty-induced hardships impact health in underrepresented communities.
Exploring the Construct Validity of Letters of Recommendation in Graduate Admissions: The Hidden “Unknowns” Within
Abstract: Letters of recommendation (LORs) are widely used in admissions decisions. Although many place heavy weight on LORs in their decision making, comparatively little is known about what information they actually provide. This study examined one unexamined feature of letters of recommendation. Specifically, no other study has examined the properties of the “unknown” or “no opportunity to observe” response a recommender might give when rating an applicant’s qualities, as many assume they contain no information. The number of “unknowns” given by a letter writer was correlated with applicant characteristics and the amount of time the applicant has worked with the letter writer. In a sample of 194 applicants to the graduate biomedical engineering program at a large public university, results confirmed that these “unknowns” do in fact contain information about an applicant as more unknown ratings were negatively associated with overall ratings and the duration of the students’ relationship with the recommender. The “unknown” responses may provide useful information and yield an improved graduate selection process in combination with other ratings. Download poster. [PDF]
Nathan R. Kuncel is the Marvin D. Dunnette Distinguished Professor at the University of Minnesota, where he received his undergraduate and graduate degrees. Nathan is a Fellow of APS and SIOP and also received the Anne Anastasi Early Career Award in 2010 and the Cattell Early Career Research Award in 2009. His research focuses on individual differences and its ability to predict various measures of performance, including work and academic success. His work has appeared in Science, Psychological Bulletin, Harvard Business Review, and Psychological Science.