Computer and laboratory simulation in the teaching of neonatal nursing: innovation and impact on learning

Objectives: to evaluate the cognitive learning of nursing students in neonatal clinical evaluation from a blended course with the use of computer and laboratory simulation; to compare the cognitive learning of students in a control and experimental group testing the laboratory simulation; and to assess the extracurricular blended course offered on the clinical assessment of preterm infants, according to the students. Method: a quasi-experimental study with 14 Portuguese students, containing pretest, midterm test and post-test. The technologies offered in the course were serious game e-Baby, instructional software of semiology and semiotechnique, and laboratory simulation. Data collection tools developed for this study were used for the course evaluation and characterization of the students. Nonparametric statistics were used: Mann-Whitney and Wilcoxon. Results: the use of validated digital technologies and laboratory simulation demonstrated a statistically significant difference (p = 0.001) in the learning of the participants. The course was evaluated as very satisfactory for them. The laboratory simulation alone did not represent a significant difference in the learning. Conclusions: the cognitive learning of participants increased significantly. The use of technology can be partly responsible for the course success, showing it to be an important teaching tool for innovation and motivation of learning in healthcare.

Entrepreneurial Motivations Questionnaire: AFC and CFA in academy.

Background Entrepreneurship has been considered essential to create value, being a powerful driver of economic and social development. Academy must invest in the development of entrepreneurial skills in students ("Entrepreneurial Academy"). Objective: To analyse the psychometric proprieties of the EMQ-Entrepreneurial Motivations Questionnaire. Methods Sample: 6,532 students from 17 polytechnic Institutes of Portugal. Measure: EMQ, composed by measures of Entrepreneurial motives for the business, Entrepreneurial influences, and Support Services. Results Exploratory factor analysis (EFA) for Entrepreneurial-Motives-for-thebusiness (KMO = .921, X2 = 54387.94, p < .001) extracted 4 factors, explaining 53.81 % of variance (EV): F1-Family security (19.92 % EV; M= 4.07, SD = 0.67), F2-Prestige (14.60 % EV; M= 3.25, SD = 0.75), F3- Independence (13.13 % EV; M= 3.33, SD = 0.75), and F4-Realization of an opportunity (11.15 % EV; M= 4.08, SD = 0.56). This factorial structure was supported by Confirmatory factor analysis (CFA), with an acceptable fit: RMSEA = .084. EFA of Entrepreneurial-Influences (KMO = .916, X2 = 60584.93, p < .001), extracted 4 factors, EV 60.08 %: F1-Resources availability (21.25 % EV; M= 3.86, SD = 0.68), F2-Stable customers and incentives (19.70 % EV; M= 3.82, SD = 0.65), F3-Social and economic instability (11.11 % EV; M= 2.96, SD = 1.06), and F4-Opportunities in the sector and residence area (8.03 % EV; M= 3.29, SD = 0.95). This factorial structure was supported by CFA, with an acceptable fit: RMSEA = .073. EFA of Support-Services (KMO = .995, X2 = 57311.43, p < .001) extracted 2 factors, EV 58.43 %: F1-Financial support (32.59 % EV; M= 3.93, SD = 0.69) and F2-Prestige (25.84 % EV; M= 3.95, SD = 0.65). This factorial structure was supported by CFA, with an acceptable fit: RMSEA = .090. The health group showed scores mostly above global average in factors. Conclusions EMQ showed adequate psychometric properties. The instrument is useful for measuring entrepreneurships motivations in health.