Cain Oathill 1999 - Inference Making Ability and Its Relation to Comprehension Failure in Young Children

Reading and Writing: An Interdisciplinary Journal11: 489–503, 1999.© 1999Kluwer Academic Publishers. Printed in the Netherlands.

489

Inference making ability and its relation to comprehension failurein young children

KATE CAIN & JANE V. OAKHILLLaboratory of Experimental Psychology, University of Sussex, UK

Abstract. Young children’s reading comprehension skill is associated with their ability todraw inferences (Oakhill 1982, 1984). An experiment was conducted to investigate the direc-tion of this relation and to explore possible sources of inferential failure. Three groups ofchildren participated: Same-age skilled and less skilled comprehenders, and a comprehension-age match group. The pattern of performance indicated that the ability to make inferenceswas not a by-product of good reading comprehension, rather that good inference skills are aplausible cause of good reading comprehension ability. Failure to make inferences could notbe attributed to lack of relevant general knowledge. Instead, the pattern of errors indicated thatdifferences in reading strategy were the most likely source of these group differences.

Keywords: Causal relations, General knowledge, Inference making ability, Reading compre-hension, Young children

Introduction

In normal reading situations, skilled readers construct text representationsthat are both integrated and coherent. Inference making is an important partof this process: Inferences are necessary to link up ideas and fill in detailsthat are not explicitly mentioned and skilled adult readers readily make infer-ences as, and when, necessary (e.g. Garnham 1985; Garnham & Oakhill1996; Graesser, Singer & Trabasso 1994; Johnson-Laird 1983; Singer 1994;Van den Broek 1994). However, not all readers make sufficient inferencesto ensure adequate comprehension. Young readers are less likely to gener-ate inferences than older children (e.g. Casteel & Simpson 1991; Omanson,Warren & Trabasso 1978; Paris & Lindauer 1976; Paris & Upton 1976), andless skilled readers draw fewer inferences than their skilled peers (e.g. Long,Oppy & Seely 1994, 1997; Oakhill 1982, 1984).

The aim of this study was to investigate the relation between inferencemaking and reading comprehension failure in young children. Early studiesby Oakhill revealed that less skilled comprehenders experience specific diffi-culties with making two types of inference necessary to construct coherentand integrated text representations. They are poor at integrating informa-

490 KATE CAIN & JANE V. OAKHILL

tion explicitly provided by the text to establish cohesion between differentsentences, such as drawing the inference that “the mouse ate some bread”from the following text: “The mouse ate some food. The food was bread. Themouse looked for some cheese” (Oakhill 1982). Less skilled comprehendersare also poor at incorporating information outside of the text, i.e. generalknowledge, with information in the text to fill in missing details (Oakhill1984), for example inferring that the protagonist was riding a bicycle fromphrases in a text such as “pedalling as fast as he could” and “he ran over somebroken bottles and had to walk the rest of the way”. In this paper, we adoptBaker and Stein’s (1981) terminology and refer to the first type of inferenceas a text-connecting inference and the latter type as a gap-filling inference.

These two early studies by Oakhill demonstrate that reading comprehen-sion skill is associated with young children’s inference making abilities, butthey do not establish the direction of the relation between the two skills. Doinference making skills determine reading comprehension or, conversely, aregood inference skills a by-product of good reading comprehension? It may bethat the skilled comprehenders’ superior inference making skills have arisenfrom their superior reading comprehension skills. Alternatively, inferencemaking ability may determine comprehension skill: The less skilled com-prehenders’ poorer inference making ability may have (in part) led to theirinadequate text comprehension. It is important to disentangle such causalissues, particularly when considering how poor comprehension might beimproved. If inference making does not determine general reading compre-hension skill, then attempts to train less skilled comprehenders in inferentialprocessing may be pointless. Causal hypotheses are best tested by longit-udinal and/or training studies but these are both time consuming and costlyendeavours and, therefore, only worth pursuing once candidate causes havebeen identified. The current study set out to assess which of these twoalternatives is the more plausible by adopting a design analogous to thereading-level match design advocated by Bryant and colleagues (e.g. Gos-wami & Bryant 1990), the comprehension-age match design (Cain & Oakhill1996; Stothard & Hulme 1992).

