GOMS as a Simulation of Cognition

1. GOMS as a Simulation of Cognition Frank Ritter, Olivier Georgeon 30 oct 2017

2. Cognitive architectures • "Brain emulator" • Simulates the computation we think the brain does (for doing a given task…). • Provides structures to store symbols • Provides instructions to manipulate symbols • Hypothesis: Goal-driven, Problem-solving, symbolic computation.

3. GOMS Architecture

4. Example: Check email • Procedure check_emails • Goal Login • Goal read_email • Goal memorize_sender's_name • Goal read_email_body • If Needed(), Goal replay_email • Goal reply_email(x) • Selection rule Select_appropriate_formulation(x) • Goal reply_email_friend • Operator Type (Hi <x>) • … • Goal reply_email_familly • Operator Type (Dear <x>) • … • Loop to read_email / Repeat Goal read_email • Goal: Logout Note: Needed ()’s will be translated as a mental op, but is usually more complex

5. Mental operations and contents Visual buffer Long term memory Perceived_item: John (John, relation, friend) (Jack, relation, family) (email, name, John) Goals Selection rule Reply_email_friend Reply_email_family Memorize_sender's_name … If Perceived_item = X And (X, relation, friend) Then Process goal reply_email_friend

6. How To Use GOMS • Analyze hierarchical structure of a task • coarse analysis focuses more on the cognitive structure of a task • fine analysis focuses more on the structure imposed by the specific interface design • Analyze alternative methods of interaction • Assign operators to base level goals • Assign times to operators • Sum the operator times to get sum for task • Look for excessive time • Look for duplicated time • Look for wasted time • Look for non-parallel construction on parallel tasks

7. GOMS Operator Times More available in FDUCS, GOMSL and CM&N

8. Summary of GOMS • A method to describe tasks and how a user performs those tasks with a specific design • bridges task analysis with a specific interface design • assumes error-free, goal-directed, and rational behavior • Views humans as information processors • small number of cognitive, perceptual, and motor operators characterize user behavior • To apply GOMS • analyze task to identify user goals (hierarchical) • identify operators to achieve goals • sum operator times to predict performance

9. KLM Times To do the KLM, keep track of

10. M Heuristics placement Do all physical ops 0. Insert Mop before all K’s not part of strings (e.g., shift to new field) and P’s that select a command (not argument) Remove all Mops fully anticipated as part of commands (PMK-> PK) Remove all after first letter of a command(CR M K M K M K M-> CR M K K K K) Remove redundant command terminators(CR M command M CR -> CR M command CR) Don’t remove variable terminators(no change)

11. Conclusion: KLM and GOMS, an inexpensive way to improve about interfaces Cheap way to evaluate expert, error-free performance (GOMS) in interfaces Cheaper way to evaluate interfaces (KLM) If done fairly, typically tells you the best interface Typically tells where improvements are possible Less movements, less keys, less Mop Keep parallel and consistent Shift from mouse to keyboard for experts Apply Fitts law where appropriate to improve targets Change users (faster Ks) or hardware (better mouse or autokeypress, etc.)