[Determining learning style and its relationship with educational achievement in nursing and midwifery students]

The health care system and the method of teaching are very dynamic. Awareness of students learning styles provides information for teachers to observe the variation in training methods and help students to facilitate learning. The purpose of this study is to determination of the learning styles of nursing and midwifery students and its relationship with their educational achievement. In this cross-sectional study, the undergraduate nursing and midwifery students of Tehran University of Medical Sciences in third and first academic year were investigated in 2008. Data were collected through the learning style questionnaire and demographic information. Gathered data were analyzed by statistical tests included t-test, ?2 and kruscal - valis through SPSS software The dominant learning styles of students, is the diverging style. Significant relationship between their learning style and educational achievement was not observed. There was significant correlation between their learning style and average scores in general courses [P=0.045]. Considering the dominant diverging styles and diversity in learning styles of nursing and midwifery students under study; consideration of individual differences and different learning styles of students in designing various methods of teaching using the existing infrastructure facilities and information technology is proposed

[Designing nursing work scheduler intelligent system based on genetic algorithm]

Adjustment of nursing scheduling for specific periods of time to meet the needs of hospitals, nurses and patients is a time-consuming and challenging task for nursing managers. The aim of this study was to design a nursing scheduler system based on genetic algorithm to render better services to patients and overcome traditional scheduling problems. In this applied research, we designed software based on the data derived from interviews with the personnel of two pediatric wards. We transformed the expert entity planning procedure to mathematic function using Genetic Algorithm Programming and create the schedule. We compared the system-designed schedule with the schedule that was written by experts in MATLAB software. The results showed that the system-designed schedule resulted in 57% reduction in the arrangement costs and 93% time saving for nursing managers in comparison with the expert-designed schedule during 6 months. System-designed schedule had higher efficiency than the expert-designed one. It entailed higher efficiency of managers and higher job satisfaction of nurses. It also reduced problems of working with paper schedules. Nurses' preferences and hospital requirements could be taking into account, as well. Since we used the limited data gathered from two selected wards for writing the program, the program should be modified based on the data provided from other wards. Further studies are needed to design similar systems with more details in order that it can be available in various wards of hospitals