thesis of reading comprehension

REVIEW article

The relationship between reading strategy and reading comprehension: a meta-analysis.

• 1 Research Center for Overseas Studies and Media Reports on Hainan, Hainan Univeristy, Haikou, China
• 2 Department of Science and Environmental Studies (SES), The Education University of Hong Kong, Taipo, Hong Kong
• 3 Department of Teacher Education, Faculty of Education, Guangzhou Huashang College, Guangzhou, China
• 4 Department of English, College of Foreigh Language, Hainan University, Haikou, China
• 5 Department of Social and Behavioral Sciences, City University of Hong Kong, Kowloon, Hong Kong
• 6 Yew Chung International School - Primary HK, Kowloon, Hong Kong

This study synthesized the correlation between reading strategy and reading comprehension of four categories based on Weinstein and Mayer's reading strategy model. The current meta-analysis obtained 57 effect sizes that represented 21,548 readers, and all selected materials came from empirical studies published from 1998 to 2019. Results showed that reading strategies in all the four categories had a similar correlation effect size with reading comprehension. The correlation between monitoring strategy and reading comprehension was significantly larger in first language scripts than second language scripts. Affective strategy and elaboration strategy had an independent effect on reading comprehension, which was not significantly moderated by selected moderators. Results suggested that the reading strategies of all the four categories may have a similar contribution to text comprehension activities.

Introduction

Reading comprehension requires readers to interpret the mental image from the given text through the interaction between both conceptual knowledge (e.g., vocabulary knowledge, metalinguistic knowledge) and procedural knowledge (e.g., reading strategy) and reading the text ( Snow, 2002 ; Anmarkrud and Bråten, 2009 ; Daugaard et al., 2017 ). Regarding comprehension, reading strategies can be defined as a series of specific, deliberate, goal-directed mental processes or behaviors which control and modify the efforts of a reader to decode a text, understand words and construct the meaning of a text ( Weinstein and Mayer's, 1986 , p. 315; Anastasiou and Griva, 2009 ). Extensive literature suggests that reading strategies facilitate the text comprehension process through reading rate ( Pattillo et al., 2004 ; McGeown et al., 2013 ; Lin and Yu, 2015 ), reading speed ( Savaiano and Hatton, 2013 ; Alharbi, 2015 ; Layes et al., 2015 ), and comprehension accuracy ( Aghaie and Zhang, 2012 ; Pei, 2014 ; Spörer and Schünemann, 2014 ). Weinstein and Mayer's (1986) categorized reading comprehension strategies into four groups based on strategy function: Affective strategy (AS), Elaboration strategy (ES), Monitoring strategy (MS), and Organization strategy (OS). Reading stages theory ( Chall, 1983 ) provides the theoretical framework for reading purpose at different grade groups, from learning to read at lower grades of primary school, to becoming more professional in reading, to then be able to learn at the undergraduate level. However, the perspectives on the developmental relations ( Kim et al., 2012 ; Quinn et al., 2015 ; Muijselaar et al., 2017 ), that is, the interaction effect between each reading strategy and reading comprehension on each reading stage remains unclear. Mayer (2005) cognitive theory of knowledge learning suggests that readers ought to employ more reading strategy levels in the first language (L1) than in the second language (L2). Readers should also employ more reading strategies in higher grades than in lower grades due to the fact that the background knowledge base is larger in higher grades than lower grades. However, previous literature shows inconsistent associations between each reading strategy and reading comprehension. Therefore, further exploration is needed on which category of reading strategy contributes more to reading comprehension. The extent of correlation between reading strategy and reading comprehension under the combined effect of reading stages and cognitive development remains unclear. Therefore, the current study employs a meta-analytic method to investigate the correlation between each reading strategy and reading comprehension. Furthermore, it investigates the effect of age effect and script differences effect on the correlation between each reading strategy and reading comprehension.

Literature Review

As and reading comprehension.

