Nursing and Health Sciences (2016), 18, 262–269

Education Article

Effectiveness of simulation with team-based learning in newborn nursing care Kyung-Ah Kang, PhD,1 Shin-Jeong Kim, DNSc,2 Jina Oh, PhD, RN,3 Sunghee Kim, PhD, RN4 and Myung-Nam Lee, PhD, RN5 1 Department of Nursing, Sahmyook University, 4Red Cross College of Nursing, Chung-Ang University, Seoul, 2Department of Nursing, Hallym University, Chuncheon, 3Department of Nursing, Institute of Health Science, Inje University, Busan and 5College of Health Science, Department of Nursing, Kangwon National University, Samcheok, South Korea


This study determines the effect of simulation with team-based learning (TBL) on newborn nursing care. This randomized controlled trial included 74 nursing students from one university located in Seoul, South Korea. Participants were categorized into two groups according to educational modality: one group involved both simulation and TBL, and the other involved simulation alone. Learning attitudes, academic achievement, and simulation performance were examined to assess effectiveness. The mean difference in learning attitudes between the two groups was non-significant. Low academic achievement differed significantly between the two groups (t = 3.445, P = 0.002). There was no significant difference in mean scores for simulation performance between the two groups. In this study, simulation with TBL was effective in improving learning outcomes. In current nursing education, various learning methods are employed within complex nursing situations and require flexibility and problem-solving approaches.

Key words

learning, new born care, neonatal, nursing education, patient simulation, team-based learning.

INTRODUCTION Simulation is an effective instructional method that allows students to practice their clinical skills in a safe environment without fear of making mistakes that may harm patients, and improves their critical and integrative thinking and decisionmaking skills (Kinney & Henderson, 2008; Moule, 2011). The effectiveness of simulation on knowledge, confidence, and skills has been noted in numerous studies in various educational nursing settings (Cant & Cooper, 2010; Garrett et al., 2010; Hope et al., 2011; Howard et al., 2011; Khalaila, 2014; Kim et al., 2014). While the benefits of simulation may have been recognized, reliance on simulation in education is subject to potential limitations and challenging questions concerning a reduction in students’ exposure to real patients and practice, and issues of “fit” with respect to staff and student preparation and the value of expensive technological investment (Moule, 2011). Buckley and Gordon (2011) reported that a combination of simulation and classroom teaching improved nurses’ perception of their responses to emergency situations Correspondence address: Myung-Nam Lee, Department of Nursing, Kangwon National University, 346, Hwangjo-gil, Dogye-eup, Samcheck-si, Gangwon-do 245710, South Korea. Email: [email protected] Conflict of interest: None of the authors have any actual or potential conflicts of interest including any financial, personal, or other relationships with other persons or organizations that could inappropriately influence or be perceived to influence this work. Received 5 April 2015; revision received 28 June 2015; accepted 9 August 2015

© 2015 Wiley Publishing Asia Pty Ltd.

and ability to transfer their skills to a real clinical environment. These results indicate that simulation should be merged with other educational methods. Facilitative methods, such as team-based learning (TBL), are can be implemented to help students to increase their engagement in learning (Tan et al., 2011). This instructional strategy has also been used in medical education and other allied health sciences, with positive learning outcomes (LOs) (Chung et al., 2009; Khogali, 2013; Flanagan et al., 2007; Lim & Seet, 2008). In addition, some studies have examined the effect of TBL on nursing education (Roh et al., 2014); however, few have explored TBL in pediatric nursing. Team-based learning uses the active processing principle to induce positive learning attitudes (LAs), and learners are required to solve clinically relevant problems using previously acquired knowledge (Mayer, 2010). TBL may stimulate higher-level thinking skills and improve long-term ability to recall and use concepts and strategies in problem solving, protecting the learner from knowledge attrition (Michaelsen, 2004; Mayer, 2010). There is growing evidence that TBL in nursing education is effective in improving students’ academic performance, knowledge, attitudes (Currey et al., 2015), satisfaction with faculties (Koles et al., 2005; 2010; Vasan et al., 2009; Tan et al., 2011), general satisfaction (Roh et al., 2014), and achievement of learning goals (Sick, 2011). TBL is rooted in teamwork, the importance of which has increased in healthcare environments (Feingold et al., 2008). In particular, in nursing practice, teamwork is an essential doi: 10.1111/nhs.12245

