Acta Psychologica 52 (1982) 197-211 North-Holland Publishing Company

197

AN ANALYSIS OF PERFORMANCE BY PRESCHOOL CHILDREN ON THE KRISP AND ON A LENGTH DISCRIMINATION TASK

Bill JONES *

Carleton Unioerslty, Canada

Jim DUFFY

York Univemty, Canada

Accepted June 1982

The speed and accuracy of judgements made by pre-school children on the Kansas Reflection-Im-

pulsivity Scale for Pre-schoolers (KRISP - Wright 1971, 1973) and on a two-choice length

discrimination task were investigated. If subjects were. relatively accurate on the KRISP then

correct responses tended to be faster than errors while if subjects were relatively inaccurate errors

were the faster. It is inferred that accurate subjects respond asymptotically in terms of a

speed-accuracy tradeoff while inaccurate subjects set a less demanding criterion. Accurate subjects

showed a tendency to increase inspection time as a function of item difficulty. This relation did not

hold for inaccurate subjects.

However, groups classified by means of the KRISP did not differ in either the speed of correct

responses or accuracy of line length discriminations. For all groups judgement times were

significantly related to stimulus differences and to stimulus ratios. There was no evidence that

so-called impulsive children engage in less efficient and less detailed processing than other children,

It is argued, contrary to the view of Kagan and his co-workers (e.g. Kakan 1966), that speed

and accuracy of responding may not reflect a stable trait dimension. Rather children appear to be

able to change their strategies according to the particular demands, implicit or explicit, of the task.

Introduction

In any choice response experiment, the experimenter’s instructions will, explicitly or implicitly, set requirements for speed and accuracy and it

* Mailing address: Bill Jones, Dept. of Psychology, Carleton University, Ottawa, Ont. KIS 5B6, Canada

000 l-69 1 S/82/0000-0000/$02.75 0 1982 North-Holland

is well-known that adults may demonstrate considerable flexibility in varying the relation between latency or responding and some measure of accuracy. This being so, it is often difficult to assess the efficiency of subjects under different experimental manipulations (e.g. Pachella 1974; Swensson 1973; Wood and Jennings 1976).

The work of Kagan and his associates with children (e.g. Kagan 1966; Kagan and Kogan 1970) has, however, rested on the assumption that speed and accuracy parameters are relatively inflexible and so may be used to define stable “cognitive styles”. Kagan has contrasted two styles. relatively slow but accurate responding which he calls “reflec- tive”, and relatively fast and inaccurate performance which he calls “impulsive”. Typically the two styles have been operationalized as performance on the Matching Familiar Figures (MFF) test for children 6 years and older, or on the Kansas ReflectionInzpulsicit.\* Scale for Pre-schoolers (KRISP: Wright 1973). Both are matching-to-sample tests in which the child must choose the uniquely correct match for a more or less complex line-drawing from a number of alternatives (six in the case of the MFF. and from four to six in the case of the KRISP). The child is allowed to continue to choose until he or she finally matches the sample. Kagan has used the total number of errors over all items on the test and the mean latency to the first choice to define an individual’s relative performance. Error and latency data are then partitioned at the medians into four quadrants. Impulsive children respond more quickly than the median mean latency for the sample and make more errors than the median number of errors. Conversely those children who make fewer errors and respond more slowly with respect to the medians are defined as reflective.

Kagan has concentrated on the overall negative correlation across subjects between error rates and mean response times (typically around - 0.60 for both the KRISP and MFF). However. as Salkind and Wright (1977) have pointed out, one cannot simply ignore those individuals, typically around two-thirds of all subjects (Messer 1976). who are either fast and accurate or slow and inaccurate. Salkind and Wright have argued that performance on the KRISP and MFF can be represented along two orthogonal axes of “Impulsivity” and “Efficiency” where efficiency is defined by the sum of standardized variates for latency and error.

