NURS 618 Week 6 Teaching with Technology Paper Example

Teaching With Technology Paper: Matching Virtual Reality and Generative AI to Learning Outcomes Instead of Adopting Them for Their Own Sake

Introduction

Every year brings a new technology that promises to transform nursing education: high-fidelity manikins, virtual simulation platforms, immersive headsets and now generative artificial intelligence. Billings and Halstead (2016) caution that technology in education should be chosen to support learning outcomes and sound pedagogy, not adopted because it is new. This paper argues that technology use is meaningful when it serves a specific learning outcome better than simpler methods would, and it tests that principle against recent evidence on two technologies: extended reality, including virtual reality, and generative AI. It then offers a framework for deciding when a technology earns a place in a course.

What Makes Technology Use Meaningful

Meaningful use, as I use the term, has three features. First, the technology is matched to an outcome: an educator can name what learners will be able to do because of it. Second, it adds something simpler methods cannot provide, such as a realistic environment for practicing a rare emergency or immediate individualized feedback. Third, its effect is evaluated, so that educators know whether it helped. A virtual reality module used because the program bought headsets, without a clear outcome or evaluation, fails all three tests even if students enjoy it.

Extended and Virtual Reality

Extended reality, which includes virtual, augmented and mixed reality, has the strongest recent evidence base among new educational technologies, and its findings illustrate why matching to outcomes matters. Sengul et al. (2026) systematically reviewed 22 randomized controlled trials of extended reality in nursing education and meta-analyzed 12 of them. Compared with traditional methods, extended reality significantly improved exam performance and learning satisfaction, but it did not significantly improve communication skills, knowledge acquisition, self-confidence, simulation performance or stress, and heterogeneity was high for several outcomes. The same technology that helped students perform on exams did not, on average, make them better communicators, which is exactly why the outcome should be chosen before the tool.

An umbrella review sharpens the picture for higher-order thinking. Delbene et al. (2026) appraised five systematic reviews of immersive technology for undergraduate nursing students and found that improvements in decision-making and problem-solving were consistently reported, especially for interactive, scenario-based virtual reality, while effects on critical thinking were mixed, with meta-analytic findings showing no significant advantage over traditional methods. They also noted generally favorable findings for clinical skills and knowledge and positive effects on satisfaction, motivation and self-efficacy, and they concluded that outcomes depend on pedagogical design, including structured debriefing and curriculum integration.

For an educator, these findings point to specific uses. Interactive virtual reality scenarios are a reasonable choice when the outcome is decision-making in situations students rarely see, such as a deteriorating patient on a night shift, and when the scenario is followed by debriefing. They are a weaker choice when the outcome is therapeutic communication, where role-play with standardized patients may serve better.

Generative Artificial Intelligence

Generative AI is newer, and the evidence is thinner. In a pilot randomized trial with 32 undergraduate students learning endotracheal suctioning, Sezgunsay et al. (2026) found no difference between ChatGPT-integrated teaching and traditional teaching on immediate knowledge scores, but the ChatGPT group retained significantly more knowledge six weeks later, and students described the interactive learning as supportive. The small sample makes the result preliminary. A larger randomized comparison of students formulating surgical nursing diagnoses found everyone improved over three weeks, whether they worked solo, with the chatbot, or with a partner and the chatbot, and the chatbot conditions showed no measurable edge (Meşe et al., 2026). An AI-enabled virtual reality simulation for 147 graduating students learning to recognize clinical deterioration produced higher, though not significantly different, knowledge scores than the conventional program, along with positive views of its acceptability and feasibility (Liaw et al., 2025).

Together, these studies suggest that generative AI may support retention and engagement but has not yet been shown to improve reasoning itself. That conclusion supports a cautious, outcome-matched use: AI tools for practice questions and review, where retention is the goal, and continued reliance on faculty-guided case work for clinical reasoning.

A Framework for Deciding

Before adopting a technology, I will ask four questions. What outcome will this technology serve, and is that outcome one the evidence suggests it supports? What does it add that a simpler method, such as a paper case or role-play, cannot? Can all learners access it, and are faculty prepared to use it well, including debriefing? How will I evaluate whether it worked? A technology that cannot answer all four questions satisfactorily does not belong in the course yet.

