From navigating electronic health records and HIPAA compliance to applying predictive analytics, health informatics is now essential to the daily work of nursing. But aligning coursework with that reality remains an ongoing effort. At the George Mason University College of Public Health, new research examines whether artificial intelligence can better connect classroom learning to clinical practice.
At George Mason, one undergraduate Health Informatics course brings together students from several programs—including, as of 2025, all nursing undergraduates. With the nursing pathway added, faculty saw an opportunity to sharpen the course’s clinical relevance. While the class taught core informatics principles, its assignments and examples were oriented more toward administrative systems than bedside nursing practice.
Rather than creating a separate course, a faculty team led by health data researcher Sanja Avramovic used AI tools to redesign the existing class for nursing students. They made two key changes: incorporating short, AI-generated videos narrated by digital avatars, and rewriting assignments around nursing-specific scenarios, such as evaluating electronic health records or applying probability models to conditions like meningitis.
“The results suggest that students respond differently when informatics is relevant to their professional identity,” said Avramovic, an associate professor in the Department of Health Administration and Policy. “When the content reflects real nursing skills and scenarios, they engage more deeply and show stronger learning gains. There’s room for improvement, but the results suggest this approach has real potential.”
Why this matters
Competence in informatics has become a foundational skill for nurses. This study, published in the Canadian Journal of Nursing Informatics , suggests that when coursework is explicitly tied to clinical practice and delivered in flexible, self-paced formats, nursing students are more likely to master informatics material and demonstrate stronger short-term learning gains.
It also points to a broader implication: AI tools, when applied thoughtfully and with clear goals, may offer educators a practical way to redesign technical courses so they better serve specific audiences and outcomes.
Study findings
To assess impact, the researchers compared outcomes for nursing students in the redesigned course with students in a traditional version of the class that did not use AI tools. What they saw:
Nursing students in the AI-enhanced course showed statistically significant learning gains from pretest to posttest. Students in the traditional course showed no significant change, though there was no reported decline in performance.
More than half of nursing students reported that AI-generated videos were more helpful than assigned readings, particularly with complex or technical topics.
Nearly four out of five students said the AI tools improved their overall learning experience. In particular, students said they valued the ability to pause, replay, and control the pacing of video lectures.
Not all students preferred AI delivery. About 40% favored traditional lectures, often citing greater energy or a less “robotic” feel.
Many students recommended a hybrid model, using AI videos to supplement, but not replace, live instruction.
People
Redesigning a Health Informatics Course for Nursing Students through AI-Driven Instruction and Clinically Contextualized Assignments
21-Dec-2025