Acta Psychologica 53 (1983) 27-35

North-Holland Publishing Company

27

SYMBOL COMPLEXITY AND SYMBOL IDENTIFICATION WITH ROTATED SYMBOLS *

Malcolm G. ELEY Unioersiy of Tarmania, Australia

Accepted October 1982

Previous studies of the identification of rotated symbols have been restricted to either al-

phanumeric characters or symbols designed to be similar in complexity and type to alphanumerics.

These researches have found identification response times to be independent of the magnitude of a

symbol’s angular displacement from a standard upright position, such findings being typically

interpreted as supporting a feature extraction model of identification. In the present experiment

complex Japanese characters were used to assess whether such a feature extraction interpretation

could be generalized to identifying complex rotated symbols. Identification response times were

also found to be constant across all non-standard orientations of the characters, supporting a

feature extraction interpretation, but quicker times for standard cases suggested that some

qualifications might be necessary.

It would seem that whether an individual is required to verify versus identify a rotated symbol will determine the use of different sets of mental processes. When a person is required to judge whether a symbol rotated away from its usual upright orientation is either veridical or mirror reflected, it is typically found that response times are longer the greater the symbol’s angular deviation from the upright (Cooper and Shepard 1973; Petrusic et al. 1978). But when a person is required to simply identify, or .name, a rotated symbol, the typical finding is that response times are constant across deviations from the upright (Corbal- lis et al. 1978). The interpretations that have been given for these findings are that verification proceeds by the mental rotation of the test

* The research reported here was supported by a grant from the Recurrent Research Funds of the University of Tasmania. The author wishes to gratefully acknowledge Deidre Smythe for her assistance in data collection.

Author’s address: M.G. Eley, Dept. of Educational Studies, University of Tasmania, GPO Box

252C. Hobart, Tasmania 7001, Australia.

0001-69 1 S/83/0000-0000/$03.00 0 1983 North-Holland

28 M. G. Eley / Symbol complexity

stimulus, or its representation, until it can be matched against some criterion; but that identification proceeds by the extraction from the test stimulus of featural information which has been encoded in a form invariant to stimulus orientation.

These verification and identification processes were initially studied using small sets of alphanumeric symbols. Both the Corballis et al. ( 1978) and the Cooper and Shepard (1973) studies used three Roman capitals and three Arabic digits as stimuli in their tasks. It could be argued, however, that the use of such small numbers of highly over- learned stimuli might have lessened the probability of Corballis et al. finding anything but feature extraction processes in symbol identifi- cation. A feature extraction interpretation of symbol identification requires that the identifying features be learned sufficiently well that their detection is independent of the symbol’s orientation. Such suf- ficiency of learning might be more likely the more familiar the subject is with the symbols being identified. Thus, for relatively unfamiliar symbols it might be that identification response times will not be independent of symbol orientation, suggesting that either mental rota- tion processes or some other orientation sensitive modification of feature extraction could be involved. Further, if the to-be-identified symbol is one of a large number of possibles, the attendant necessity to maintain a large set of features encoded invariant to orientation might eventually constitute a cumbersome processing load. That is, with large rather than small sets of symbols, subjects could opt for an identifica- tion strategy that employed less demanding forms of symbol encoding in which features were not encoded invariant to orientation. Thus for large symbol ‘sets also, identification response times might not be independent of symbol orientation.

The possibilities listed above were tested in a recent study (Eley 1982) which had subjects learn CVC labels for 20 novel letter-like symbols to either high or low familiarity overlearning criteria. Follow- ing this label-symbol learning, subjects then identified the symbols. presented singly and at varied orientations, under conditions where a presented symbol was one of either five or 20 possibilities. Response times were found to be constant across deviations from the upright orientation, irrespective of either familiarity or set size variations. These findings would seem to support the generalization of the Corballis et al. (1978) feature extraction interpretation to varying numbers of symbols of varying familiarity.

