Background: Game-based learning has attracted much attention in education in recent years due to its ability to increase student motivation and engagement in learning. This study reviewed the literature to answer the research questions: What learning outcomes have been linked to games in nursing education? What are potential gaps in the field's knowledge regarding games in nursing education? Method: A systematic literature search was completed in CINAHL and Google Scholar from 2009–2019 with the keywords of games , gaming , and nursing education . Results: A total of 49 papers were identified; of these, 34 were excluded, and 15 empirical studies were evaluated. The majority reported beneficial learning outcomes, such as increased knowledge, higher test scores, and positive student comments. Several methodological weaknesses were noted, such as small sample sizes, convenience samples, and lack of control groups or randomization. Conclusion: Games have the potential to prepare new nurses for improved clinical decision making. More robust research methodologies are needed to confirm best practices for educators. [ J Nurs Educ . 2020;59(7):375–381.]

Background: Developing engaging presimulation learning materials that provide contextualized patient information is needed to best prepare students for nursing simulation. One emerging strategy that can be used by educators to create visual images for storytelling is generative artificial intelligence (AI). Purpose: The purpose of this pilot study was to determine how the use of generative AI–created patient backstories as a presimulation strategy might affect student engagement and learning in nursing simulation. Methods: A qualitative cross-sectional survey with content analysis was completed with undergraduate nursing students following an acute care simulation. Results: Student surveys point to positive pedagogical outcomes of using AI image generation as a strategy to prepare for simulation such as decreased anxiety in simulation, increased preparatory knowledge, and increased emotional connection with the patient's story. Conclusions: Images created with generative AI hold promise for future research and transforming nursing education.

Generative artificial intelligence (AI) allows for the transformation of written text into artistic images. Scholars and researchers are beginning to explore the benefits of this technology to improve reflective practices and critical analysis in education. The extent to which AI-generated images can be used to explore cultural stereotypes and mental representations of the nursing profession has not yet been studied. This article describes a case study of using generative-AI images created by Midjourney with undergraduate nursing students to examine their perceptions and fears of the nursing profession. The research explored how students experienced the process of using AI-generated art as a teaching tool to increase their reflections and discussions on professional nursing topics. Images were used to encourage both individual and collaborative reflection and discussion on nursing topics. Results of this qualitative, exploratory study point to therapeutic and technological outcomes of using AI image-generation as a strategy to encourage reflection and discussion on student’s perceptions and fears of the nursing profession. Implications for education and practice are discussed. Keywords- artificial intelligence, image-generation, Midjourney, nursing education