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Learning Where to Look: An ACT-R/PM Model

Learning Where to Look: An ACT-R/PM Model. Brian D. Ehret ARCH Laboratory Human Factors and Applied Cognition George Mason University ACT-R Workshop - August 7, 1999. Overview. HCI research has demonstrated that users learn the locations of interface objects

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Learning Where to Look: An ACT-R/PM Model

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  1. Learning Where to Look: An ACT-R/PM Model Brian D. Ehret ARCH Laboratory Human Factors and Applied Cognition George Mason University ACT-R Workshop - August 7, 1999

  2. Overview • HCI research has demonstrated that users learn the locations of interface objects • However, not much known about mechanisms underlying location learning • Systematically vary conditions under which location learning may occur in order to • Infer characteristics of location learning mechanisms • Embed these characteristics into a computational cognitive model using ACT-R/PM (Byrne & Anderson, 1998)

  3. Color-Match Condition

  4. Meaningful Text Condition

  5. Arbitrary Icon Condition

  6. Performance Time Results Trial Time (sec) Blocks

  7. Overview of Model • 35 rules for all four conditions • 20% of rules common to all four conditions • Overlap between conditions ranges from • 23% between Color-Match and Arbitrary to • 86% between Arbitrary and No-Label • Interacts directly with software via ACT-R/PM • Relies on search vs. retrieve paradigm • Akin to compute vs. retrieve (arithmetic facts) • Preference for less costly strategy

  8. Overview of Model (cont’d) • Declarative structures • Buttons • Locations • Labels • Colors • Learning Parameters • Base level learning (d=0.3) • Merging and retrieval • Associative strength learning (:al=1) • Source spread

  9. Search Cost and Strategies • Search Cost - number of buttons evaluated per trial

  10. Search Cost - Buttons Evaluated Number of Buttons Evaluated Blocks

  11. Search Phase Summary • Pre-attentive Search • Search for location of button with correct color • ACT-R/PM find-location command • Controlled Search • Attempt to retrieve a past use of the correct button and its associated location chunk • If retrievals fail, attend to random button • Retrieval attempted first (search vs. retrieve)

  12. Evaluation Cost and Strategies • Evaluation Cost - time required to determine if currently attended button is currently needed

  13. Evaluation Cost - Time Per Button Average Time Per Button (sec) Blocks

  14. Evaluation Phase Summary • Color-Match and Meaningful always label match • Arbitrary label matches only if label retrieved in search phase • No-Label and Arbitrary (if label not retrieved) try location assessment • Attempt to retrieve a past use of the currently attended button and its associated location chunk • If retrievals fail, then wait for ToolTip • Retrieval attempted first (wait vs. retrieve)

  15. Implications • Locations encoded as a by-product of attention • Default ACT-R/PM behavior • Location knowledge, once encoded into memory, is like any other knowledge • Subject to the same learning mechanisms • Task performance characterized as rational • Attempt less costly strategies first • Pre-attentive < retrieve location < search [search phase] • Label-match < location assessment < tip [evaluation phase] • Results in differential location learning

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