Applying the Framework to a Familiar Decision

Consider a decision many programs face: whether to purchase a virtual reality platform for a pediatric course in which clinical placements are scarce. The outcome is the first question. If the program's concern is that students rarely see a deteriorating child, the outcome is recognizing and responding to pediatric deterioration, an outcome closely related to the decision-making benefits the umbrella review reported. The second question asks what the technology adds; here, it provides repeated exposure to rare, high-stakes situations that a paper case cannot make vivid. The third question, access and preparation, may be the deciding one: if only a few headsets are available and faculty have no training in debriefing virtual scenarios, the platform is likely to disappoint. The fourth question requires an evaluation plan, such as comparing students' performance in a mannequin assessment before and after the virtual reality sessions. Working through the questions in this way often reveals that the barrier to meaningful use is not the technology but the conditions around it.

Ethical and Practical Considerations

Technology raises issues of equity, privacy and integrity. Students without reliable internet or devices may be disadvantaged by online tools. Generative AI raises questions about accuracy, data privacy and academic honesty, and students need clear guidance about when its use is permitted and how to verify its output. Costs, including licensing and faculty training, must be weighed against outcomes. Billings and Halstead (2016) emphasize that faculty development is essential when new technologies are introduced, since even good tools fail in untrained hands.

A Faith Perspective on Stewardship

Jesus' parable of the talents commends servants who used what they were given wisely (English Standard Version Bible, 2001/2016, Matthew 25:14-30). Technology budgets and students' time are resources entrusted to educators, and stewardship means investing them where they produce real learning rather than where they merely impress.

Application in My Practicum

In my practicum, I will apply the framework to one decision my preceptor's program is considering: whether to replace one mannequin simulation on deterioration with a virtual reality scenario. Using the evidence above, I will recommend a pilot with one cohort, paired with structured debriefing and an evaluation that measures decision-making, the outcome the evidence most supports.

Conclusion

Technology in nursing education is meaningful when it is matched to an outcome it supports better than simpler methods, when learners can access it and faculty can use it well, and when its effects are evaluated. Recent evidence shows that extended reality helps with exam performance, satisfaction and decision-making but not every outcome, and that generative AI may aid retention without yet improving reasoning. Educators who choose technology by outcome rather than novelty will use their resources more wisely and serve their students better.

References

Billings, D. M., & Halstead, J. A. (2016). Teaching in nursing: A guide for faculty (5th ed.). Elsevier.

Delbene, L., Sallai, T., Mezini, S., Serrenti, E., Barbieri, M., Bagnasco, A., & Greaves, P. J. (2026). Effectiveness of immersive technologies in nursing education: An umbrella review. Nurse Education Today, 166, Article 107306. https://doi.org/10.1016/j.nedt.2026.107306

English Standard Version Bible. (2016). Crossway. (Original work published 2001)

Liaw, S. Y., Rusli, K. D. B., Tan, J. Z., Wee, Y. H. C., Neo, N. W. S., & Chua, W. L. (2025). Artificial intelligence-enabled virtual reality simulation for clinical deterioration training: An effectiveness-implementation hybrid study. Nurse Education in Practice, 87, Article 104462. https://doi.org/10.1016/j.nepr.2025.104462

Meşe, S., Pan, Y., Meşe, C., & Sirganci, G. (2026). Comparing individual and peer-supported ChatGPT use in nursing case analysis: Effects on nursing diagnostic skills and cognitive load in a randomized controlled trial. Nurse Education in Practice, 96, Article 104949. https://doi.org/10.1016/j.nepr.2026.104949

Sengul, T., Sarikose, S., Gul, A., & Murat, N. (2026). The effectiveness of extended reality methods (augmented reality, virtual reality, and mixed reality) in enhancing clinical competency in nursing education: A systematic review and meta-analysis. Nurse Education Today, 168, Article 107350. https://doi.org/10.1016/j.nedt.2026.107350

Sezgunsay, E., Polat, A. B., & Kılıcer, S. B. (2026). Integrating ChatGPT into nursing education: A randomized trial exploring knowledge, retention, and student perspectives on endotracheal suctioning. BMC Medical Education, 26(1). https://doi.org/10.1186/s12909-026-09483-2