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Understanding the nature and severity of reading difficulties among students with language and reading comprehension difficulties

  • Published: 07 May 2022
  • Volume 72 , pages 249–275, ( 2022 )

Cite this article

  • Philip Capin   ORCID: orcid.org/0000-0003-4955-9879 1 ,
  • Sandra L. Gillam   ORCID: orcid.org/0000-0003-4401-4669 2 ,
  • Anna-Maria Fall   ORCID: orcid.org/0000-0002-6257-6684 1 ,
  • Gregory Roberts   ORCID: orcid.org/0000-0003-3063-0559 1 ,
  • Jordan T. Dille   ORCID: orcid.org/0000-0002-5110-8973 3 &
  • Ronald B. Gillam   ORCID: orcid.org/0000-0003-0106-1908 2  

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This study investigated the presence of word reading difficulties in a sample of students in Grades 1–4 ( n  = 357) identified with language and reading comprehension difficulties. This study also examined whether distinct word reading and listening comprehension profiles emerged within this sample and the extent to which these groups varied in performance on cognitive and demographic variables. Findings showed that the majority of students (51%) with language and reading comprehension difficulties demonstrated significant risk in word reading (more than 1 SD below the mean), even though the participant screening procedures did not examine word reading directly. Three latent profiles emerged when students were classified into subgroups based on their performance in listening comprehension (LC) and word reading (WR): (1) severe difficulties in LC and moderate difficulties in WR (11%), (2) mild difficulties in both LC and WR (50%), and (3) moderate difficulties in LC and mild difficulties in WR (39%). Of note, even though students were identified for participation on the basis of poor oral language and reading comprehension abilities, all profiles demonstrated some degree of word reading difficulties. Findings revealed there were differences in age and performance on measures of working memory, nonverbal reasoning, and reading comprehension performance between profiles. Implications for educators providing instruction to students with or at risk for dyslexia and developmental language disorders were discussed.

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This research was supported by the Institute of Education Sciences, US Department of Education, through Grant R305A170111. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Institute of Education Sciences or the US Department of Education.

Ronald B. Gillam receives royalties from the sale of the Test of Narrative Language, which was administered to the participants. No other authors have any conflicts of interests to disclose.

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Capin, P., Gillam, S.L., Fall, AM. et al. Understanding the nature and severity of reading difficulties among students with language and reading comprehension difficulties. Ann. of Dyslexia 72 , 249–275 (2022). https://doi.org/10.1007/s11881-022-00255-3

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Received : 08 December 2021

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DOI : https://doi.org/10.1007/s11881-022-00255-3

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ORIGINAL RESEARCH article

The overlap of poor reading comprehension in english and french.

\r\nNadia D&#x;Angelo*

  • 1 Ontario Ministry of Education, Toronto, ON, Canada
  • 2 Department of Applied Psychology & Human Development, Ontario Institute for Studies in Education, University of Toronto, Toronto, ON, Canada

This study examined overlap and correlates of poor reading comprehension in English and French for children in early French immersion. Poor comprehenders were identified in grade 3 in English and French using a regression method to predict reading comprehension scores from age, non-verbal reasoning, word reading accuracy, and word reading fluency. Three groups of poor comprehenders were identified: 10 poor comprehenders in English and French, 11 poor comprehenders in English, and 10 poor comprehenders in French, and compared to 10 controls with good reading comprehension in both English and French. There was a moderate degree of overlap in comprehension difficulties in English and French among poor comprehenders with equivalent amounts of exposure to French, with a prevalence rate of 41.7% in our sample. Children who were poor comprehenders in both English and French consistently scored the lowest on English vocabulary in grade 1 and grade 3 and in French vocabulary in grade 3 suggesting that poor comprehenders’ vocabulary weaknesses in English as a primary language may contribute to comprehension difficulties in English and French.

Introduction

There is considerable evidence to suggest that children who are at risk for reading difficulties in a second language (L2) can be identified through early assessment of word reading and cognitive skills in their first language (L1), before their oral language proficiency is fully developed in L2 ( Geva and Clifton, 1994 ; Da Fontoura and Siegel, 1995 ; MacCoubrey et al., 2004 ). Much of this previous research is based on the premise that certain cognitive and linguistic skills, such as phonological processing, transfer across languages (e.g., Comeau et al., 1999 ; August and Shanahan, 2006 ). More recently, studies have investigated children’s reading comprehension difficulties that occur despite age-appropriate decoding skills (e.g., Nation et al., 2010 ; Tong et al., 2011 ). Relatively little is known about the identification of poor reading comprehension in the absence of poor decoding, and even less is known about whether reading comprehension difficulties manifest in a similar manner in L1 and L2 for children learning in a bilingual context. The present study aims to investigate overlap and early contributors of poor reading comprehension for children in early French immersion programs in Canada who receive school instruction in French, an additional language, while being exposed to English, their primary language of the community.

Reading comprehension is a complex process that involves the integration and coordination of various skills, including word decoding, the ability to decipher or recognize printed words, and oral language or listening comprehension, the ability to understand what is decoded in spoken form (Simple View of Reading; Gough and Tunmer, 1986 ). Most research into reading comprehension difficulties has focused on children with poor decoding whose weaknesses manifest early in reading development as phonological awareness and word reading deficits (e.g., Snowling, 2000 ). In contrast to poor decoders, poor comprehenders’ difficulties appear to emerge later, when decoding becomes automatized and more variance in reading comprehension is accounted for by oral language skills ( Catts et al., 2012 ). Oral language difficulties tend to be masked by poor comprehenders’ age-appropriate decoding skills, and as a result, early indicators of later reading comprehension difficulties are often overlooked.

Existing longitudinal studies have used a retrospective approach to examine poor comprehenders’ deficits across previous grades and suggest that oral language weaknesses are prevalent in poor comprehenders before their reading comprehension difficulties become apparent ( Catts et al., 2006 ; Nation et al., 2010 ; Tong et al., 2011 ). For example, Nation et al. (2010) identified poor comprehenders based on reading achievement at age 8 and retrospectively examined their reading and language skills beginning at age 5. While poor comprehenders’ phonological processing and word reading skills progressed over time, their oral language skills remained persistently weak, suggesting that early weaknesses in understanding and producing spoken language contributed to poor comprehenders’ comprehension difficulties.

The linguistic interdependence hypothesis suggests that L1 and L2 reading skills are interdependent, and that language and literacy skills acquired in one language facilitate reading development in the L2 ( Cummins, 1984 ). Thus, it seems probable that the same cognitive and linguistic skills needed for successful reading comprehension in L1 contribute to reading development in L2 (e.g., Gottardo and Mueller, 2009 ; Mancilla-Martinez and Lesaux, 2010 ). Indeed, previous research suggests that it is possible to identify children at-risk for L2 reading difficulties based on their performance in L1 ( Geva and Clifton, 1994 ; Da Fontoura and Siegel, 1995 ). However, few studies have investigated poor comprehenders in a bilingual context largely due to the complexity of understanding reading comprehension processes in L1 and L2. Children learning in an L2 are in the process of acquiring the language of instruction and it may be difficult to determine whether weaknesses in L2 reading comprehension reflect limited language learning experiences or are indicative of a language or reading impairment ( Paradis et al., 2010 ; Li and Kirby, 2014 ; D’Angelo and Chen, 2017 ).

Li and Kirby (2014) examined the reading comprehension profiles of grade 8 emerging Chinese-English bilinguals in an English immersion program in China. Poor comprehenders were distinguished from average comprehenders based on their performance on English L2 vocabulary measures. The authors concluded that because the groups did not differ on Chinese L1 word reading and reading comprehension, poor comprehenders’ reading comprehension difficulties were due to limited English L2 proficiency. However, the comprehender groups in this study were selected using English L2 assessments only and therefore, children with an underlying oral language impairment across the two languages could not be identified. Since Chinese and English and are not closely related languages, vocabulary and reading comprehension may not have the same underlying mechanisms in each language.

A few studies have identified poor comprehenders based on English L1 reading performance in a French immersion context and suggest that poor comprehenders demonstrate relatively poor oral language skills in both English L1 and French L2 (e.g., D’Angelo et al., 2014 ; D’Angelo and Chen, 2017 ). D’Angelo et al. (2014) retrospectively investigated the reading and language abilities of a small sample of English L1 children in French immersion who were identified as poor and average comprehenders based on their English L1 reading performance in grade 3. They found that poor comprehenders scored relatively lower on English and French vocabulary across grades 1 to 3, despite average phonological awareness and word reading skills in both languages. Such findings suggest that poor comprehenders may indeed have an underlying problem in oral language. The current study extends the existing research to a larger, more representative sample of children in French immersion to facilitate comparison. The purpose is to determine the extent to which those identified as having poor reading comprehension in English, the societal language, also demonstrate poor reading comprehension in French, an additional language and the language of instruction.

Studies that have examined the co-occurrence of reading difficulties between an L1 and L2 have primarily focused on poor readers and suggest that there is some overlap of reading difficulty in L1 and L2 ( Manis and Lindsey, 2010 ; McBride-Chang et al., 2013 ; Tong et al., 2015 ; Shum et al., 2016 ). For example, Manis and Lindsey (2010) found that 55% of grade 5 children who met the criteria for reading difficulties in English L2 (decoding scores at or below the 25 th percentile) were also identified with reading difficulties in Spanish L1. Similarly, McBride-Chang et al. (2013) tested the overlap of poor readers in Chinese L1 and English L2 (defined as those at or below the 25 th percentile on Chinese and English word reading tests) among 8-year-old children in Beijing and found that 40% of poor readers in Chinese L1 were also poor readers in English L2. In each study, children who were identified as poor readers in both languages scored lower on cognitive and linguistic tasks than children who were poor readers in only one language. On the other hand, children with poor reading in one language did not necessarily have difficulties in the other. It appears that the degree of overlap between poor reading is increased when the two languages are more closely related. However, these studies focused on the overlap status of poor readers based on poor decoding. We were interested in whether such overlap occurs for poor comprehenders who show discrepancies between their reading comprehension and decoding skills.

