2 resultados para practice model

em QSpace: Queen's University - Canada


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Formative assessment was introduced in Rehabilitation Therapy students’ information literacy programs in Fall Term 2006 in the course OT/PT 892: Evidence-Based Practice. It was subsequently employed in the Winter Term 2008 and again in the Spring Term 2008. Formative assessment during student/librarian face-to-face consultations was one of a variety of teaching techniques used in the program. Other techniques included: a required reading; an interactive hands-on searching session; and a summative assessment of the final revised search strategy assignment (these techniques varied somewhat over the 3 classes). With the 2008 entrance class, this course content moved to OT/PT 898: Critical Enquiry, largely in Module 3: Reviewing the Literature. One of the Critical Enquiry’s learning objectives is: “recognize and reflect on the complexity of gathering evidence to inform decision-making.”

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Background: Academic integrity (AI) has been defined as the commitment to the values of honesty, trust, fairness, respect, and responsibility with courage in all academic endeavours. The senior years of nursing studies provide an intersection for students to transition to professional roles through student clinical practice. It is essential to understand what predicts senior nursing students’ intention to behave with AI so that efforts can be directed to initiatives focused on strengthening their commitment to behaving with AI. Research Questions: To what extent do students differ on Theory of Planned Behaviour (TPB) variables? What predicts intention to behave with academic integrity among senior nursing students in clinical practice across three different Canadian Schools of Nursing? Method: The TPB framework, an elicitation (n=30) and two pilot studies (n=59, n=29) resulted in the development of a 38 question (41-item) self-report survey (Miron Academic Integrity Nursing Survey—MAINS: α>0.70) that was administered to Year 3 and 4 students (N=339). Three predictor variables (attitude, subjective norm, perceived behavioural control) were measured with students’ intention to behave with AI in clinical. Age, sex, year of study, program stream, students’ understanding of AI policies, and locations where students accessed AI information were also measured. Results: Hierarchical multiple regression analyses revealed that background, site, and TPB variables explained 32.6% of the variance in intention to behave with academic integrity. The TPB variables explained 26.8% of the variance in intention after controlling for background and site variables. In the final model, only the TPB predictor variables were statistically significant with Attitude having the highest beta value (beta=0.35, p<0.001), followed by Subjective Norm (beta=0.21, p<0.001) and Perceived Behavioural Control (beta=0.12, p<0.02). Conclusion: Student attitude is the strongest predictor to intention to behave with AI in clinical practice and efforts to positively influence students’ attitudes need to be a focus for schools, curricula, and clinical educators. Opportunities for future research should include replicating the current study with students enrolled in other professional programs and intervention studies that examine the effectiveness of specific endeavours to promote AI in practice.