Simulation with team-based learning


factor in caring for patients with various health problems, because of the value of nurses’ cooperation with fellow nurses and other healthcare personnel. To accomplish the final goal of improving students’ clinical competency via simulation, nursing educators should consider team approaches in both lectures and clinical practice, to promote effective functioning within teams. However, few studies have been conducted to examine simulation with TBL in nursing education. The neonatal period is the first stage of growth and is crucial to human development. Even when born at full term and apparently healthy, within one month of birth newborns may develop various latent health problems. As well as providing care for newborns around the time of their birth, neonatal nurses support their growth and development and make a substantial contribution to the prevention of illness and death (Healy & Fallon, 2014). While teaching students to care for healthy newborns is a priority in pediatric nursing curricula, this has been identified as problematic for learners, as invisible nursing problems may be present in apparently healthy newborns, and nursing students experience difficulty in recognizing and caring such conditions (Dennis & Jesek-Hale, 2003). Both of these aspects of newborn care may be taught via clinical scenarios in which students are required to make a number of evaluative decisions and form judgments to select the most appropriate form of nursing care (Haidet & Fecile, 2006). In clinical practice involving healthy newborns, the determination of required care is a necessary step in the identification of nursing problems, which validate the priority and type of care that is provided (Dennis & Jesek-Hale, 2003). In this study, to prepare nursing students with these abilities, we developed a module involving the integration of simulation and TBL in

Experimental 1

newborn nursing care and verified the effect of this educational method.

Purpose The purpose of the study was to determine the effectiveness of simulation with TBL, relative to that of simulation alone, in newborn nursing care.

METHODS Design The study was a randomized controlled trial, which was conducted to evaluate the effects of simulation with TBL in newborn nursing care by comparing learning attitudes and outcomes between nursing students taught via simulation with TBL and those taught via simulation alone. The module for newborn nursing care was based on a framework for simulation with TBL (Michaelsen, 2004; Jeffries, 2007). Two educational modalities were used. Experimental group 1 (E1) received a combination of learning methods, including simulation and TBL, while experimental group 2 (E2) was taught via simulation only (Fig. 1).

Participants The sample size was calculated using G*Power 3.1, with a minimum of 78 participants (39 in each group) in the total sample, a medium effect size of 0.5, 70% power, a significance level of 0.5, and two independent groups in the t-test (Faul et al., 2007). In total, 85 nursing students were selected from

Simulation with team-based learning

Experimental 2

Simulation only


Team-based learning





1 LA st 1 LO1


TBL: Preparation

TBL: Application TBL: Assessment

Out-of-class individual learning

IRAT/GRAT Team discussion



Group discussion

Cooperative problem solving





Cooperative problem solving



2 LA nd 2 LO1

Figure 1. Research design. IRAT, Individual Readiness Assessment Test; GRAT, Group Readiness Assessment Test; LA, learning attitude; LO1, learning outcome 1 (academic achievement); LO2, learning outcome 2 (simulation performance).

© 2015 Wiley Publishing Asia Pty Ltd.

K.-A. Kang et al.


one university located in Seoul, South Korea. The inclusion criteria applied to ensure homogeneity were: (i) junior-grade status; (ii) completion of a child health nursing course with the equivalent of four credits; and (iii) no prior participation in either TBL or simulation newborn nursing care classes. Of the 85 participants (E1 45, E2 40), 11 were excluded because of missing data. Ultimately, the data of 74 participants (87.1%) were analyzed.