AS refers to a mental power that enables the reader to overcome negative feelings linked with the reading experience (e.g., reading anxiety). AS enhances the reading comprehension process through increasing performance goal attention time ( Berthiaume et al., 2010 ), maintaining reading motivation level ( Law, 2009 ; Logan et al., 2011 ; Schaffner and Schiefele, 2013 ), and controlling the negative experience effect ( Guthrie et al., 2007 ; Bråten et al., 2013 ). For example, Lu and Liu (2015) , Springer et al. (2017) , and Wigfield et al. (2016) reported that the AS increased the reading interest and reading motivation of readers, and controlled feelings of boredom while reading. The assessment of AS included all possible strategies that decrease negative emotions and increase positive emotions or affective feelings (e.g., reading motivation strategy). However, previous studies showed various correlation levels between the AS and reading comprehension, from low (e.g., Bråten et al., 2013 ) to moderate (e.g., Law, 2009 ). Furthermore, it was unknown whether the various correlations could be explained by the reading stage or the level of cognitive development.

ES and Reading Comprehension

ES refers to paraphrasing, summarizing, or describing the information of a mental image through existing knowledge on addressing target reading questions. ES establishes referential coherence, causal antecedents, and the emotion(al) reactions to the characters for both text-adjacent and global information inference, comprehension, and mental image construction ( Cain et al., 2004 ; Currie and Cain, 2015 ; Daugaard et al., 2017 ). For example, ES establishes the local coherence between adjacent events and cues, constructing a global coherence among events and statements provided in the text ( Long and Chong, 2001 ). The assessment of ES in a comprehension task requires the ability of the reader to integrate the target information among individual sentences in the text or the integration of general knowledge with information in the text (e.g., sentence-meaning inference). Reading stages theory suggests that students have a higher proficiency in ES due to the increase in background knowledge. However, previous studies showed that the association between the ES and reading comprehension varies from moderate (e.g., Cain et al., 2004 ) to high (e.g., Tsai et al., 2010 ). The developmental effect on the correlation between the ES and reading comprehension was also still unclear.

MS and Reading Comprehension

MS refers to the ability to self-regulate or self-question the reading process and monitor the speed or quantity of the given text. MS is regarded as an essential metacognitive knowledge that supervises the reading state (e.g., the awareness on which categories of the content a reader needs to search) application ( Baker and Brown, 1984 ; Kolić-Vehovec and Bajšanski, 2007 ). MS supervises the way that readers plan, evaluate, and utilize the available information from the text that makes sense of what they read from the literal textual information ( Grabe and Mann, 1984 ; Dabarera et al., 2014 ). MS was assessed via supervision on the awareness of the reader on the reading progress. For example, MS was assessed by an error detection task, which required the detection of inconsistencies in the text that required readers to evaluate their understanding of the text and to regulate their reading to resolve any reading problems and to facilitate their understanding ( Cain et al., 2004 ). Other assessments of comprehension monitoring included rating the awareness of the importance of sentences in a text, evaluating text complexity, and a cloze-task ( Baker and Brown, 1984 ). Reading stages suggested that higher-level students should be more proficient with MS due to the increase in reading experience. However, previous studies reported that the association between the MS and reading comprehension varies from moderate (e.g., Taboada et al., 2009 ) to high (e.g., McNeil, 2011 ) at the same grade level. The effect of reading stages on the correlation between the MS and reading comprehension remains unclear.