Undoubtedly this approach has some intuitive appeal. Subjects who are fast and accurate will be counted as the most efficient and those

B. Jones, J. Daffy / An analysis of performance 199

who are slow and inaccurate as the least efficient. However, the definition rests upon the rather dubious assumption that if we plot accuracy as a function of latency then the resulting speed-accuracy tradeoff function (SATF) will be linear. In fact, SATFs obtained from adults tend to be curvilinear and negatively accelerated (e.g. Pachella 1974) with the consequence that when the subject is responding at close to asymptotic accuracy a large increase in latency may produce only a small increase in accuracy. On the lower limb of the curve an equivalent increase in latency may be associated with a much greater increase in accuracy. In other words, the same expenditure of time purchases more accuracy for subjects who are relatively inaccurate than for those who are relatively accurate. In these circumstances simply summing stan- dardized variates for latency and error may lead to misleading conclu- sions about differences in efficiency between subject groups.

In practice we know very little of the speed-accuracy strategies which children are likely to adopt. Kagan argues that subjects should trade speed for accuracy since he assumes that correct responses are more likely to occur if subjects ponder their choices. Yet it is empirically demonstrable that latencies for errors may be in some cases longer than latencies for correct responses (see e.g. Vickers 1979). Hence one need not assume that increasing the time taken to make a perceptual decision necessarily increases the probability of making a correct decision.

In practice examination of the relation between correct and error response times may allow inferences about a subject’s speed-accuracy tradeoff. Swensson (1973), for example, has shown that correct re- sponses tend to be faster than errors when subjects favour accuracy over speed while errors tend to be faster when subjects trade accuracy for speed. To some extent the difficulty of discrimination determines the tradeoff since correct responses seem to be the shorter when a discrimination is easy and the longer when a discrimination is more difficult (Swensson 1973; Vickers 1979). In other words, we may be able to draw conclusions about the child’s speed-accuracy strategy from the relation between latencies for correct and incorrect responses.

The purpose of the present work with pre-school children was two-fold. We wished to examined in detail the performance of children on the KRISP. Secondly, we wished to compare this performance to that observed on a two-choice line discrimination task.

200 B. Jones, J. DuJJy / An analysis ~Jperformance

Experiment 1

Method

Subjects The Ss were 51 children (mean age 4 years 7 months with a range of 3 years 11

months to 4 years 10 months) enrolled in two pre-schools drawing from predominantly upper-middle class areas.

Muterials and procedure

Form A of the KRISP was administered individually to each child according to standard procedures (see Wright 1971, 1973, for details). Responses were timed with a stop-watch.

Results and discussion

The mean total error rate was 5.56 items (S. D. = 1.21) and the mean time to the first response was 4.39 set (S. D. = 1.49). Medians were respectively 5 items and 4.32 sec.

The sample was divided into four groups, Fast-Accurate, Slow-Accurate, Fast-lnac- curate and Slow-Inaccurate in terms of the medians for total errors and response times. Of particular interest here is the relationship between correct response times and error response times for the first choice. Since response time distributions are typically positively skewed (e.g. McCormack and Wright 1964) and since we had only a small number of measurements for each child, we chose the median time to make a correct response, Mdn(C), and the median time to make an error, Mdn(E) as our statistics. Table 1 shows means and standard deviations for each subject group.

Table 1

Mean medium correct response times, Mdn(C) and mean median error times, Mdn(E), in sets. on

the KRISP for the four subject groups.