Educational interventions The simulation with TBL module was developed via review and analysis of the learning content for care of healthy newborns in a pediatric nursing textbook. We reviewed the literature, and the standard was based on the content established by the Korea Academy of Child Health Nursing (2012). The core concepts of healthy newborn care were: to foster optimal physical and psychological growth and development, which requires nursing care to facilitate normal physiological function; and to promote and maintain health in the newborn and their family. The needs of healthy newborn babies were identified via this process. The key concepts in neonatal nursing courses were selected, and learning objectives were established according to learning goals and essential content for both TBL and simulation (Fig. 2). The scenario was based on real cases in which newborn babies were admitted to the nursery from the delivery room, and developed according to the learning objectives. Learning content for both TBL and simulation consisted of respiratory function and body temperature maintenance, body measurements, physical examination subsequent to birth, infection control, skin integrity, and neurological reflexes. The Individual Readiness Assessment Test (IRAT), Group Readiness Assessment Test (GRAT), and discussion topics in TBL, including lecture content, were developed based on the learning goals, and an algorithm was formulated for the simulation (Fig. 2).

Procedure Data collection was conducted over a three-month period from September to November 2014. All participants enrolled in the study voluntarily and anonymously. Participants were randomly allocated to group E1 or E2. Group assignments were documented in sealed envelopes, randomly selected, and issued to participants. There was no significant difference in baseline LO 1(t = 1.841, P = 0.071). A pretest was performed to measure students’ LAs and LO1 (academic achievement) prior to implementation of the educational interventions. A 15-week developmental pediatric nursing course was divided into seven lessons. The class involving the care of healthy newborns proceeded for two weeks, as lesson 1 of seven lessons, and was used as the theme for TBL and simulation. Ten teams containing three to four students were formed in group E1. The ideal number of students per TBL group was estimated at five to six by Koles et al. (2005). The reason we assigned the same number of students to each TBL group was to avoid alteration of team membership in the © 2015 Wiley Publishing Asia Pty Ltd.

simulation session. The instructor was a full-time faculty member with 15 years of experience in nursing education. The TBL for group E1 consisted of three phases: preparation, application, and assessment (Haidet et al., 2002; Fig. 1).

I: Team-based learning (TBL) – preparation In the preparation phase, students were required to complete out-of-class reading concerning the learning objectives prior to attending class. These reading assignments consisted of textbook chapters on the care of healthy newborns and related articles. The reading was completed by both groups.

II: Simulation – orientation phase Simulation was implemented between the preparation and application phases of the TBL for both groups and included the learning goals for simulation using a scenario. All participants were enrolled at the same university; therefore, we modified the sequence of the research procedure to avoid contamination between groups. Teams of three to four students participated in the simulation sessions. In each team, one student played the role of a primary nurse, assumed ultimate responsibility for newborn care and interventions, and delegated tasks to team members. Prior to the simulation, students attended an orientation session to learn how to operate the simulator and were provided with scenario information comprising delivery history and conditions related to health status.

III: Simulation – simulation phase The simulation took place in a dedicated room via a highfidelity human patient simulator. Two instructors observed the simulation from a control room. Each simulation session lasted approximately 20 min, and each team attended a debriefing session lasting 30 min immediately after the simulation. In addition, two instructors evaluated LO2 (simulation performance) during simulation. Students’ performance was evaluated twice: once during and once after the simulation. In the second phase of the evaluation, the evaluators rechecked the students’ performance via the video recordings in order to enhance evaluation accuracy and decrease possible evaluation bias.

IV: TBL – application phase The application phase involved in-class activities consisting of the completion of the IRAT and GRAT. The purpose of these tests was to check students’ understanding of their reading assignments. The IRAT, consisting of 15 questions with multiple-choice responses, took 15 min and was completed at the beginning of the class, to ensure that the students adequately reviewed the reading. The 15 items of the IRAT consisted of learning goals and multiple-choice questions and provided various clinical situations involving LO1 items. Scores ranged from 0–20, with a higher score indicating a higher level of knowledge.