M.G. Hey / Symbol complexity 29

However, one further possibility would seem to be in need of testing, namely symbol complexity. As noted above, a requirement that critical features be encoded invariant to symbol orientation is likely to be relatively demanding. If it is assumed that complex symbols will entail greater feature encoding than will simple, then it is reasonable to expect that the identification of complex symbols via feature extraction processes could prove burdensome. The subject might thus be prompted to opt for a less demanding strategy, one which perhaps did not require that symbols be encoded invariant to orientation. The symbols used in the above (Eley 1982) study were designed to be similar in complexity to standard Roman characters. Thus even though the. symbols varied in complexity, they just might not have been complex enough to prompt the abandonment of a feature extraction strategy. The present study then tested this further possibility that with relatively complex symbols identification response times might no longer be independent of symbol orientation.

The experiment

Method

Subjects Twelve staff and student volunteers, six males and six females, served as Ss in the

experiment. None of them had any prior knowledge of oriental languages.

Stimulus materials Ten Japanese characters, each comprising 13 strokes, were selected (A guide to . . .

1959). Each character was randomly paired with a CVC trigram selected from Archer’s (1960) scaling (see fig. 1). All 10 trigrams had a meaningfulness rating in the range 60 to 70 on Archer’s scale. Further, the trigrams were selected such that (a) each had a different initial consonant, (b) each of the vowels A, E, I, 0, U were represented twice, (c) all were pronounceable, (d) none used repeated or silent consonants, and (e) none were words or homophones of words.

Each character was photographed onto 1 IO-size transparencies at orientations of 0” (standard upright), 60” (clockwise), 120”, 180”, 240”, and 300”. The characters were shown in black line centered on a white circular background surrounded by brown. Each character had a small dot which designated its top. The trigram labels were also photographed onto transparencies having the same circular layout format as for the characters.

The 10 character-label pairs, with standard upright orientations, were ordered into three random sequences for use as training blocks. Also for use in training, the 10

30 M. G. Hey / Symbol complexity

Fig. 1. Characters and their CVC labels as used in the experiment.

standard characters and their labels were laid out in a random sequence on a 20 by 24 cm card. The 10 characters at each of the six orientations were randomly ordered into four 3q-trial experimental blocks such that each character occurred three times per block, and each orientation occurred five times per block.

Procedure All Ss were initially trained to label the 10 characters. An S first studied the card

showing each character with its label for two minutes, following which one of the IO-trial training blocks was presented. In each trial a single character remained in view while the S attempted to recall its label. The correct label was provided each time as feedback. An S continued through these study plus training block cycles until a criterion of two consecutive all-correct training blocks was achieved.

Following this training, each S was administered the four 30-trial experimental

blocks. In each trial, S was presented with a single character at one of the six orientations and was required to say its label. With each trial, a half second warning tone occurred half a second before the character’s onset, and the character remained in view until after the S’s response. Responses were timed from the onset of the character. Ss were run individually, and were instructed to respond as quickly as they could consistent with accuracy. The order of the experimental blocks was counterbalanced across Ss.

Results and discussion

For each S, the response times for correct responses to a single character orientation within one block (a maximum of 5 times) were used to produce an initial median and

M. G. Eley / Symbol complexity 31

1.5

/

.

.

1 \ l ---‘1. BLOCK 1

.

b 6’0 150 180 I

240 360 DEG -I

Fig. 2. Mean identification response times (in seconds) for each character orientation within each block.

mean. If the median-mean difference exceeded 10% of the distribution’s range then the most skewed extreme response time was discarded and the mean and median re-calcu- lated. This procedure continued iteratively until either the median-mean difference no longer exceeded 10% of the range, or a maximum of 40% of the initial set of response times had been discarded. The resulting mean was then taken as the response time measure for that orientation within that block for that S. Calculating response time measures in this fashion was intended to control for any overly long response times due to wavering attention and other distractions. It resulted in the discarding of 16.4% of the response times for correct responses.

The 24 response time measures thus derived for each S were entered into a two factor (character orientation versus blocks) repeated measures analysis of variance. Errors were not analyzed due to their very low frequencies; 0.6% overall. The mean response times by cells are shown in fig. 2.

