Dimensions of the perception of art: verbal scales and similarity judgements

O'Hare, David; Gordon, Ian

doi:10.1111/j.1467-9450.1977.tb00257.x

Cited by 23 publications

(15 citation statements)

References 16 publications

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“…Nevertheless, the role of both non-stylistic details and possible alternative dimensions in facilitating style detection should be noted. The presence of non-stylistic distinguishing details would serve to attenuate the relationship between sensitivity to salient cues and concept learning performance, whilst the possibility that sensitivity to other dimensions or attributes could contribute to style detection is made unlikely by the short exposure durations used and the previous findings (O 'Hare, 1976;O'Hare & Gordon, 1977) that the two dimensions of 'verisimilitude' and 'clarity' account for most of the variance in subjects judgements of similarity between painting styles.…”

Section: Dimension Saliencementioning

confidence: 90%

“…Twenty of these subjects were later recruited to rate each picture on a set of nine semantic differential scales. Six of these had previously been shown to correlate significantly with scaling dimensions (O' Hare, 1976;O'Hare & Gordon, 1977), and the remaining three were constructed on the basis of a preliminary inspection of the scaling solution. Subjects were provided with a booklet containing one page for each scale.…”

Section: Unidimensional Scalesmentioning

confidence: 99%

“…In addition these scales ('clear vs. indefinite'; 'broad vague masses vs. sharp, clear contours' and the 'outline vs. colour areas' scale) are highly intercorrelated, with rhos of 0.96, 0.86 and 0.84, suggesting a coherent factor. The interpretation of this dimension as one contrasting paintings with clear, sharp line ('linear ') from those with merging areas, broad O'Hare & Gordon, 1977) with different samples of subjects and paintings.…”

Section: Property-fittingmentioning

confidence: 99%

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Multidimensional scaling representations and individual differences in concept learning of artistic style

O’Hare

1979

British J of Psychology

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Several previous studies in which a concept learning task has been used to investigate the acquisition of the concept of artistic style, have noted a wide range of individual differences in performance. Tighe (1968) has proposed that these may reflect differential sensitivity to the relevant dimensions of stylistic variation. The INDSCAL technique of multidimensional scaling, which has previously been used to determine the predominant dimensions of variation in responses to visual art was used here to determine the salience of such dimensions for different individuals. These scores were then used to predict individual differences in performance on a concept formation task. The results offer support for a differential cue salience explanation for individual differences in learning about artistic style. Implications for aesthetic education are discussed.Recent research in experimental aesthetics can be characterized both by an increasing methodological sophistication, and by a growing concern with one or two topics of central importance rather than a scattered interest in a variety of disparate areas. One such topic is that of sensitivity to artistic style. The ability to recognize similarities and differences between the works of different painters has been investigated from a number of different viewpoints. Two of these, the developmental approach (e.g. Gardner, 1972) and the multidimensional scaling approach (e.g. O'Hare, 1976) have been outlined separately (O'Hare, 1978). The present article will be chiefly concerned with a third approach involving the concept learning of artistic style. the criteria that define the concept are hard to identify. Since two works of art may vary on an indefinite number of dimensions, an artist's style can only be defined with reference to positive instances. In Walk's experiment, subjects were presented with positive instances of an artistic style, and the ability of the subject to extend this to new instances was measured. Using this simple transfer technique, Walk was able to demonstrate concept learning of the styles of six Impressionist painters.Tighe (1968) modified the basic procedure to permit measures of the subject's concept formation after the presentation of each instance. Slides of samples of five Cubist painters' works were divided into sets so that each set contained one painting by each artist. Each set was then presented three times. On the first occasion the subject was required to guess the name of each artist. The second presentation, or training trial, consisted of the pairing of each painting with the appropriate artist's name. The final trial was the same as the first, except that after the subject had made a choice, the correct artist's name was provided.Once again, clear evidence of concept learning was obtained. The percentage of correct classifications improved from near-chance (17 per cent) on the first test trial to 60 per cent correct on the final test trial. These figures are all the more impressive in view of the fact that the slides of these closel...

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Section: Dimension Saliencementioning

confidence: 90%

Section: Unidimensional Scalesmentioning

confidence: 99%

Section: Property-fittingmentioning

confidence: 99%

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Multidimensional scaling representations and individual differences in concept learning of artistic style

O’Hare

1979

British J of Psychology

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“…But style also affects aesthetic experiences in a broader sense. Non‐experts like representative artworks more than abstract art (O'Hare & Gordon, ), patterns of visual exploration in terms of number and lengths of fixation vary with different art styles (Latif, Gehmacher, Castelhano, & Munhall, ), and experts use art styles to classify artworks according to similarity, while non‐experts do not (Augustin & Leder, ). Leder et al .…”

Section: Contributions Of Leder Et Al's () Model Of Aesthetic Experimentioning

confidence: 99%

Ten years of a model of aesthetic appreciation and aesthetic judgments : The aesthetic episode – Developments and challenges in empirical aesthetics

Leder

Nadal

2014

British J of Psychology

435

390

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About a decade ago, psychology of the arts started to gain momentum owing to a number of drives: technological progress improved the conditions under which art could be studied in the laboratory, neuroscience discovered the arts as an area of interest, and new theories offered a more comprehensive look at aesthetic experiences. Ten years ago, Leder, Belke, Oeberst, and Augustin (2004) proposed a descriptive information-processing model of the components that integrate an aesthetic episode. This theory offered explanations for modern art's large number of individualized styles, innovativeness, and for the diverse aesthetic experiences it can stimulate. In addition, it described how information is processed over the time course of an aesthetic episode, within and over perceptual, cognitive and emotional components. Here, we review the current state of the model, and its relation to the major topics in empirical aesthetics today, including the nature of aesthetic emotions, the role of context, and the neural and evolutionary foundations of art and aesthetics.

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“…The INDSCAL procedure has found frequent application in experimental aesthetics (e.g. Berlyne & Ogilvie, 1974; Hare, 1975;OHare & Gordon, 1977). This is because the INDSCAL takes account of individual differences in the perception of stimuli.…”

mentioning

confidence: 99%

Dimensions in the perception of architecture: identification and interpretation of dimensions of similarity

Oostendorp¹,

Berlyne²

1988

Environmental Aesthetics

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Dimensions in the perception of architecture. I. Identification and interpretation of dimensions of similarity. Scand. J . Psychol. 19, 73-82, 1978.Painvise similarity4issimilarity ratings of 20 slides of buildings representing major architectural styles were subjected to an INDSCAL analysis. Four major similarity dimensions were identified. Subsequently, the stimuli were rated on two batteries of scales: (1) collative and affective ratings, and (2) stylistic and technical ratings. Canonical correlations and redundancy indices revealed close relations between the multidimensional stimulus locations and the scale and factor spaces. The findings of the three experiments suggest that the four principal dimensions in the perception of architecture appear to be (1) Clarity, (2) Hedonic TonelArousal, (3) Uncertainty, and (4) Familiarity.

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Dimensions of the perception of art: verbal scales and similarity judgements

Cited by 23 publications

References 16 publications

Multidimensional scaling representations and individual differences in concept learning of artistic style

Multidimensional scaling representations and individual differences in concept learning of artistic style

Ten years of a model of aesthetic appreciation and aesthetic judgments : The aesthetic episode – Developments and challenges in empirical aesthetics

Dimensions in the perception of architecture: identification and interpretation of dimensions of similarity

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