Three groups were selected: Skilled and less-skilled comprehendersmatched for reading accuracy, sight vocabulary, and chronological age, and acomprehension-age match group comprising younger normally developingreaders of equivalent comprehension ability to the less skilled compre-henders. The comparison between the less skilled and comprehension-agematch groups provides a particularly strong test of the causation hypothesis.If the comprehension-age match group make more inferences than the lessskilled comprehenders we can rule out the possibility that their superior infer-ential abilities are a by-product of good reading comprehension, because the

COMPREHENSION FAILURE IN YOUNG CHILDREN 491

two groups are matched on this measure. A more plausible interpretationof such data is that poor inferential skill is a candidate cause of readingcomprehension.

The second aim of this work was to explore the reasons why childrenfail to make these common types of inference. Yuill and Oakhill (1991) sug-gest different reasons why poor comprehenders may fail to make inferences,which were investigated in the current study.

First, poor comprehenders may simply have a poorer memory for the textthan good comprehenders. Although both memory for a text and inferencegeneration improve with age, the gains in general memory capacity cannotwholly account for the improvements in inference making (Omanson, Warren& Trabasso 1978). The evidence relating to comprehension skill, inferencemaking and memory for literal detail is contradictory. Oakhill (1982) foundthat skilled and less skilled comprehenders demonstrated equivalent recog-nition of verbatim statements from short texts, but similarly selected groupsdiffered in their ability to answer questions about information that was actu-ally presented in stories (Oakhill 1984). Yuill and Oakhill (1991) suggestedthat skilled comprehenders’ superior comprehension skills may aid theirmemory for text in general because they construct more integrated and there-fore more stable representations of texts. Thus, it is important to determinethe extent to which memory for literal details of a text explains inferentialprocessing.

Another possibility is that general knowledge deficits restrict perform-ance. Oakhill (1983) ruled out knowledge deficits as the source of poorcomprehenders’ failure to instantiate the most contextually appropriate mean-ing of category nouns. However, the gap-filling inferences in the current studyrely on the integration of general knowledge with information provided in thetext and are, therefore, different from the instantiations studied by Oakhill.It is important to assess whether children possessed the general knowledgerequired to make the gap-filling inferences in cases where they were not made(a crucial omission from Oakhill’s 1984 study).

A third possible source of inferential failure may be that poor compre-henders do not know when it is appropriate to make inferences. They may notrealise how particular inferences are cued: For example that text-connectinginferences are cued by mapping an instance of a non-specific noun to a later,more specific, referent, e.g. drink→ orange juice. An additional difficultymight be not knowing when it is permissible to bring in general knowledgefrom outside of a text in order to make sense of a passage, the type of pro-cessing necessary to make gap-filling inferences. If we find that children areable to draw inferences when guided, but do not do so when first asked a


Table 1. Example of test passage from Neale Analysis of Reading Ability (revised Britishedition) (Neale 1989)

Story

A bird hopped up to my window. I gave her some bread. She made a nest in my garden.Now I look after her little ones.

Questions

1. Where did the bird hop to?

2. What did the little boy/girl give the bird?

3. What did the bird do in the garden?

4. What does the little boy/girl do now for the bird?

© Marie D. Neale, 1958, 1988, 1989. Reproduced by permission of the publishersNFER-NELSON Publishing Company Ltd. All rights reserved.

question, it would seem likely that they are failing to use the textual cuesspontaneously.

Hence, this experiment was designed to investigate whether there was anyevidence to suggest that poor inferential skill was a cause of comprehensiondifficulties and, in addition, to explore possible reasons for comprehensionfailure.

