Aug 2026· Journal of Clinical Nursing· 0 citations· 47 references
Medicine
TL;DR
Embedding structural changes within assessment design, rather than relying on rule enforcement, will ensure nursing and midwifery graduates are prepared to thrive in an AI-enabled world.
Abstract
Aims
This paper equips nursing and midwifery academics with strategies to assess student competence in an educational landscape shaped by generative artificial intelligence (GenAI). It examines assessment design approaches, highlighting the shift from tasks reliant on unenforceable rules (discursive changes) toward redesigning assessment mechanics (structural changes) to preserve validity.
Background
The rapid adoption of GenAI tools like ChatGPT is transforming higher education, challenging assumptions about teaching, learning, and academic integrity. Traditional assessments are increasingly unsuited when AI can replicate student outputs. Rather than policing AI use, institutions must leverage its potential whilst ensuring assessment remains authentic, equitable, and valid.
Methods
A narrative review was undertaken, drawing upon peer-reviewed literature, expert commentary, and policy documents related to GenAI in nursing and midwifery education, emphasising assessment design and academic integrity.
Discussion
Two primary approaches are presented. Lane One creates GenAI-resistant tasks fostering higher-order thinking. Lane Two embraces human-AI collaboration, focusing on transparency, process, and developing evaluative judgement. A hybrid Lane Three allows conditional AI use within defined boundaries. Effective redesign requires structural, not merely discursive change, adopting systemic program-level assessment and clarifying acceptable AI use. Supporting staff and students through uncertainty is essential for sustainable reform.
Conclusion
Valid and ethical assessment in the GenAI era demands explicit institutional policies, clear communication, and rubrics promoting authentic learning. Embedding structural changes within assessment design, rather than relying on rule enforcement, will ensure nursing and midwifery graduates are prepared to thrive in an AI-enabled world.
IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE
Ensuring patient safety principles remain central to assessments whilst demanding that GenAI integration upholds professional standards will prepare nursing and midwifery graduates to thrive in an AI-enabled healthcare environment.
Introduction: The integration of Evidence-Based Practice (EBP) into nursing education faces challenges in linking theory to clinical application in complex family health contexts. Students struggle with efficiently accessing, appraising, and applying evidence influenced by sociocultural factors. Artificial intelligence (AI) offers transformative potential but requires pedagogical design to foster critical thinking and ethical use beyond technical skills.Method: An action research with mixed methods was conducted with 100 nursing students. The intervention had four phases: participatory family diagnosis, AI-assisted evidence retrieval and validation, community educational workshops design and execution, and multi-level evaluation.Results: A significant shift in AI use from basic to strategic, with a 40% reduction in literature search time. Qualitative data revealed enhanced critical awareness and ethical reasoning, while quantitative results indicated 90% of students improved critical appraisal skills and 70% felt more confident in evidence-based decisions. The project impacted 100 families, with 90% trusting evidence-based recommendations.Conclusions: Integrating AI in experiential pedagogies like Design Thinking and Service-Learning effectively develops nursing competencies, ensuring technology adoption supports context-sensitive family health learning outcomes.
Maria Graciela Villalba-Condori, Carla Cuya-Zevallos· Publicaciones· 0 citations
Introduction Theoretical assessment design is crucial in nursing education, ensuring students develop cognitive and problem-solving skills for clinical practice. However, misalignment with learning outcomes and inconsistent cognitive level distribution remain complex issues. Methods and findings This multimethod qualitative study explored theoretical assessment design in a South African nursing school through in-depth interviews with nurse educators and a document review of moderators’ reports. Stratified purposive sampling ensured diverse representation across National Qualifications Framework Levels 5–8. Data saturation was reached after nine interviews, analysed using Creswell and Creswell’s six-step thematic framework. The document review analysed 70 moderation reports (22 internal and 48 external) from 2015 to 2019, focusing on feedback related to final theoretical assessments. Content analysis, following Krippendorff’s framework, was used to identify themes and patterns. Findings revealed an overemphasis on lower-order cognitive skills (Bloom’s taxonomy), inconsistent question distribution, and misalignment with national qualification standards. Educators acknowledged these issues but cited time constraints, inadequate training, and institutional pressures as contributing factors. Moderation reports confirmed assessment inconsistencies, emphasising the need for better alignment with constructive alignment principles. Triangulation of data highlighted a gap between perceived best practices and actual assessment quality, suggesting assessments do not fully support higher-order cognitive skill development. Conclusion To improve the validity and reliability of theoretical assessments, nursing programmes should prioritise training in assessment design, strengthen alignment with learning outcomes, and implement moderation strategies to address inconsistencies. These findings contribute to the broader discourse on improving assessment practices in nursing education globally.
G. Donough, K. Mthimunye, F. Daniels· PLoS ONE· 0 citations
BACKGROUND
The rapid integration of generative artificial intelligence (GenAI) into nursing education presents both opportunities and challenges, yet empirical evidence on students' critical engagement with AI-generated content within assessment contexts remains limited.
AIM
To examine undergraduate nursing students' reflections when comparing their own evidence-based summaries with AI-generated outputs in response to the same clinical research questions.