OS and Reading Comprehension

OS represents the ability to outline the passage or creating a hierarchy from the given reading text ( Oakhill and Cain, 2012 ; Currie and Cain, 2015 ). OS is regarded as the determining factor in the explanation for comprehension failure or reading comprehension difficulties ( Yap et al., 2012 ; Potocki et al., 2013 ). This means that the possible source of comprehension difficulties is inadequate knowledge about text structures. Past studies confirm explicit awareness about text structure, and the expectations engendered by certain common features of text may be useful aids for readers, helping them to invoke relevant background information and schemas to facilitate their construction of a meaning-based representation ( Dabarera et al., 2014 ; Guajardo and Cartwright, 2016 ). The assessment of OS application includes passage organization identification and passage structure awareness ( McNamara, 2004 ; Samuelstuen and Bråten, 2005 ). Higher proficiency in OS on reading comprehension needs more reading cognitive knowledge and reading experience ( Guthrie et al., 2004 ; McNamara, 2004 ), suggesting the correlation between the OS and reading comprehension increases with reading experience and cognitive ability development. However, previous studies show variations in correlation between the OS and reading comprehension, from moderate (e.g., Samuelstuen and Bråten, 2005 ) to high (e.g., Guthrie et al., 2007 ). The effect between the reading stage and cognitive development on the correlation between the OS and reading comprehension requires further investigation.

Potential Moderators

The current study selected grade group and language type as two potential moderators.

Grade Group

Reading stage theory ( Chall, 1983 ) suggests that students start learning to read at early primary school and become more professional in reading to learn at university level. The different reading stages may result in students developing different levels of proficiency in reading strategies application. Past studies report that older readers performed better in ES on text comprehension, as readers were better able to explain the sorts of information that may be provided by the introduction and ending of a text ( Adlof and Catts, 2015 ; Spencer and Wagner, 2018 ). Previous meta-analysis studies confirmed that the ability of reading procedural knowledge application was higher in higher-grade groups (e.g., Mol and Bus, 2011 ); the reason for this was identified as the larger interaction effect between literature knowledge and reading strategies, which was shown in higher-grade students than lower-grade students ( Grabe and Mann, 1984 ; Berthiaume et al., 2010 ; Turnbull, 2016 ; MacSwan, 2017 ). Therefore, the grade group was selected as a potential moderator for this study.

Language Type

Mayer (2005) cognitive theory suggests that the proficiency in reading strategy application is higher in first language (L1) than second language (L2) reading comprehension, because readers obtain more background knowledge (e.g., vocabulary knowledge, grammatical knowledge, and word reading ability), which contributes text information coding and processing ( Amadieu et al., 2009 ; Tarchi, 2015 ). Therefore, the current study selected language type as a potential moderator.

The Current Study

To clarify the impact of the reading stage and the effects of cognitive developmental relations on the association between the four categories of reading strategy and reading comprehension, this study expanded the current literature concerning the impact of the four categories of reading strategy on reading comprehension through the meta-analytic method, exploring the correlation between four reading strategies and reading comprehension in different grade groups and language types. García and Cain (2014 ) showed that procedural knowledge of readers on comprehension develops faster before the master's degree learning period. Moreover, most students start formal reading comprehension at grade 1 of primary school ( Law et al., 2008 ; García and Cain, 2014 ; Alharbi, 2015 ); therefore, the current study investigated grade group of students ranging from grade 1 of primary school to undergraduate level.

The current study followed official PRISMA guidelines on data collection and data analysis.

Literature Base

This study selected dissertations, book chapters, and journal articles from a number of popular databases, such as CNKI, PsycINFO, ERIC, and EBSCO. Two groups of keywords were used for potential materials search. The first group of keywords related to strategy (reading strategy * , self-regulated reading * , memory reading * , monitor reading * , sentence verification * , word recognition * , inference * , predict * , sensitive * , letter knowledge * , reading skills * , mental skills * , meta-reading * , elaboration * , organization * , affective reading * , and psychological reading * ). The second group of keywords related to reading comprehension (comprehension * , text comprehension * , passage comprehension * , paragraph comprehension * , sentence comprehension * , reading comprehension * , reading performance * , reading ability * , comprehension ability * , and reading acquisition * ). All relevant materials published between January 1, 1998 and June 1, 2019, were selected, resulting in a total of 2206 articles.

Inclusion Criteria

This study tried to include all possible studies that reported the correlation between reading strategy and reading comprehension. To control the possible cognition impact of the writing systems ( García and Cain, 2014 ), this study only selected those that were written in Chinese or English. As a result, 183 articles were retained.