Method

Participants. The skilled and less skilled comprehenders were selected in thefollowing way. The 7–8-year-old intake of six British Junior schools weretested on theGates-MacGinitie Primary Two Vocabulary Test(Gates & Mac-Ginitie 1965). This is a group administered task in which children have toselect one of four words that goes best with an accompanying picture. Thetest provides an index of a child’s ability to read and understand single wordsout of context. Performance on this test was used to exclude exceptionalreaders. The remaining 129 ‘average’ readers were assessed on Form Oneof the Neale Analysis of Reading Ability – Revised British Edition(Neale1989). The Neale Analysis is an individually administered test, comprised ofa series of short stories, graded in difficulty. Children read each story aloudand any word reading errors are corrected. After each story they are asked aseries of questions. Testing stops after the child has made a prescribed numberof reading accuracy errors on a given story. The Neale Analysis providesseparate age equivalent scores for both reading accuracy, based on the numberof word pronunciation errors that a child makes, and reading comprehension,


based on the number of questions about the stories that the child answerscorrectly.

The comprehension questions in the Neale Analysis tap recall of bothliteral information and that which can be inferred, as is evident from theexample story and questions provided in Table 1, which is the starting levelpassage and questions from Form One of this test. The Neale test was notdeveloped to assess different component skills of comprehension ability, e.g.literal memory versus inferential skills, thus it is not appropriate or possibleto analyse responses to the Neale questions on this basis. The purpose ofthe current investigation was to assess how one component skill of goodreading comprehension, inference making skill, is related to overall readingcomprehension skill, measured by this widely used test.

On the basis of performance on the Neale test, 29 less skilled compre-henders were selected to take part in further testing. The less skilled compre-henders all had age-appropriate reading accuracy, but their comprehensionages were below their chronological ages, and at least 6 months below theirreading accuracy age. The mean difference between reading comprehensionand reading accuracy was approximately 19 months. A comparison group ofskilled comprehenders was selected from the original sample. These childrenhad also obtained age-appropriate reading accuracy levels but their compre-hension scores were at or above that predicted by their reading accuracy age.The skilled and less skilled comprehender groups were matched for readingaccuracy,t(51)< 1.0 (skilled = 7 years and 10 months; less skilled = 7,11)but differed in reading comprehension,t(51) = 14.15,p < 0.001 (skilled =8,2; less skilled = 6,7).

The two groups were also matched for chronological age, Gates-MacGinitie vocabulary scores, and the number of stories that they had readfrom the Neale Analysis (allts< 1.0, see Table 2 for group means).1 Becausetesting on the Neale Analysis stops after a prescribed number of readingaccuracy errors, the latter measure was necessary to ensure that the skilledgroup’s higher comprehension scores did not arise simply because they hadread more stories and were therefore asked more comprehension questions.

The same tests were used for the selection of the comprehension-agematch (or CAM) group. All of the 6–7-year-old children in four Infantschools completed the Gates-MacGinitie vocabulary test. Because these chil-dren were a year younger than the older groups, a slightly lower standardon the Gates-MacGinitie was used to select the ‘average’ performers to betested on the Neale Analysis. Twenty-seven children were selected for furtherexperimental work. The criteria for this selection were that both their accur-acy and comprehension ages were within 6 months of their chronological ageand that there was no more than 6 months difference between the two scores.


Table 2. Group characteristics (and standard deviations)

Less skilled Skilled Comprehension-comprehenders comprehenders age match(n = 29) (n = 24) (n = 27)

Chronological age 7,8 (3.81) 7,8 (3.27) 6,8 (4.02)

Reading accuracy 7,11 (7.44) 7,10 (5.28) 6,8 (4.67)

Reading comprehension 6,7 (3.94) 8,2 (5.97) 6,8 (3.45)

Number of stories 3.31 (0.66) 3.33 (0.64) 2.37 (0.49)

Gates-MacGinitie 37.14 (3.46) 37.88 (2.92) 33.59 (3.60)

(max. = 48)

Note. Ages are given as years, months (with standard deviations in months). Thereading accuracy and reading comprehension scores are the age equivalent scoresprovided by the Neale test, and the number of stories read refers to the numbercompleted during the Neale assessment.

Furthermore, this group was selected so that their mean comprehension agewas not significantly different from that of the less skilled comprehenders,t(54) = 1.27, ns (less skilled = 6,7; CAM group = 6,8). Group means arepresented in Table 2.