Only one known study at this time has explored the overlap between L1 and L2 reading comprehension difficulties. Tong et al. (2017) examined the co-occurrence of reading comprehension difficulties and associated longitudinal correlates in 10-year-old children with poor reading comprehension (defined as those at or below the 25 th percentile on reading comprehension tasks) in Chinese L1 and English L2. The authors found that approximately half (53%) of children with poor reading comprehension in Chinese L1 also experienced poor reading comprehension in English L2. Results indicated that word reading and language skills were longitudinal correlates of poor reading comprehension in Chinese and English. This study was among the first to investigate overlap of reading comprehension difficulties in L1 and L2 and to retrospectively examine sources of poor reading comprehension. However, the selection method used in this study identified poor comprehenders based on reading comprehension scores only and did not distinguish between children with poor oral language skills from those with poor decoding skills. In the present study, we aimed to understand the overlap of poor reading comprehension in English and French in the absence of decoding problems.

Given the challenges associated with defining poor reading comprehension in an additional language, the goal of the present study was to extend previous research on reading comprehension difficulties to English–French bilinguals to answer two specific research questions.

First, we asked whether children identified as poor comprehenders in English are also identified as poor comprehenders in French. Whereas most previous studies have examined overlap with word reading and reading comprehension scores at or below an arbitrary cut-off score, we utilized a regression technique to identify poor comprehenders in English and French by examining associations between reading comprehension scores, age, non-verbal reasoning, word reading accuracy, and word reading fluency. This approach defines groups more precisely than the cut-off score method because it examines relative discrepancies between various skills related to reading comprehension by distinguishing poor comprehenders from average and good comprehenders (e.g., Tong et al., 2011 , 2014 ; Li and Kirby, 2014 ; D’Angelo and Chen, 2017 ).

Second, we asked what reading and language skills distinguish between poor comprehenders in English and French, poor comprehenders in English, and poor comprehenders in French. We anticipated that children identified as poor comprehenders in both English and French would show early and persistent oral language difficulties in both languages. English and French share many similarities in vocabulary, morphology, and syntax (e.g., LeBlanc and Seguin, 1996 ; Roy and Labelle, 2007 ; D’Angelo and Chen, 2017 ; D’Angelo et al., 2017 ). Both are represented by the Roman alphabet and an opaque writing system ( Seymour et al., 2003 ). These shared structural properties are thought to facilitate cross-language associations between two languages ( Koda, 2008 ). Therefore, we expected to see similar characteristics of reading comprehension difficulties between the two languages.

The socio-linguistic and educational context of the current study makes it possible to assess and compare English and French reading outcomes among children acquiring both languages. In Canada, French immersion is an additive dual language program that promotes oral and written language proficiency in both English and French, the official languages. Children in early French immersion programs are non-francophones who receive integrated language and content instruction primarily in French beginning in kindergarten or grade 1. However, these children often live in predominantly English-speaking environments with limited opportunity to hear and speak French outside of the classroom. Thus, French immersion classrooms are comprised of English-speaking children for whom French is the L2 and minority language children for whom English is the L2 and French the L3. English language arts instruction is generally introduced in grade 4.

Since the children in this study had similar and limited levels of French proficiency upon school entry, any differences in French reading and language abilities between children would be unlikely a result of differences in the amount of exposure the children had to French. Specifically, for children with poor reading comprehension in both English and French, we could be confident that weaknesses in oral language reflect a pervasive language impairment rather than a less developed French proficiency.

Materials and Methods

Participants.

Participants were 180 children consisting of 83 males and 97 females who were recruited from early French immersion schools in a large Canadian city and tested in English and French in the spring of grade 1 ( M age = 80.36 months, SD = 4.18) and grade 3 ( M age = 104.66 months, SD = 4.06). As part of the inclusion criteria, children selected for this study were non-native speakers of French receiving school instruction entirely in French since school entry. Out of the 180 children, 135 (75%) spoke English as a primary language. Forty-five children (25%) were exposed to additional languages at home.

The data in this study are from longitudinal research, in which several reading-related tasks were administered to participants between grades 1 and 3. Trained research assistants, who were fluent in the respective test language, administered tasks to participants at school. English and French instructions were used for French measures to ensure comprehension of the task. The order of the sessions was counterbalanced across participants and within each session the order of the task administration was randomized. Due to limited testing time, not all the same tasks were administered in each year of the study.

Non-verbal Reasoning

Children were administered the reasoning by analogy subtest of the Matrix Analogies Test in English to assess non-verbal reasoning in grade 1 (expanded form; Naglieri, 1985 ). For each item, children were asked to complete a figural matrix by choosing the missing piece from 5 to 6 possible choices. There were 16 items and testing was discontinued after four consecutive errors.

Phonological Awareness

This task was measured in grade 1 using the elision subtest of the Comprehensive Test of Phonological Processing (CTOPP; Wagner et al., 1999 , 2013 ). The examiner read individual words aloud and children were asked to delete a syllable or phoneme from each word (e.g., “say time without saying/ m /”). There were 34 test items presented in order of increasing difficulty. Testing was discontinued after three consecutive errors.

A parallel measure was created to assess phonological awareness in French. Twenty-six items were selected to match characteristics of the English task (i.e., syllable and phoneme deletion) and presented in order of increasing difficulty. The administration of the test was discontinued if the children made six consecutive errors.

The Peabody Picture Vocabulary was used to measure English receptive vocabulary (PPVT-IV Form A; Dunn and Dunn, 2007 ) in grades 1 and 3. Each time a tester orally presented a target word, the child was required to point to one of four pictures that best corresponded to that word. Testing was discontinued when the child made eight or more errors in a set of 12.

The Échelle de Vocabulaire en Images Peabody (EVIP Form A; Dunn et al., 1993 ) was used to assess French receptive vocabulary in both grades. The examiner read a target word and the child was asked to identify the picture that best represented the word from a set of four pictures. Testing was discontinued after six errors were made on the previous eight consecutive items.

Word Reading Accuracy

Word reading accuracy in English was assessed in grades 1 and 3 with the Letter-Word Identification subtest from the Test of Achievement, Woodcock Johnson-III (WJ-III; Woodcock et al., 2001 ). Children were asked to read a series of 76 letters and words that were presented in order of increasing difficulty. Testing was discontinued after participants misread the six consecutive highest-numbered items on a given page.

French word reading accuracy was assessed using an experimental task ( Au-Yeung et al., 2015 ). The test consists of 120 items arranged in 15 sets of eight words each. The children were asked to read the words accurately and fluently. Testing was discontinued when the children misread five or more words within a set of eight words. The total score represents the number of words read correctly.

Word Reading Fluency

Children’s word reading fluency in English was measured by the Sight Word Efficiency subtest of the Test of Word Reading Efficiency (TOWRE Form A; Torgesen et al., 1999 ) in grade 3. Children were provided with 45 s to quickly and accurately identify as many words as they could from a vertical list of 104 items. A parallel experimental measure was created to assess word reading fluency in French.

Reading Comprehension

The comprehension subtest (Level 3 Form S) of the Gates-MacGinitie Reading Tests (GMRT; MacGinitie et al., 2000 ) was used to assess children’s English reading comprehension in grade 3. Children were asked to read short passages and answer 48 corresponding multiple-choice questions. The score was the total number of correct answers. Level C Form 4 of the Gates-MacGinitie Reading Tests – Second Canadian Edition ( MacGinitie and MacGinitie, 1992 ) was translated into French and administered in the same way as the English task.

To prepare the data for analyses, we first examined whether there was statistical support for merging the samples of children who spoke English as a primary language at home and those who were exposed to additional home languages into one sample. A Box’s M test using the grades 1 and 3 measures, indicated no significant difference in variance-covariance patterns between the two language groups on English, Box’s M = 40.88, p = 0.09, and French, Box’s M = 7.74, p = 0.99, reading and language measures. Based on these results, the two groups were combined to create one sample. Table 1 presents the mean raw scores, standard scores for standardized measures, standard deviations and reliability estimates for the entire sample on all English and French measures in grade 1 and grade 3.

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Table 1. Means, standard deviations, and reliabilities for the total sample ( N = 180) on English and French measures in grade 1 and grade 3.

We selected groups of comprehenders in grade 3 using separate regression techniques for English and French measures to predict children’s reading comprehension scores from age, non-verbal reasoning, word reading accuracy, and word reading fluency. These variables are correlated with reading comprehension (e.g., Deacon and Kirby, 2004 ; Lesaux et al., 2006 ) and have been widely used for identifying comprehender subgroups ( Li and Kirby, 2014 ; Tong et al., 2014 ; D’Angelo and Chen, 2017 ). Together, the predictors explained a total of 43% of the variance in English reading comprehension and 37% of the variance in French reading comprehension. The observed reading comprehension scores were plotted against the standardized predicted scores. Children below the lower 65% confidence interval of the regression line were identified as poor comprehenders and those above the upper 65% confidence interval were identified as good comprehenders. Those children who scored within the 15% confidence interval were identified as average comprehenders. Children with very poor or good word reading skills (predicted value 1 SD above or below the mean) were not selected and excluded from analyses.

