Multidimensional scaling methods for absolute identification data. (original) (raw)
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Revising the limits of learning in Absolute Identification.
review of a series of absolute identification (AI) experiments, as well as a multitude of subsequent absolute identification research, suggests a fundamental limit to human information processing capacity. This limit is thought to be highly resistant to practice, independent of stimulus modality, and has been universally accepted as a fundamental constraint on human information processing capacity. Generally it is expected that people improve their performance slightly in absolute identification tasks, but quickly reach an asymptote after which they fail to improve any more. Recently however, we have replicated an experiment that demonstrates significant improvement in AI performance with only moderate practice. We conclude that there are several factors that are essential to the ability to learn unidimensional AI stimuli. Motivation is essential for improvement in performance, as is an initial performance level that greatly exceeds what would be expected by chance -this also constrains the type of stimuli that can be learned. In addition, in contrast to Miller's conclusion that the asymptote in performance is independent of set size, we suggest that indeed set size does affect the asymptote in performance, namely that a larger set size (around n=30), allows a higher asymptote in performance.
Learning in a unidimensional absolute identification task
Psychonomic Bulletin & Review, 2004
We tested whether there is long-term learning in the absolute identification of line lengths. Line lengths are unidimensional stimuli, and there is a common belief that learning of these stimuli quickly reaches a low-level asymptote of about seven items and progresses no more. We show that this is not the case. Our participants served in a 1.5-h session each day for over a week. Although they did not achieve perfect performance, they continued to improve day by day throughout the week and eventually learned to distinguish between 12 and 20 line lengths. These results are in contrast to common characterizations of learning in absolute identification tasks with unidimensional stimuli. We suggest that this learning reflects improvement in short-term processing.
Absolute identification is a deceptively simple task that has been the focus of empirical investigation and theoretical speculation for more than half a century. Observers are shown a set of N stimuli varying on a single dimension (e.g., length or loudness) and each stimulus is given a label (e.g., 1, .., N ). They then attempt to identify stimuli presented one at at time by producing the associated label. Since seminal paper the puzzle of why people are severely limited in their capacity to accurately perform absolute identification has endured. Despite the apparent simplicity of absolute identification, many complicated and robust effects are observed in both response latency and accuracy, including capacity limitations, strong sequential effects and effects of the position of a stimulus within the set. Constructing a comprehensive theoretical account of these benchmark effects has proven difficult, and existing accounts all have shortcomings in one way or another. We review classical empirical findings, as well as some newer findings that challenge existing theories. We then discuss a variety of theories, with a focus on the most recent proposals, make some broad conclusions about general classes of models, and discuss the challenges ahead for each class.
Absolute identification is a deceptively simple task that has been the focus of empirical investigation and theoretical speculation for more than half a century. Observers are shown a set of N stimuli varying on a single dimension (e.g., length or loudness) and each stimulus is given a label (e.g., 1, .., N ). They then attempt to identify stimuli presented one at at time by producing the associated label. Since seminal paper the puzzle of why people are severely limited in their capacity to accurately perform absolute identification has endured. Despite the apparent simplicity of absolute identification, many complicated and robust effects are observed in both response latency and accuracy, including capacity limitations, strong sequential effects and effects of the position of a stimulus within the set. Constructing a comprehensive theoretical account of these benchmark effects has proven difficult, and existing accounts all have shortcomings in one way or another. We review classical empirical findings, as well as some newer findings that challenge existing theories. We then discuss a variety of theories, with a focus on the most recent proposals, make some broad conclusions about general classes of models, and discuss the challenges ahead for each class.