32 M.G. Eley / Symbol complexity

The main effect for character orientation proved significant (F(5.55) = 2.66, p < 0.05), as did also that for blocks (F(3,33) = 28.39, p < 0.001). The interaction was not significant (F < 1) indicating that the pattern across orientation could be interpreted as being equivalent for each block. From fig. 2 it is clear that the blocks main effect was the predictable result of practice across blocks. Specifically, it was due to the Block 1 times having been very much slower than those for the other blocks. This was verified with Newman-Keuls tests which showed the Block 1 mean response time to be significantly (at f < 0.05) slower than that for each of the other blocks, and with a significant contrast which compared the Block 1 mean to the average of the other blocks (F( 1,33) = 72.40, p < 0.001).

Newman-Keuls tests were also used to compare response time means in the orientation main effect. Only one significant comparison, that showing the 0” mean to be faster than that for 120”, was found (at p < 0.05). From fig. 2 however, it would seem that this pattern might have been clearly the case only for Block 1. Since the a posteriori evaluation of the blocks main effect showed the Block 1 times to be separable from those of the other blocks, it seemed reasonable to conduct a further analysis based only on data derived from Blocks 2, 3, and 4. Response time measures for each of the six orientations were generated for each S using an iterative procedure similar to that described previously, but based on correct responses pooled across Blocks 2 to 4 and using a discarding criterion of 5% and a maximum discard proportion of 25%. This procedure resulted in the discarding of 11.5% of the response times for correct responses. The resulting response time measures for each S were entered into a single factor (character orientation) repeated measures analysis of variance.

In this further analysis, the single effect of orientation proved significant (f( 1.55) = 3.59, p -C 0.01). Individual comparisons between orientation means (see table 1) were again conducted using a Newman-Keuls procedure, and the mean response time for 0” was found to be significantly less than that for each of the other orientations (at p -e 0.05). None of the other pairwise comparisons proved significant. These results would appear to support a tentative interpretation that in general the identification of 0” orientations occurs faster than that for each of the other orientations. but that the times to identify non-upright orientations are relatively equivalent. Further corrobora- tion was however sought. The response time measures from Blocks 2 to 4 were reanalyzed with the 0” orientation omitted. This time the orientation effect proved singularly non-significant (F < l), indicating that the means for the non-upright orientations should be treated as equivalent. As one final check, the means for these non-upright orientations were tested for quadratic trend since symbol verification studies had shown that response times increased with angular displacement from a standard upright. This trend also proved to be singularly non-significant (F < 1). The previously offered interpretation would thus now seem reasonable. That is, that in the identification of the complex characters employed in the present experiment, response times do not vary with a character’s dis-orientation away from a standard upright position excepting that those in that standard position are identified faster.

Such a finding would seem to give qualified support to a feature extraction interpretation. If symbols are identified by a process of extracting critical feature information from the stimulus display, which information has been encoded in a form invariant to the symbol’s orientation, then identification should be a simple function of

M. G. Eley / Symbol complexity 33

Table 1 Mean identification response times in seconds for data pooled over blocks 2 to 4.

Character orientation O0 60’

1.592 1.155

1200 180’ 240” 3000

1.799 1.819 1.756 1.749

the presence or absence of a feature and not of its degree of dis-orientation. That the response times for non-upright characters in the present experiment were equivalent would certainly appear to fit such an interpretation. Apart from the single effect of not being in a standard upright position, the response times for these cases gave no evidence of any sensitivity to symbol orientation. The necessary qualification of course is that the 0” finding does not neatly fit with this same interpretation. That is, while identification response times do not appear sensitive to the magnitude of a symbol’s dis-orientation, they are in quantum fashion sensitive to the presence of dis-orientation. If the simple presence or absence of a feature was the sole determinant of identification such should not happen.

Perhaps the most obvious potential explanation for the 0” finding would be that it represents a relative familiarity effect. Since the training trials employed only standard orientation characters it could be argued that Ss would therefore be relatively more familiar with these than with the dis-oriented versions. However, while such an effect would be difficult to discount entirely, familiarity can be discounted as the predomi- nant explanation. As an S progresses through the experimental blocks, and as that S’s exposure to non-upright symbols increases, the relative familiarity of the 0’ cases should lessen. That is by the third of fourth block it could reasonably be expected that the 0” response times might be equivalent to those for the other orientations. From fig. 2 it would appear that such was not the case, that the 0” times remained faster throughout.