Through this regression method, we identified three groups of comprehenders in English (24 poor, 24 average, and 24 good) and three groups of comprehenders in French (24 poor, 24 average, and 24 good). Sixteen children out of the 24 poor comprehenders of English and 18 children out of the 24 poor comprehenders of French identified as English-speaking. 1 The remaining children came from diverse linguistic backgrounds and were exposed to additional languages at home, including Russian, Hebrew, and Mandarin. A chi-square test of independence indicated a non-significant relationship between the children who spoke English as a primary language at home and those who were exposed to additional languages at home within the comprehender groups identified in English, χ 2 (1, N = 72) = 3.11, p = 0.21, and in French, χ 2 (1, N = 72) = 1.01, p = 0.61. Based on these results, and given that the children exposed to additional languages met the inclusion criteria (non-native speakers of French), they were retained in the sample.

We conducted multivariate analyses of variance (MANOVAs) to confirm the reading comprehension profiles of the English comprehender groups and to determine whether poor comprehenders differed from average and good comprehenders on English and French reading-related measures in grade 1 and grade 3. As illustrated in Table 2 , there were no significant differences between the three groups on age, non-verbal reasoning, English and French word reading accuracy, and English and French elision in grade 1 and English and French word reading accuracy and fluency in grade 3 (all p s > 0.08). However, as expected, poor comprehenders differed significantly from average ( p < 0.001) and good comprehenders ( p < 0.001) on English and French reading comprehension in grade 3. Poor comprehenders also differed from average ( p < 0.001) and good comprehenders ( p < 0.001) on English vocabulary in grade 1 and grade 3. Similarly, French vocabulary distinguished poor comprehenders from average comprehenders in grade 1 ( p < 0.05) and grade 3 ( p < 0.01).

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Table 2. Means (standard deviations) of poor, average, and good comprehenders selected with English measures on English and French reading and language variables in grade 1 and grade 3.

For the comprehender groups identified using French measures, there were no significant differences between poor, average, and good comprehenders on age, non-verbal reasoning, and English and French phonological awareness in grade 1. Poor comprehenders differed significantly from average and good comprehenders on grade 1 measures of English ( p < 0.01) and French vocabulary ( p < 0.01) and English ( p < 0.001) and French word reading accuracy ( p < 0.001). In grade 3, English ( p < 0.05) and French vocabulary ( p < 0.001), English word reading accuracy ( p < 0.001), English ( p < 0.001) and French word reading fluency ( p < 0.001), and English ( p < 0.001) and French reading comprehension ( p < 0.001) distinguished poor comprehenders from average and good comprehenders ( Table 3 ).

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Table 3. Means (standard deviations) of poor, average, and good comprehenders selected with French measures on English and French reading and language variables in grade 1 and grade 3.

Table 4 presents the prevalence rates of the overlap between comprehender groups in English and French. Of particular interest to this study was the number of children who were identified through the regression technique as poor comprehenders for both English and French relative to the entire sample. Three subgroups of reading comprehension difficulties in the two languages were considered: 10 children who were poor comprehenders in both English and French (PCB), 11 children who were poor comprehenders in English only (PCE), and 10 children who were poor comprehenders in French only (PCF). We selected an additional 10 children from among the good comprehenders in both English and French, matched on age and gender, to serve as the control group. In this way, we could compare the three groups of comprehenders to children who had average English and French word reading skills, but good comprehension in both English and French. There were no significant differences between the four groups on age (PCB: M = 104.26, SD = 3.97; PCE: M = 105.01, SD = 4.98; PCF: M = 104.01, SD = 4.40; Control: M = 105.02, SD = 3.46) and non-verbal reasoning (PCB: M = 3.80, SD = 3.01; PCE: M = 2.82, SD = 2.40; PCF: M = 3.80, SD = 2.25; Control: M = 5.00, SD = 4.14). Chi-square results demonstrated that the chance of poor comprehenders in English also being poor comprehenders in French was significantly above the baseline level, χ 2 (1, N = 180) = 14.02, p < 0.001.

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Table 4. The overlap and distribution of poor reading comprehension in English and French.

It should be noted that children identified as poor comprehenders in English only had not been selected for a comprehender status in French. Similarly, those identified as poor comprehenders in French only did not fit a comprehender group in English. Of the remaining children who were poor comprehenders identified in English, two were average comprehenders in French and one was a good comprehender in French. Of the remaining poor comprehenders identified in French, two were average comprehenders in English and two were good comprehenders English.

The next step in our analyses was to retrospectively examine the correlates of English and French reading comprehension difficulties for each of the three subgroups of poor comprehenders and the control group. We conducted separate MANOVAs, controlling for gender, for the English and French reading and language measures in each grade. Univariate analyses were computed for tasks tested at one time point only (i.e., English and French phonological awareness, English and French word reading fluency, and English and French reading comprehension). Table 5 shows the mean raw scores and standard deviations of the English and French reading and language measures for each group in grade 1 and grade 3, as well as comparisons across groups.

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Table 5. Means (standard deviations) and comparisons of poor comprehenders in English and French, poor comprehenders in English only, poor comprehenders in French only, and controls on English and French measures in grade 1 and grade 3.

As expected, there were no significant differences between the four groups on the word reading measures used to select comprehender groups, word reading accuracy and fluency, for both English and French in grade 3, and consistent findings were revealed retrospectively for English and French word reading accuracy in grade 1. Similarly, the groups did not differ significantly on English and French phonological awareness in grades 1 and 3.

Results of univariate analyses showed that there was a significant overall group effect for English reading comprehension, F (3,41) = 38.83, p < 0.001, η p 2 = 0.76 and French reading comprehension, F (3,41) = 37.84, p < 0.001, η p 2 = 0.76. Tukey’s HSD post hoc comparisons showed that the PCB, PCE, and PCF groups performed worse than the control group on English reading comprehension in grade 3. The PCB group also scored significantly lower than the PCF group on English reading comprehension. For French reading comprehension in grade 3, all three poor comprehender groups (PCB, PCE, and PCF) scored significantly lower than the control group, with the PCF group also scoring lower than PCE group.

There was a significant overall group effect for English vocabulary, Wilks’ Λ = 0.41, F (6,70) = 6.64, p < 0.001, η p 2 = 0.36, and French vocabulary, Wilks’ Λ = 0.29, F (6,72) = 3.60, p < 0.05, η p 2 = 0.22. Univariate tests revealed that the four groups differed significantly in English vocabulary in grade 1, F (3,41) = 9.05, p < 0.001, η p 2 = 0.43, and in grade 3, F (3,41) = 13.47, p < 0.001, η p 2 = 0.54. Tukey’s HSD post hoc comparisons showed that children in the PCB and PCE groups scored significantly lower than the control group on English vocabulary in grades 1 and 3. However, in grade 3, the PCB group also scored lower than the PCF group on English vocabulary. The univariate tests for French vocabulary found no significant difference between groups on grade 1 French vocabulary, but there were significant group differences on French vocabulary in grade 3, F (3,41) = 3.04, p < 0.05, η p 2 = 0.20. The post hoc test for French vocabulary showed that the PCB and PCF groups had significantly lower scores than control groups on French vocabulary in grade 3. The PCB group also had lower French vocabulary scores than the PCE group in grade 3. 2

The aim of the present study was to investigate correlates and overlap of reading comprehension difficulties for bilingual poor comprehenders who are exposed to English, the societal language, and French, the language of classroom instruction. By identifying poor comprehenders of both English and French, we were able to determine to what extent poor comprehenders in English, a primary language, are also poor comprehenders in French, an additional language.

We found that there is a moderate degree of overlap in comprehension difficulties in English and French among poor comprehenders with equivalent amounts of exposure to French, with a prevalence rate of 41.7% in our sample. However, our findings also indicate that children who have reading comprehension difficulties in one language do not necessarily have difficulties in another. In addition, we found that English and French vocabulary was a strong and persistent indicator of reading comprehension difficulties in the same language for poor comprehenders of English, French, and both English and French.

Consistent with previous studies, results demonstrate that deficits in oral language are characteristic of children with poor reading comprehension (e.g., Nation et al., 2004 , 2010 ; Catts et al., 2006 ). Building on previous work ( D’Angelo et al., 2014 ), we found that poor comprehenders of English who received classroom instruction in French demonstrated concurrent vocabulary weaknesses in English and French relative to average and good comprehenders, despite comparable word decoding skills. Lower English vocabulary scores distinguished poor comprehenders from average and good comprehenders, whereas lower French vocabulary scores distinguished poor comprehenders from good comprehenders but not from average comprehenders. Similarly, for children identified in French, poor comprehenders differed from average and good comprehenders on English vocabulary, and from good comprehenders, but not average comprehenders on French vocabulary. These findings suggest that the average comprehenders in this study may have not yet reached a level of French proficiency needed to move beyond the performance of the poor comprehenders on French vocabulary. Vocabulary acquisition in French, an additional language, may be more challenging for immersion children because of their limited exposure to French outside of the classroom. Future research should include measures of cognitive abilities, such as phonological short-term memory that may be better at distinguishing group differences in the early grades ( Farnia and Geva, 2011 ).

Regardless of English or French identification, the retrospective analyses indicated that differences between the three comprehender groups in English and French vocabulary were apparent in grades 1 and 3, with no group differences on English and French phonological awareness in grade 1. These findings clearly demonstrate that poor comprehenders’ oral language weaknesses are evident in the early stages of learning to read in both English and French. Although our study examines poor comprehenders in a bilingual context, these results are strikingly similar to findings reported by Catts et al. (2006) and Nation et al. (2010) and confirm that vocabulary weaknesses are apparent before poor comprehenders’ reading comprehension difficulties emerge. However, our study also found that there were differences between poor and average and good comprehenders identified in French on word reading measures in grade 1 and grade 3, indicating that different skills may lead to poor reading comprehension in English and French, and French reading comprehension may be more dependent on word level skills.

