Factors associated with academic performance among Master of Nursing students: An exploratory study using the ALSET Educational Data Lake
Wednesday 23 September 2020 - 3:30-4:30 pm
---> [UPDATE: watch the seminar recording on the ALSET YouTube Channel] <---
Health institutions’ nursing leaders play a significant role in the selection of registered nurses (RNs) for the Master of Nursing (MN) programme, the preparatory advanced practice nurse (APN) training provided by the NUS. Nursing leaders were observed to select RNs who were more senior in age, work experience and job title; however, RNs with these characteristics were less likely to have interest for the role. Instead, the RNs’ undergraduate grade point average was reported to have a strong predictive value for academic success in graduate studies, potentially suggesting that clinical experiences may not ensure the academic success of MN study.
Therefore, the aim of the study was to explore the factors associated with better academic performance in the MN programme. A retrospective study was conducted in Feb 2020 and students enrolled to the MN program between 2010 to 2017 were included in the study. ALSET Data Lake was assessed through a secured connection (Jupyter Notebook). R was used to merge the tables into an operational format for data analysis. MN students’ demographic characteristics were compared with the CAP scores of different modules using inferential statistics and regression. 246 graduates were eligible for this study. The mean age was 34.1 (SD=5.5). Majority were Female (93.1%) and Chinese (90.2%), 54.3% were married. Younger age (b= -0.010, p<0.001) and NUS alumni (b= 0.393, p<0.001) had a significant greater likelihood of achieving a higher overall CAP score. For six of the eight individual modules, age was also negatively associated with CAP score (p < 0.01). At present, to be enrolled in the MN programme, a RN needs to have at least five years of relevant work experience. Considering that younger MN students have a higher likelihood of doing well in the MN programme, it may be propitious to review the current MN programme enrolment criteria.The whole research team included Ms Brigitte Woo, Dr Wentao Zhou, Dr Wilson Tam (From the Alice Lee Centre for Nursing Studies, Yong Loo Lin School of Medicine, NUS) and Kevin Hartman (from NUS-ALSET)
The presentation will provide further insights into this study and additional details on the way NUS faculty can use the ALSET Data Lake for their own educational research.
Ms Brigitte Woo, PhD candidate – Ms Woo’s research interests centre around the role, utilisation, and professional development of advanced practice nurses in Singapore. Thus far, she has conducted two nationwide cross-sectional studies and has ongoing collaborations with MOH Chief Nursing Officer office.
Dr Wilson Tam, Assistant Professor – Dr Tam is an epidemiologist and statistician by training, his research focuses on the risk factors of cardiovascular diseases. He has experience in database management and analysis.
Mr Kevin Hartman is Translational Research Coordinator at ALSET and oversees the use of ALSET Data Lake. Prior to ALSET, Kevin completed his undergraduate coursework in communication. His graduate studies in educational psychology focused on the intersection of learning and technology design.
The presentation will be held online.
Please RSVP to be invited to the webinar
(picture credits: NUS)