Regarding materials selection, both abstract and methodology were reviewed. Only the materials that met all the following requirements were entered into the database: (a) not case or review study; (b) materials should be empirical articles; (c) reading comprehension ability was reported by a specific measurement scores; (d) grade group of the participants ranged from grade 1 of primary school to undergraduate level; (e) participants without any diagnosed physical problem (e.g., deaf, blind); (f) materials provided the concurrent correlation indicator (correlation r, R 2 , t , and p -value) between reading strategy and reading comprehension, which could be transformed to Fisher's z , to investigate the concurrent correlation between reading strategy and reading comprehension; (g) the minimum number of participants was 30; and (h) provided a clear description on reading strategy, which can be coded by Weinstein and Mayer's (1986) reading strategy theory . Based on these criteria, this study removed 125 articles leaving 58 articles.

Coding Process

Two independent coders coded the following information independently: (a) first author; (b) publication year; (c) sample size; (d) sampling area; (e) language type; (f) grade group; and (g) reading strategy category (AS, ES, MS, and OS). Regarding the reading strategy category, coders categorized reading strategy strictly according to the Weinstein and Mayer's (1986) reading strategy model definition. If the article only presented the general reading strategy score or the reading strategy category was not clear, the article was removed, because this study tried to investigate the correlation between each category of reading strategy and reading comprehension based on the reading strategy model. Any unclear information was emailed to the correspondence author of the article for confirmation. If the key information of the article (grade group, language type, and correlation indicators) was not clear, the article was removed. If one article provided more than two reading strategy categories (e.g., ES–reading comprehension, MS–reading comprehension), this study treated this article as two independent studies. If one article provided more than one available effect size in the same reading strategy category, this study ran the cluster regression method for effect size calculation ( Hedges et al., 2010 ), thus ensuring that each study only provided one effect size ( Mol and Bus, 2011 ). The intercoder reliability of coding was 0.96. The differences came from the sampling area coding. After discussion, this study solved the inconsistent results on sampling area coding through using the sampling country name to represent the sampling area. Two coders removed a total of 10 articles that were unclear in reading strategy category. All details of the remaining 48 articles are listed in Table 1 .

Table 1 . Description and outcomes in meta-analysis.

Meta-Analytic Procedures

After inclusion and coding of materials, only 48 articles met all the requirements and were collected into the database for further analysis. All correlations between each category of reading strategy and reading comprehension scores were transformed into Fisher's z through inputting correlation indicator to Comprehensive Meta-Analysis. We selected Fisher's z for effect size because Fisher's z has asymmetrical distribution and the variance of Fisher's z is approximately constant ( Borenstein et al., 2009 ). In general, the values of Fisher's z are 0.10, 0.31, and 0.55, which should be interpreted as that the effect size was small, moderate, and large, respectively ( Cohen, 1988 ). If one of the selected articles measures the reading comprehension ability of students through both standardized and researcher-developed measurements, this study calculated the effect size from the standardized measurement. If one study provided more than one available measurement for the correlation indicator, this study ran cluster regression for effect size calculation ( Hedges et al., 2010 ).

This study reported the effect size through the random-effects model from a conservative perspective, which provided the large range for correlation indicator estimation ( Borenstein et al., 2009 ). Second, this study provided the 95% confidence interval (CI), and effect size should be interpreted as significant only if CI did not cross zero. Next, this study applied moderator analysis (e.g., meta-regression) when Chi-square value ( Q -value) reached a significant level ( p < 0.05). The meta-regression could only be used if the number of studies for analysis exceeded four ( Hedges et al., 2010 ). Otherwise, this study applied sub-group analysis for the estimation of potential moderators ( Borenstein et al., 2009 ).

Regarding publication bias examination, the current study used the funnel plot through the trim-fill method, rank correlation test, Egger's regression test, and Rosenthal's fail-safe number. Rosenthal's fail-safe number reflects the number of missing studies with null effects that would have to be retrieved and included in the analyses before the p- value becomes insignificant ( Borenstein et al., 2009 ).