This study is the first to demonstrate that children with poor reading comprehension may experience difficulties with comprehension in English, in French, or in both English and French. Of these groups, children who were poor comprehenders in both English and French consistently scored the lowest on English vocabulary in grade 1 and grade 3 and in French vocabulary in grade 3 suggesting that severe English vocabulary weaknesses in poor comprehenders may contribute to comprehension difficulties in English and French. While there were no significant group differences found on phonological awareness, word reading and word fluency tasks, it is interesting to note that the poor comprehenders of both English and French, who were the poorest on English and French reading comprehension, also scored the lowest on all English and French reading and language measures in both grades 1 and 3. Results provide support for the linguistic interdependence hypothesis and suggest that children with poor reading comprehension in L1 may be at risk for being a poor comprehender in L2.

We found that 41.7% of children classified as poor comprehenders in grade 3 were poor comprehenders of both English and French. As expected, this overlap is less than reported in previous studies (e.g., Tong et al., 2017 ) in part due to differences in the approach to defining poor comprehender groups. More specifically, whereas most previous studies have defined poor comprehender groups based on a cut-off score on word reading, reading comprehension, or both, the present study utilized a regression method to identify poor comprehenders based on the relative discrepancy between wording reading, word reading fluency, and reading comprehension, while controlling for age and non-verbal reasoning, therefore, avoiding overidentification and narrowing the sample of children who qualify for poor comprehender status.

However, it could be argued that the overlap between English and French poor comprehender status should be greater given that English and French are alphabetic orthographies and share many linguistic features. It is worth noting that children in this study had been receiving classroom instruction in French for approximately 3 years at the time of comprehender classification. It is possible that children’s poor comprehension in French would have been more apparent had they been exposed to French for a longer period of time. This explanation is consistent with that of previous research, which has demonstrated that relative to poor decoders, poor comprehenders’ difficulties with reading comprehension emerge around the age 10, when performance in reading comprehension is equally accounted for by oral language and decoding skills (e.g., Elwér et al., 2013 ). Therefore, it seems plausible that there would be a greater overlap of poor comprehender status with more exposure to the French language in spoken and written form. Further research is needed to investigate the overlap of English and French reading comprehension difficulties in the later elementary grades, as decoding becomes more automatized and greater variance is accounted for by oral language skills.

The current study examined the learning needs of poor comprehenders in immersion education and has important implications for the assessment and remediation of reading comprehension difficulties in emerging bilingual learners. Our findings demonstrate that poor comprehenders exhibit pervasive oral language difficulties from the onset of reading that manifest similarly in English, their primary language, and French, the language of instruction. Furthermore, the results suggest that it is possible for children to experience poor reading comprehension in one language but be relatively good at comprehension in another language. Since many children begin French immersion with limited levels of French language proficiency, it is beneficial to gather information on children’s reading and language abilities with parallel measures in English and French. Limiting assessment to French, an additional language, may underestimate children’s reading and language ability or misattribute reading difficulties to a lack of French proficiency ( Geva and Herbert, 2012 ).

This research also suggests that intervention strategies should be targeted at poor comprehenders’ underlying language difficulties regardless of language of instruction. While there have been relatively few intervention studies with poor comprehenders, existing studies have shown that intervention practices that promote oral language skills and text comprehension strategies are effective supports for monolingual children with poor reading comprehension ( Snowling and Hulme, 2012 ). Evidently, there is a need for future intervention research that fosters the development of children’s oral language skills in immersion programs.

There are some limitations of the current study that should be noted. First, the sample of poor comprehenders identified within the three subgroups (i.e., PCB, PCE, PCF) was small, which limits the generalizability of our findings. However, obtaining a large sample of poor comprehenders is particularly challenging in a bilingual educational context. Our study is among the few longitudinal studies that have examined bilingual poor comprehenders’ reading and language skills in both languages over time. Given the attrition of students in French immersion (e.g., Chen et al., 2019 ) and the prevalence rate of poor comprehenders in middle elementary years at approximately 10% (e.g., Nation and Snowling, 1998 ; Clarke et al., 2010 ), our sample size may be considered representative of poor comprehenders in a bilingual context. Nevertheless, larger sample sizes for the subgroups of poor comprehenders would benefit future work.

Reading comprehension is a complex process that involves the coordination of various skills that are assessed differently across measures of reading comprehension. In the present study, we used a single standardized measure of reading comprehension. Although the use of this standardized test makes our sample of poor comprehenders comparable to those in the existing monolingual literature (e.g., Tong et al., 2014 ), results reported in this study need to be replicated with more varied reading comprehension measures to disentangle whether poor comprehenders score low on reading comprehension because they do not understand the text or because they are unable to read the question. Similarly, the use of a single measure of vocabulary knowledge may not fully capture the influence of other language skills on reading comprehension, such as vocabulary depth, listening comprehension, morphological awareness, and inference ( Nation and Cocksey, 2009 ; D’Angelo and Chen, 2017 ).

Another limitation is that approximately 25% of the children identified as poor comprehenders in either English, French, or both were exposed to another language at home in addition to English. While this sample is representative of students enrolled in French immersion programs in Canada, there is a need for further research to explore whether significant differences exist between children identified as poor comprehenders from English monolingual backgrounds and those who speak additional languages.

Finally, there is some difficulty in interpreting poor comprehender status in French only, particularly for children in this study who grew up in an English-speaking community. Poor reading comprehension in French may not be attributed to a language impairment or limited proficiency in French but associated with children’s lack of motivation to learn in an L2. Evidently, there is a need for further research to explore the role of motivation in L1 and L2 reading comprehension for children enrolled in immersion programs.

Taken together, the present study demonstrates that poor comprehenders experience similar and persistent difficulties with components of language in both English, a primary language, and French, an additional language, that are present in the early stages of reading development, and therefore, likely indicators of later reading comprehension difficulties in both languages. These results also show while there is a moderate degree of overlap in English and French reading comprehension difficulties, not all poor comprehenders of English are poor comprehenders of French, suggesting that somewhat different skills may be involved in comprehending text in English and French.

Data Availability Statement

The datasets generated for this study are available on request to the corresponding author.

Ethics Statement

The studies involving human participants were reviewed and approved by University of Toronto Research Ethics Board. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.

Author Contributions

ND’A and XC contributed to the conception and design of the study. ND’A and KK organized data collection and managed the database and performed the statistical analyses. ND’A wrote the first draft of the manuscript. KK and XC wrote sections of the manuscript. All authors contributed to manuscript revisions and read and approved the submitted version.

This research was funded by the Social Sciences and Humanities Research Council (SSHRC) (Grant Number: 435-2013-1745) (Title: Ensuring reading success for all students in early French immersion).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

The authors are grateful to the parents, educators, and students in participating school boards.

  • ^ For children to be classified as English-speaking, parents had to indicate that English was spoken in the home environment 50% of the time or more.
  • ^ Due to the small group sizes, equivalent non-parametric tests were calculated for each analysis. The Kruskal–Wallis test, used for comparing two or more independent samples, confirmed our parametric results.

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Keywords : poor comprehenders, reading comprehension, French immersion, oral language skills, vocabulary, comprehension difficulties, bilingual learners

Citation: D’Angelo N, Krenca K and Chen X (2020) The Overlap of Poor Reading Comprehension in English and French. Front. Psychol. 11:120. doi: 10.3389/fpsyg.2020.00120

Received: 11 July 2019; Accepted: 16 January 2020; Published: 05 February 2020.

Reviewed by:

Copyright © 2020 D’Angelo, Krenca and Chen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Nadia D’Angelo, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Primary School Students with Reading Comprehension Difficulties and Students with Learning Disabilities: Exploring Their Goal Orientations, Classroom Goal Structures, and Self-Regulated Learning Strategies

Christina kampylafka.

1 Department of Philosophy, Pedagogy and Psychology, School of Philosophy, National and Kapodistrian University of Athens, 15703 Athens, Greece

2 Department of Education, School of Education, University of Nicosia, 1700 Nicosia, Cyprus

Fotini Polychroni

3 Department of Psychology, School of Philosophy, National and Kapodistrian University of Athens, 15703 Athens, Greece

Alexandros-Stamatios Antoniou

4 Department of Primary Education, National and Kapodistrian University of Athens, 10680 Athens, Greece

Associated Data

Not applicable.

The aim of the present study was to investigate goal orientations and classroom goal structures and their relationship with strategies of self-regulated learning (SRL) in students with and without learning disabilities (LD) and reading comprehension difficulties (RCD). The sample consisted of 537 students attending the two last grades of primary school, fifth and sixth grade (Mage = 11.28 years, SD = ±0.59). Of these, 58 students were diagnosed with LD, and 70 students, after individually administered assessments in reading accuracy and reading comprehension, were assigned to the RCD group. Self-reported questionnaires were administered, assessing students’ personal goal orientations, classroom goal structures, and strategies of SRL. The results showed that students with LD and students with RCD scored lower in mastery orientation and higher in performance avoidance compared to their peers without difficulties (ND). LD students reported lower scores of adaptive strategies than their peers. In addition, the results confirmed the adaptive character of mastery-approach goals and mastery goal structures and the negative effects of performance-avoidance goals and performance goal structures on the adaptive strategies of SRL. Performance-approach goals predicted adaptive behaviors for all students, confirming the argument of an adaptive type of motivation. The findings of the current study highlight the importance of goal orientations and classroom goal structures for students’ SRL. Implications of the findings for enhancing motivation for students with LD and students with RCD are discussed.

1. Introduction

Self-regulated learning (SRL) constitutes an essential skill for learning and psychosocial adjustment of students of all ages [ 1 , 2 ]. According to the literature [ 3 , 4 , 5 ], learners are self-regulated to the degree that they are cognitively, metacognitively, motivationally, and strategically active participants in their own learning. Improving students’ self-regulation is critical for the educational process, especially for at-risk students. Achievement goal theory [ 6 , 7 ], one of the most prominent theories in the field of motivation and school psychology [ 8 ], also extended in the classroom [ 9 , 10 ], provides the conceptual framework for this study. Different goal orientations are associated with different, more or less adaptive behaviors in the school context [ 11 , 12 ].

