A cost-effective IoT learning environment for the training and assessment of surgical technical skills with visual learning analytics Articles uri icon

publication date

  • December 2021

start page

  • 1

end page

  • 19

issue

  • 103952

volume

  • 124

International Standard Serial Number (ISSN)

  • 1532-0464

abstract

  • Background
    Surgeons need to train and certify their technical skills. This is usually done with the intervention of experts who monitor and assess trainees. Nevertheless, this is a time-consuming task that is subject to variations among evaluators. In recent decades, subjectivity has been significantly reduced through 1) the introduction of standard curricula, such as the Fundamentals of Laparoscopic Surgery (FLS) program, which measures students" performance in specific exercises, and 2) rubrics, which are widely accepted in the literature and serve to provide feedback about the overall technical skills of the trainees. Although these two elements reduce subjectivity, they do not, however, eliminate the figure of the expert evaluator, and so the process remains time consuming.

keywords

  • technical skills; surgery; iot; sensors; learning analytics; visualizations