Simulation with team-based learning


Figure 2. The flow of educational interventions. GRAT, Group Readiness Assessment Test; IRAT, Individual Readiness Assessment Test; LOA position: left occipitoanterior position (fetal position).

© 2015 Wiley Publishing Asia Pty Ltd.

K.-A. Kang et al.


The TBL exercise consisted of a clinical case scenario performed within small groups in the classroom. Immediately subsequent to the completion of the IRAT, the GRAT, which consisted of the same test questions used in the IRAT, was completed by the teams, with a time limit of 30 min. The teams were permitted to converse and debate freely to establish a team consensus for all 15 questions; however, they were not permitted to consult with other teams or use reference materials, including textbooks or the Internet. Upon completion of the GRAT, the instructor, as the content leader, provided the correct answers and feedback regarding the course concepts.

V: TBL – assessment phase During the assessment phase, the instructor issued team assignments to cultivate problem solving ability in real conditions observed in apparently healthy newborns and facilitated team discussion (Fig. 2). A post-test that measured students’ LAs and LO1 (academic achievement) was performed subsequent to the TBL assessment phase. The TBL class was held subsequent to the post-test for group E2.

Instruments Learning attitudes were measured using a tool developed by the Korean Educational Development Institute (1991), which consisted of 16 items, each scored on a five-point Likert-type scale (1 = strongly disagree, 2 = disagree, 3 = neither agree nor disagree, 4 = agree, 5 = strongly agree). A higher score indicated a more positive attitude regarding theory and practice in newborn nursing care. The Cronbach’s alpha for the scale was 0.796. Learning outcome 1 was a written evaluation used to identify TBL levels of academic achievement and was tested using 20 multiple-choice questions, developed by the researchers, concerning postnatal care for healthy neonates. LO1 consisted of 20 items formulated according to learning goals regarding the following procedures: respiratory function and body temperature maintenance, body measurements, physical examination following birth, infection control, and neurological reflex testing. Scores ranged from 0–20, and a higher score indicated a higher level of knowledge. Learning outcome 2 was a checklist for simulation performance evaluation, which was used to identify students’ ability to care for healthy newborns and measured using a tool developed by researchers, based on the Lasater Clinical Judgment Rubric (LCJR; Lasater, 2007). The tool consisted of 32 items categorized into four categories: noticing (8 items), interpreting (5 items), responding (14 items), and reflecting (5 items). Each item was scored on a three-point Likert-type scale (1 = beginning, 2 = developing, 3 = accomplished). The higher the checklist score, the better the student’s ability to care for healthy newborns. The Cronbach’s alpha from the scale was 0.865. Content validity for these tools was tested twice by seven experts with backgrounds in research and nursery © 2015 Wiley Publishing Asia Pty Ltd.

Table 1. Homogeneity test for dependent variables between groups (N = 74)


E1 (n = 37) Mean (SD)

E2 (n = 37) Mean (SD)



Learning attitude Learning outcome 1

3.74 ± 0.46 10.51 ± 3.09

3.54 ± 0.30 8.98 ± 2.27

0.831 1.841

0.410 0.071

E1, experimental group 1; E2, experimental group 2; SD, standard deviation.

management. The experts comprised four researchers and three head nurses who worked in nurseries at general hospitals.

Ethical approval Ethical approval for this study was granted by the Hallym University Institutional Review Board (HIRB; No: 2014-76). The HIRB confirmed that no elements of the study violated human rights, and all content and processes conformed to established research ethics requirements, including issues surrounding voluntary participation, anonymity, and confidentiality. The researchers explained the study protocol to all participants, who provided informed consent.

