Canadian Journal of Nursing Informatics

Pilot Evaluation of a Virtual Clinical Excursion (VCE) Among Senior Nursing Students: Part 1 – Quantitative Findings

Print Friendly, PDF & Email

Loretta Secco, RN PhD

Kathy Wilson, RN, PhD

Donna Bulman, RN, PhD

Faculty of Nursing, University of New Brunswick

Funding Source

The research project was funded by a grant from Sigma Theta Tau International  – National League of Nursing

Abstract

This pilot study used a one group, post-test survey design to explore 4th year nursing students’ satisfaction with a simulated virtual clinical excursion (VCE) learning experience.  The roles of student generational age, learning style and computer competence are explored.  Eleven nursing students, with an average of 24.7 years, completed the online Satisfaction with VCE Survey (SVCES). The SVCES assessed students’ evaluation of user-friendliness, realism, knowledge, and quality of the VCE resource.  Millennial and Gen X’ers did not report different SVCES scores.  However, students’ ratings on eight SVCES items were positively and strongly correlated with computer competence.  Practical recommendations are offered for educators to consider as they integrate VCE resources within the nursing curriculum.

Introduction

Nurse leaders have strongly encouraged educators to integrate simulation learning approaches to prepare graduates to practice safely within the current highly complex, evolving health care system (Galloway, 2009).  In response to this expectation, many nursing programs have integrated simulation manikins within undergraduate nursing curricula despite a relative lack of research on whether student learning, patient safety or effectiveness is improved (Galloway, 2009).  Consequently, a wide variety of high tech nursing simulation teaching resources are being implemented such as simulated patient manikins (Ackermann, 2009), virtual clinical learning environments (Curran, Elfrink, & Mays, 2009), computerized care plan developers and documentation systems (Fetter, 2009). Simulation resources are also used for various nursing settings such as community health (Yeager & Gotwals, 2010), postpartum (Bambini, Washburn, & Perkins, 2009) and palliative care nursing (Leighton & Dubas, 2009).

Selection of appropriate simulation resources requires that faculty consider numerous factors such as cost, learning outcomes, availability of the technology, faculty ability and support (Seropian, Brown, Gavilanes, & Driggers, 2004).  It is also important to consider the match of the simulation learning resource with student satisfaction and preferences for learning resources and modes.  One important consideration is student generational age as most nursing students today fall within the ‘Generation X’ (born between 1963 and 1980) or Millennial (born 1980 to 2000) categories (Oblinger, 2003; Sherman, 2006).  Millennial students are especially comfortable with technology (Pardue & Morgan, 2008) and disappointed with low technology  abilities of faculty (Oblinger, 2003).

Quantitative research evidence has consistently demonstrated that simulation learning with manikins results in positive outcomes such as improved student confidence (Brannan, White, & Bezanson, 2008), self-efficacy (Pike & O’Donnell, 2010), clinical judgement and communication style (Bambini et al., 2009).  Unfortunately, despite the lower cost and temporal flexibility of computer-assisted instruction (CAI) software resources (Fernandez Aleman, Carrillo de Gea, & Rodraguez Mondajar, 2011), few researchers have evaluated nursing students’ satisfaction with this type of learning resource (Ford, Mazzone, & Taylor, 2005).

Research with medical students who used a CAI reported that, despite an overall positive evaluation, students preferred more traditional lecture and text-based learning (Steele, Johnson Palensky, Lynch, Lacy, & Duffy, 2002).  In another study, physical therapy students reported a CAI learning resource was just as effective as live demonstration and more effective than textbook instruction, especially for skills acquisition and retention (Ford, et al., 2005).  One group of researchers reported that, compared with the face-to-face control group, nursing students who used a CAI learning module achieved similar handwashing knowledge and skill acquisition (Bloomfield, Roberts, & While, 2010).  Other evidence from a small pilot study by Bailey and Bursey supported use of VCE as almost all participating first year nursing students positively evaluated a ‘fundamentals’ VCE.  However, although the students recommended the VCE, there was full agreement that the VCE resource could not replace actual clinical practice (Bailey & Bursey, 2009).  More knowledge is needed on student perspectives on the value of VCEs in order for faculty to make decisions about integration within the nursing curriculum.