Durlak (2009) equation ( Teta ) was used for effect size comparison: Diff = Fisher's z 1 - Fisher's z 2 , SE = Sqrt (Variance z 1 + Variance z 2 ). Teta = Diff / SE, if Teta ≥ 1.96 or Teta ≤ −1.96, the difference between Fisher' z 1 and Fisher's z 2 should be significant ( p < 0.05).

Descriptive Statistics

Four articles were removed due to the effect size over 3.5 standard deviation of the list ( García and Cain, 2014 ). Specifically, the effect size of McNeil (2011) was removed from the MS–reading comprehension list and three effect sizes ( Cromley and Azevedo, 2007 ; Klauda and Guthrie, 2008 ; Tsai et al., 2010 ) were removed from the ES–reading comprehension list. Finally, there were 44 articles with 57 effect sizes ( N = 21,548). Specifically, 24 effect sizes ( N = 4,163) related to the correlation between the ES and reading comprehension, 15 effect sizes ( N = 3,078) related to the association between the MS and reading comprehension, 15 effect sizes ( N = 13,826) related to the association between the AS and reading comprehension, and three effect sizes ( N = 481) reported the correlation between the OS and reading comprehension. Twelve (12) effect sizes ( N = 1,934) reported the correlation between L2 reading comprehension and reading strategy, and 45 effect sizes ( N = 19,614) related to the correlation between L1 reading comprehension and reading strategy. Twenty-five (25) effect sizes ( N = 5,591) reported the correlation between reading strategy and reading comprehension in primary school, 16 effect sizes ( N = 13,506) related to the correlation between reading strategy and reading comprehension in secondary school students, and 16 effect sizes ( N = 2,451) related to the correlation between reading strategy and reading comprehension in university students.

Meta-Analysis 1

Table 2 provides each effect size between each category of reading strategy and reading comprehension. The effect sizes of reading strategies for all the four categories (AS–reading comprehension, ES–reading comprehension, MS–reading comprehension, and OS–reading comprehension) were close to large (Fisher's z ES = 0.43, Fisher's z MS = 0.48, Fisher's z AS = 0.45, Fisher's z OS = 0.58). The effect size comparison showed insignificant difference between every two categories of reading comprehension ( Teta < 1.96, p >0.05). The Chi-square examination showed that the MS–reading comprehension and OS–reading comprehension correlations were significant ( Q MS−reading comprehension = 47.27, p < 0.001; Q OS−reading comprehension = 9.27, p < 0.05). The moderator analysis showed that language type had a significant interaction effect on the correlation between the MS and reading comprehension (coefficient = 0.19, p < 0.01) with 77% variance explanation. Because only three studies were selected for the correlation between the OS and reading comprehension, sub-group analysis showed that the difference may be the grade group.

Table 2 . Reading strategy and reading comprehension of four categories.

Regarding publication bias examination, as for the correlation between the AS and reading comprehension, the funnel plot ( Figure 1 ) showed that the effect size followed symmetric distribution, the safe-number was huge ( N = 3,622), continuity Kendall's tau was.06 ( p > 0.05), and Egger's regression intercept was −0.51 ( p > 0.05). All four examination results suggested that the publication bias for the correlation between the AS and reading comprehension was not significant.

Figure 1 . Funnel plot of the correlation between the affective strategy and reading comprehension.

As for the correlation between the ES and reading comprehension, the funnel plot ( Figure 2 ) showed that the effect size followed a symmetric distribution, the safe-number was huge ( N = 3,693), continuity Kendall's tau was 0.08 ( p > 0.05), and Egger's regression intercept was −0.26 ( p > 0.05). All four examination results suggested that the publication bias for the correlation between the ES and reading comprehension was not significant.

Figure 2 . Funnel plot of the correlation between the elaboration strategy and reading comprehension.

As for the correlation between the MS and reading comprehension, the funnel plot ( Figure 3 ) showed that the effect size followed symmetric distribution, the safe-number was huge ( N = 2,118), continuity Kendall's tau was 0.15 ( p > 0.05), and Egger's regression intercept was 0.93 ( p > 0.05). All four examination results suggested that the publication bias for the correlation between the ES and reading comprehension was not significant.