Data analysis Data were analyzed using SPSS version 21.0 (IBM Corp., Armonk, NY, USA) to obtain descriptive statistics and perform paired and independent t-tests. LAs and LOs were determined according to two educational modalities and test scores for the IRAT and GRAT were compared for group E1. The significance level was set at a P < 0.05.

RESULTS Descriptive results and homogeneity test Of the 74 participants, 93% were women, and their mean age was 21 (± 1.19). The mean scores for LA and LO1 for both groups are presented in Table 1. There were no significant differences in the baseline LA (t = 0.831, P = 0.410) or LO1 (t = 1.841, P = 0.071) between groups.

Mean differences in dependent variables between groups Learning outcome 1 scores were classified into two groups based on mean pretest scores (9.74 ± 2.80); scores of more than 10 indicated higher academic achievement, while scores of less than 10 indicated lower academic achievement. The mean differences between pretest and post-test scores for LA and LO1 are shown in Table 2. LA did not differ significantly in lower (t = 1.002, P = 0.324) or higher achievers (t = −0.392, P = 0.698) between the groups.

Simulation with team-based learning


Table 2. Mean difference in dependent variables according to LO1 between groups (N = 74)

n Lower achiever Higher achiever

Learning attitude E1 (n = 37) E2 (n = 37) Mean difference Mean difference (SD) n (SD) 0.05 ± 0.24 0.06 ± 0.24

15 22

−0.04 ± 0.29 0.25 ± 0.29

20 17




1.002 −0.392

0.324 0.698

15 22

Learning outcome 1 E1 (n = 37) E2 (n = 37) Mean difference Mean difference (SD) n (SD) 5.20 ± 2.11 1.55 ± 2.61

20 17

2.55 ± 2.35 1.18 ± 1.74



3.445 0.502

0.002 0.619

Mean difference: post-test-pretest in mean score. Lower achiever means score below 10 in learning outcome 1 (LO1, academic achievement) pre-test, higher achiever means score above 10 in LO1 pre-test. E1, experimental group 1; E2, experimental group 2; SD, standard deviation.

Table 3. Differences in LO2 between groups (N = 20 groups, 74 students)


E1 (n = 10 groups) Mean (SD)

E2 (n = 10 groups) Mean (SD)


14.40 ± 0.24

15.50 ± 2.07

9.00 ± 0.16

10.20 ± 2.20

t = 1.1406, P = 0.177 Responding

34.50 ± 3.81

Focused observation (4) Recognizing deviations from expected patterns (2) Information seeking (2)

t = −1.095, P = 0.288


E1 (n = 10 groups) Mean (SD)

Subcategory (number of items)

Prioritizing data (2) Making sense of the data (3)

36.40 ± 2.41

Calm, confident manner (4) Clear communication (3)

t = −1.33, P = 0.199

Well-planned intervention/flexibility (5) Being skilled (2)


9.00 ± .94

10.00 ± 2.05

t = −1.399, P = 0.186 Total

– –

Evaluation/self-analysis (3) Commitment to improvement (2)

– –

– –

E2 (n = 10 groups) Mean (SD)

9.80 ± 1.55 10.30 ± 1.42 t = −0.753, P = 0.461 2.50 ± 0.85 3.10 ± 0.99 t = −1.450, P = 0.164 2.10 ± 0.57 2.10 ± 0.32 t = 0.000, P = 1.000 4.10 ± 1.20 4.80 ± 1.14 t = −1.342, P = 0.196 4.90 ± 0.74 5.40 ± 1.84 t = −0.798, P = 0.440 10.20 ± 1.23 10.90 ± 1.20 t = −1.290, P = 0.213 6.50 ± 1.08 6.50 ± 1.08 t = 0.000, P = 1.000 13.70 ± 1.42 12.60 ± 1.65 t = −1.601, P = 0.127 5.20 ± 0.63 5.30 ± 0.48 t = −0.397, P = 0.696 5.90 ± .74 6.60 ± 1.17 t = −1.597, P = 0.128 3.10 ± 0.57 3.40 ± 0.97 t = −0.847, P = 0.411 66.90 ± 6.95 72.10 ± 6.37 t = −1.744, P = 0.098

E1, experimental group 1; E2, experimental group 2; LO2, learning outcome 2 (simulation performance).