The comprehension abilities of the younger comprehension-age matchgroup may have been underestimated because they completed fewer storiesduring Neale testing than the older children who had better reading accuracyskills and were, thus, asked a greater number of comprehension questions.Therefore the comprehension scores were re-analysed excluding the scoresobtained by older children on stories that had been too difficult for theyounger children to read. Ten children in the comprehension-age match grouphad completed three Neale stories, the remaining 17 children had completedtwo. Therefore, ten less skilled comprehenders matched to these 10 CAMchildren for comprehension skill had their scores from the first three storiesincluded in this re-analysis. The remaining less skilled comprehenders onlyhad their scores from the first two Neale stories considered (see Cain &Oakhill 1996, for further details on this procedure). This additional checkconfirmed the initial group selection: the two groups did not differ in thenumber of questions they answered correctly in this more stringent test,t(54)< 0.10. Thus, we can be satisfied that, in this sample, the CAM group was ofequivalent comprehension ability to the less skilled comprehenders. Whenre-analysed in a similar way, the skilled comprehenders’ scores remainedsignificantly better than the CAM group,t(49) = 4.57,p< 0.001, indicatingthat their superior comprehension skill was not simply because their superior


Table 3. Sample story and questions

Debbie was going out for the afternoon with her friend Michael. By the time theygot there they were very thirsty. Michael got some drink out of his duffel bag andthey shared that. The orange juice was very refreshing. Debbie put on her swimmingcostume but the water was too cold to paddle in, so they made sandcastles instead.

They played all afternoon and didn’t notice how late it was. Then Debbie spottedthe clock on the pier. If she was late for dinner her parents would be angry. They quicklypacked up their things. Debbie changed and wrapped her swimming costume in hertowel. She put the bundle in her rucksack. Then they set off for home, pedalling as fastas they could. Debbie was very tired when she got home, but she was just in time fordinner.

Questions

Literal information:

1. Who did Debbie spend the afternoon with?

2. Where was the clock?

Text-connecting inference:

3. Where did Michael get the orange juice from?

4. Where did Debbie put her towel when she packed up her things?

Gap-filling inference:

5. Where did Debbie and Michael spend the afternoon?

6. How did Debbie and Michael travel home?

word reading ability had enabled them to read more stories and, thus, answera greater number of comprehension questions. All of the children who parti-cipated in this study spoke British English as their first language and had noknown behavioural problems or learning difficulties.

Materials. Four experimental stories and a further practice story werewritten in a suitable vocabulary. The stories were between 137 and 150words in length. The children read each story and answered six questionsabout each one immediately after reading it. It was necessary to makean inference to correctly answer four of these questions. There were twoinstances of each type of inference: Text-connecting and gap-filling (asdescribed in the Introduction). In addition, there were two questions tappingliteral information that was explicitly stated in the story. An example of anexperimental story and questions is provided in Table 3.


Procedure. A pilot study was conducted first to test out the experimentalmethod, to detect and make changes to any ambiguous questions, and toensure that the task was not so easy as to result in ceiling levels of per-formance. Five skilled comprehenders participated. They all had reading andcomprehension ages at or above their chronological ages but they did notparticipate in the main study because they could not be matched with poorcomprehenders on all of the necessary criteria. Seventy-five percent of ques-tions tapping information that was either literally stated or could be inferredby means of a text-connecting inference were answered correctly. Perform-ance on the gap-filling inferences was slightly lower at 70%. These figuressuggested that the materials were at an appropriate level of difficulty. Theprocedure tested out in the pilot study worked well and was therefore used inthe experiment proper. This procedure was as follows.

