Literature DB >> 10827101

Age and 'type' of domain specific entry qualifications as predictors of student nurses' performance in biological, social and behavioural sciences in nursing assessments.

R Ofori1.   

Abstract

The present study explored the effects of age and 'type' of entry qualifications in psychology, sociology and biology on student performance in 'the psychological, sociological and biological perspectives in nursing' module assessments, respectively. Data from 222 students undertaking 'the pre-registration diploma in nursing' programme at a university in the north West of England were analysed. The study found no significant differences in performance among those students with GCSE 'O' level, those with access and those without any type of domain specific qualifications. However, student age significantly predicted performance, with such performances found to be highly consistent across the three modules. The 'non-mature' students (aged < 20 years) were identified in the study as being at risk in terms of academic performance whilst the 'very mature' students (aged > 34 years) were found to predict better overall performance. The findings suggest that, paper qualifications such as GCSE O.level, GNVQ or BTEC in psychology, sociology or biology should not be relied upon as predictors of academic performance in their related nursing modules when selecting potential nurses. On the basis of the findings and their probable explanations, it seems possible that the entry gate to nursing can further be widened by giving more credit to the older applicant who has, for example, achieved NVQ at level 2 or 3. However, such flexibility in nurse selection will have to be matched with equal flexibility in the pre-registration diploma in nursing curriculum which at present fails to recognize 'at risk' groups. The findings and the implications for nurse education and recruitment and discussed with support from a growing number of studies investigating student approaches to studying and learning.

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Year:  2000        PMID: 10827101     DOI: 10.1054/nedt.1999.0396

Source DB:  PubMed          Journal:  Nurse Educ Today        ISSN: 0260-6917            Impact factor:   3.442


  4 in total

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3.  Evidence-based selection process to the Master of Public Health program at Medical University.

Authors:  Mariusz Panczyk; Grzegorz Juszczyk; Aleksander Zarzeka; Łukasz Samoliński; Jarosława Belowska; Ilona Cieślak; Joanna Gotlib
Journal:  BMC Med Educ       Date:  2017-09-11       Impact factor: 2.463

4.  Risk Factors for Positive Appraisal of Mistreatment during Childbirth among Ethiopian Midwifery Students.

Authors:  Rena Bakker; Ephrem D Sheferaw; Tegbar Yigzaw; Jelle Stekelenburg; Marlou L A de Kroon
Journal:  Int J Environ Res Public Health       Date:  2020-04-14       Impact factor: 3.390

  4 in total

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