Figure 3 . Funnel plot of the correlation between the monitoring strategy and reading comprehension.

As for the correlation between the OS and reading comprehension, the funnel plot ( Figure 4 ) showed that the effect size followed symmetric distribution, the safe-number was huge ( N = 113), continuity Kendall's tau was 0.33 ( p > 0.05), and Egger's regression intercept was −3.42 ( p > 0.05). All four examination results suggested that the publication bias for the correlation between the ES and reading comprehension was not significant.

Figure 4 . Funnel plot of the correlation between the organization strategy and reading comprehension.

Meta-Analysis 2

The association between L1 monitoring strategy and reading comprehension was nearly large (Fisher's z = 0.43), and the Chi-square examination showed that heterogeneity within the 12 selected studies was not significant ( Q = 16.59, p > 0.05). The association between L2 monitoring strategy and reading comprehension was large (Fisher's z = 0.63), the Chi-square examination showed that heterogeneity within the four selected studies was not significant ( Q = 4.59, p > 0.05). The correlation between the MS and reading comprehension was larger in L1 than in L2 (Teta = 3.00, p < 0.001 see Table 3 ).

Table 3 . Language type comparison on MS–reading comprehension.

The current study investigated the correlation between four reading strategies (AS, ES, MS, and OS) and reading comprehension. Results showed that each reading strategy had a similar effect size with reading comprehension. The AS–reading comprehension and ES–reading comprehension correlations did not moderate significantly by grade group and language type, suggesting that the reading stage and Mayer's cognitive theory had limited application on AS–reading comprehension and ES–reading comprehension. The effect size was larger in L2 than in L1 of the correlation between the MS and reading comprehension, extending Mayer's cognitive theory application on MS–reading comprehension: more background knowledge may inhibit the application on MS in reading comprehension. Sub-group analysis reported that the grade group may impact the correlation between the OS and reading comprehension, suggesting that the rule of the reading stage may influence the correlation between the OS and reading comprehension, higher-grade students should have more knowledge on text structure identification, but the association of OS–reading comprehension did not interact significantly by language type.

Effect Size Comparison

Results showed that the four correlations between reading strategy (AS, ES, MS, and OS) and reading comprehension were similar, suggesting that different reading strategies may work together to contribute to the same comprehension task. For example, both OS and ES significantly predicted text main idea (e.g., McNamara, 2004 ; Samuelstuen and Bråten, 2005 ). Regarding behavior information process of text comprehension, this result informed us that there might be a reciprocal effect through all four categories' reading strategy on reading comprehension tasks, which means that students could improve their reading strategy knowledge in all the four categories by receiving any category of reading strategy training program. Results also informed that regardless of text categories (e.g., narrative, descriptive), readers needed to apply four reading strategies together for text comprehension in both surface and deep comprehension processes.

The effect size between the AS and reading comprehension was nearly large and was not significantly impacted by selected moderators. This result is consistent with those reading affective/psychological factors studies ( Lu and Liu, 2015 ; Rai et al., 2015 ; Arslan, 2017 ), which showed that processing text comprehension must experience negative emotion at the same time. Readers needed to overcome these negative emotions to finish the comprehension task. This result informed us that AS performed a vital role in negative emotion regulation on text comprehension, no matter at which reading stage or the level of cognitive load this took place. Results also informed that at any grades or language scripts text reading activities, OS were applied in these comprehension activities to enable the reader to overcome negative feelings linked with the reading experience.