The children were tested individually. After reading each story out loudthey were asked a set of questions about what happened in that story. Thequestions were not randomised, but referred to information in the order inwhich it had occurred in the story itself. When a child gave an incorrectanswer, first they were asked to look through the story again. If the child stillgave an incorrect answer, the experimenter directed them to the relevant partof the text, told them that it contained a clue, and repeated the question. If thechild was still having problems after this intervention, an additional questionwas asked to assess both their ability either to draw that inference (for text-connecting inferences) or to assess their general knowledge (for gap-fillinginferences). For example, when a text-connecting inference was not madethe experimenter read out the relevant part in the story, saying, for example,“It says here: ‘Debbie changed and wrapped her swimming costume in hertowel. She put the bundle in her rucksack.’ ” The child was then asked: “Isthe swimming costume part of the bundle?” and the original question wasrepeated. The questioning procedure for gap-filling inferences was as similaras possible, so as to be comparable. The experimenter again read out therelevant text, e.g. “It says here: ‘Then they set off for home pedalling as fastas they could.’ ” and asked “what sorts of things can we pedal?” After givingtheir response, i.e. bike or bicycle, the original question was repeated. Forquestions tapping literal information the appropriate line in the text was readout and the question repeated. A similar procedure was followed in instanceswhere no answer was given initially.


Results

Performance when questions were first asked

A two-way analysis of variance was performed on the initial response data:The mean number of correct responses when the questions were first askedand the text was covered. These data are reported in Table 4.

Table 4. Mean percentage of correct responses (and standard deviations) for eachskill group when text covered

Less skilled Skilled Comprehension-

comprehenders comprehenders age match

Literal 72.4 80.7 75.0

information (15.5) (16.0) (14.3)

Text-connecting 59.9 83.3 76.9

inference (17.5) (15.0) (12.8)

Gap-filling 52.6 70.3 58.3

inference (13.1) (14.7) (15.1)

There was a main effect of Skill Group,F(2, 77) = 16.33,p < 0.0001,and a main effect of Question TypeF(2, 154) = 32.33,p < 0.0001. Theseeffects were qualified by a significant interaction:F(4, 154) = 3.24,p <0.02. The between-group differences were tested using Bonferroni’st-teststo take the number of comparisons into account (using adjusted tables inHowell 1992). The less skilled comprehenders did not answer significantlyfewer of the literal questions correctly than the other groups, but they werepoorer at answering text-connecting inference questions than both the skilledcomprehenders,t′(51) = 5.17,p < 0.01, and the comprehension-age matchgroup, t′(54) = 4.11,p < 0.01. The less skilled comprehenders were alsopoorer than the skilled comprehenders on the gap-filling inference questions,t′(51) = 4.65,p< 0.01, but the difference between the less skilled and CAMgroups on this question type was not significant.

To explore further the relative contribution of literal memory and infer-ence making skill to reading comprehension, we conducted a series of linearfixed-order multiple regressions with reading comprehension ability as thedependent variable, taking into account the contribution of many of the vari-ables used in our initial selection and matching procedure. We also includedscores from The British Picture Vocabulary Scale (BPVS) (Dunn, Dunn,Whetton & Pintillie 1982), which is a measure of verbal ability. The scores


of the younger comprehension-age match were excluded from this analysisbecause they were not matched to the two other groups on a number ofvariables, e.g. age, reading accuracy, vocabulary skill. In each analysis thefirst three variables were entered in the following fixed order: chronologicalage; BPVS raw scores; Neale reading accuracy scores. At the fourth step weentered either the scores obtained for the literal questions, text-connectinginferences, or gap-filling inferences. These three analyses are summarised inthe top panel of Table 5.

Table 5. Summary of linear regressions predicting comprehension ability

Step Variable R square R2 change Level of significance

1 age 0.000 0.000 ns

2 BPVS (raw) 0.250 0.250 p< 0.001

3 reading accuracy 0.252 0.002 ns

4 literal scores 0.271 0.019 ns

4 text-connecting inferences 0.437 0.185 p< 0.001

4 gap-filling inferences 0.376 0.124 p< 0.004

4 literal scores 0.271 0.019 ns

5 text-connecting inferences 0.442 0.171 p< 0.001

5 gap-filling inferences 0.388 0.117 p< 0.005

Neither age (step 1) nor reading accuracy (step 3) contributed significantlyto the prediction of comprehension skill because the groups were matched onthese two variables. However, as would be expected, the verbal ability meas-ure (BPVS scores) did explain a significant portion of the variance in readingcomprehension skill when entered at step 2. More interesting is the findingthat literal recall scores did not predict additional variance when entered atstep 4, whereas both inference measures did. Two subsequent analyses con-firmed that inferencing ability continued to predict variance in comprehensionskill when entered as a fifth step, after literal recall (see bottom panel ofTable 5).