Absolute identification is surprisingly faster with more closely spaced stimuli
2006
Bow and set size effects on response times in absolute identification mirror the effects on accuracy: Central stimuli and stimuli in large sets are responded to more slowly and less accurately. In an analysis of the response time data from Experiment 1 of N. Stewart, G. D. , involving the absolute identification of tone frequency (pitch), we find that in contrast to the accuracy data, where widely spaced stimuli are responded to slightly more accurately than narrowly spaced stimuli, widely spaced stimuli receive slower responses than narrowly spaced stimuli. This result poses an additional challenge for models of absolute identification, as accuracy and response times are not jointly linked to some unified difficulty factor.
Dissociating Speed and Accuracy in Absolute Identiļ¬cation: The Effect of Unequal Stimulus Spacing
Identification accuracy for sets of perceptually discriminable stimuli ordered on a single dimension (e.g., line length) is remarkably low, indicating a fundamental limit on information processing capacity. This surprising limit has naturally led to a focus on measuring and modeling choice probability in absolute identification research. We show that choice response time (RT) results can enrich our understanding of absolute identification by investigating dissociation between RT and accuracy as a function of stimulus spacing. The dissociation is predicted by the SAMBA model of absolute identification (Brown, Marley, Dockin, & Heathcote, 2008), but cannot easily be accommodated by other theories. We show that SAMBA provides an accurate, parameter free, account of the dissociation that emerges from the architecture of the model and the physical attributes of the stimuli, rather than through numerical adjustment. This violation of the pervasive monotonic relationship between RT and accuracy has implications for model development, which are discussed.
An integrated, principled account of absolute identification.
Psychological Review, 2008
Recent theoretical developments in the field of absolute identification have stressed differences between relative and absolute processes, that is, whether stimulus magnitudes are judged relative to a shorter term context provided by recently presented stimuli or a longer term context provided by the entire set of stimuli. The authors developed a model (SAMBA: selective attention, mapping, and ballistic accumulation) that integrates shorter and longer term memory processes and accounts for both the choices made and the associated response time distributions, including sequential effects in each. The model's predictions arise as a consequence of its architecture and require estimation of only a few parameters with values that are consistent across numerous data sets. The authors show that SAMBA provides a quantitative account of benchmark choice phenomena in classical absolute identification experiments and in contemporary data involving both choice and response time.
Why is accurately labelling simple magnitudes so hard?
2015
Absolute identification is a deceptively simple task that has been the focus of empirical investigation and theoretical speculation for more than half a century. Observers are shown a set of N stimuli varying on a single dimension (e.g., length or loudness) and each stimulus is given a label (e.g., 1, .., N ). They then attempt to identify stimuli presented one at at time by producing the associated label. Since seminal paper the puzzle of why people are severely limited in their capacity to accurately perform absolute identification has endured. Despite the apparent simplicity of absolute identification, many complicated and robust effects are observed in both response latency and accuracy, including capacity limitations, strong sequential effects and effects of the position of a stimulus within the set. Constructing a comprehensive theoretical account of these benchmark effects has proven difficult, and existing accounts all have shortcomings in one way or another. We review classical empirical findings, as well as some newer findings that challenge existing theories. We then discuss a variety of theories, with a focus on the most recent proposals, make some broad conclusions about general classes of models, and discuss the challenges ahead for each class.
Increasing Capacity: Practice Effects in Absolute Identification
In most of the long history of the study of absolute identification-since Miller's (1956) seminal article-a severe limit on performance has been observed, and this limit has resisted improvement even by extensive practice. In a startling result, Rouder, Morey, Cowan, and Pfaltz found substantially improved performance with practice in the absolute identification of line lengths, albeit for only 3 participants and in a somewhat atypical paradigm. We investigated the limits of this effect and found that it also occurs in more typical paradigms, is not limited to a few virtuoso participants or due to relative judgment strategies, and generalizes to some (e.g., line inclination and tone frequency) but not other (e.g., tone loudness) dimensions. We also observed, apart from differences between dimensions, 2 unusual aspects of improvement with practice: (a) a positive correlation between initial performance and the effect of practice and (b) a large reduction in a characteristic trial-to-trial decision bias with practice.