Academic Integrity and Senior Nursing Undergraduate Clinical Practice

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.

Using WebCT to Support a Community of Practice

Reflecting a view of “teaching as both an intellectual and practical activity” the Queen’s University Bachelor of Education program has multi-week in-school practicum sessions separated by periods of on-campus course work. The expectation is that teacher candidates will bring together theory and practice as they reflect upon their daily classroom experiences. The reality often is that, while isolated from the university environment and caught up in the pressures of teaching, little deep reflection takes place. For reflection and critical examination of experience to occur, teacher candidates need to share and discuss on a daily basis their practice teaching experience. For the past few years, students in my secondary school mathematics curriculum course, through a WebCT based conference, have been provided, while away from campus, with a place for on-going sharing of teaching stories and dilemmas. In the Fall of 2004 eight-five percent of the class took part in the discussions, posting a total of 667 messages over a 9 week period. In an effort to increase the value of this practicum conference we have analysed the topic threads arising in the conversation, surveyed the participants concerning their impressions of the sharing experience, and conducted in-depth interviews with a sampling of the class. This session will present the results of this study and provide an opportunity to discuss ways in which an online discussion can support the building of community and the exchange of experience while students in professional programs are disbursed in practice/clinical settings.