Learning outcome 1 differed significantly between the lower achievers of the groups (t = 3.445, P = 0.002), but did not differ significantly in the higher achievers (t = 0.502, P = 0.619). There were no significant differences in mean scores for any subcategories of LO2 between groups (Table 3).

Table 4.

Comparison of test scores (n = 37)

IRAT score Mean (SD)

GRAT score Mean (SD)



8.14 ± 2.10

12.30 ± 1.63


< 0.001

GRAT, Group Readiness Assessment Test; IRAT, Individual Readiness Assessment Test; SD, standard deviation.

Comparison between Individual Readiness Assessment and Group Readiness Assessment tests and scores in group E1 The mean IRAT and GRAT scores differed significantly in group E1 (t = 5.543, P < 0.001; Table 4).

DISCUSSION The recent trend toward the rapid development of educational environments has influenced undergraduate nursing programs.Active learning methods have become increasingly © 2015 Wiley Publishing Asia Pty Ltd.

K.-A. Kang et al.


popular in modern curricula (Clark et al., 2008). Therefore, nursing educators are continuously challenged to find evidence-based, effective learning methods that actively engage learners and help students to develop critical thinking and professional judgment skills in practical situations.Therefore, simulation with TBL was implemented in pediatric nursing practice to determine its effectiveness relative to that of simulation alone. There was no significant difference in LAs between the groups in this study. In contrast, Currey et al. (2015) reported that TBL led to significant changes in nursing students’ LAs within teams. In addition, the quality of learning, clinical reasoning ability, professional development, and satisfaction with the team experience were increased. In another study, TBL significantly influenced students’ learning interests (Cheng et al., 2014). The reason for this may be that TBL appears to enhance students’ attitudes regarding learning and working in teams and raises their knowledge-based performance (Michaelsen & Knight, 2004). Team-based learning has been found to exert a particularly strong effect in academically weaker students and allows learners to reinforce and retain knowledge (Koles et al., 2005; Tan et al., 2011; Cheng et al., 2014). We can assume that, during a TBL session, poorly prepared students completing the GRAT benefit from their prepared peers by sharing knowledge and ideas. Our results indicate that simulation combined with TBL was effective in improving LO1 in academically weaker students. During interactions with peers, students learned how to approach patient case scenarios as part of a team and reach a consensus regarding how to proceed. However, this result is inconsistent with that of another study, in which perception of TBL was significantly more positive in high-achieving relative to low-achieving students (Vasan et al., 2009). Therefore, further research is required to confirm our findings. In this study, we did not measure student satisfaction; however, Roh et al. (2014) investigated satisfaction with TBL and influential factors in nursing students. They reported that nursing students were generally satisfied with TBL, and that influential factors, including learning process, preassignment, course content, peer evaluation, and team activity, were significantly associated with learner satisfaction. In light of this result, we can assume that students’ attitudes regarding the TBL educational method are positive. In addition, influential factors should be considered when designing TBL education. TBL that includes the management of a variety of cases may be applied in nursing education. In this study, we implemented simulation within the TBL phase, and the difference in LO2 scores did not differ significantly between the groups. If the simulation had been applied subsequent to the completion of the TBL phase, the result might have been different. In addition, we did not classify the simulation groups according to levels of academic achievement. Therefore, further studies should design the sequence of educational modalities according to levels of academic achievement. Team-based learning studies have reported significantly higher mean scores for the GRAT relative to those for the IRAT (Wiener et al., 2009; Tan et al., 2011). The educational © 2015 Wiley Publishing Asia Pty Ltd.

