1. Predicting trained task performance: The interaction of taxonomy, data, and modeling

2. Goal: Predict and optimize performance on trained tasks Four dimensions of analysis: 1. Task type 2. Training methods 3. Performance measures 4. Training principles The function of taxonomic analyses Develop analyses for dimensions that can: -Relate similar tasks -Cover task and training domains -Capture meaningful aspects of performance -Provide useful generalizations for optimization constraints

3. Iterative development process Analysis framework Empirical training and performance data Task analyses Target phenomena (including general principles) Task models

4. Modeling performance using task features: An earlier approach Roth, Thomas J. 1992. Reliability and validity assessment of a taxonomy for predicting relative stressor effects on human performance. Micro Analysis & Design Technical Report 5060-1. Roth described military tasks as weighted vectors of five features: Task features were found to be non-independent. Need task features that are (more) independent and provide more detail about cognition. Attention Perception Psychomotor Physical Cognitive

5. A decomposition for cognitive tasks Perception/attentional processing Cognitive/affective processing Physical/communicative response Vision, hearing, tactile sensation Executive control/Monitoring Memory/Representation Reasoning/Problem solving Motivation/Affect Concept formation Imagery SynthesisResponse planning Language/Speech Manipulation/Fine motor Action/Gross motor Speech planning Motor planning

6. Modeling the data entry task Task of data entry is simple, but decomposable: Read number Encode number Type number Perceptual processing Cognitive processing Response Plan motor output Performance is measured by speed and accuracy of typing Training consists of practice and repetition (1 pass/item) Synthesis Planning

7. Understanding componential performance Consider effects of training practice and repetition on: …as measured by speed and accuracy of data entry. Reading Planning Encoding Typing

8. Empirical phenomena Fixed processing of perception and response Reading and typing numbers requires a fixed amount of time, which does not improve with practice. Repetition priming of motor planning Repeatedly planning the motor response for numbers leads to specific learning and speeding of responses. Speed–accuracy trade-off Increased response speed is associated, for most people, with a decrease in the accuracy of responses. Encoding improvement of only some percepts Repeated encoding of numerals does not improve with practice, but (non-usual) encoding numbers from words does.

9. Modeling implementation of phenomena Reading and typing speeds are constant, but depend on format.  t read (n) = c ReadFormat ; t type (n) = c TypeFormat Repetitious motor planning speeds responses (according to the power law of learning) and lowers accuracy.  t planning (n) = a p + b p (N(n,t) + p p ) -  p  a planning (n) = f(t planning (n)) Repetitious encoding only affects speed for less familiar percepts  t encoding (n) = a e + b e (N(n,t) + p e ) -  e OR c Encoding  a encoding (n) =  ?

10. The IMPRINT simulation Practice = N RT = t data entrym (n) Data Entry Encoding Typing Reading Repeated motor planning

11. Iteration: Decomposition  Modeling  Experimentation Feedback Fact: Accuracy can be improved with feedback.  Update model to decouple speed and accuracy functions.  Include monitoring function in task decomposition. Fatigue Fact: Speed of cognitive processing decreases without repetition priming.  Update model to reflect cognitive fatigue from practice. Error types Prediction: Accuracy decline is due to motor planning errors.  Examine effects on accuracy of encoding and planning.  Representations and error types in task may be different.

12. Iteration: Enhancing the taxonomic analyses Individual differences Fact: Not everyone exhibits the speed–accuracy trade-off. Fact: Higher cognitive ability leads to faster skill acquisition.  Add a dimension of individual variation.