Department of Industrial Man-agement Engineering

2. Psychology and HCI○ Hard science (ComSci) would drive out soft science (Psy)

“harden Psy” to improve scientific caliber○ Evaluation tool rather than design tool○ 3 possible roles in Psy1. Primary professionals like in mental health and counseling2. Working with primary professionals, the system engineers3. The primary professionals could apply psychology them-

selves

Hick-Hyman Law

Department of Industrial Man-agement Engineering

3. INFORMATION THEORY1. THE COMMUNICAION SYSTEMS

○ Hick-Hyman assessed the cognitive info capacity in choice reaction experiments. Fitts’ law for an empirical determina-tion of the info capacity of the human motor system

Hick-Hyman Law

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○ Channel capacity (C) – the amount of info transmitted per time through a channel

○ 1/b (bits/sec) = the rate of gain of information (Hick, 1952) and index of performance (IP) in Fitts (1948)

Hick-Hyman Law

Department of Industrial Man-agement Engineering

2. QUANTIFYING INFORMATION○ Information (bit) – reduction in uncertainty (Shannon & Weaver,

1949)○ Shannon-Weiner measure of information

or ○ Have : the entropy of a stimulus or a set of stimuli when the alterna-

tives are not equiprobable○ Hmax : the alternatives are equiprobable○ HT = H(x) – Hy(x)

where H(x): the expected information of the source Hy(x): the received information at the destination

Hick-Hyman Law

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4. THE HICK-HYMAN LAW1. Hick (1952) Original Experiments

Hick-Hyman Law

choice RT vs. stimulus info content Trained himself until attaining error-

less responses (over 2,400)

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○ Experiment II○ 3 phases – as fast as possible, then as accurately as possi-

ble, finally as fast as possible again

Hick-Hyman Law

training (accurate)

diamonds for fast RT

antilogarithm of the info gained

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2. Hyman (1952) Original Experiments

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2. Hyman (1953) Original Experiments○ The amount of info extracted is proportional to the

time taken to extract it, on the average (1952)○ Not postulate a linear relationship between RT & Ht

○ The first to articulate the linearity between RT and HT

○ Altered the probabilities of the stimuli to assess RT as a function of HT

○ RT was linear as a function of bits of the alternatives with unequal probabilities

○ RT = a + b HT

○ 1/b: the rate of gain of information (information capacity)

Hick-Hyman Law

Department of Industrial Man-agement Engineering

3. Theoretical Developments○ Longstreth et al. (1985) – the law is false

○ RT = a + b (1 – N-1)○ Welford (1987) against Longstreth

○ Negative intercept○ Decreasing RT variability as function of the number of alterna-

tives○ Effective for a sequential and hierarchical process○ Christie and Luce (1956), Laming (1968)

○ Parallel exhausted process model instead of serial process

Hick-Hyman Law

Department of Industrial Man-agement Engineering

4. Research and ApplicationsSpeed-Accuracy TradeoffStimulus-Response Compatibility (SRC)○ Compatible S-R pairs facilitate the responding of a stimulus,

thus yielding a higher rate of information transferPsychometrics○ investigate RT-IQ relationshipHCI Applications

Hick-Hyman Law

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5. FITTS’ LAW○ a linear relationship between task difficulty (ID) and RT

○ Adapting Shannon’s (1948) Theorem 17 -- human motor system as a communication channel, movement amplitude as the signal, target width as the noise

1. Fitts (1954) Original Experiemtns○ the reciprocal tapping task○ Experiment I – metal-tipped stylus (1 oz vs. 1 lb); W from 0.25” to

2”; D from 2 to 16 ”; accuracy was encouraged

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Fitts’ Law

○ IP (index of performance or throughput) = ID/MT the rate of gain of info (Hick, 1952), the capacity of the human motor system

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○ channel capacity (Shannon’s Theorem 17)

○ B is the bandwidth, S is the signal power and N is the noise power

2. Theoretical Development○ Welford (1960) ○ MacKenzie (1992) ○ Meyer et al. (1988) ○ deterministic iterative-correction model (Crossman and Goodeve,

1983), stochastic optimized-submovement model (Meyer and col-leagues, 1990)

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○ Meyer et al. (1998) where n is number of submovements

3. Research and Applications○ kinematics and neurocognitive focusSpeed-Accuracy TradeoffPsychometrics○ No correlation between IQ and MTHCI ApplicationsPointing.Angle of Approach.○ the original Fitts’ paradigm – 1D task

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○ Accot and Zhai (2003) – classical paradigm as AP (pointing with amplitude constraints); paradigm with height constraints as DP (pointing with direction constraints)

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Semantic Pointing.○ both decreasing A and increasing WText Entry on Soft Keyboards.○ text entry on GUINavigation.

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6. INTEGRATION OF THE LAWS○ Combine the Hick-Hyman Law and Fitts’ Law

○ Beggs et al. (1972)○ Fitts’ Law did not hold in the fusion

○ Hoffman and Lim (1997)○ Home-to-target paradigm with both sequential and con-

current tasks○ The sum of the decision and movement time (sequential)○ Substantial interference (concurrent)

○ Soukoreff and MacKenzie (1995)○ Unable to fit the data to the model

Hick-Hyman Law

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7. THE HICK-HYMAN LAW AND HCI○ Common characteristics in both Laws

a. Same analogies based on Shannon and Weaver’s (1949) ITb. Same temporal dependent measures and accuracy to address

performance rates & limits of a human systemc. Substantial support in research

○ Possible reasons for the lack of momentum in HCI (Laming, 1966)1. The law’s analogy to the classic IT cannot be maintained2. Victim for the eviction of the soft sciences by hard sciences

I. Fitts’ Law has also comparable quantitative componentsII. HCI has shifted its focus to include some soft sciences

such as sociology

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1. Difficulty in Application○ No need to engage in the complexity of the information theoretic

measures

2. Complexity of Stimuli○ Multidimensional stimuli for the highly complex interfaces

needed with simple unidimensional stimuli to reduce confound-ing

3. Levels and Types of Performance○ Fitts’ for somewhat monotonous tasks

Hick-Hyman Law