design of this study allowed students to participate more actively in sequential engagement and planned a learning environment in which they were actively involved in class assignments and communicated with each other to solve nursing problems. Through this process, knowledge was retained and used practically. In addition, the results are consistent with those of other studies in nursing and medical education (Chung et al., 2009; Wiener et al., 2009; Tan et al., 2011). We compared two educational methods that focused on the care of healthy newborns. Mixed educational methods could be applied more broadly to other child health nursing problems to evaluate their effectiveness. In future, simulation could be merged with other new educational strategies to obtain evidence of valuable, optimal LOs in nursing education methodology. In addition, further experimental studies are required to confirm the positive effects and LOs observed in nursing students. The limitation of our study was that we only implemented two educational modalities, with one lesson delivered to each group. Other educational strategies should be compared and their long-term effects assessed.

CONCLUSION Simulation is increasingly popular in nursing education. Relative to simulation alone, simulation with TBL was effective in improving academic achievement, particularly in lowachieving students. The strength of TBL was that it improved understanding and knowledge via a sequence of activities that consisted of individual and group work, and immediate feedback, which may have increased the effect of simulation on academically low-achieving students. Additional practical teaching methods that include active learning are recommended. A variety of learning strategies should be integrated into relevant nursing curricula, as new teaching models could assist nursing educators in the implementation of a holistic approach to teaching.

ACKNOWLEDGMENT We would like to thank all of the nursing students who participated in this study.

CONTRIBUTIONS Study Design: KKA, KSJ, OJ, KS, LMN. Data Collection and Analysis: KS, LMN. Manuscript writing: KKA, KSJ, OJ, LMN.

REFERENCES Buckley T, Gordon C. The effectiveness of high fidelity simulation on medical–surgical registered nurses’ ability to recognise and respond to clinical emergencies. Nurse Educ. Today 2011; 31: 716– 721. Cant RP, Cooper SJ. Simulation-based learning in nurse education: Systematic review. J. Adv. Nurs. 2010; 66: 3–15.

Simulation with team-based learning

Cheng CY, Liou SR, Hsu TH, Pan MY, Liu HC, Chang CH. Preparing nursing students to be competent for future professional practice: Applying the team-based learning-teaching strategy. J. Prof. Nurs. 2014; 30: 347–356. Chung EK, Rhee HA, Baik YH, A OS. The effect of team-based learning in medical ethics education. Medical Teacher 2009; 31: 1013–1017. Clark MC, Nguyen HT, Bray C, Levine RE. Team-based learning in an undergraduate nursing course. J. Nurs. Educ. 2008; 47: 111–117. Currey J, Oldland E, Considine J, Glanville D, Story I. Evaluation of postgraduate critical care nursing students’ attitudes to, and engagement with, team-based learning: A descriptive study. Intensive Crit. Care Nurs. 2015; 31: 19–28. Dennis CM, Jesek-Hale S. Calculating therapeutic self-care demand for a nursing population of normal newborns. Self Care Depend. Care Nurs. 2003; 11: 3–10. Faul F, Erdfelder E, Lang AG, Buchner A. G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav. Res. Methods 2007; 39: 175–191. Feingold CE, Cobb MD, Givens RH, Amold J, Joslin S, Keller JL. Student perceptions of team learning in nursing education. J. Nurs. Educ. 2008; 47: 214–222. Flanagan E, Walsh C, Tubridy N. “Neurophobia” attitudes of medical students and doctors in Ireland to neurological teaching. Eur. J. Neurol. 2007; 14: 1109–1112. Garrett B, Macphee M, Jackson C. High-fidelity patient simulation: Considerations for effective learning. Nurs. Educ. Perspect. 2010; 31: 309–313. Haidet P, Fecile ML. Team-based learning: A promising strategy to foster active learning in cancer education. J. Cancer Educ. 2006; 21: 125–128. Haidet P, O’Malley KJ, Richards B. An initial experience with “team learning” in medical education. Acad. Med. 2002; 77: 40–44. Healy P, Fallon A. Developments in neonatal care and nursing responses. Br. J. Nurs. 2014; 23: 21–24. Hope A, Graside J, Prescott S. Rethinking theory and practice: Preregistration student nurse’s experiences of simulation teaching and learning in the acquisition of clinical skills in preparation for practice. Nurse Educ. Today 2011; 31: 711–715. Howard V, Englert N, Kameg K, Perozzi K. Integration of simulation across the undergraduate curriculum: Student and faculty perspectives. Clin. Simul. Nurs. 2011; 7: e1–e10. Jeffries PR. Simulation in Nursing Education: From Conceptualization to Evaluation. New York: National League of Nursing, 2007. Khalaila R. Simulation in nursing education: An evaluation of students’ outcomes at their first clinical practice combined with simulations. Nurse Educ. Today 2014; 34: 252–258.