Especially for students with learning disabilities (LD), for whom motivation is of primary importance for learning involvement and achievement, research on achievement goals is relatively limited and the findings conflicting [ 13 ]. Moreover, taking into account the shallow orthographic system of the Greek language, Greek students with LD face prominent difficulties in reading fluency and comprehension rather than solely in reading accuracy. The identification of learning disabilities usually takes place after the third year of primary school and usually follows the discrepancy criterion, including administering an intelligence test and reading, spelling, and writing standardized, and informal tests. (see Method for assessment process in students with LD). Apart from students with LD, there are also students with reading comprehension difficulties (RCD) almost in every classroom. Because of the nature of reading comprehension, these deficits are often not as easily detected as reading difficulties, and there is no universally agreed identification criterion, so, consequently, students are not assessed and supported on time [ 14 , 15 ]. Children with RCD are usually identified as having low scores in reading comprehension tasks, with typical reading accuracy and intelligence scores. There is evidence that children who struggle with reading employ fewer and less effective learning and self-regulating strategies and report decreasing motivation [ 16 ]. Nevertheless, there is limited evidence on the motivational profiles and self-regulation of children who struggle with reading comprehension with no apparent reading difficulties and who remain undetected for a long time. Drawing from the achievement goal theoretical model, the present study explores personal and classroom goals and their link to the self-regulating strategies of students with RCD compared to students with LD and a group with no difficulties.

1.1. Goal Orientations, Classroom Goal Structures, and Self-Regulation

Achievement goals are conceptualized as the reason or the purpose for which someone is engaged in an achievement situation [ 17 ]. According to the theoretical framework in achievement tasks, students can pursue two distinct types of personal goals [ 18 ]: mastery goals, which correspond to the opportunity to learn, acquire knowledge, and develop competency [ 10 , 11 ] and performance goals , which correspond to competence demonstration and social/peer comparison [ 7 , 19 ]. According to the 2 × 2 framework [ 20 ], by adding the dimensions of approach (desire to engage in a task) and avoidance (effort of non-involvement in a task), four distinct goal orientations were formed. Students with mastery-approach goals are usually engaged in school tasks motivated by personal interest, aiming at the improvement of their own skills, while students with mastery-avoidance goals focus on avoiding task-based or intrapersonal incompetence [ 21 ]. Nevertheless, research findings for mastery-avoidance goals are relatively limited compared to other types of goals [ 22 , 23 ]. On the contrary, attaining superior competence or outperforming others is the basic aim for students with performance-approach goals [ 18 , 24 , 25 , 26 ]. Finally, performance-avoidance goals focus on avoiding failure and avoiding demonstrating lack of ability relative to others [ 27 , 28 ].

Given that personal attitudes and students’ motivation toward learning tasks are gradually shaped by the influence received from familiar surroundings, including the school classroom setting and the opposite [ 29 , 30 ], goal achievement theory has been extended from the individual-level construct to the characteristics of the educational setting, forming classroom goal structures [ 9 , 24 ]. Classroom goals reflect the perceptions of students about the messages received by the educational practices promoted during the learning process, such as the lesson’s organization, structure, and evaluation process [ 27 , 31 ]. Although the majority of goal orientation studies have widely adopted the trichotomy framework, research on classroom goal structures followed the initial dichotomy framework of mastery versus performance goals [ 32 ], including mastery goal structures, which focus on knowledge acquisition and individual progress, and performance goal structures, which focus on school performance and social comparison [ 33 ].

Empirical research data have shown that adopting a goal orientation and being in a classroom that promotes a specific goal is associated with either positive or negative outcomes, creating a divided model of adaptive and maladaptive goals [ 34 , 35 ]. Μastery-approach goals are positively linked to internal motivation and adaptive patterns of behavior [ 36 , 37 , 38 ], such as attention, effort, on-task persistence, deep processing of information [ 39 , 40 ], effective help-seeking [ 41 , 42 ], self-effectiveness, and use of cognitive and metacognitive strategies [ 43 , 44 , 45 ]. Strategies aiming at deep processing and a better understanding of the cognitive material fit a more adaptive pattern of knowledge acquisition than those aiming to surface processing, temporary memorization, and retrieval, which are considered to be more maladaptive [ 46 , 47 ].

On the other hand, findings regarding performance-approach goals are contradictory [ 48 , 49 ]. Τhere is evidence of an absence of a link between this orientation and deep processing strategies, particularly for primary school pupils [ 11 , 50 ], or that performance-approach goals are associated with undesirable outcomes, including anxiety, negative affect [ 51 ] and surface learning strategies [ 52 ]. However, data exist showing that in the case of demanding learning tasks [ 53 ], performance-approach goals have, at times, predicted more strongly than mastery-approach goals grades and academic achievement [ 54 , 55 ], self-regulation [ 56 ], engagement, effort [ 57 ], and persistence [ 33 , 58 ] among people high in need for achievement [ 35 ]. Based on these patterns, researchers accepted the benefits stemming from adopting this goal and promoted the revision of achievement goal theory through multiple goals [ 59 ]. Through multiple goals, students take advantage of the positive effects of both mastery and performance goals, as they are not mutually exclusive, and each of them could be beneficial and useful in a different way [ 35 ]. It is possible that controversies over the effects of performance-approach goals are due to differences in definition [ 60 ]. More specifically, as both elements are reported in the definition, the performance-approach goals’ emphasis mostly demonstrates competence and earning favorable judgments or outperforming peers [ 20 , 61 ]. This distinction is maybe crucial for these goals’ outcomes, as normative comparison seems to evoke more engagement, interest, and effort [ 62 , 63 ].

Finally, performance-avoidance goals have been described mainly as maladaptive, as they are positively linked to negative outcomes in both cognitive and emotional domains [ 30 , 64 ], including self-handicapping strategies [ 65 , 66 ], instances of acquired helplessness, withdrawal [ 33 , 67 ], procrastination behavior [ 68 ], high anxiety [ 69 ], strategies of surface processing [ 70 , 71 ], and low achievement [ 28 ]. In addition, performance-avoidance goals were found to be negatively correlated with effective strategies of self-regulation [ 72 ] and school performance [ 73 ].

As with personal achievement goals, students’ perceptions of mastery classroom goals or goal structures have been associated with positive behavior patterns, such as mastery goals, deep strategies, effort, internal motives, help-seeking, support autonomy, and positive affect [ 74 , 75 , 76 ]. Mastery goal structures were found to be a positive predictor of deep-level learning strategies, critical thinking, metacognitive skills, effort, and school engagement [ 77 , 78 , 79 ]. In contrast, performance-oriented classrooms are linked to maladaptive educational behaviors, such as self-handicapping strategies, surface strategies, anxiety, and shame [ 67 , 71 , 80 ]. They are also negatively associated with internal motives, deep strategies, effective management of demanding tasks [ 24 , 30 , 81 ] and persistence [ 76 ].

1.2. Personal and Classroom Goals and Self-Regulated Learning of Children with LD and RCD

At-risk students or low achievers often present difficult motivational and behavioral profiles [ 82 , 83 , 84 ]. Nevertheless, relatively few studies have been conducted on personal goals, classroom goal structures, and their outcomes for students with LD or RCD [ 13 , 85 , 86 , 87 , 88 , 89 ]. Particularly, students with LD may report low levels of motivation and engagement in learning tasks [ 90 ], task avoidance [ 91 ], high levels of learned helplessness, academic procrastination, negative affect, self-handicapping, low levels of academic self-efficacy, and low help-seeking [ 13 , 92 , 93 , 94 , 95 ]. Empirical data also show that students with LD adopt high levels of performance-avoidance goals, low mastery-approach goals [ 13 , 96 ], perceive their class as more performance-oriented [ 85 ], use reduced self-regulating strategies, adopt surface approach to learning, present diminished persistence toward the learning goal, high levels of shallow cognitive processing strategies, low use of deep strategies, deficits in metacognitive skills, low levels of monitoring, and high anxiety [ 97 , 98 , 99 , 100 ]. Moreover, for students with LD, mastery-approach goals have been positively linked with adaptive motivational and behavioral outcomes, whereas performance-avoidance goals are associated with mostly maladaptive patterns [ 101 ], indicating similar outcomes with students without difficulties. For example, Sideridis [ 102 ] found that mastery-approach goals negatively predicted helplessness and positively predicted performance, while performance-avoidance goals positively predicted helplessness.

Struggling readers present a similar motivational profile to LD students reporting low motivation, negative attitudes toward reading, surface approach to learning, poor self-regulation skills, and low use of deep approach as compared to skilled readers [ 103 , 104 , 105 ]. Especially for poor comprehenders, empirical findings indicate deficits in motivation and working memory, low levels of monitoring, lower use of evaluation/integration and self-regulation strategies, lower school enjoyment, and higher levels of burnout than typical students [ 106 , 107 , 108 , 109 ]. Moreover, students with reading disabilities are significantly more performance-avoidant compared to typical students [ 110 ].

Although the effects of performance-approach goals are not sufficiently clear [ 111 ], it is argued that performance-approach goals are more adaptive for high-risk students, since they are positively associated with effort and school performance [ 102 , 112 ]. In addition, performance-approach goals are more adaptive for students with low self-perceived competence [ 35 , 113 ]. Finally, there are a few results highlighting the importance of mastery goal structures in reading comprehension [ 32 ], indicating that performance goal structures are associated with less positive affect and less engagement, adopting the opposite pattern of mastery goal structures [ 114 ].