METHODS
A qualitative descriptive design was employed using retrospective analysis of 497 assessment submissions from an undergraduate nursing cohort at an Australian university. Students formulated a research question, synthesised peer-reviewed evidence, submitted the same question to an AI tool, and critically reflected on the comparison. Data were analysed using qualitative content analysis and thematic analysis.
RESULTS
Four themes were identified: 1. Credibility, quality of evidence and academic rigour. Students identified fabricated references, outdated information, and absence of peer-reviewed sourcing as key limitations. Additionally, students reflected on algorithmic limitations and the challenge of verifying AI outputs without prior topic knowledge; 2. Critical thinking, depth of analysis, and human intelligence. AI was perceived as unable to replicate contextual reasoning or multi-source synthesis; 3. Efficiency, accessibility, and practical utility. AI's speed and clarity were valued for brainstorming and initial scoping; and 4. Student identity, learning, and professional development were shaped by the view that engaging in manual, hands-on research was integral to forming a safe, evidence-informed nursing identity.
CONCLUSION
This study suggests that structured AI-comparison tasks offer the opportunity to develop AI and digital health literacy in nursing students. Students are neither naively accepting of AI nor reflexively dismissive but are actively working to understand its place within the ethical frameworks of nursing education. These findings contribute to AI integration in nursing education and offer practical guidance for educators seeking to support graduates to be AI-critical and well-equipped to leverage the efficiencies of these tools.
Background: Preparing midwifery graduates to be confident, competent, and resilient is essential for workforce sustainability, yet students report a disconnect between academic preparation and clinical realities. Increasing care complexity, workforce shortages, and variable clinical learning environments globally highlight the need to examine how educational strategies support effective transition to practice. Objective: To map and synthesise the evidence regarding educational approaches, learning experiences, and transition-to-practice factors that influence preparedness for professional practice among midwifery students, and to identify gaps in the existing literature to inform a coherent and future-ready educational framework. Methods: A PRISMA-ScR-guided scoping review was conducted across seven databases. Data were extracted through a standardised template and analysed using narrative synthesis. Qualitative, quantitative, and mixed-method studies were examined for learning approaches, practice conditions, and transition experiences. Results: Three overarching domains and seven sub-domains were identified. Reflective practice, blended learning, simulation, and collaborative approaches were widely valued but inconsistently implemented. Students frequently experienced transition shock, limited scaffolding of higher-order thinking, variable supervision, with misalignment between curricula, competency frameworks, and clinical expectations, leading to uneven confidence and skill development. Educator capacity constraints particularly in feedback, reflection, and simulation pedagogy were recurrent barriers. Positive clinical environments and structured reflective opportunities consistently strengthened competence, identity formation, and readiness. Conclusion: Midwifery education is evolving towards contemporary, competency-based pedagogies, yet persistent inconsistencies undermine the reliability of graduate preparation. Strengthening curriculum coherence, standardising key learning experiences, investing in educator capability, and embedding structured reflection and simulation are essential. A unified educational framework that integrates these components is required to enable confident, adaptable, and practice-ready midwives.
Introduction. Midwifery education integrates theoretical instruction with clinical practice, in which supervisory relationships are pivotal. The quality of mentorship substantially influences students’ competence, confidence, and professional identity, and is largely determined by midwives’ awareness of their role as preceptors and how this is enacted in practice. This study aims to provide a valid instrument for evaluating clinical teaching in midwifery education by translating, culturally adapting, and psychometrically validating the Midwifery Perceptions and Assessment of Clinical Teaching (MidPaACT) tool in the Italian context. Methods. The MidPaACT questionnaire was translated and culturally adapted following established international guidelines. The process included forward translation, synthesis, back translation, expert panel review, and pilot testing. Data were collected through an online survey completed by preceptor midwives involved in undergraduate midwifery education. Construct validity was assessed using confirmatory factor analysis using a Diagonally Weighted Least Squares estimator. Model fit was evaluated using RMSEA, SRMR, CFI, and TLI indices. Internal consistency reliability was assessed using Cronbach’s alpha coefficients. Results. A total of 168 preceptor midwives participated. Confirmatory factor analysis supported the original two-factor structure (‘Supporting students to learn’ and ‘Safety in learning’) and indicated acceptable model fit (RMSEA = 0.08; SRMR = 0.105; CFI = 0.973; TLI = 0.971). Internal consistency was satisfactory for both subscales (α = 0.88 and α = 0.77). Participants reported high levels of engagement in supporting student learning and ensuring safety in clinical practice, while highlighting areas for improvement in academic–clinical collaboration and culturally responsive supervision. Discussion. The Italian version of the MidPaACT demonstrates satisfactory psychometric properties and provides a valid tool for the systematic evaluation of clinical teaching in midwifery education. Its use can support the development of targeted faculty development initiatives and strengthen evidence-informed approaches to improving the quality of clinical education.
S. Neri, Maria Panzeri, Margaret Smith et al.· Interdisciplinary Journal of...· 0 citations
The impact of transitioning from a traditional to an AI-aware rubric in a Health and Medicine course is evaluated, examining how this shift influenced educators’ grading practices, instructional strategies, and perceptions of student engagement.
Suzanne Estaphan, Tehzeeb Zulfiqar· Frontiers in Education· 0 citations