Enhancing learning as theoretical thinking in robotic surgery
Laura Seppänen, Marika Schaupp, Mikael Wahlström
- Year
- 2018
- Citations
- 6
- Access
- Open access
Abstract
Professionals in many domains need to deal with increasingly complex, technology-mediated and uncertain work. Thus ways of learning that continuously and flexibly create new knowledge are needed at work. The aim of this article is to describe the logic of theoretical-genetic generalisation, and to use this, in addition to other methodological resources from pragmatism and cultural-historical psychology, for devel-oping a learning method for robotic surgery. In theoretical generalisation, or theoretical thinking, the learner orientates him-/herself in two directions: towards producing general, abstract understanding of dynamic interrelations within a phenomenon, and towards flexibly tailoring good solutions for each particular situation. Based on our ongoing study of robotic surgery, we sketch three different designs for learning which are all based on video-supported joint reflection of real robotic surgical operations. We outline the necessary principles and steps of the method in this context, and finally, discuss the potential of the outlined method for learning.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002