Mdn(C) Mdn( E)

Fast-Accurate ( y = 16)

x

S

Slow-Accurate (n = 14) x

S Fast-Inaccurate (n = 12)

x

s

Slow-Inaccurate (n = 9) x

s

3.03 3.86

0.64 1.09

4.48 5.24

0.83 1.62

2.95 2.88

1.07 1.14

5.70 4.84

1.56 1.19

B. Jones, J. Duffy / An analysis of performance 201

It is apparent from table 1 that correct responses tend to be faster than errors for the two Accurate groups and that the reverse relation tends to hold for Inaccurate Ss. A convenient summary of the data can be obtained from a 2 (Speed) X 2(Accuracy) X

2(Correct Response-Errors) ANOVA with the first two levels as between-Ss variables and the third as a within-S variable. A least-squares solution was used for unequal

sample sizes (Winer 1962: 374-375). Necessarily the effect of speed must be significant, F (1, 47) = 63.06, p < 0.0001. The only other significant effect was the Accuracy X

Response interaction, F (1, 47) = 7.43, p < 0.01. The Newman-Keuls procedure using the harmonic mean of group size (Winer 1962: 101-102) showed that correct responses were significantly faster than errors for Accurate Ss (p < 0.01) and errors were significantly faster than correct responses for Inaccurate Ss (p -z 0.01). In terms of our argument (cf. Swensson 1973), Accurate Ss may be characterized as performing on the upper limb of a hypothetical speed-accuracy tradeoff function while Inaccurate Ss may be said to have adopted a less demanding criterion.

A detailed comparison of the four subject groups is shown in fig. 1. This is a plot of median response times against the so-called log likelihood ratio, the natural log of the ratio of correct responses to the number of errors for a given item across all Ss. Items with a common error rate were combined to obtain greater stability and in consequence there were less than ten points for each curve. Functions for the two Accurate groups were strictly monotone decreasing. These children responded quicker when the odds

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Fig. 1. Log likelihood ratio (the natural log of the odds in favour of a correct response) on the child’s first choice as a function of response time. Accurate subjects are represented by circles,

Inaccurate subjects by squares. Hollow symbols represent Fast subjects and filled symbols. Slow

subjects.

202 B. Jones, J. Duffi / An onulyns of performance

favoured a correct response and slower when they were more likely to make an error. Put another way, Accurate children were likely to increase initial inspection time as the difficulty of an item increased. Inaccurate children, and in particular the children in the Impulsive group. showed much less flexibility. It can be seen in fig. 1 that response times for Fast and Slow Inaccurate children remained roughly constant as a function of the log likelihood rate. If anything, these children tended to make their initial response slightly more quickly as the test items became more difficult.

Concentration on the overall latency of responding on the KRISP (and perhaps also on the MFF) may lead to over-simplified conclusions. Although we find clear dif- ferences between Accurate and Inaccurate children (and hence between “Reflective” and “Impulsive” children) the assumption that longer response times by an individual S must be related to increased accuracy (e.g. Kagan 1966; Kagan and Kogan 1970) is clearly untenable. Indeed, for Accurate Ss longer response times may only indicate that the child is uncertain about a discrimination and so is more likely to make a mistake. The assumption that “cognitive styles” can be meaningfully described as “impulsive”

or “reflective” may therefore be misleading. Fast responding may not be impulsive in the ordinary sense of without prior thought or strategy. Some children may respond relatively quickly simply because they are certain about the discrimination and there is nothing to gain from increasing their inspection time.

Experiment 2

Detailed analysis of children’s performance on the KRISP can clearly reveal important differences between groups of children in speed-accuracy strategies. We need not assume, however, that Ss, whether children or adults, will use the same strategy in every situation.

In the second experiment we shall use a length discrimination task which requires the child to choose the longer of a pair of lines. Unlike the KRISP the child is allowed only one choice on each trial. Moreover, this task has been proven useful in discerning variation in speed-accuracy strategies in adults (Henmon 19 1 I ; Link and Tindall 197 1; Swensson 1973).

Stein and Prindaville (1976) found that reflective chidlren acquired a line dis- crimination more quickly than impulsive children and achieved an apparently higher level of discriminative ability. They argued that impulsive children use only a global categorization of length (“short” or “long”) while reflective children differentiate more precisely. However. Stein and Prindaville did not measure response latencies and so could not assess whether or not their results were confounded by differences in speed-accuracy tradeoffs.

Whether or not the KRISP accurately predicts length discrimination, the task is of some importance in itself. Petrusic and Jamieson (1979) have convincingly demon- strated with adult Ss that arithmetic relations on pairs of visual extents (difference and ratio) are coded precisely by judgement times. They found that response times increased monotonically as the ratio of extents approached unit (see also Link and Tindall 1971) and decreased monotonically as the difference between extents increased.

B. Jones, J. Dufb / An analysis of performance 203

It would clearly be of interest if we could demonstrate that judgement times by pre-schoolers are also sensitive to stimulus structure since some developmentalists have argued for a fundamental continuity in information processing between children and adults (cf. Brainerd and Howe 1978; Chi 1978).

In the following experiment speed and accuracy of line discrimination were assessed for children in the four groups defined by the KRISP.

Method

Subjects

The Ss were the 42 pre-school children who had taken part in the previous experiment and who were also available for further testing. The mean age of the group was 4 years 4 months (range, 3 years 7 months to 5 years 0 months).

Apparatus and materials Pairs of horizontal lines were drawn on 20 x 13 cm white index cards. The lines

were 10, 10.5, 11, 11.5, 12, or 12.5 cm in length. All possible combinations of pairs of different lengths and of positions (top or bottom of the card) were used for a total of 30 stimulus items. Lines were presented horizontally, and in parallel. with a separation of 5 cm. The top line began 2 cm from the left hand border of the card. The bottom line began approximately 3.25 cm from the left hand border. A Casio AQ-1000 stop-watch was used to collect the latency data.

Procedure The length discrimination experiment was performed approximately six weeks after

testing on the KRISP. Children were tested individually. The children were told that they would have to point to the longer of two lines. Two practice trials ensured that the child understood the concept “longer than”. The child was then shown each of the 30 stimulus cards in a random order.

Results and discussion

One child was a statistical outlier, making only four correct responses out of a possible thirty, and was dropped from further analysis.

Preliminary analyses showed no differences between S groups in skew and we shall. therefore, analyze mean latencies. Mean latencies across all responses will be sym- - - bolized by RT and mean latency of correct responses and of errors by RT(C) and - RT(E) respectively. We also found that S groups did not differ in either within-S variance or in response bias. As a measure of bias we computed the probability of choosing the top line. Overall children were biased to choose the top line (0.59) though bias was roughly constant across the groups.

Before discussing detailed differences between groups it is necessary to demonstrate whether or not RT is sensitive to stimulus structure.

204 B. Jones, J. Duffv / An analysis ojperformance

Table 2

m collapsed across subjects for each stimulus comparison (experiment 2).

Length (cm) 10.5 11 11.5 12 12.5

10 2.12 2.62 2.32 2.25 2.17

10.5 3.75 2.43 2.17 3.31

11 2.68 2.47 2.1 I 11.5 2.59 2.51

12 2.58

Does RT code stimulus relations in pre-schoolers? - Table 2 shows RT across Ss for all paired comparisons of line lengths. Apart from

one violation for columns and two for rows, RT is a strictly decreasing monotone function of the difference between pairs of lines. For the group as a whole, judgement times by children younger than 5 years are remarkably sensitive to physical differences in line length.

We also found some evidence of ratio coding, albeit relatively crude. in the - pre-schoolers (table 3). As ratios approach unity RT tended to increase though there were a number of violations of strict monotonicity. Nevertheless, the rank order

-. correlation between ratio and RT IS significant, r, = 0.53, t (13) = 2.22, p < 0.03.

Does the KRISP predict speed and uccuracy of length discrimmation? Correlations between reaction time and errors for the KRISP and length discrimina-

Table 3

m as a function of the ratio of the shorter to the longer line for all SubJects, and for reflective and

impulsive subjects (experiment 2).

Ratio All subjects Reflective Impulsive

0.9600 2.58 I .97 2.53

0.9583 2.59 2.66 2.20

0.9565 2.68 2.59 2.54

0.9545 3.15 3.53 3.54

0.9524 2.72 2.48 2.52 0.9200 2.52 2.21 2.15

0.9167 2.47 2.06 2.18 0.9 130 2.43 2.43 2.22

0.9091 2.62 2.58 2.6 I

0.8800 2.1 I 2.03 1.96 0.8750 2.17 2.14 1.77

0.8696 2.32 2.53 1.86 0.8400 3.31 2.46 2.14

0.8333 2.25 1.94 2.17 0.8000 2.17 1.96 2.12

B. Jones, J. Duffy / An analysis of performance 205

Table 4 Proportion correct, P(C), mean latency, RT, and mean latency for correct responses, RT(C), and errors, m(E), (latencies in set) for length discrimination when children were classified by the

KRISP (experiment 2).

KRISP

classification P(C) RT RT(C) RT(E)

Fast-Accurate x S

Slow-Accurate x s

Fast-Inaccurate x s

Slow-Inaccurate x s

0.73 2.33 2.28 2.78

0.02 0.79 0.75 1.65

0.73 2.46 2.22 2.58

0.02 0.71 0.56 1.00

0.70 2.30 2.27 2.52

0.03 0.45 0.45 0.62

0.80 3.28 3.24 4.11

0.01 1.42 1.61 1.68

tion were 0.44 ( p < 0.005) and 0.19 ( p < 0.10) for times and errors respectively. The basic data for line length discrimination when children were classified according to the KRISP are shown in table 4. Two-way ANOVA’s with Speed and Accuracy as factors (least-squares solution for unequal cell size) indicated no significant differences be- -- - tween groups on any of the dependent measures, P(C)JT, RT(C), or RT(E). In short if

Table 5

RT for each stimulus comparison for children classified as reflective and impulsive by the KRISP.

Length (cm)

10.5 11 11.5 12 12.5

Reflective 10 10.5 11 11.5

12

Impulsive 10 10.5 11

11.5 12

2.48 2.58 2.53 1.94 3.53 2.43 2.14

2.53 2.09

2.61

1.97

2.52 2.6 1 1.86 2.17 3.45 2.22 1.77

2.59 2.18 2.20

1.90

2.46

2.03 2.21

2.12 2.14 1.96

2.15

2.53

206 B. Jones, J. Duff / An analyses of performance

we classify pre-school children by means of the KRISP we can find no differences between groups in mean accuracy and mean latency of two-choice discrimination.

It is also worth examining the degree to which judgement times by children who are reflective and impulsive on the KRISP are sensitive to stimulus relations. Table 5 shows RT as a function of stimulus differences for Reflective and Impulsive children. There were 5 violations of monotonicity for Impulsive children and 6 for Reflective children. There is no evidence. in other words, that one group codes stimulus dif- ferences any more precisely than the other.

Ratios make the same point (table 3). There were several violations of monotonicity by both groups. Nevertheless both rank-order correlations are significant and the correlation for the Impulsive group, <s = 0.68, f (13) = 3.33. p c 0.005, is substantially higher than the correlation for Reflective children. ‘\ = 0.47, t (13) = 1.93, p < 0.05. Children who are classified as impulsive were apparently slightly better able to map stimulus ratios into response times than are children classified as reflective. -

We may also examine the child’s strategy by comparing RT(C) and RT(E) across stimulus differences (fig. 2). For reflective children RT(C) was faster than RT(E) across all differences, i.e. at a deeper level of analysis there are commonalities between the behaviour of reflective children on the KRISP and their hehaviour here. Slower responses tended to be strongly associated with errors in both cases. For impulsive children, on the other hand, there is evidence of a switch in strategy. When the discrimination was more difficult RT(C) tended to be longer than RT(E) while for easier discriminations the reverse relation held.

400 Reflective

4oc

3oc

2oc

I oc

lmpulslve

.A_... I 111

05 loo 150 200 250 05 100 150 200 250

STIMULUS DIFFERENCES

Fig. 2. RT(C) and RT(E) for “Reflective” and “Impulsive” children clasified according to the

KRISP.

B. Jones, J. Duff / An anabsis of performance 207

Speed-accuracy strategies for length judgements

Longer judgement times were more strongly associated with errors. Correct responses, - RT(C) = 2.46 set, were significantly faster than errors, RT(E) = 3.38 set, t (40) = 2.22, p < 0.005. The probability of a response being correct was only 0.67 after 3 set compared to 0.80 for responses made before 3 sec.

Since the KRISP does not allow us to distinguish speed and accuracy of length judgements by the four Ss, we reclassified Ss on the basis of length discrimination per se. Using median splits on latency and errors, 7 children were classified as Fast-Accu- rate, 12 as Fast-Inaccurate, and 8 as Slow-Inaccurate. Means for the four groups are - shown in table 6. RT(C) and RT(E) were analyzed by means of separate 2 (Speed) x 2 (Accuracy) ANOVA’s (least-squares solution for unequal cell size) and indicated only that both correct responses and errors were made more quickly by Fast Ss (RT(C), F - (1, 31) = 12.85, p < 0.01; RT(E), F (1, 31) = 25.98, p < 0.0001). However, a similar analysis of differences, R T( E)-R T(C), indicated a tendency for the differences to be greater for Accurate Ss, F (1, 31) = 3.58, p < 0.10, and that differences were signifi- cantly greater if Ss were slow, F (1, 31) = 41.74, p -C 0.05.

In other words, children whose general performance on the length discrimination task would lead them to be classified as “reflective” are more likely to be wrong when they take a longer time to make a response, and more likely to be correct when they respond more quickly.

Table 6

P(C), RT, RT(C) and RT(E) in experiment 2 when children were classified by speed and accuracy of length discrimination.

Classification P(C) RT RT(C) RT(E)

Fast-Accurate

x

S

Slow-Accurate x

S

Fast-Inaccurate x

s Slow-Inaccurate

x

S

0.89 1.84 1.81 2.14

0.06 0.27 0.31 0.82

0.89 3.12 2.96 4.50

0.05 0.51 0.53 1.56

0.65 I .98 1.99 1.95

0.09 0.22 0.27 0.28

0.62 3.26 3.14 3.39

0.10 1.45 1.71 1.03

208 B. Jones, J. Dufjv / An UIIU!L’SIS of performance

General discussion

A brief summary of our main findings may be useful at this point. Detailed analysis of performance on the KRISP allowed us to infer differences between Accurate and Inaccurate children in speed-accu- racy tradeoffs. Typically correct responses were faster than errors if children were accurate and errors were the faster if children were inaccurate. Accurate children showed greater flexibility in responding to KRISP items. In general they tended to increase inspection times as the items increased in difficulty. This relation was not observed for Inaccurate children. However, the KRISP did not predict performance on the line discrimination task very efficiently. Finally, preschool children showed some ability to code stimulus relations (ratios and differences).

This last result is particularly interesting given that we were able to run only 30 trials per child with only 2 replications of each pair of line lengths (Petrisuc and Jamieson 1979, had subjects make 60 replications of each stimulus pair and they observed essentially error free perfor- mance). Differences appear to be coded rather more accurately than ratios though, of course, differences and ratios were confounded to some extent in our experiment. We need an experimental study to judgement times in young children when ratio is varied and difference held constant and when ratio is held constant and difference varied. Nevertheless, our results do suggest commonality of processing in young children and adults and reinforce the position of some devel- opmentalists (e.g. Brainerd and Howe 1978; Chi 1978) that there is a fundamental continuity across the age span in information processing and decision making.

Although we may infer differences in speed-accuracy strategy be- tween subjects in experiment 1 this is not, of course, sufficient to show that subjects can adopt at will any position on a speed-accuracy tradeoff. On the other hand, the demonstration of detailed differences between so-called “impulsive” and “reflective” groups is not sufficient to show that we are dealing with consistent trait dimensions. In fact, experiment 2 shows that the two groups may be well-nigh indis- tinguishable on a second task that also allowed the child to vary speed and accuracy. Impulsive and reflective children made relative judge- ments of length about as accurately and about as quickly as each other. Moreover, there was no evidence of merely global processing by the

B. Jones, J. Duffv / An analysis of performance 209

impulsive group (cf. Stein and Prindaville 1976). Stimulus relations

were coded as efficiently by the two groups. One might perhaps argue that our results hold only for pre-schoolers

and that impulsivity and reflectivity are more reliable traits in older children. On the one hand this argument might simply be directed against the KRISP as a measuring instrument. Yet if anything the KRISP is more reliable than the MFF. Test-retest reliabilities for the MFF have ranged from 0.19 (Block et al. 1974) to 0.96 (see Messer 1976) for latencies with a mean of around 0.58, whlie for errors reliabilities range from 0.23 to 0.43 (Ault et al. 1972). Coefficients of

stability and equivalence for the two forms of the KRISP (the MFF has only one form) range between 0.61 and 0.80 (Johnson 1976). Across tasks, as we have noted, the MFF tends to predict latency better than it predicts accuracy (e.g. Jones and McIntyre 1976; not surprisingly since repeated testing with the MFF yields higher relablities for latency). The present data show that essentially the same relationships hold for the KRISP.

An alternative version of this argument might be that “impulsivity” and “reflectivity” are cognitive styles which become manifest only in older children. Though our data do not speak to this issue, we may note evidence which suggests that the notion of a stable trait is difficult to sustain with respect to older children. “Impulsive” children on the MMF were as accurate as “reflective” children in a recognition mem- ory experiment (Jones and McIntyre 1976).

In our opinion differences between the KRISP and length dis- crimination may be best explained by reference to the nature of the two tasks. Following Jones and McIntyre (1976) we would suggest that the KRISP, like the MFF, is likely to encourage greater variation between subjects in the choice of a speed-accuracy strategy. A key feature of both tests is that the child continues to choose between alternatives until the correct match has been achieved. However much the task instructions may stress accuracy, allowing children to make mistakes that can be rapidly corrected may suggest to some children that initial accuracy is not in fact unreasonable for a child to make no genuine discriminations. They could guess as quickly as possible until the correct match is made. Hence the lack of flexibility shown by Inaccu- rate children in experiment 1 may be an artefact of the task. The child is aware that other choices are possible so that an initial fast and inaccurate response may not be troublesome. (If the item is easy the

impulsive group may be the more efficient. Fig. 1 shows that a log likelihood ratio of about 9.0 is obtained in 3.5 set by impulsive children and in something over 5 set by reflective children.)

In experiment 2 the first response on any trial was also the ultimate response and here, although subjects may be more or less arbitrarily divided into speed-accuracy groups, we find much less variability in inferred tradeoffs. For subjects classified on the basis of the length discrimination task, only the Fast-Inaccurate group showed the relation RT(C) >RT(E) and even here the difference is quite small. The KRISP classification resulted in the same relation, RT(C) < RT(E), for all four groups (table 4).

In sum, we would argue, contrary to the notion of cognitive style, that a child’s behaviour may be relatively flexible. Across situations children, like adults, may spontaneously adopt a variety of speed-accu- racy tradeoffs. In some situations the strategy may be suggested by implicit or explicit instructions. In others, the task itself may imply an appropriate strategy. Perhaps we should not be so ready to label a child’s performance as “impulsive” or “reflective”. Instead we might ask whether the child’s behaviour is an appropriate response to the sometimes ambiguous demands that we have made.

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