Performance when text was made available

Performance on all question types improved for all groups once the childrenhad been given the text to look over again but were not directed to the par-ticularly relevant portion of the text (see Table 6). Note that these responsesare collated from first and second responses. For this reason, these data are


Table 6. Mean percentage of correct responses for each skill group after textis available to refer to, undirected

Less skilled Skilled Comprehension-

comprehenders comprehenders age match

Literal 94.4 99.0 95.8

information (22.0) (18.3) (20.8)

Text-connecting 94.0 97.9 97.7

inference (34.1) (14.6) (20.8)

Gap-filling 67.7 82.3 73.6

inference (15.1) (12.0) (15.3)

Note.The values in parentheses are the percentage improvement from whenthe question was first asked.

not independent of those from the first analysis, so the pattern of results willsimply be described and not subjected to statistical analysis.

Most strikingly, the pattern of performance on literal and text-connectinginference questions was now the same for all three groups: All of the groupswere performing at or near ceiling level on the questions tapping these sorts ofinformation. Performance on the gap-filling inferences improved for all threegroups but did not reach ceiling levels of performance and the less-skilledcomprehenders and the CAM group continued to find this sort of inferenceharder than the skilled comprehenders.

Performance when directed to relevant part of the text

When children did not answer the question correctly after being allowed tolook at the text again, they were directed to the relevant part of the story andtold that there was a clue in that part. Even with this degree of help the less-skilled comprehenders and CAM group could not make all of the requiredgap-filling inferences. The percentage of correctly answered questions was95.8% for the skilled, 87.0% for the CAM, and 84.9% for the less-skilledchildren. The children who had not made the gap-filling inferences by thisstage were asked questions to test their general knowledge and their abilityto draw such inferences, as described in the method section. All childrenanswered all categories of questions correctly.


Discussion

This study was designed to identify the most likely direction of the relationbetween inferential skill and comprehension ability and, in addition, to invest-igate possible sources of less skilled comprehenders’ failure to make as manyinferences as skilled comprehenders. The findings relating to each of theseaims will be discussed, in turn.

When answering questions from memory, the skilled comprehenders werebetter at both types of inference than the less skilled comprehenders. Thisfinding supports previous research that has demonstrated a relation betweencomprehension and inferential skill in young children (e.g. Oakhill 1982,1984). However, as with previous work, this comparison alone does nottell us anything about the likely direction of the relation. We addressed thedirection of this relation by comparing the performance of the less skilledcomprehenders and younger children of equivalent comprehension ability, theCAM group. The CAM group’s superior performance on the text-connectinginferences indicates that, rather than poor comprehension causing inadequateinference making skills, poor comprehension is (at least in part) the resultof a failure to make sufficient inferences. The additional regression analysesconfirm the relation between reading comprehension and inference makingskill. However, the CAM group were not significantly better than the lessskilled comprehenders on the gap-filling inferences, which all three groupsfound more difficult. It may be that competence with this type of inferenceemerges later in development than for the other type investigated in this study,and that differences between less skilled comprehenders and CAM childrenmight be apparent in older age groups.

The second aim of this study was to explore possible sources of inferentialfailure. One source of poor performance on the inference questions may bedeficient memory for the text as a whole. Previous work on this issue hasproved inconclusive (e.g. Oakhill 1982, 1984; Omanson et al. 1978). In thecurrent study, the less skilled comprehenders were not significantly poorer atanswering questions about literal information despite their inferential diffi-culties, and inference making improved when the text was available. Thus,the less skilled comprehenders’ initially poor performance on the inferencequestions cannot simply be attributed to poor memory for the text per se.Indeed, when we controlled for performance on literal questions in the regres-sion analyses, inferential processing remained a strong predictor of readingcomprehension level.

