Abstract:

Internationally educated nurses (IENs) bring vital clinical expertise to Canadian health systems, yet critical appraisal of research literature - a foundational competency in evidence-informed practice - remains an under-addressed challenge in IEN transition programming. Language barriers, unfamiliar academic conventions, and intimidating methodological terminology create conditions for disengagement that traditional instructional approaches have been insufficient to address.

This presentation introduces CASP Mentor, a purpose-built AI chatbot guiding IEN nurses through the Critical Appraisal Skills Programme (CASP) using plain language scaffolding, embedded glossary definitions, and Socratic prompting. Free, browser-based, and requiring no login or data collection, CASP Mentor was designed from the ground up for the IEN learner.

CASP Mentor was designed through an iterative development process. An initial version using standard academic language was reviewed and identified statistical and methodological terminology as a primary barrier to accessibility for IEN learners. This directly drove the development of a fully IEN-adapted version incorporating plain language checklist questions, word-level prompts, proactive vocabulary scaffolding, and a built-in glossary for terms such as heterogeneity and confidence interval.

A feasibility and acceptability pilot of Version 2 was conducted with 9 IEN nurses enrolled in a transition program. Participants independently selected and completed three CASP checklists relevant to a single research question. All pre-defined feasibility criteria were met: 100% task completion, mean completion time of 38 minutes, zero critical technical failures, and 87% independent use without facilitator assistance. A purpose-built acceptability questionnaire yielded a high overall mean (M = 4.45/5.0), with comfort working at one's own pace rated highest (4.8), understanding of CASP questions close behind (4.7), and 93% willing to recommend the tool to a peer.

Building on these findings, a third version has since been developed enabling students to synthesize findings across multiple studies and generate an evidence summary based on a research question - expanding CASP Mentor from single-study appraisal to full evidence integration. Future directions include a pre-post effectiveness study using validated critical appraisal knowledge measures, and LMS integration for longitudinal competency tracking. CASP Mentor demonstrates that purpose-built, equity-oriented AI tools can make complex research skills accessible, progressive, and engaging for IEN learners across Canada.

Keywords:

Internationally educated nurses, critical appraisal, AI chatbot, nursing education, IEN transition, evidence-informed practice, plain language scaffolding, educational technology.