Human Performance Engineering
Dotan Shvorin & Kevin Taaffe
Identification System
M. Matthen, Seeing, Doing, and Knowing: A Philosophical Theory of Sense Perception Oxford: Clarendon
Press, 2005.
Sensory Input
Classification System
Comprehension System
L. F. Schlecht, Classifying Fallacies Logically, Teaching Philosophy, 14:1, March 1991
D. T. Quzts, M. J. Palombo, Case Method in a Graduate Children's Literature Course to Foster
Critical Thinking: Picture Books and the QAR, SPRIN(J 2005, Val. XXIV, NO. 3
Vibration
Translation
Data Base
Update
Information
Directory
Our body’s external and internal sensors are providing signals (40
billion), which are being translated in our brain (CPU).
Decision Making
Game Theory Approach
Cause and Effect in Sports Performance Errors
Shvorin, D. and Taaffe, K.(2015) ‘Evaluating the player’s decision-making capabilities in the sport
recruitment process’, to be submitted.
Shvorin, D. and Taaffe, K.(2014) ‘Improving tennis player performance using system development interpretations
methodology’, Int. J. Quality Engineering and Technology, Vol. 4, No. 3, pp.225–242.
Second Order
First Order
With a goal in mind, we follow a course of action, which was
developed from logical reasoning.
Upon receiving sensory input, our brain creates an information directory
and clusters groups of data with similar characteristics.
Error List
Decision Making Tree
Expected Value
Weight
No point construction from the game plan
Follow up reaction misses
Wrong stroke selection misses
Degraded performance under pressure
Misses when outside of the hitting comfort zone
Misses of back movement strokes
Decision Making
Execution
45%
20%
5%
15%
P(
10%
Player (i)
5%
1%
Low motivation misses
1%
P(
Qu
ali
ty)
=7
0%
3%
Easy put away misses
Q
ty
i
l
ua
5
=
)
System Development Interpretations (SDI) methodology is a quality tool designed to identify and map the
causes that contribute to defect creation in a manufacturing system. We extended its use into the setting of
professional sports in order to understand how defects / errors are being created in the system.
Strategy A
Cost = 3
Benefit = 5
Strategy B
Cost = 1
Benefit = 2
u
P(Q
45%
=
)
ality
P(Q
ualit
y) =
6
5%
)=7
y
t
i
l
a
(Qu
5%
P
P(Q
u
ality
)=
65%
Tactic 1
Cost = 2
Benefit = 4
Tactic 2
Cost = 4
Benefit = 6
Tactic 3
Cost = 0
Benefit = 4
Game Plan
Evaluation
Tactic 4
Cost = 2
Benefit = 0
The integration of game theory and quality engineering techniques lead to the design of a recruitment
evaluation for specific player positions in sports. We examine the player decision-making capabilities
given a certain game scenario.
Performance Characteristics Quantification, Analysis & Design of Experiments (Current Research – CI)
The Agility cycle represents a sequential development of a few performance characteristics that can be quantified and measured. The cycle begins and ends with awareness which expresses
our ability to integrate information to our system. Given relevant information, we make a prediction that could be based on pre-knowledge or artificial knowledge. When a decision is made ,
we prepare ourselves to act and follow through. The execution demonstrates our ability to integrate each step in the process in order to achieve the expected result .
In research
Awareness
Awareness
Anticipation
Integrating
Information to our
system
Prediction
We make a
prediction based on
anticipation or
intuition
Decision Making
Logical &
Emotional
Intuition
Reaction
Preparation
Reaction would be
based on the
prediction type
Execution
In research
Adaptation
Adaption will be the
critical factor
Agility
Endurance
Information Update
Motivation