Stochastic Systems/Heuristic Response
I have been thinking about the ways in which children navigate software that they are initially unfamiliar with. It is as if they have a mental map of the software. This 'mental map' may be acquired from using other software which deploys similar architectural templates. The architecture is fixed, the rules and parameters of the map are unwritten but adhered to by the software user.
If one applies this to the problem of tension encountered when learning CG software, the map is unfamiliar as it is an unfamiliar template. However, certain things are known, such as icons and labels which act as signposts leading towards certain software functions.
The process of training a user to better understand how to navigate the architecture and functions of a software can be taught in a similar way in which the Master Crafts person teachers an apprentice a craft. Knowledge is imparted as a "show and tell" process of short tutorials designed to build knowledge and produce basic models. My own training was taught in this way and was aligned with the basic engineering terms such as loft, spline, extrusion and Boolean functions.
It was in this way that I built a knowledge of the CG software as a kind of 'mental map'. Following this basic training, I found that accessing online network of experts helped to develop further knowledge through a process of virtual peer by peer sharing.
Basic training and peer to peer tutorials provided solutions to problems in achieving pre-determined aims. However, the practice of trial and error, although slow to provide finite solutions, did offer a more natural way of learning about software architecture. Testing the affordances and constraints of the system in practice. This did throw up unpredictable results with errors and glitches in a fixed system but also allowed for a more natural exploration of the software.
What is interesting is the way in which heuristic play a part in the tension between learning about a fixed architecture and a stochastic system. By stochastic, I mean that a system in pre-determined but has an element of randomness.
Engineers, artists, craft workers, stop-motion animators all apply a number of heuristic methods to find solutions that will work in stochastic and Determined systems. Although there is a great desire to be Masters of their profession, to develop high levels of skill and tacit knowledge. However, there is a marked desire to find bespoke solutions throwing away "the rule book", ignoring instructions a turning preconceptions about a problem on its head, breaking a thing, to fix it, to break it again, to engineer, over engineer and simplify. Experience in a family of engineers and artists has taught me this.
Further research into architecture/stochastic systems and Heuristics as well as a review of the practice experiments will help to identify if this area might reveal more about the tension between CG/craft in animation practice.
If one applies this to the problem of tension encountered when learning CG software, the map is unfamiliar as it is an unfamiliar template. However, certain things are known, such as icons and labels which act as signposts leading towards certain software functions.
The process of training a user to better understand how to navigate the architecture and functions of a software can be taught in a similar way in which the Master Crafts person teachers an apprentice a craft. Knowledge is imparted as a "show and tell" process of short tutorials designed to build knowledge and produce basic models. My own training was taught in this way and was aligned with the basic engineering terms such as loft, spline, extrusion and Boolean functions.
It was in this way that I built a knowledge of the CG software as a kind of 'mental map'. Following this basic training, I found that accessing online network of experts helped to develop further knowledge through a process of virtual peer by peer sharing.
Basic training and peer to peer tutorials provided solutions to problems in achieving pre-determined aims. However, the practice of trial and error, although slow to provide finite solutions, did offer a more natural way of learning about software architecture. Testing the affordances and constraints of the system in practice. This did throw up unpredictable results with errors and glitches in a fixed system but also allowed for a more natural exploration of the software.
What is interesting is the way in which heuristic play a part in the tension between learning about a fixed architecture and a stochastic system. By stochastic, I mean that a system in pre-determined but has an element of randomness.
Engineers, artists, craft workers, stop-motion animators all apply a number of heuristic methods to find solutions that will work in stochastic and Determined systems. Although there is a great desire to be Masters of their profession, to develop high levels of skill and tacit knowledge. However, there is a marked desire to find bespoke solutions throwing away "the rule book", ignoring instructions a turning preconceptions about a problem on its head, breaking a thing, to fix it, to break it again, to engineer, over engineer and simplify. Experience in a family of engineers and artists has taught me this.
Further research into architecture/stochastic systems and Heuristics as well as a review of the practice experiments will help to identify if this area might reveal more about the tension between CG/craft in animation practice.