1.3. The Present Study

In the present study, we examined goal orientations, classroom goal structures, and strategies of SRL in three separate groups: students with LD, students with RCD, and students with no difficulties, with the aim of describing their motivational profiles. A second aim was to explore the different patterns of predictors for adaptive and surface strategies for the three groups, aiming to investigate the outcomes of personal goals and classroom goal structures. In this context, we explored the adaptive or non-adaptive role of performance-approach goals on self-regulation. The literature regarding the effects of this personal goal has been inconclusive, on the one hand supporting the adaptive character of the goal and, on the other, promoting the negative outcomes [ 56 , 115 ].

In this study, the emphasis is given to students with LD and students with RCD, given the few and inconsistent findings of previous studies that have not led to a clear pattern for students facing difficulties [ 49 , 116 ]. Most of the existing literature for students with RCD focuses on the fundamental skills of the reading process [ 117 , 118 , 119 ], disregarding the psychosocial ramifications of this specific difficulty [ 84 ]. Furthermore, motivation and SRL in relation to reading comprehension skills have been rather neglected in empirical studies [ 120 , 121 ]. Finally, the sample was primary school students since they have received relatively limited research attention regarding these variables [ 122 ] compared to high school and University students [ 123 , 124 , 125 ].

Taking into account the existing literature, the research hypotheses and research question were formed as below:

  • It is more likely that students with LD and students with RCD would report lower scores of mastery-approach goals and mastery goal structures and higher performance-avoidance goals and performance goal structures than students without difficulties;
  • It is more likely that students with LD and students with RCD would report lower levels of adaptive self-regulating strategies (i.e., deep, motivational, persistence, and monitoring) and higher levels of surface strategies as compared to students with no difficulties;
  • In terms of differences between the LD group and the RCD group, it is less likely that LD students would present an adaptive profile, reporting fewer mastery goals, more performance-avoidance goals, more performance goal structures, and fewer adaptive strategies;
  • Are personal goals and classroom goal structures predictors of SRL strategies, and which of them is a predictor of adaptive and surface strategies separately for the three groups?

2. Materials and Methods

2.1. participants and procedure.

Five hundred and thirty-seven students attending the 5th and 6th grades of 28 public primary schools in Athens, Greece, participated in the study, selected from a larger pool of 568 students. The mean age of the participating students was 11.28 years (SD = ±0.59, Min = 10 years, Max = 12.75 years). All students were native speakers of Greek. Of them, 58 students had a formal statement of learning disabilities (LD group; 31 fifth graders and 27 sixth graders; 41 boys and 17 girls) by the state assessment Centers for Differential Diagnosis, Diagnosis, and Support (KEDASY). To get a formal statement of learning disabilities, the following criteria were met: average intelligence using the WISC-III test [ 126 ] (standardized in Greek), low reading ability (decoding and fluency) as measured by standardized and informal tests and no other coexisting neurodevelopmental difficulties. The LD group included children with average and above-average comprehension abilities. For the reading comprehension group (RCD group), 70 students from the total sample, 42 fifth graders and 28 sixth graders, 36 boys and 34 girls (excluding the students identified with LD), were selected after individualized assessments. For inclusion in the RCD group, the following criteria were met: students (a) scored at or above the 25th percentile on reading accuracy, (b) scored lower than the 25th percentile on reading comprehension [ 119 , 127 ] (see the measures in the next section) following the criteria used in other relevant empirical studies [ 128 , 129 ], and (c) had no known coexisting difficulties. Students included in the RCD group were not included in the LD group, and vice versa. The third group of the study consisted of 409 students (189 fifth graders and 220 sixth graders; 191 boys and 218 girls) with no formal statement and no other known difficulties according to their teachers and comprised the non-difficulties (ND) group. Finally, it should be stated that students who according to their classroom teachers’ perceptions had reading difficulties or were in the process of assessment for any other developmental disorder were not included nor in the ND group or in the RCD group.

2.2. Measures

2.2.1. personal goal orientations.

The Questionnaire of Achievement Goal Orientations [ 96 , 102 ] was used to assess students’ personal achievement goals. The questionnaire is domain specific (language) and consists of 18 items with three subscales, i.e., Mastery-Approach Goals-MAP goals- (6 items; e.g., “How important is to you to understand the language course?”), Performance-Approach Goals-PAP goals- (6 items; e.g., “How important is to you to get the best grade in the language course?”), and Performance-Avoidance Goals-PAV goals- (6 items; e.g., “Are you worried that you might not get a high grade in the language course?”). Τhe mastery-avoidance subscale (3 items) was not included in the present study since it is argued that this construct is more present in academic and competitive settings and less so in young students and different settings, especially in elementary school students [ 22 , 130 , 131 ]. A four-point Likert-type scale (from 1 = not at all to 4 = very much) was used. Cronbach’s alpha for MAP goals was α = 0.88, α = 0.92, and α = 0.91; for PAP goals α = 0.86, α = 0.92, and α = 0.83; and, finally, for PAV goals was α = 0.74, α = 0.90, and α = 0.74 (for ND, LD, and RCD groups, respectively).

2.2.2. Classroom Goal Structures

Classroom goal structures were assessed with the Questionnaire of Classroom Goal Structures [ 114 ]. Its items derived from a synthesis of scales (e.g., the Patterns of Adaptive Learning Scales-PALS) [ 31 , 67 ]. The questionnaire includes 16 items, and the students select a response from a four-point Likert-type scale, ranging from 1 (Not at all) to 4 (Very much). The questionnaire contains 2 subscales, Mastery Goal Structures (M-STR) (e.g., “The teacher tells us that mistakes don’t matter”) and Performance Goal Structures (P-STR) (e.g., “During the lesson, there is a lot of competition between students”) (M-STR α = 0.89, α = 0.85, α = 0.91; P-STR α = 0.87, α = 0.91, α = 0.89 for ND, LD, RCD groups, respectively).

2.2.3. Strategies of Self-Regulated Learning

Children’s Perceived Use of Self-Regulated Learning Inventory [ 132 ] is a self-report tool that assesses students’ self-regulation in school tasks. The questionnaire includes 75 items in a 5-point Likert-type scale from 1 (Never) to 5 (Always) that examine 9 basic components of SRL, i.e., task orientation, planning, motivation, self-efficacy, monitoring, learning strategies, motivational strategies, persistence, and self-evaluation. For the purpose of the present study, four subscales were used, learning strategies, motivational strategies, persistence, and monitoring. The learning strategies contain 14 items grouped into two factors, the surface strategy with four items (e.g., “When studying, I read or recall everything again and again until I know it by heart”) (α = 0.71, α = 0.74, α = 0.75 for ND, LD group, and RCD, respectively) and the deep strategies with 10 items (e.g., “When studying, I make a scheme or a mind map”) (α = 0.87, α = 0.90, α = 0.91 for the three groups, respectively). Motivational strategies contain 4 items (e.g., “During my schoolwork, I say to myself: You can do it, just keep on working!”) (α = 0.82, α = 0.79, and α = 0.87 for ND, LD, and RCD group, respectively), monitoring contains 7 items, (e.g., “If I notice something isn’t working out, I try a different approach”) (α = 0.83, α = 0.79, and α = 0.89 for ND, LD, and RCD group, respectively), and persistence includes 6 items such as “Even if I would rather do other things, I finish my schoolwork (α = 0.80 for ND group, α = 0.91 for LD group, and α = 0.92 for RCD group). In accordance with the theoretical models, deep strategies, motivational strategies, monitoring, and persistence were categorized as adaptive self-regulating strategies.

2.2.4. Reading Accuracy

A word reading task and a non-word reading task of the Greek standardized Reading Test TEST-A [ 133 ] were administered individually as indicators of reading accuracy. The word reading task consists of 53 isolated words, and the non-word reading task consists of 24 non-words printed in two columns. Both words and non-words are presented in order of difficulty. The test is discontinued when children score zero on five consecutive items (α = 0.86, α = 0.74, and α = 0.76 for ND, LD, and RCD group, respectively).

2.2.5. Reading Comprehension

Two short informative texts, from the reading comprehension task of the Reading Test TEST-A [ 133 ] were administered to the students. Students were asked to read the texts aloud or silently and then to respond to six multiple choice literal, vocabulary-dependent, and inferential questions. The number of correct responses in both texts was employed as measure of comprehension (α = 0.72, α = 0.78, and α = 0.73 for ND, LD, and RCD group, respectively).

2.3. Procedure and Ethics

The questionnaires and individual assessments were administered to students during school hours by the researcher. Students completed the self-report questionnaires in the classroom, and then they were assessed individually in reading accuracy and comprehension tasks. Students were assisted with their reading by the researcher, if necessary, especially in the case of students with learning disabilities. The study was approved by the Hellenic Institute of Educational Policy of the Ministry of Education, a body that granted consent for access to schools, and parental consent was a prerequisite for students’ participation in the study. Students having parental consent were also asked if they were willing to participate in the study, and they were informed that they had the opportunity to withdraw from the study at any stage.

3.1. Descriptives and Group Comparisons

Kruskal–Wallis tests were performed to test for differences in median scores on goal orientations and classroom goal structures between the three groups of students (ND, LD, RCD) as the normality hypothesis was rejected for all variables (Shapiro–Wilk normality test). There were statistically significant differences between the medians of the groups for all the goal orientations and classroom goal structures ( p < 0.05).

Post hoc analyses based on Mann–Whitney U test pairwise comparisons showed that students with LD and students with RCD reported significantly lower MAP goals, M-STR, and higher PAV goals and P-STR as compared with the ND group. Moreover, LD students reported significantly lower PAP goals as compared with the ND group. Finally, LD students presented lower MAP goals, higher PAV goals, and P-STR as compared to RCD group ( Table 1 ).

Mean scores, median scores, and standard deviations for the study variables.

Notes: Median scores that share the same index (a,b,c) are not statistically different according to the post hoc test Mann–Whitney U test for α = 0.05. MAP = mastery-approach goals; PAP = performance-approach goals; PAV = performance-avoidance goals; M-STR = mastery goal structures; P-STR = performance goal structures. * p < 0.05 ** p < 0.001.