The improvement in performance by poor comprehenders when theirerrors were pointed out to them, and they could search through the textagain, demonstrates that they were capable of making inferences. Indeed,when given such prompting the less skilled comprehenders’ ability to answer


text-connecting inference questions was comparable with that of the othertwo groups. It is difficult to attribute their initial difficulties to a poor under-standing of how this type of inference is cued, because the less skilledcomprehenders were capable of making these links when allowed to go backto the text. One reason for the less skilled comprehenders’ initial failure maybe that they approach the task of reading with a different set of aims tothe skilled comprehenders, focusing more on word reading accuracy ratherthan comprehension monitoring (e.g., Garner & Kraus 1981–1982; Yuill &Oakhill 1991). Thus, skilled comprehenders in this study may simply be morelikely to make inferences to integrate sentences and fill in details that arejudged to be missing when they reflect on their model of the text, becausethey are more likely to be striving for coherence. Use of such cues may havebecome a fairly automatic reading strategy for them. In addition, it is not clearfrom these data whether the differences between groups arose during readingor when retrieving information to answer questions, an issue that needs to beaddressed in future work.

Although the less skilled comprehenders improved their performance onthe text-connecting inferences when the text was uncovered, they were stillpoorer on the gap-filling inferences than the other two groups. We can ruleout deficient text searching skills as the source of this difference becausethe less skilled comprehenders were able to locate the information necessaryfor the other question types under such conditions. Furthermore, question-ing revealed that all of the children possessed the requisite knowledge toanswer these questions. Thus, failure to make this type of inference cannot beattributed to deficits in general knowledge. Again, strategy differences maybe the source of this finding: The less skilled comprehenders may be poorerat knowing when and how to relate general knowledge to the text in order tosupply missing details.

In summary, the design of this experiment enabled us to assess the likelydirection of the relation between comprehension skill and inference makingfound in previous work. The pattern of performance suggests that skill atdrawing inferences (at least, text-connecting ones) is more plausibly a causeof comprehension failure rather than a result of it. A more stringent test ofthe direction of causality would be to train children to make inferences. If thepoor comprehenders benefit more from such training than their skilled peerswe can assume that a deficit in the trained behaviour can lead to compre-hension difficulties. Indeed, there is already some evidence to support thisconclusion. Poor comprehenders benefit more than skilled comprehendersfrom training programmes that focus on how to make inferences from keywords in a text, and such gains transfer to other measures of comprehension(Yuill & Oakhill 1988; Yuill & Joscelyne 1988). Thus, instruction in how to


make inferences has, so far, yielded positive results and should be exploredfurther.

However, training will only be beneficial if the skills crucial for mak-ing inferences are included in the programme. In the current study we haveidentified certain skills that we think are suitable for future training, namelyknowledge about the aims and purposes of reading and, in particular, knowinghow to recognise and use the implicit and explicit cues that signal that aninference is required. Thus, in future training work it would be prudent tofocus on these abilities.

Acknowledgments

This work was conducted whilst the first author was in receipt of a studentshipfrom the Economic and Social Research Council. We would like to thank thestaff and pupils from all of the Brighton & Hove schools who participatedin this work. An abbreviated account of this experiment appears in Hulme,C. & Joshi, R. M. (1998)Reading and Spelling: Development and Disorder.Mahwah, NJ: Lawrence Erlbaum Associates.

Note

1 Our own work has demonstrated that skilled and less skilled comprehenders do not differon measures of phonological or syntactic skills (Cain, Oakhill & Bryant 2000 (forthcoming);Yuill & Oakhill 1991, cf. Stothard & Hulme 1992). Thus, basic linguistic abilities do notappear to be the cause of the less skilled group’s comprehension difficulties.

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Address for correspondence:K. Cain, Laboratory of Experimental Psychology, University ofSussex, Brighton BN1 9QG, UKPhone: +44 1273 877056; Fax: +44 1273 678611; E-mail: [email protected]

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Cain Oathill 1999 - Inference Making Ability and Its Relation to Comprehension Failure in Young Children