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Qualitative & quantitative analyses of nursing panel teaching strategy for non-nursing courses

Abstract

Dale M Hilty

I ntroduction:

In four-year baccalaureate programs, nursing students begin actual nursing courses in the second year. Since most beginning nursing students are developing an authentic perception of a nurse, students are highly motivated and enthusiastic about the nursing panel (NP) experience.  The NP consists of seasoned nursing faculty members, and is used to socialize these beginning nursing students into the profession of nursing.

Method:

NP experience lasts 90 minutes.  First, the NP members introduce themselves and share their nursing background.  Second, students ask questions. In the last 5 years approximately 400 students have been participants.  This innovative, interdisciplinary teaching approach assists students in developing authentic nursing knowledge and perceptions.  Examples of strategies: nursing faculty on the panel being oriented to the content in the non-nursing class, a caring and respectful educational environment, students come prepared with questions, and all faculty engage in the discussions.

Qualitative Findings:

The outcomes: Enhanced learning, positive student evaluations, awareness of the role of the nurse, reciprocal connections, student and faculty satisfaction, increased knowledge of the profession of nursing, nurse self-concept images, and nursing values (trust, caring, unconditional positive regard).  These outcomes were derived from student evaluations and reflection papers.           

Quantitative Findings:

Calling & Vocation Questionnaire (CVQ) was used to assess the presence of, and search for, a calling.  CVQ exploratory factor analysis revealed six reliable common factors (subscales) forming CVQ-Presence and CVQ-Search scores.  CVQ items provided pre-/post-test evaluating the NP.  Using SPSS 25, dependent t-test analyses found significance (p=.001-.042) on all CVQ common factors.

 

Isenção de responsabilidade: Este resumo foi traduzido usando ferramentas de inteligência artificial e ainda não foi revisado ou verificado

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