Background: Most simulation centers are equipped with static videoing capabilities, and are not being used to their full potential as the evaluators are restricted to writing broad notes due to the ongoing simulation. This often leads to a non-specific evaluation of the student’s performance.
Conceptual Framework: Fink’s Significant Learning Experience Framework based in educational theory, and the Family Nursing Constructs Framework grounded in the science of nursing and nursing education.
Method: To overcome these limitations, we are proposing an innovative process of evaluating students during simulation by automatically tagging a video in such a way that the evaluator can directly move to a point of interest. We are incorporating a variety of technologies such as verbal computing, smart glass, and intelligent software to improve the quality of evaluation and feedback provided to the student.
Results: Student and the evaluator use smart glasses that record high quality video and audio from the perspective of the person wearing the technology. The evaluator follows a taxonomy to verbally evaluate the students’ performance in real-time. This will generate a written text transcript from the evaluator’s feedback that is coupled with the student’s performance by processing through the smart application’s internal language processing abilities. These transcripts can now interactively be used to search the video and evaluate the student performance.
Conclusions: We have developed an evaluation process to identify the strengths and weaknesses of the student nurse’s performance during a family-focused nursing simulation. This taxonomy assists the student and evaluator to bypass insignificant sections of the video and advance to a point of interest or teachable point where the keywords occurred. This enables the student and evaluator to see the important points of the evaluation in a fraction of time which makes the video an important part of learning family nursing.