This pilot study explored student nurses level of satisfaction with a VCE learning experience and relationships with student learning style, generational age, and computer competence.  Satisfaction was measured as the student’s ratings on user-friendliness, appropriateness of match with learner’s abilities, and improved clinical judgment, reflection, and critical thinking around patient care decisions.  Kolb’s Learning Styles Inventory (KLSI) measured four learning styles (Kolb, 1976). The diverging learner is imaginative, emotional and people-orientated while an assimilating learner is less interested in people, more interested in abstract concepts, and prefers basic over applied sciences.  The converging learner finds uses for theories, likes to hypothesize and deal with things rather than people while the accommodating learner is highly action-orientated and relies more on information provided rather than their own analysis (Wang, Wang, Wang, & Huang, 2006).

Generational age was assessed as it has been associated with predominant learning styles, attitudes about use of technology, and expectations or preferences about learning experiences (Oblinger, 2003).  ‘Generation X’ students are born between 1963 and 1980 and Millennial students are born between 1980 and 2000 (Oblinger, 2003; Sherman, 2006) .  Mellennial students are known for their affinity toward use of technology (Pardue & Morgan, 2008; Sherman, 2006) and disappointment when university faculty don’t apply technology within teaching strategies (Oblinger, 2003).  Computer competence was defined as ‘attitudes toward computers’ or their perceived ability and comfort using computers to accomplish goals and the ‘extent of preference using computers as a learning tool’.

Method

This pilot used a one group, post-test only survey design to collect quantitative data on students’ level of satisfaction with the VCE learning resource.  Ethical approval for the study was received from the University Ethics Board.  Study measures included the Satisfaction with VCE Survey (SVCES) developed to asses user-friendliness (‘easy to install’), realism (‘hospital was realistic’), knowledge (‘increased my level of knowledge for clinical practice’) on a Likert scale from 1= ‘strongly agree’ to 5 = ‘strongly disagree’ (or not/applicable).  Students also completed Kolb’s Learning Style Inventory (C) (KLSI)  (Kolb, 1999), a validated (Kayes, 2005; Wang, et al., 2006), self-scored, measure with 12 item that are completed with four potential endings to determine learning style along four dimensions.  The four dimensions, concrete experience (CE) or direct experience, feelings and emotions; reflective observations (RO) or looking back, remembering and gathering new information about an experience; abstract conceptualization (AC) or creating meaning from an experience as a guide for subsequent action, and active experimentation (AE) or testing a plan by carrying it out (Kayes, 2005).  According to Kolb, preference for two modes of learning, either CE versus AC or RO versus AE, defines individual ‘learning style’ and when plotted the particular learning style is identified, i.e., diverging, assimilating, converging, or accommodating (Wang, et al., 2006).  Date of birth was collected to determine participant generational age of ‘Generation X’ (born between 1963 and 1980) or Millennial (born 1980 to 2000) (Oblinger, 2003; Sherman, 2006) .

Procedures

The 4th year nursing students (N = 80) were orientated to the VCE during two, one-hour sessions and completed the KLSI.  After the session a subset of 20 students volunteered to use the Evolve Elsevier medical surgical VCE (Mathers, 2007) workbook guide and software DVD.  The VCE contains a virtual clinical hospital complete with a nursing unit, medication room, and five patients with associated diagnoses, care plans, medical orders, and electronic charts.  After six, eight and ten weeks students were emailed the study explanation and invitation to complete the SVCES (askitonline.com).

Results

Seven nursing students with an average age of 24.7 years completed the online SVCES.  The learning styles breakdown for the students included three (42.9%) diverging, two (28.6%) assimilating, and one each of converging  and accommodating (14.2%).

Student nurses reported high mean computer competence, 4.33, SD = 1.07, and lower mean preference for computers as learning tools, 3.5, SD = 1.24.  The mean SVCES, 3.81, reflected quite high student satisfaction with the VCE resource.  The SVCES item means ranged from 3.0 to 4.75 (See Figure 1).  The lowest mean was the rating on whether the VCE helped prevent medication errors, 3.0.  Three SVCE means ranged between 4.5 and 5, ten between 4.0 and 4.4 and three between 3.5 and 3.9.  Only two SVCE item means were between 3.0 and 3.4.  The highest satisfaction mean, 4.75, was that the VCE ‘improved my ablity to access information’.  The next highest means, 4.5, were for ‘provided positive patient care experiences’ and ‘easy to install’.  Nine SVCES item means, 4.25, were related to the quality of the learning experience or user friendliness of the resource.   Some examples of items with a mean of 4.25 related to the quality of the learning experience included ratings on ‘helped prepare me for preceptorship’, ‘helped me learn about clinical pracice’, and ‘patient care was challenging’. The SVCE items with a mean of 4.25 related to user-friendliness included ‘easy to install’, ‘positive learning experience’, and ‘the workbook had enough information to guide me’.    Two tem means at  3.5 included rating of whether the VCE increased ‘knowledge about safe patient care’ and ‘ability to organize patient care’.  The two lowest item means were ratings on whether the VCE ‘decreased time preparing for patient care’, 3.25, and ‘helped prevent medication errors’, 3.0.

