Dataset Information

Multi-institutional study of GRE scores as predictors of STEM PhD degree completion: GRE gets a low mark.

ABSTRACT: The process of selecting students likely to complete science, technology, engineering and mathematics (STEM) doctoral programs has not changed greatly over the last few decades and still relies heavily on Graduate Record Examination (GRE) scores in most U.S. universities. It has been long debated whether the GRE is an appropriate selection tool and whether overreliance on GRE scores may compromise admission of students historically underrepresented in STEM. Despite many concerns about the test, there are few studies examining the efficacy of the GRE in predicting PhD completion and even fewer examining this question in STEM fields. For the present study, we took advantage of a long-lived collaboration among institutions in the Northeast Alliance for Graduate Education and the Professoriate (NEAGEP) to gather comparable data on GRE scores and PhD completion for 1805 U.S./Permanent Resident STEM doctoral students in four state flagship institutions. We found that GRE Verbal (GRE V) and GRE Quantitative (GRE Q) scores were similar for women who completed STEM PhD degrees and those who left programs. Remarkably, GRE scores were significantly higher for men who left than counterparts who completed STEM PhD degrees. In fact, men in the lower quartiles of GRE V or Q scores finished degrees more often than those in the highest quartile. This pattern held for each of the four institutions in the study and for the cohort of male engineering students across institutions. GRE scores also failed to predict time to degree or to identify students who would leave during the first year of their programs. Our results suggests that GRE scores are not an effective tool for identifying students who will be successful in completing STEM doctoral programs. Considering the high cost of attrition from PhD programs and its impact on future leadership for the U.S. STEM workforce, we suggest that it is time to develop more effective and inclusive admissions strategies.

SUBMITTER: Petersen SL

PROVIDER: S-EPMC6205626 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Multi-institutional study of GRE scores as predictors of STEM PhD degree completion: GRE gets a low mark.

Petersen Sandra L SL Erenrich Evelyn S ES Levine Dovev L DL Vigoreaux Jim J Gile Krista K

PloS one 20181029 10

The process of selecting students likely to complete science, technology, engineering and mathematics (STEM) doctoral programs has not changed greatly over the last few decades and still relies heavily on Graduate Record Examination (GRE) scores in most U.S. universities. It has been long debated whether the GRE is an appropriate selection tool and whether overreliance on GRE scores may compromise admission of students historically underrepresented in STEM. Despite many concerns about the test, ...[more]

PMID: 30372469

Similar Datasets

Project description:In order to acquire consistent k-space data in MR elastography, a fixed temporal relationship between the MRI sequence and the underlying period of the wave needs to be ensured. To this end, conventional GRE-MRE enforces synchronization through repeated triggering of the transducer and forcing the sequence repetition time to be equal to an integer multiple of the wave period. For wave frequencies below 100 Hz, however, this leads to prolonged acquisition times, as the repetition time scales inversely with frequency. A previously developed multi-shot approach (eXpresso MRE) to multi-slice GRE-MRE tackles this issue by acquiring an integer number of slices per wave period, which allows acquisition to be accelerated in typical scenarios by a factor of two or three. In this work, it is demonstrated that the constraints imposed by the eXpresso scheme are overly restrictive. We propose a generalization of the sequence in three steps by incorporating sequence delays into imaging shots and allowing for interleaved wave-phase acquisition. The Ristretto scheme is compared in terms of imaging shot and total scan duration relative to eXpresso and conventional GRE-MRE and is validated in three different phantom studies. First, the agreement of measured displacement fields in different stages of the sequence generalization is shown. Second, performance is compared for 25, 36, 40, and 60 Hz actuation frequencies. Third, the performance is assessed for the acquisition of different numbers of slices (13 to 17). In vivo feasibility is demonstrated in the liver and the breast. Here, Ristretto is compared with an optimized eXpresso sequence, leading to scan accelerations of 15% and 5%, respectively, without compromising displacement field and stiffness estimates in general. The Ristretto concept allows us to choose imaging shot durations on a fine grid independent of the number of slices and the wave frequency, permitting 2- to 4.5-fold acceleration of conventional GRE-MRE acquisitions.

Project description:To conduct a comprehensive analysis of radiologist-made assessments of glioblastoma (GBM) tumor size and composition by using a community-developed controlled terminology of magnetic resonance (MR) imaging visual features as they relate to genetic alterations, gene expression class, and patient survival.Because all study patients had been previously deidentified by the Cancer Genome Atlas (TCGA), a publicly available data set that contains no linkage to patient identifiers and that is HIPAA compliant, no institutional review board approval was required. Presurgical MR images of 75 patients with GBM with genetic data in the TCGA portal were rated by three neuroradiologists for size, location, and tumor morphology by using a standardized feature set. Interrater agreements were analyzed by using the Krippendorff α statistic and intraclass correlation coefficient. Associations between survival, tumor size, and morphology were determined by using multivariate Cox regression models; associations between imaging features and genomics were studied by using the Fisher exact test.Interrater analysis showed significant agreement in terms of contrast material enhancement, nonenhancement, necrosis, edema, and size variables. Contrast-enhanced tumor volume and longest axis length of tumor were strongly associated with poor survival (respectively, hazard ratio: 8.84, P = .0253, and hazard ratio: 1.02, P = .00973), even after adjusting for Karnofsky performance score (P = .0208). Proneural class GBM had significantly lower levels of contrast enhancement (P = .02) than other subtypes, while mesenchymal GBM showed lower levels of nonenhanced tumor (P < .01).This analysis demonstrates a method for consistent image feature annotation capable of reproducibly characterizing brain tumors; this study shows that radiologists' estimations of macroscopic imaging features can be combined with genetic alterations and gene expression subtypes to provide deeper insight to the underlying biologic properties of GBM subsets.

Dataset Information

Multi-institutional study of GRE scores as predictors of STEM PhD degree completion: GRE gets a low mark.

Publications

Multi-institutional study of GRE scores as predictors of STEM PhD degree completion: GRE gets a low mark.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets