Conceptual process as a function of age and enforced attention in learning-disabled children: Evidence for deficient rule learning

CONTEMPORARY

Conceptual Attention

EDUCATIONAL

PSYCHOLOGY

7, 1.52- 160 (1982)

Process as a Function of Age and Enforced in Learning-Disabled Children: Evidence for Deficient Rule Learning LEE SWANSON of Northern Colorado

The University

Adapting a modified reception paradigm, three bidimensional rules (conjunctive, disjunctive, conditional) and two instructional conditions (enforced attention vs standard rule learning) are used to test the assumption that deficient rule learning rather than inattention is responsible for poor learning with learning-disabled children. Main findings indicate learning-disabled children are deficient on binary conceptual rule tasks for three age groups (6 to 7, 8 to 9, 12 to 13) compared to normal children matched on sex and IQ regardless of experimental instructions. For both groups, learning is retarded by rule complexity while rate of learning diminishes with increasing age. Data reflect a truth-table logic at all ages for both groups, although there is evidence that disabled children perseverate with a rule-learning hypothesis characteristic of younger nondisabled children. Results are consistent with the hypothesis that rule learning is deficient in children with learning disabilities.

A vast number of specific issues and various theoretical persuasions have accounted for the poor learning of disabled children; however, many of the same processes appear to be interwoven with performance on nearly all learning problems. One such process, concept formation, concerns the child’s ability to integrate attention-dependent, temporally disparate informational sequences in order to eliminate an incorrect strategy and thereby generate new and more appropriate ones concerning the solution to a problem (e.g., Bourne, 1974; Staudenmayer & Boume, 1977; Sternberg, 1979). Attentional deficits are popularly thought to account for disabled children’s poor concept formation in some tasks; therefore, it has been suggested that intermittent attention is responsible for poor learning in these children (e.g., Douglas, 1976; Dykman, Ackerman, Clement% & Peters, 1971; Ross, 1976). The notion that disabled children are intermittent in attending to task-relevant information is partially supported by studies directing their overt responses (e.g., verbalizing, pointing, or rehearsing task-relevant information) prior to actual problem solving, and This research was supported by a grant from the Publication and Research Committee, the University of Northern Colorado. The manuscript was prepared while the author was a postdoctoral student at the University of California at Los Angeles. The author is indebted to Lejune Ellison-Brown and to Warren Schulte for their administrative assistance. Requests for reprints should be sent to the author, School of Special Education, University of Northern Colorado, Greeley, CO 80639. 152 0361-476X/82/020152-09$02.00/O Copyright @ 1982 by Academic Press, Inc. All rights of reproduction m any form reserved.

RULE

LEARNING

153

thereby improving performance (cf. Douglas, 1976; Dykman ef al. 1971; Meichenbaum & Goodman, 1971; Ross, 1976). Although attention is required for adequate performance on conceptformation tasks, it has not been established that learning-disabled children do not attend in learning or that inattention is responsible for their poor learning. For example, Swanson (1981), using a rule-learning reception paradigm, found no difference between disabled and nondisabled children’s learning rate for identifying relevant attributes, but solution rate became more difficult for disabled as binary rules (e.g., conjunction, disjunction, conditional) were introduced. Implicit in the finding was the notion that disabled children attend to relevant attributes but lag behind nondisabled in rule-learning rate. Learning-disabled children typically made the error of focusing on a single hypothesis and attempted to gather supporting evidence by repeating a single value or attribute. The holdone-thing-at-a-time or unidimensional strategy entailed the possibility of gaining no new information from any presentation, and it never allowed the elimination of cooccurring alternatives. The nondisabled children in Swanson’s (1981) study utilized a truth-table algorithm (cf. Boume, 1974) in which they attended only to relevant attributes with the implicit understanding that the joint presence (T = True) and absence (F = False) of attributes determines the classification of conceptual rules. Unknown from current research is whether problem-solving efficiency in leamingdisabled children can be corrected through enforced attending procedures. The present study tested two competing hypotheses within a developmental framework. First, problem-solving efficiency in learningdisabled children can be improved under instructions that require direct attention to relevant attributes. Several authors (e.g., Johnson, Silleroy, & Warner, 1971; King & Holt, 1970) have suggested that enforced attention was beneficial for nonsolvers in developing a truth-table type of coding system. It may be that requiring learning-disabled children to attend to key attributes simplifies stages of processing by giving them relevant subsets of operations required for understanding of the full task (see Douglas, 1976). Second, problem efficiency of learning-disabled children is impaired by their reductive coding ability. As suggested from Swanson’s study (1981), disabled children preseverate with a single hypothesis beyond age appropriateness in their assignment of attributes (TT, TF, FT, FF) to response categories (positive and negative instance of rule). METHOD

Subjects and Design Seventy-two children (disabled and nondisabled) separated into two groups of 12 each for three age levels (matched on IQ and sex between groups and chronological age (CA) within age levels) served as subjects in the experiment. Ten males and two females were in each

154

LEE SWANSON

cell. Children were selected from regular or special education (learning disability) classes in the Columbia, South Carolina, and Ft. Collins and Greeley, Colorado, public school systems All children were presented three binary rules under both enforced-attention and standard learning instructions with presentation orders randomized and cells counter balanced. Computed mean IQ scores from the Otis-Lennon Intelligence Test and mean chronological ages for the younger age group were 98.5 (SD = 5.39) and 6.1 years (SD = 59) for disabled and 101.75 (SD = 4.59) and 5.9 (SD = .42) for nondisabled children; in the intermediate age group, mean IQ scores and ages were 101 (SD = 8.01) and 8.7 (SD = .55) for disabled and 106(SD = 8.67) and 9.0 (SD = .59) for nondisabled children; in the older age group, mean IQ scores and ages were 105(SD = 4.36) and 13.1 (SD = 1.48) for disabled and 107(SD = 3.46) and 12.6 years (SD = 1.23) for nondisabled children, respectively. Groups did not differ significantly @ > .25) on IQ within or between cells nor by CA within age groups. Selection of learning-disabled children was determined by the Federal Register definition (1977) and reading scores below the 35th percentile. Metropolitan Achievement reading mean and standard deviation percentiles and grade equivalent (GE) subtest scores in younger, intermediate, and older ages were M 23.1, SD 10.22, GE preprimer; M 19.33, SD 12.72, GE 2.4; M 13.3, SD 5.3, GE 5.1, respectively. Selection criterion for nondisabled children was a standardized reading test score at grade level or above.

Procedure and Stimuli The procedure used in this study was similar to Cahill and Hovland’s (1960) simultaneous presentation technique. The entire stimulus population was laid out before the child, permitting access to all previously identified and yet-to-be-identified stimuli. Three dimensions with three attributes or values per dimension were employed in all rule-learning problems with number (1, 2, 3), color (red, yellow, green), and shape (circle, triangle, star) common to all problems. Stimuli were drawn on 10 x IO-cm white index cards. Attribute identification. To establish that children could identify relevant and irrelevant attributes as well as familiarize them with the task, an affirmation rule (all red ones) was employed. Children were informed that their task was to tell which card in the array was an example or nonexample of a rule. The experimenter then showed a relevant predetermined attribute (hint card) to the child and placed it back in the stimulus array. The experimenter than pointed to a stimulus card and the child responded by classifying the card as an example or nonexample of the concept within 15 sec. Children’s responses were followed by information feedback-a yes or no, indicating whether or not the response was an example or nonexample of the concept. Predetermined stimulus cards were chosen from a table of random numbers, with the stipulation that stimulus sequences include each of the four attribute contingencies (TT, TF, FT, FF) at least twice every 12 trials. One trial constituted stimulus presentation, child response, and experimenter feedback. Rule /earning. Presentation procedures were the same as in attribute identification session, except all children participated in both standard and enforced-attending instruction for conjunctive, disjunctive, and conditional rules. During the standard rule-learning instruction, children were told to look at the hint card, and each child correctly guessed the card’s color, shape, and number to determine the game’s solution. Enforced-attention procedures (e.g., Johnson ef al., 1971), in contrast to standard rule-learning instruction, required the child to (1) point to correct attributes on the stimulus card (hint card given at beginning of task and all correctly guessed cards), and (2) correctly verbalize the attributes on these cards. For each prior stimulus card guessed correctly, the child was required to point to the values on the cards and verbalize those correct values before going on to the next trial. Children were given the correct response if they erred. Entire procedures, performed in one session, took no more than 45 min per child.

RULE

LEARNING

155

RESULTS

Percentage of errors through criterion on pretraining for the affirmation rule did not differentiate nondisabled from disabled problem solvers, X2 < 1 for all ages. Therefore, no difference was found between children in attending to relevant attributes. Further, the total per unit time disabled subjects’ eyes oriented to stimulus card during presentation of binary rules, utilizing a time-sampling procedure, did not differentiate disabled from normals for any age, X2 < 1 for all comparisons. Because several subjects did not reach criterion on the binary rules, the mean proportion of errors for all subjects was compared with that of subjects who solved rule-learning tasks, an inspection of these data indicated that the addition of nonsolving subjects did not alter the arrangement of mean scores. A Fisher’s exact probability test of distribution of subjects in the factorial aspect of the experiment was not significant (X2 < 1). Only the results of the analysis of the total group are reported here in view of the fact that findings were virtually identical. Mean error and standard deviations for all children over the three rules are presented in Table 1 in terms of age, group, and instruction. An ANOVA of age (5 to 6, 8 to 9, 12 to 13), group (normal vs disabled), instruction (enforced vs standard), and rules (conjunction, disjunction, conditional) with repeated measures on the last two factors was performed. Results showed significant sources of variation due to age, F(2,66) = 4.77, p < .05; age x group interaction, F(2,66) = 5.46,~ < .Ol; rules, F(2,198) = 44.11,~ < .OOl; age x rule interaction, F(4,198) = 4.12, p < .05; and instruction x group x rule interaction, F(2,198) = 3.00, p < .05. Results corroborate current studies (cf. Sternberg, 1979) that indicate rule-learning ability increases with age, and conjunctive/disjunctive rules are easier than conditional rules for all age levels. As can be seen from Table 1, a curvilinear effect accounted for age x group and age x rule interactions; younger children were less efficient problem solvers, intermediate age performing best, and older children performing at or below intermediate age levels. In view of the significant interactions, a separate 2 (group) x 2 (instructions) x 3 (rules) ANOVA with repeated measures on the last two factors within each separate age group was undertaken. As suggested by the significant age X group interaction, superior rule-learning performance of nondisabled across rules compared to disabled children was found at older, F(1,22) = 4.27,~ < .05; intermediate, F(1,22) = 5.13,~ < .05; but not younger ages, F < 1. For older children, no significant main effect was found for instructions (F < l), while a group x instruction x rule interaction was reliable, F(2,44) = 4.93, p < .05. A t test (df = 44) indicated sources of variation in main effects were due to inferior performances of disabled on the conditional rule for the enforced-attention instruction compared to standard instructions (t = 2.32, p < .05), with better perfor-

6-7 Normal Disabled 8-9 Normal Disabled 12-13 Normal Disabled

As

11.02 11.43

4.05 9.66

2.43 8.15

7.83 11.16

5.25 8.08

3.42 5.92

6.42 5.33

10.08 12.66

11.83 13.33

SD

10.24 8.44

7.44 9.84

10.74 8.55

M

M

SD

Disjunctive

attention

Conjunctive

Enforced

16.83 27.25

9.83 15.50

17.00 19.46

8.75 9.65

7.17 10.01

12.48 10.00

4.17 3.67

2.75 8.08

9.67 10.50

2.48 1.97

1.58 5.08

3.41 9.01

10.92 2.42

11.17 15.75

19.00 15.50

SD

12.03 1.68

7.43 12.36

10.20 10.53

M

SD

M

M SD

Disjunctive

Conjunctive

Conditional

Standard rule learning

18.50 19.83

16.5 21.83

18.67 21.75

M

9.35 9.93

SD

10.57 13.12

10.37 13.18

Conditional

TABLE 1 MEAN ERROR AND STANDARD DEVIATIONS TO SOLUTION ACCORDING TO AGE, GROUP, INSTRUCTIONS, AND RULE

RULE

LEARNING

157

mance of disabled compared to nondisabled for the standard instruction disjunctive rule (t = 2.66, p < .Ol). No significant difference between groups was noted on standard instructions for conjunctive (CJ) and conditional (CD) rules or attention-enforced instructions on conjunctive and disjunctive (DJ) rules 0) < .25). Newman-Keuls analysis of rule difticulty, F(2,44) = 61.98, p < .OOl, collapsed across instructional conditions, indicated significant (p < .OS)ordering of rule difficulty for normals, CJ < DJ < CD, while disabled children’s ordering yielded CJ < CD and DJ < CD with no difference between conjunctive and disjunctive learning. As shown in Table 1, nondisabled were superior to disabled children on all rules at the intermediate age. Sources of variation were found for the instruction x rule interaction, F(2,44) = 4.70, p < .05. Rule learning for nondisabled and disabled was facilitated for the enforced-attention instruction on the conditional rule, t(44) = 2.34,~ < .05; t(44) = 2.22,~ < .05, respectively. Significant sources of variation for the intermediate group were also found for rules, F(2,44) = 24.56, p < .OOl. Order of rule difficulty (CJ < DJ < CD) was the same for both groups. For younger children, rule difficulty was the only significant source of variation, F(2,44) = 15.57, p < .OOl. A Newman-Keuls analysis (scores collapsed across group and instructions) yielded significant (p < .05) ordering levels, CJ < DJ < CD. To determine the extent to which disabled and nondisabled children acquired a truth-table system, data were analyzed for solvers one at a time. Outcomes of a unidimensional hypothesis would predict a marked inequality in the number of errors for TF and FT attributes. The index of such inequality was an obtained ratio of errors for TF:FT (or FT:TF) of at least 2: 1. Only problems in which two errors were made on TF and/or FT attributes were included. As shown in the upper half of Table 2, reliance on the unidimensional hypothesis (e.g., all red ones are positive, when the correct rule is, e.g., all red and/or star are positive ones) decreased with age. Chi square analysis for critical values on combined cell frequencies across rules for unidimensional problem solvers indicated reliable sources of variation for older, X2( 1) = 2.88, p < .05; intermediate, X2( 1) = 9.68, p < .Ol ; and younger ages, X2( 1) = 5.53, p < .05. Disabled children relied more heavily on the unidimensional hypothesis than nondisabled children at all ages. An optimal or truth-table rule-learning strategy (bottom half of Table 2) was defined as no more than one error on each attribute (e.g., TT, TF . . .) combination. As shown in Table 2, more frequent optimal solvers were found with enforced-attention than standard instructions, while more optimal solvers were noted for the nondisabled compared to disabled group. Analysis of optimal rule-learning strategies is consistent with the results that disabled children utilized a unidimensional hypothesis even when enforced-attending instructions were implemented.

158

LEE SWANSON

TABLE 2 PROPORTIONOF CHILDREN ATTAINING UNIDIMENSIONALOR~~IIMAL SOLUTIONRATE Enforced attention Age Unidimensional solution 6-7 Normal Learning disabled 8-9 Normal Learning disabled 12- 13 Normal Learning disabled Optimal solution 6-7 Normal Learning disabled 8-9 Normal Learning disabled 12- 13 Normal Learning disabled * CJ, DJ, CD-Conjunction,

Standard rule learning

CJ*

DJ*

CD*

CJ

DJ

CD

25 41

25 33

08 25

33 50

41 58

41 50

16 25

08 50

08 25

08 50

33 33

33 50

16 16

08 08

25 66

08 33

16 25

25 66

41 00

16 00

08 00

08 16

08 08

00 00

50 50

16 00

16 00

50 08

08 00

00 08

42 25

66 58

00 00

42 50

66 42

00 08

disjunction, and conditional, respectively.

DISCUSSION

If learning-disabled children differ from nondisabled children in the quality of their attention to relevant attributes but not in conceptual rule-learning ability, then the performance gap between disabled and nondisabled children would lessen as disabled children attend to task-relevant information. From this premise, it would be predicted that procedures which force children to attend to each attribute would facilitate rulelearning performance, a prediction that has been confirmed by several findings (e.g., Johnson et al., 1971; King & Holt, 1970) which use enforced-attentional procedures for young children. But this prediction for disabled children was not confirmed. Comparable performance on the attribute identification task (affirmation rule) coupled with immature hypothesis bias on binary rules provide strong support for the assumption that disabled children lag developmentally behind nondisabled in conceptual rule learning. In concept learning, it is assumed that in order to successfully solve learning problems, subjects must attend to stimulus examples according

RULE

LEARNING

159

to the rule that defines problem solution while concurrently mapping that stimulus population into subclasses through a reductive (e.g., truth-table) coding type procedure (cf. Swanson, 1981). Since some disabled children ultimately solved the most difficult problem (conditional rule), these children can attend, implicitly, to the subclass or attribute combinations. In contrast to predictions from an attentional deficit notion, enforcedattention instructions had marginal effects on disabled children’s solution rate. Disabled children, as suggested from the ratio of TF:FT (or FT:TF) errors, maintain an inefftcient hypothesis regardless of rule-learning instruction. In view of the extensive literature suggesting that truth-table coding is necessary for superior rule-learning performance (e.g., Johnson et al., 1971; Swanson, 1981), the higher incidence of unidimensional problem solving is consistent with the hypothesis that concept-formation processes of these children are inferior to those of nondisabled children. The present study replicated earlier findings (e.g., Boume, 1974)in that learning rates are retarded by increasing rule complexity and diminish with increasing age (e.g., Stemberg, 1979). However, as also found in King (1968), a curvilinear effect of age occurred. No explanation can be offered for the older children’s decrement in performance when compared to intermediate-aged children except that rule-learning difficulty for older children coincides with Piaget’s transition from concrete to formal operations. While interpretation is beyond the confines of this experiment, older children’s reliance on an erroneous abstract hypothesis may have caused a decrement in overall performance. In terms of the disabled ehildren’s development, results suggest three developmental processes. First, young learning-disabled children, as with nondisabled, were unable to efficiently discover bidimensional rules nor did they profit from enforced-attention instructions. Second, the disabled children of intermediate age were less proficient than nondisabled in rate of learning, but did profit along with normals from enforced-attention procedures for the conditional rule. (These children maintain, however, an inefficient problem-solving strategy characteristic of young normals.) Third, at older ages they discover conjunctive and disjunctive rules comparable to normal children regardless of instruction; they lag, however, in performance when confronted with the more difficult rule (conditional). In summary, conceptual rule-learning difficulties in learning-disabled children across age seemed to depend on their ability to develop a stimulus coding system similar to a truth-table algorithm. REFERENCES BOWRNE, L. An inference

in cognitive

model for conceptual rule learning. In R. L. Solso (Ed.), Theories psychology: The Loyola symposium. Potomac, Md.: Erlbaum, 1974.

160

LEE SWANSON

CAHILL, H., & HOVLAND, C. The role of memory in the acquisition of concepts. Journal of Experimental Psychology, 1960, 59, 137-144. DOUGLAS,V. Perceptual and cognitive factors as determinants of learning disabilities: A review chapter with special emphasis on attentional factors. In R. Knight & D. Baker (Eds.), The neuropsychology of learning disorder. Baltimore, Md.: Univ. Park Press, 1976. DYKMAN, R., ACKERMAN,P., CLEMENTS,S., & PETERS, J. Specific learning disabilities: An attentional deficit syndrome. In H. Myklebust (Ed.), Progress in learning disabilities. New York: Grune & Stratton, 1971. Vol. 2. Federul Register, Vol. 41, No. 250; Thursday, December 29, 1977. JOHNSON,P., SILLEROY,R., & WARNER,M. The stability and transferability of conceptual coding children. Journal of Experimental Child Psychology, 1971, 12, 212-222. KING, W. Rule learning and transfer as a function of age and stimulus structure. Child Development, 1968, 39, 31l-324. KING, W., & HOLT, J. Conjunctive and disjunctive rule learning as a function of age and forced verbalization. Journal of Experimental Child Psychology, 1970, 10, lOO- 111. KOPPELL, S. Testing the attentional deficit notion. Journal of Learning Disabilities, 1979, 12, 52-57. MEICHENBAUM, D., & GOODMAN, J. Training impulsive children to talk to themselves. Journal of Abnormal Psychology, 1971, 77, 115- 126. ROSS,A. Psychological aspects of learning disabilities and reading disorders. New York: McGraw-Hill, 1976. STAUDENMAYER,H., & BOURNE, L. Learning to interpret conditional sentences: A development study, Developmental Psychology, 1977, 13, 616-623. STERNBERG,R. Developmental patterns in the encoding and combination of logical connectives. Journal of Experimental Child Psychology, 1979, 28, 469-498. STERNBERG,R., & RIFKIN, B. The development of analogical reasoning processes. Journal 1979, 27, 195-232. of Experimental Child Psychology, SWANSON,L. Encoding of logical connective rules in learning disabled children. Journal of Abnormal Child Psychology, 1981, in press.