There was no significant mean SVCES total score difference for generational age, in fact the mean ranks were almost the same, Gen X and Millennial mean rank = 5.55, Z = .000, NS.  There were no significant relationships found between student age and either total SVCES mean, Kendall tau = .025, p = .93, or Computer Attitudes (very competent competence user), Kendall tau = .456, p = .126.  However, student Computer Competence was strongly and significantly associated with eight SVCE items (Kendall’s tau = .70), two that assessed user friendliness (‘easy to install’ and ‘the workbook guide contained enough information to guide me through the simulated experience’) and six qualities of the learning experience (‘improved ability to access information’, ‘helped me learn about clinical practice’, ‘positive learning experience’, ‘positive patient care experiences’, the medication room was a helpful learning tool’, and ‘patient care was challenging’).

Figure 1: SVCES Items with All Students Included

Figure 1: SVCES Items with All Students Included

Discussion

While student age and generational age were not related with student satisfaction with the VCE learning experience, the positive relationship between computer competence and satisfaction suggests students with computer technology skills may have self-selected into the study.  The two, in-class orientation sessions may have sufficiently enabled students with higher computer competence to independently use the VCE.  The less tech savvy students may have anticipated anxiety and/or frustration and opted out of the VCE study.  Another indication of the role of student computer competence was the association between satisfaction and two user friendliness items.  These findings suggest that the student with more computer competence could better navigate the software and virtual clinical hospital. The study findings also suggest that, when given a choice, not all millennial generation students choose computer learning approaches. The findings suggest that educators should consider student computer competence as they integrate higher tech learning experiences within the curriculum and to build in learning opportunities with greater technology support such as tutorials or guided session in class so students can acquire computer competence and comport with the learning approach.

Findings suggest that nurse educators should carefully and intentionally place VCE learning opportunities within the nursing curriculum.  The high item ratings on improved information access suggest the VCE may be a helpful teaching tool to assist student to acquire information from sources to plan patient care in clinical practice.  Patient care applications required students to access realistic information sources, including the patient chart, medical administration record, and electronic patient record, to make patient care decisions.  In contrast, lower ratings on items related to whether the VCE increased patient care knowledge and organization ability suggests more appropriate placement of the resource with lower level students may be required.

Potential uses for the VCE resource include practice before clinical practice for clinical units where students tend to have less clinical time so that students can prepare for clinical learning and enter the clinical rotation with adequate knowledge and skill level to feel competent for clinical learning.  Integration of the VCE within classroom lecture with lower level students would introduce them to the learning approach, improve their confidence using the computer-based VCE, and allow them to make nursing decisions along with the course instructor.  Gradual, independent VCE learning can be scheduled as required course component along with appropriate supportive class and/or tutorial sessions for students may need computer and/or technical sport.  Such intentional planning would lower anxiety/frustration related to computer use and enhance the learning experience and outcomes.  This study also strongly suggests that nurse educators should not assume all millennial nursing students have the same proclivity for technology.  Compared with other student groups, nursing students may have a preference for interpersonal rather than textbook or database sources of information (Jamieson, et al., 2009) which may reflect students’ acknowledgement of the complexity of nursing practice and decisions around patient care (Ebright, 2010).

 References

Ackermann, A. D. (2009). Investigation of learning outcomes for the acquisition and retention of CPR knowledge and skills learned with the use of high-fidelity simulation. Clinical Simulation in Nursing, 5(6), e213.

Bailey, J., & Bursey, M. (2009). Evaluation of a virtual clinical excursion: Impact of knowledge transfer in relation to critical thinking skills and psychomotor skills in first year nursing students. Canadian Journal of Nursing Informatics, 4(1), 3-39.