An alternative potential explanation for the 0” finding derives from the work of Hinton and Parsons (1981). These writers argue that spatial entities are able to be represented by relationships between frames of reference. The shape of the entity (be it an object, an array, or even a symbol) can be represented in terms of the relationship of the features of components to a frame of reference which is embedded in or intrinsic to that entity. The general orientation or positioning of the entity can in turn be represented by the relationship of that intrinsic frame of reference to a further contextual frame of reference. This representational process could of course continue in hierarchical fashion, but two levels are sufficient for the purposes of interpreting the present experiment. Hinton and Parsons argue that in order to make judgments about the shape of an entity, the S must first impose an appropriately oriented intrinsic frame of reference upon the entity, and then check its features in relation to that frame of reference.

With the present tasks such a model would suggest that identification proceeds by the S first establishing the orientation of the symbol (i.e. works out where the top is)

34 M.G. Eley / Symbol complexit)

and thus imposing an intrinsic frame of reference, and then determining the presence or absence of features in relation to this intrinsic frame of reference. If it is assumed first. that neither the time required to impose an intrinsic frame of reference nor the time taken to assess features in relation to this frame need be a function of orientation, and second, that Ss are always preliminarily set to impose a standard upright intrinsic frame of reference, then this model would predict the present findings. For a 0” orientation, the assessment of features could begin without delay. For other orienta- tions, such assessment processes would need to await the imposition of an intrinsic frame of reference.

This frames of reference interpretation can also be discussed in relation to the findings from previous symbol identification studies. No 0’ orientation effect was found for small sets of either alphanumeric symbols (Corballis et al. 1978) or relatively simple letter-like symbols (Eley 1982) but such an effect was found with larger sets of letter-like symbols (Eley 1982). Could it be that with small sets of simple symbols the task of determining a symbol’s orientation is relatively easy and that there is no great processing advantage to be gained by preliminarily setting on a 0” intrinsic frame of reference? When a greater number of possible symbols are involved, or when the symbols are more complex, and the task of determining a single presented symbol’s orientation is thus perhaps more difficult, might there then be an overall advantage in preliminarily setting to impose a 0” orientation?

Conclusions

The findings of the present experiment suggest that the feature extrac- tion processes reported by Corballis et al. (1978) and Eley ( 1982) in the identification of alphanumeric and novel letter-like symbols apply alsc to symbols more complex than those of the standard Roman alphabet However, the present findings also suggest that a simple feature extrac- tion interpretation may need to be qualified to include the possibility that before feature extraction processes begin an intrinsic frame of reference must be imposed on the to-be-identified symbol.

Perhaps a generalization could be tentatively suggested that symbol identification, irrespective of the characteristics of the symbols, is essentially a process of extracting critical feature information. Such a tentative generalization is supported by the findings of two recent studies using symbol identification tasks other than with rotated sym- bols. Haber and Cole (1980) had subjects judge pairs of letters, one upper case and one lower, as to whether they were of the same identity. Response times for “same” judgments were faster than for “different”, but interestingly the “different” response times were slower the greater the degree of visual similarity between the paired letters. This latter

M.G. Eley / Symbol complexity 35

finding was interpreted as showing that subjects “. . . go through a visual information extraction when identifying a letter” (Haber and Cole 1980: 191).

In similar vein Kaye et al. (1981) had subjects ranging from kinder- garten to undergraduate search for the presence of a target letter within fields of other symbols. Response times were found to be longer the greater the visual similarity between the target and distractor letters, interpreted as evidencing feature extraction processes, but of greater interest was the finding that this same pattern occurred for all age levels of subjects. It would seem that while overall processing efficiency might improve with age, featural distinctions are important even at ages where very little formal practice in letter identification is likely to have occurred. Together with these two studies then,. the findings from rotated symbol identification studies (Corballis et al. 1978; Eley 1982; and the present study) suggest that the above tentative generalization is at least tenable.

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