3.2. Predictors of Surface and Adaptive Strategies

Pearson’s r coefficients for the study variables are presented in Table 2 for the three groups of the study. The correlations between the predictor variables of the study were examined, and they were found to be low to moderate, indicating that collinearity was unlikely to be a problem [ 134 ].

Correlations of personal goals, classroom goal structures, and strategies of self-regulated learning.

Note: MAP = mastery-approach goals; PAP = performance-approach goals; PAV = performance-avoidance goals; M-STR = mastery goal structures; P-STR = performance goal structures. ** p < 0.001.

The results for all groups showed that MAP goals and M-STR were positively correlated to adaptive strategies and negative correlated to surface strategies of SRL. PAP goals were also positively linked to adaptive strategies. Finally, PAV goals and P-STR were negatively linked to adaptive strategies and positively linked to surface strategies.

For each one of the two dependent variables (Surface and Adaptive Strategies), a series of linear regressions analyses was run to estimate the effect of each one of the predictors (MAP, PAP, PAV, M-STR, P-STR, Group, Gender, Class) and their possible interactions on the dependent variables. The assumptions of the linear regression analysis were not violated (normality assumption, assumption of equal variance, multicollinearity as GVIF values <10). Starting from “Surface Strategies”, a linear regression model that included all the main effects was conducted. Moving forward, we eliminated all the predictors that did not have a statistically significant effect-each time, the predictor with the highest non-significant p-value was excluded-and then tried to add only significant interaction terms.

The procedure was repeated until the Model 5 ( F (5, 531) = 140.579, p = 0.000, R 2 = 0.570) included only statistically significant main effects ( Table 3 ). To evaluate if the latest reduced model (Model 5) was similar to the initial full one (Model 1), an Anova test was utilized. No statistically significant difference was found in the fit between Model 1 and Model 5 since p = 0.834 > α = 0.05, so Model 5 consisted the base to identify possibly significant interactions (MAP and Group, PAP and Group, P-STR and Group).

Model 5: Linear regression analysis for predicting surface strategies.

Note: MAP = mastery-approach goals; PAP = performance-approach goals; P-STR = performance goal structures. * p < 0.05 ** p < 0.001.

Table 4 shows that only in Model 8 ( F (7, 529) = 102.809, p = 0.000 R 2 = 0.576) the group RCD by P-STR term had a statistically significant effect on surface strategies ( p = 0.005 < α = 0.05). It was observed that, for the models 6 and 7 that contained the other two possible interaction terms, the interaction terms did not have a statistically significant effect on surface strategies (both p > 0.05).

Model 8: Linear regression analysis for predicting surface strategies.

The final model was Model 8, as the ANOVA tests comparison showed that Model 8 had a statistically significantly better fit than Model 5 ( p = 0.017 < α = 0.05). Looking into Model 8, it was observed that there was a positive effect of MAP, PAP, and P-STR on surface strategies, and more specifically, if MAP was increased by one unit, then the surface strategies was increased by 0.097 on average. Similarly, if PAP was increased by one unit, the surface strategies was increased by 0.490 ceteris paribus. In the case of the ND group (level of reference of group), when P-STR was increased by one unit, the surface strategies was increased by 0.363 on average, ceteris paribus. Furthermore, we observed that also for the LD group, P-STR had a similar effect on surface strategies with the ND group since the interaction term group LD by P-STR was not statistically significant ( p = 0.854 > α = 0.05). On the other hand, for the RCD group, the interaction term group RCD by P-STR was statistically significant ( p = 0.005 < α = 0.05) with a positive coefficient of 0.257, which means that the increase rate in the surface strategies was higher than the other two groups (0.36 + 0.26 = 0.62) when the P-STR was increased by one unit. It should be noted that on average, the group RCD had a lower coefficient (−0.411) as an initial value compared to ND (level of reference) and LD (0.518). Bringing together the main group effect and the interaction term, regarding the RCD group, for low values of P-STR, the surface strategies value was lower than the other two groups but as P-STR increased, the surface strategies increase was more aggressive than for the other two groups. To better visualize the interaction effect of P-STR and groups on surface strategies, we utilized the sjPlot R package [ 135 ] to construct the plot of surface strategies with respect to P-STR for each group separately.

As expected, the RCD green line had lower surface strategies values than the other two groups for low P-STR values, but it had a higher slope, and it crossed the two other lines, resulting in higher values of surface strategies than the two other groups for high values of P-STR ( Figure 1 ).

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Object name is behavsci-13-00078-g001.jpg

Interaction effect of P-STR and Groups on Surface Strategies.

Passing now to adaptive strategies, a linear regression model that included all the main effects of the adaptive strategies was conducted. As in the case of surface strategies, we excluded all the predictors that did not have a statistically significant effect and then added only significant interaction terms.

As Model 2 ( Table 5 ) consisted of only the statistically significant terms ( F (8, 528) = 199.570, p = 0.000, R 2 = 0.751), an ANOVA test was utilized to evaluate if the latest model (Model 2) showed a similar fit to the initial one (Model 1). No statistically significant difference was found in the fit between Model 1 and Model 2 ( p = 0.8054 > 0.05), so Model 2 was used as a base to identify significant interactions (PAP and Group, MAP and Group, PAV and Group, M-STR and Group, P-STR and Group).

Model 2: Linear regression analysis for predicting adaptive strategies.

Note: MAP= mastery-approach goals; PAP= performance-approach goals; PAV= performance-avoidance goals; M-STR= mastery goal structures. * p < 0.05 ** p ≤ 0.001.

Running linear regressions models with interactions, we observed that only the Group LD by MAP interaction term in Model 4 ( Table 6 ) ( F (10, 526) = 162.208, p = 0.000, R 2 = 0.755) had a statistically significant effect on adaptive strategies ( p = 0.011 < α = 0.05). All the other models did not have any extra significant terms.

Model 4: Linear regression analysis for predicting adaptive strategies.

Note: MAP = mastery-approach goals; PAP = performance-approach goals; PAV = performance-avoidance goals; M-STR = mastery goal structures. * p < 0.05 ** p ≤ 0.001.

An Anova test was utilized to examine if the fit of Model 4 is statistically significantly better than Model 2, which contains all the main effects. Since p = 0.020 < α = 0.05, we concluded that Model 4 with the interaction term of Group LD by MAP had a statistically significantly better fit to the data.

As far as Model 4 is concerned, there was a main positive effect of MAP on adaptive strategies for the level of reference ND of Group, where the adaptive strategies score was increased by 0.493 when the MAP was increased by one unit. For the RCD group, a similar pattern was observed as the interaction term was small and non-significant ( p = 0.477 > α = 0.05). However, for the LD group, there was a negative interaction term MAP by group (−0.266) that decreased the overall positive effect of MAP on the adaptive strategies score (0.493 − 0.266 = 0.227). So, for the LD group, a unit increase in MAP brought a 0.227 increase in adaptive strategies. The above differences in the slopes of MAP for each group level are also presented in the estimated marginal means interaction plot below, where the blue line (LD group) has a smaller slope than the slopes of the other two groups ( Figure 2 ).

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Object name is behavsci-13-00078-g002.jpg

Interaction effect of MAP goals and Groups on Adaptive Strategies.

3.3. Descriptives and Group Comparisons Based on Final Models

For an overall comparison of the mean Surface and Adaptive Strategies between the three groups (ND, LD, RCD), the estimated marginal means together with their 95% confidence intervals were calculated ( Table 7 ) and pairwise Tukey comparisons between the three groups were conducted using the “emmeans” R package [ 136 ].

Descriptives of Surface and Adaptive Strategies based on final models.

From the Tukey tests, we concluded that the mean ND surface strategies were statistically significantly lower than the ones of LD and RCD ( p < 0.0001 and p = 0.0021 < 0.05), and marginally, there is no statistically significant difference between LD and RCD surface strategies ( p = 0.0641 < α = 0.05). Moreover, based on the estimated marginal means comparison t-test with Tukey adjustment, it was observed that the LD group had a statistically significantly lower adaptive strategies score than the two other groups ( p < 0.001 and p = 0.003), while the ND and RCD groups showed similar performance ( p = 0.124).

4. Discussion

The aim of the present study was to explore self-reported goal orientations, classroom goal structures, and strategies of self-regulated learning of students with learning disabilities, students with reading comprehension difficulties, and students with no difficulties. Moreover, we examined the predictors of adaptive and surface strategies for the three groups.

The results of the present study showed that the students with learning disabilities and the students with comprehension difficulties were less mastery and more performance-avoidant-oriented and reported higher levels of performance goal structures as compared to students without difficulties. This result confirms the first hypothesis and is in line with extant research showing that students with learning disabilities and poor comprehenders present low mastery goals and avoid learning tasks because of their fear of poor performance and deficits exposure, and they usually perceive the classroom context as performance-oriented [ 85 , 137 ].

In terms of self-regulated strategies, students with learning disabilities and reading comprehension difficulties reported more surface strategies than their typical peers, partly confirming the second hypothesis and the existing literature [ 90 , 138 ]. Moreover, only the group with learning disabilities reported lower scores on the adaptive self-regulating strategies (deep, motivational, monitoring, and persistence) as compared to students with no difficulties. This finding partly confirms the second hypothesis and agrees with previous studies showing that students with learning disabilities report lower levels of self-regulation strategies than typical peers [ 97 , 139 ]. Nevertheless, poor comprehenders showed similar use of adaptive strategies to students without difficulties, contrary to the bulk of evidence showing the use of fewer self-regulating strategies [ 106 ]. This may imply that these students may try to use adaptive strategies, but since these are particularly demanding, they may not be effective and lead to low comprehension performance. These findings underline the motivational deficits of students with learning disabilities and comprehension difficulties, highlight the importance of enhancing their self-regulation for learning and turn the focus on students with comprehension difficulties, a group whose difficulties remain undetected and are largely underestimated [ 14 ]. In the case of students with comprehension difficulties, suitable decoding skills might mask comprehension deficits, and low performance in comprehension tasks is often attributed to external causes, such as low attention or lack of effort [ 128 ]. For poor comprehenders, being intrinsically motivated and using effective strategies of self-regulated learning during the reading process can lead to the successful completion of a comprehension task. Therefore, further research is needed using methods such as behavioral observation tasks for students with comprehension difficulties, as these groups frequently do not have a formal special educational needs statement and whose self-regulation profile is not straightforward.