Bambini, D., Washburn, J., & Perkins, R. (2009). Outcomes of clinical simulation for novice nursing students: Communication, confidence, clinical judgment. Nursing Education Perspectives, 30(2), 79.

Bloomfield, J. G., Roberts, J., & While, A. (2010). The effect of computer-assisted learning versus conventional teaching methods on the acquisition and retention of handwashing theory and skills in pre-qualification nursing students: A randomised controlled trial. International Journal of Nursing Studies, 47(3), 287.

Brannan, J., White, A., & Bezanson, J. (2008). Simulator Effects on Cognitive Skills and Confidence Levels. Journal of Nursing Education, 47(11), 495.

Curran, C. R., Elfrink, V., & Mays, B. (2009). Building a virtual community for nursing education: the town of Mirror Lake. Journal of Nursing Education, 48(1), 30.

Ebright, P. R. (2010). The complex work of RNs: implications for healthy work environments. The Online Journal of Issues in Nursing, 15(1), 12.

Fernandez Aleman, J., Carrillo de Gea, J., & Rodraguez Mondajar, J. (2011). Effects of competitive computer-assisted learning versus conventional teaching methods on the acquisition and retention of knowledge in medical surgical nursing students. Nurse Education Today, 31(8), 866.

Fetter, M. S. (2009). Improving information technology competencies: Implications for psychiatric mental health nursing. Issues in Mental Health Nursing, 30, 3-13.

Ford, G. S., Mazzone, M. A., & Taylor, K. (2005). Effect of computer-assisted instruction versus traditional modes of instruction on student learning of musculoskeletal special tests. Journal of Physical Therapy Education, 19(2), 22.

Galloway, S. (2009). Simulation techniques to bridge the gap between novice and competent healthcare professionals. The Online Journal of Issues in Nursing, 14(2), 3.

Jamieson, B., Secco, M. L., Profit, S., Bailey, J., Brennick, D., Whitty-Rogers, J., et al. (2009). An evidence-based pilot project: The influence of handheld computers on computer competence, information sources, and stress levels of nursing students. Canadian Journal of Nursing Informatics, 4(4), 3-34.

Kayes, D. C. (2005). Internal validity and reliability of Kolb’s learning style inventory Version 3 (1999). Journal of Business and Psychology, 20(2), 249-257.

Kolb, D. A. (1976). Learning style inventory manual. Boston: McBer & Company.

Kolb, D. A. (1999). Learning style inventory., version 3. Boston: The Hay Group.

Leighton, K., & Dubas, J. (2009). Simulated death: An innovative approach to teaching end-of-life care. Clinical Simulation in Nursing, 5(6), e223.

Mathers, D. (2007). Virtual clinical excursion For Medial-Surgical Nursing, Pacific View Regional Hospital. St. Louis: Mosby/Elsevier.

Oblinger, D. (2003). Boomers and Gen-Xers Millenniels Understanding the new student. Educause, 37-47.

Pardue, K. T., & Morgan, P. (2008). Millennials considered: a new generation, new approaches, and implications for nursing education. Nursing Education Perspectives, 29(2), 74.

Pike, T., & O’Donnell, V. (2010). The impact of clinical simulation on learner self-efficacy in pre-registration nursing education. Nurse Education Today, 3(5), 405-410.

Seropian, M. A., Brown, K., Gavilanes, J. S., & Driggers, B. (2004). An approach to simulation program development. Journal of Nursing Education, 43(4), 170.

Sherman, R. O. (2006). Leading a multigenerational nursing workforce: issues, challenges and strategies. Online Journal of Issues in Nursing, 11(2), 3.

Steele, D. J., Johnson Palensky, J. E., Lynch, T. G., Lacy, N. L., & Duffy, S. W. (2002). Learning preferences, computer attitudes, and student evaluation of computerised instruction. Medical Education, 36(3), 225.

Wang, K. H., Wang, T. H., Wang, W. L., & Huang, S. C. (2006). Learning styles and formative assessment strategy: Enhancing student achievement in Web-based learning. Journal of Computer Assisted Learning, 22(3), 207-217.

Yeager, S. T., & Gotwals, B. (2010). Incorporating high-fidelity simulation technology into community health nursing education. Clinical Simulation in Nursing, 6(2), e53.

Return to Index

Return to Index

Be Sociable, Share!

Comments are closed.