Khogali SE. Team-based learning: a practical guide: guide Supplement 65.1 – viewpoint 1. Med Teach. 2013; 35: 163–165. Kim SJ, Oh J, Kang KA, Kim SH. Development and evaluation of simulation-based fever management module for children with febrile convulsion. Nurse Educ. Today 2014; 34: 1005–1011. Kinney S, Henderson D. Comparison of low fidelity simulation learning strategy with traditional lecture. Clin. Simul. Nurs. 2008; 4: 15–18. Koles P, Nelson S, Stolfi A, Parmelle D, Destephen D. Active learning in a year 2 pathology curriculum. Med. Educ. 2005; 39: 1045– 1055. Koles PG, Stolfi A, Borges NJ, Nelson S, Parmelee DX. The impact of team-based learning on medical students’ academic performance. Acad. Med. 2010; 85: 1739–1745. Korea Academy of Child Health Nursing. Learning objectives in pediatric nursing. 2012. [Cited 26 Dec 2012.] Available from URL: Korean Educational Development Institute. A study of thinking ability development program. Seoul: Korean Educational Development Institute, 1991. Lasater K. Clinical judgment development: Using simulation to create an assessment rubric. J. Nurs. Educ. 2007; 46: 496–503. Lim EC, Seet RC. Demystifying neurology: Preventing “neurophobia” among medical students. Nat. Clin. Pract. Neurol. 2008; 4: 462–463. Mayer RE. Applying the science of learning to medical education. Med. Educ. 2010; 44: 543–549. Michaelsen LK. Getting Started with Team-based Learning. Sterling, VA: Stylus Publishing, 2004. Michaelsen LK, Knight AB. Creating Effective Assignments. Sterling, VA: Stylus Publishing, 2004. Moule P. Simulation in nurse education: Past, present and future. Nurse Educ. Today 2011; 31: 645–646. Roh YS, Lee SJ, Mennenga H. Factors influencing learner satisfaction with team-based learning among nursing students. Nurs. Health Sci. 2014; 16: 490–497. Sick RJ. Team-based learning: Systematic research review. J. Nurs. Educ. 2011; 50: 665–669. Tan NCK, Kandiah N, Chan YH, Umapathi T, Lee SH, Tan K. A controlled study of team-based learning for undergraduate clinical neurology education. BMC Med. Educ. 2011; 11: 91. Vasan NS, DeFouw DO, Compton S. A survey of student perceptions of team-based learning in anatomy curriculum: Favorable views unrelated to grades. Anatom. Sci. Educ. 2009; 2: 150–155. Wiener H, Plass H, Marz R. Team-based learning in intensive course format for first-year medical students. Croat. Med. J. 2009; 50: 69–76.

© 2015 Wiley Publishing Asia Pty Ltd.

Effectiveness of simulation with team-based learning in newborn nursing care.

This study determines the effect of simulation with team-based learning (TBL) on newborn nursing care. This randomized controlled trial included 74 nu...
568B Sizes 2 Downloads 10 Views