Regarding the differences between the students with learning disabilities and the students with comprehension difficulties, the former group reported lower levels of mastery-approach goals, higher levels of performance-avoidance goals and performance goal structures, and fewer adaptive strategies than their peers with poor comprehension. These findings confirm our third hypothesis and are in agreement with other studies showing that students with learning disabilities are a highly heterogeneous group, facing a wide range of deficits in motivational, behavioral, cognitive, and psychosocial characteristics [ 140 , 141 ]. As far as their goal orientation is concerned, given that they have difficulties in more than one learning area [ 90 , 142 ], it is expected that they adopt fewer mastery-approach goals and more performance-avoidance goals, probably in order to avoid exposure of their weak areas [ 143 ]. On the other hand, students with comprehension difficulties present difficulties mainly in one specific domain [ 118 ].

The present study also explored the different patterns of predictors for strategies of self-regulated learning for the three groups, looking into the prediction of more and fewer adaptive strategies. Regarding the research question, the results highlighted the importance of motivation (personal and contextual) by adopting a personal goal or being in an environment that promotes specific goals for self-regulated learning of all students, regardless of the type of difficulty [ 144 ]. Mastery-approach goals and mastery classroom goals were positive predictors of adaptive strategies of self-regulated learning for all three groups (typical students, students with learning disabilities, and students with reading comprehension difficulties). This finding confirmed that mastery orientation personal goals and classroom mastery orientation goals are associated with positive behavior models at a cognitive level, not only for the group without any known difficulties but also for students with learning disabilities and reading comprehension difficulties. In essence, students who estimate that the educational practices in their class are focused on learning and who, on their own, aim at self-improvement might be led to the use of more strategies that aim at in-depth processing of the learning material and demonstrate higher levels of motivational strategies, monitoring, and persistence. This result concurs with other findings and confirms the adaptive character of mastery goals and the corresponding classroom goal structures for all students [ 8 ]. Given that mastery goal structures are associated with adaptive self-regulatory strategies, such as monitoring, deep, and motivational strategies, these should be reinforced at school [ 55 , 114 ]. Reinforcing mastery goal structures will probably increase the adoption of personal mastery goals since the school setting, and the classroom’s practices seem to affect the students’ personal attitudes and behaviors [ 10 ]. In the case of LD students, mastery goals had a lower impact as a predictor of adaptive strategies. This finding is probably due to the fact that students with learning disabilities are less oriented to learning, adopt lower mastery goals than other students, and their mastery goals are not stable during learning tasks. As a result, they have very low engagement in a learning task and avoid using deep and complex strategies for it [ 90 ].

However, the reverse pattern was observed in performance-avoidance goals. Avoiding learning engagement for fear of low performance and adopting performance-avoidance goals were found to be positively linked to surface strategies and were negatively linked to adaptive strategies. More specifically, performance-avoidance goals negatively predicted adaptive strategies of self-regulated learning in all groups. This result confirms the extant literature that supports the less adaptive character of one’s performance-avoidance goals toward learning behaviors and school performance [ 28 , 70 , 96 ]. Performance goal structures positively predicted surface strategies, and they were also negatively linked to adaptive strategies of self-regulating learning for all groups. This finding concurs with previous research [ 24 , 71 , 76 ] for typical students and both at-risk groups. On the other hand, for students with comprehension difficulties, performance classroom goals were a stronger predictor of surface strategies. Taking into account that poor comprehenders’ difficulties are detected in a specific domain, these students may better adapt and respond according to the classroom’s orientation. In other words, in a performance-oriented classroom, they might use more surface strategies since they are simpler and easier strategies. However, further research is also warranted. On the whole, the results regarding performance classroom goals seem to justify the researchers who have considerable reservations about the introduction of such structures into the educational setting [ 81 ].

According to the present study, performance-approach goals significantly predicted surface strategies for all groups, in agreement with the literature [ 51 ]. Moreover, performance-approach goals, whose role is questionable [ 61 ], were a positive predictor of adaptive strategies for all groups. This finding is consistent with studies showing that performance-approach goals could be effective for all students, leading to the adoption of more adaptive behavioral models [ 61 , 115 ]. Additionally, researchers claim that students with learning disabilities and students with reading comprehension difficulties or low-performance students, by adopting performance-approach goals, are motivated toward the achievement of a specific goal and refrain from task resignation or avoidance, so even this presence of motivation becomes beneficial as compared to the absence of any motives [ 88 ]. Moreover, awareness of shortcomings and elevated stress levels due to fear of exposure to weaknesses and desire for higher performance, apart from negatively affecting psychosocial adjustment and well-being [ 51 ], could possibly intensify effort and lead to the use of more effective strategies [ 145 ]. It might facilitate our understanding of the results if we take into consideration that the performance-approach goals can include both normative and appearance standards and that the normative standards activate the use of self-regulating strategies [ 146 ]. Consequently, this finding highlights that avoidance orientation is the one negatively linked to adaptive behaviors for all students, while the effect of performance-approach goals warrants further research.

Taking the above results into consideration, emphasis is put on the value of classroom goals and personal mastery goals for learning, but also on the negative effect of personal performance-avoidance goals for all students, regardless of their presented difficulties. Promoting mastery of classroom goals and therefore encouraging students to adopt personal goals of acquiring knowledge and improving themselves by individual standards is of the essence in the classroom [ 80 ]. At the same time, the importance of performance-approach goals for more adaptive learning behaviors, in the case of poor-performance students, is not to be understated. The above findings are in favor of promoting educational orientation toward learning in the classroom, while further investigation is required concerning the role played by performance-approach goals to the performance of students with learning disabilities and comprehension difficulties. Furthermore, these results are in agreement with studies that favor the revision of the goal orientation theory since they demonstrate that performance-approach goals do not necessarily lead to negative behavior models [ 59 ]. Consequently, multiple goals, which aim both at learning and performance, are more likely to lead to a more adaptive behavioral model [ 26 , 147 ].

Limitations and Conclusion

The use of self-report may lead students to report strategies that they have not used, offering socially desirable responses, or that they might be unaware of strategies they used automatically. It is equally probable that the individual characteristics of students are incorporated into the perceived classroom goals, thus highlighting the subjective nature of the interpretation of educational practices within the classroom. For example, the relationship between teachers and students or between peers could be an important factor affecting students’ attitudes toward the school environment; however, this was not taken into account in the present study [ 122 ]. Future studies may employ rating scales by teachers and parents and behavioral observation as additional methodological tools. In addition, the learning disabilities group included students with a formal statement of learning disabilities, without further assessment by the authors. Students might present difficulties in other learning areas, and the majority of these might have already participated in intervention programs, and this may have an effect on the reported strategies. It should also be noted that students identified with poor reading comprehension were only selected by the pool of students with no known difficulties following reading comprehension tasks. This therefore, did not explore students’ other possible learning needs.

These findings of the present study expand our knowledge of achievement goals and self-regulated learning strategies in students with comprehension difficulties and students with learning disabilities. Given the importance of motivation in the learning process, the results of the present study may have implications for the identification of the motivational profile of at-risk students and the implementation of primary and secondary prevention programs with the aim of forming self-regulated learners.

Funding Statement

This research received no external funding.

Author Contributions

Conceptualization, C.K. and F.P.; methodology, C.K., F.P. and A.-S.A.; formal analysis, C.K. and F.P.; investigation, C.K.; writing—original draft preparation, C.K.; writing—review and editing, C.K., F.P. and A.-S.A.; supervision, F.P. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved as a Ph.D. by the Hellenic Institute of Educational Policy of Ministry of Education, Protocol Code: Φ15/734/162551/Γ1, Approval Date: October 2014.

Informed Consent Statement

Informed consent was obtained from all students’ parents involved in the study.

Data Availability Statement

Conflicts of interest.

The authors declare no conflict of interest.

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    In this article, we review the theoretical and empirical research in reading comprehension. We first explore different theoretical models for comprehension and then focus on components shown to be important across models that represent potential targets for instruction. ... Learning Disabilities Research & Practice, 33, 11-23. Crossref. Google ...

  20. (PDF) An Analysis of Students' Difficulties in Reading Comprehension

    The data was gathered using a reading comprehension test and questionnaires. The test indicated that 77.5 percent of students struggled with the text's main idea. Then, 72.78 percent of students ...

  21. Primary School Students with Reading Comprehension Difficulties and

    Empirical research data have shown that adopting a goal orientation and being in a classroom that promotes a specific goal is associated with either positive or negative outcomes, ... Additionally, researchers claim that students with learning disabilities and students with reading comprehension difficulties or low-performance students, ...

  22. (PDF) Reading Comprehension Difficulties Encountered by English

    PDF | The aim of this research is to find out the difficulties of reading comprehension faced by the first semester of students in FKIP UIR Pekanbaru.... | Find, read and cite all the research you ...

  23. THE STUDENTS' DIFFICULTIES IN LEARNING READING

    This research is an attempt to find out the difficulties faced by students in doing reading comprehension to find the perfect technique or method to overcome the problem and answer the research ...