Abstracts of the Psychonomic Society — Volume 14 — November ...

Saturday Morning Papers 182–189
11:40–11:55 (182)
The Role of Physical Similarity Versus Numerical Distance in
Numerical Judgment Tasks. DALE J. COHEN, University of North
Carolina, Wilmington—For decades, researchers have been studying
how people perceive numbers. Researchers have generally come to the
conclusion that, when people are presented a number (such as 2, 3, etc.),
they will automatically perceive the quantity symbolized by that number.
I present and test an alternative hypothesis.
Implicit Memory
Independence Ballroom, Saturday Morning, 10:20–11:55
Chaired by Eric-Jan Wagenmakers, University of Amsterdam
10:20–10:35 (183)
Are Researchers Egoistic When They Write an Abstract? A Bayesian
Hierarchical Test of the Name Letter Effect. ERIC-JAN WAGEN-
MAKERS, University of Amsterdam, OLIVER DYJAS, University of
Tübingen, & RAOUL GRASMAN & RUUD WETZELS, University of
Amsterdam—People prefer their initials to the other letters of the alphabet,
a phenomenon known as the name letter effect. This effect, researchers
have argued, makes Angela move to Los Angeles, makes Phil buy a Philips
TV, and influences Dennis to become a dentist. In order to establish such
associations between people’s initials and their behavior, researchers typically
carry out statistical analyses of large databases. Unfortunately, the
standard p-value procedures ignore the hierarchical structure of the data
and do not allow one to confirm the null hypothesis. Here, we propose a
Bayesian hierarchical hypothesis test that avoids these limitations. We illustrate
the method with examples that involve the use of author initials in
scientific abstracts. The conclusions from our Bayesian hypothesis test are
sometimes in radical opposition to those based on p-value procedures.
10:40–10:55 (184)
Sequential Effects Reflect Learning of Temporal Structure. MATT
JONES, TIM CURRAN, MICHAEL C. MOZER, & MATTHEW H.
WILDER, University of Colorado, Boulder—Binary choice tasks such
as two-alternative forced choice tasks show a remarkably consistent pattern
of sequential effects, whereby choices and response times depend
on the detailed pattern of prior stimuli going back at least five trials. We
show that existing data are well explained by a combination of two priming
mechanisms, reflecting incremental learning of the base rate and
of the repetition rate in the sequence. EEG and other types of evidence
indicate that the base rate mechanism resides in response preparation
(i.e., response priming) and that the repetition mechanism resides in
stimulus identification (i.e., learning the rate of stimulus repetitions vs.
alternations). However, results from a new experiment that manipulated
the repetition rate between subjects show that the learning mechanism
is more sophisticated than simple priming. The findings highlight a tension
between the two broad and well-established classes of trace-based
memory models and error-driven learning models. Attempts at reconciling
these approaches will be discussed.
11:00–11:15 (185)
Knowledge Representation in a New Perceptual–Motor Sequence
Learning Task. PAUL J. REBER, DANIEL J. SANCHEZ, & ERIC W.
GOBEL, Northwestern University—A new experimental paradigm is
described for studying perceptual–motor sequence learning that combines
the well-studied serial reaction time (SRT) task with a novel interface
derived from several popular video games. The new task naturally
incorporates timing information into motor sequence learning. In Experiment
1, timing is shown to be integrated with sequence knowledge
so that minimal transfer is observed when participants attempt to execute
a familiar sequence of actions with unfamiliar interitem timing demands.
The level of cognitive challenge can be easily manipulated to increase
the difficulty of the task. In Experiment 2, we show that making the task
challenging produces an unusually strong dissociation between performance
and awareness in healthy participants. Following learning a randomly
selected sequence, participants’ error rates can be used to identify
which sequence was learned even though their ability to recognize the
trained sequence is approximately at chance.
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11:20–11:35 (186)
Different Musical Features Predict Implicit and Explicit Memory
for Melodies. ANDREA R. HALPERN, Bucknell University, & DAN-
IEL MÜLLENSIEFEN & GERAINT WIGGINS, Goldsmiths College—
Evidence for the separation of implicit and explicit memory systems
has come from experimental dissociations as well as patient and activation
studies. A completely different kind of evidence may be gleaned
from discovery-driven approaches. We presented a set of melodies from
40 unfamiliar pop tunes, followed by 40 old and 40 new melodies for
explicit recognition, and for rating on pleasantness. A set of musical
features was selected to represent first-order characteristics relating to
pitches, durations, and so on, of the melodies, as well as second-order
information about the frequencies of melodic patterns relative to both
the 80-item test set, and the parent corpus of 14,000 tunes. Regression
models were quite successful in predicting which tunes elicited better
explicit and implicit performance. However, the actual features retained
in the models differed considerably. This dissociation between implicit
and explicit memory measures was thus based entirely on sensitivity to
different stimulus features.
11:40–11:55 (187)
Breaking Miller’s 7�2 Limit: Practice Effects in Absolute Identification
(“Dead Reckoning”). PENNIE DODDS, CHRIS DONKIN,
SCOTT D. BROWN, & ANDREW HEATHCOTE, University of Newcastle,
Australia (read by Scott D. Brown)—Miller’s (1956) review of a
series of absolute identification experiments suggested a fundamental
limit to human processing capacity. This limit has been confirmed by
50 years of subsequent research, and is thought to be highly resistant to
practice. Following work from Rouder and colleagues, we outline an extensive
series of experiments that show that people can learn to increase
their information capacity. We discuss effects of stimulus manipulations
(including modality and set size) as well as individual differences between
participants. We also provide a framework in which our results
(and Rouder et al.’s) can be reconciled with 50 years of prior research—
which appears incongruent.
Human Learning and Instruction I
Back Bay Ballroom C, Saturday Morning, 10:20–11:55
Chaired by John B. Black, Teachers College, Columbia University
10:20–10:35 (188)
Haptic and Immediate Visual Feedback Increases Learning of
Mental Models. INSOOK HAN, JOHN B. BLACK, IRINA PALEY,
& GREG HALLMAN, Teachers College, Columbia University (read
by John B. Black)—In two studies, students learned mental models of
simple systems such as gear and pulley configurations through interactive
visual simulations of the systems. These were direct manipulation
animations in which the students directly manipulated one variable and
got immediate feedback on the other variables. Providing haptic feedback
using a force-feedback joystick, so that the students could feel how
hard it was to move the gears or pulleys, increased learning over just
providing visual feedback. A narrative voice-over also provided better
learning than an expository voice-over. These results are consistent with
a perceptually grounded approach to mental models of systems.
10:40–10:55 (189)
Learning at Study Versus Learning at Test: Does Familiarity Matter?
KERRY A. CHALMERS & BEATRICE BORA, University of Newcastle,
Australia—Learning during study and test was examined in a
three-phase (i.e., study, Test 1, Test 2) recognition memory paradigm. In
Experiment 1, 32 undergraduate psychology students studied a list consisting
of familiar (high- and low-frequency) and unfamiliar (very lowfrequency)
words prior to completing two yes/no recognition memory
tests. Items from the study list served as targets for Test 1. Test List 1
served as the target list for Test 2. Significant interactions between familiarity
and testing were observed. High-frequency words were recognized
more accurately at Test 2 than at Test 1, whereas very low-frequency
words were recognized more accurately at Test 1 than at Test 2. In Experiment
2, using the same paradigm but different stimuli (words and