Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Nursing schools strive to select a diverse student population who are likely to succeed by ensuring timely student progression through the program and effective use of educational sources. The purpose of this systematic literature review is to explore the preadmission variables and selection criteria that predict student success in 4-year baccalaureate nursing programs in the U.S. Sixteen articles met the eligibility criteria, and six measures were used to define student success: (a) early academic success, particularly during the first and second year; (b) attrition; (c) timely completion of the program; (d) graduation; (e) performance in nursing courses; and (f) academic performance in other science courses. Typically, the core set of cognitive predictors used in the admission process in nursing schools were pre-nursing GPA, pre-nursing collegiate science GPA, and scores on standardized aptitude exams. This review suggests that it is challenging to isolate one single variable as the best predictor of student success; however, using a combination of variables can offer a reliable prediction method. More researchers should consider using a theoretical basis to guide their inquiry on this topic. Additionally, researchers should examine admission variables that are most relevant across programs.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1016/j.nepr.2020.102865 | DOI Listing |
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