When it comes to clinical nursing education, timely and detailed feedback is essential, but often difficult to capture in fast-paced hospital settings. Adam Blank, MSN, RN, a clinical instructor at The University of Texas at Austin School of Nursing, is tackling this challenge head-on with an innovative AI tool he developed alongside Ruoke Zhang, master’s student in Computer Science, Paul Toprac, PhD, Professor of Instruction in Computer Science, Cody Antunez, Senior IT Manager at Enterprise Technology, and Bo Xie, PhD, FGSA, Lee and Joseph D. Jamail Endowed Professor in Nursing and Director of the Center for Healthcare Innovation and Technology Advancements (CHITA).
The tool, called Active Performance Evaluation in the Clinical Setting (APECS), enables clinical instructors to capture anecdotal notes—on the spot—through speech-to-text, then uses AI to refine and organize the observations into an editable feedback report.
“This allows for more detailed capture of observations of nursing students in the clinical environment,” Blank said. “Oftentimes, because of the pace and setting of these observations, it is extremely challenging for a clinical instructor to capture granular data on student performance.”
Review and Refine
Blank described how the—conventional—process of taking notes, revising them, and sharing them with students is time-consuming and often lacks sufficient detail. While clinical instructors provide thorough verbal feedback throughout the day, much of it can be lost amid the fast pace and emotional intensity of clinical activities, he said.
“APECS will allow students to reflect on their clinical performance outside of the hospital setting, with the hopes of recognizing opportunities to build and refine their practice in subsequent clinical experiences,” he added.
Through APECS, clinical instructors can dictate notes during the day, and the AI organizes and refines them into structured feedback reports.
“After each interaction, I can dictate what I observed, and any areas for improvement or key successes,” Blank explained. “At the end of the day, I use the tool to 'polish' the observations according to an evaluation template that I have developed. In essence, that template is a rubric with predefined fields. Each of the fields uses a customizable prompt for the AI that directs it to pull in aspects of the note. It corrects spelling, adds appropriate grammar, and organizes these non-linear notes into a feedback report. That report will be sent to students promptly.”
The tool follows a three-step process: data collection, AI refinement, and instructor review. The faculty instructor reviews the AI-generated notes for clarity, accuracy, and completeness before finalizing and sending the report to students.
Having completed these three steps in Fall 2025, the team will advance the tool in Spring 2026. This next phase will involve integrating it with Canvas, enabling instructors to send the reviewed and approved report directly to students via Canvas.
“Ultimately, the goal is that the feedback will be reviewed and edited in the Canvas assignment itself prior to release to the students, further reducing the administrative burden on clinical faculty. It is critical that the faculty add the final 'polishing' step to ensure that nothing has been missed.”
Blank shared that the 'AI polish' primarily functions as a tool for categorization and organization, guided by the rubric. This rubric is based on a standardized Clinical Evaluation Tool, which was developed using the American Association of Colleges of Nursing Essentials and emphasizes building competency in nursing practice. Each clinical course at the School of Nursing has a specific Clinical Evaluation Tool, which can be integrated into the APECS rubric to collect and deliver feedback tailored to that course’s clinical setting.
From Idea to Execution
What sets this AI tool apart is its flexibility and portability, allowing structured feedback to be delivered in an exportable format. It enables multiple observations to be recorded, refined and categorized according to the clinical guidelines critical for success in each course. The tool also generates reports that can be shared with students promptly, all while keeping the administrative burden on clinical faculty low.
Blank’s inspiration for APECS came from his own teaching experiences.
“Throughout my experience in teaching undergraduate clinical nursing courses, I have sought a mechanism by which to improve the depth and timeliness of my feedback,” he said.
Having used various iterations of dictation, handwritten notes, and speech-to-text software, he found the process inevitably time-consuming and often lacking in detail. Moreover, he was unable to process both his own notes and those from clinical teaching assistants quickly enough for students to make the necessary adjustments on a weekly basis.
An event hosted by CHITA in early 2025 gave him an idea.
“When Dr. Xie solicited proposals for the inaugural NURSING-AI Challenge last Spring, I knew immediately that this would be an opportunity to work with AI-savvy students to create an AI-based tool that would help solve this long-lingering problem,” he added.
APECS is designed to help provide more effective feedback, enabling students to maximize their growth during clinical hours while spending less time on administrative tasks, like transcribing and categorizing notes—the AI tool takes care of that. By reducing this administrative burden, Blank hopes students can reflect on their clinical experiences while they are still fresh in their minds, but in a calmer, non-clinical environment.
Future Focus
Looking ahead, Blank envisions APECS enabling students to create comprehensive clinical portfolios.
“If this is successful, I would hope to be able to allow students to also develop a detailed clinical portfolio, that can automatically summarize their entire body of clinical work throughout the curriculum,” he said. “Every medication, type of pathophysiology encountered, technical skill and nursing intervention that they have performed. This would help students and faculty to ensure that each student is getting adequate exposure to clinical opportunities and that they are best prepared for success in clinical practice.”
Although APECS is still being refined, early results are promising. Using the tool to capture notes has already increased the level of detail, and with further refinement of the rubric prompts next semester, it could soon produce comprehensive reports that give students even more meaningful, actionable feedback.
Beyond efficiency and accuracy, Blank sees APECS as a tool that could shape the future of nursing education more broadly.
“I hope that this tool improves student feedback and reduces the administrative burden for clinical faculty,” he added. “I can also envision this tool used more broadly for capturing feedback from preceptors during nursing residency programs, and in other health profession education programs where direct observation is a key component of their education model.”
Reflecting on the project, Blank emphasizes the collaborative nature of the work.
“I've really enjoyed the teamwork between myself, Dr. Xie, and the technical faculty and staff that have helped build the application,” he concluded. “It's amazing working with programmers who can actualize features that in the past I have only been able to visualize.”
With APECS, Blank and Xie in the School of Nursing and their collaborators in Computer Science and Enterprise Technology are bridging clinical observation and AI technology, ensuring nursing students receive richer, more actionable feedback, while equipping faculty with a powerful tool to enhance education in an evolving healthcare environment.
APECS is a direct result of a strategic partnership between the School of Nursing and the CIO’s Office. Under an MOU, both parties jointly commit to co-develop 1–2 real-world AI in action “success stories” per semester that demonstrate practical impact, time reclaimed, and elevated work quality. APECS is the first of such AI in action success stories, with more to come next year.