The current result was inconsistent with previous studies that showed the correlations between the ES and reading comprehension were different in different grade groups and L1 or L2 reading comprehension (e.g., Nation et al., 2010 ; Daugaard et al., 2017 ; Stanley et al., 2018 ). The correlation between the ES and reading comprehension was independent, which was not significantly moderated by the selected moderators. Reasons could be that the ES mainly contributed to the text mental information construction and integration process, which means that the ES has an independent working process whereby all different information needs to be abstracted from eyes first for coding, and then moved to the information integration process for comprehension. The current results showed that the grade group and language type did not have a significant impact on the correlation between the ES and reading comprehension through developmental relations, informing us that the ES might be the fundamental ability in text comprehension at any stage of reading and in any script of text comprehension. Results also informed that regardless of grades and language scripts comprehension activities, ES had similar contributions to printed text comprehension, enable readers to establish referential coherences, text semantic meaning identification, and mental image construction.

The effect size in L2 was larger than in the L1 scripts. The familiarity of background knowledge on reading comprehension may be the main reason for the difference in the correlation between the MS and reading comprehension, because readers experienced more difficulties on L2 text comprehension due to less vocabulary knowledge, grammatical knowledge, and decoding ability than the L1 readers. Therefore, readers needed more cognitive resources on reading task supervision ( Oakhill et al., 2003 ; Wigfield et al., 2008 ). This result reported that the supervision effect was different in different language scripts text comprehension, and readers needed to apply higher supervision effect on unfamiliar information processes.

The effect size of the correlation between the OS and reading comprehension was large, revealing that the text structure awareness played a key role in main idea identification (e.g., Samuelstuen and Bråten, 2005 ), which echoed findings of previous studies on the impact of awareness on text comprehension process. Moreover, moderator analysis showed that the grade group might explain the main reason for various correlations between the OS and reading comprehension across different reading stages. Previous studies pointed out that the OS would be applied more frequently in a higher-grade group than in younger groups for more complexity of the comprehension task ( Cain et al., 2004 ; Guthrie et al., 2004 ; Silva and Cain, 2015 ). In the higher grade group, the requirement of the comprehension task is higher and the structure of the task comprehension gains more complexity, so higher proficiency in OS application contributed to completing the comprehension task. These results inform us that at the reading-to-learn stage, readers gain more professional awareness of text structure on reading comprehension tasks.

Limitations

The current study has several limitations. First, it did not involve students who were diagnosed with serious special education needs (e.g., blind, deaf). Second, this study only synthesized those studies written in Chinese or English, and those studies written in other languages were not involved. Past studies have already demonstrated that the different language scripts cognition effect (e.g.,transparent vs. opaque) would enhance or inhabit text comprehension process ( Wydell, 2012 ; Filippello et al., 2016 ; Rappo et al., 2017 ). Finally, this study reported the effect size between each reading strategy and reading comprehension based on Weinstein and Mayer's (1986) reading strategy model. However, the number of empirical studies on organization strategy effect was limited.

Conclusions

This study derived conclusions from the combined results of 57 effect sizes that represented more than 20,000 students. To summarize, this meta-analysis has confirmed that AS, ES, MS, and OS contributed similar effect size on the text comprehension process, implicating all the four reading strategies had closed interactions and collaborations which contributed to text comprehension activities together. The reading stage statement might impose limitations on AS and ES on text comprehension application. Readers had greater awareness of L2 reading progress supervision than L1. Correlation between the OS and reading comprehension might be impacted by reading stage, and higher-grade readers performed with higher OS proficiency on reading comprehension task.

Author Contributions

YS draft the manuscript. JW provided the dataset and instructions on draft writing. YD contributed to data analysis and report writing. HZ provided ideas in a theoretical framework construction. JY, YZ, and WD provided comments and suggestions on manuscript revision. All authors contributed to the article and approved the submitted version.

The current study was funded by two funding: Guangdong Provincial Educational Science Planning Leading Group: Investigating the Development Pattern Utilization in Kindergarten-University Teaching and Learning Integration Mode for Creative Students whose Major is Early Childhood Education amongst Oversea and Mainland China (Project number: 2018GXJK277). Guangdong Provincial Philosophy and Social Science Planning Youth Project Group: The Effects of Mastery Goal Intervention on Reading Anxiety and Reading Comprehension (Project number: 2020WQNCX120).

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.

Publisher's Note

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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* ^ Marked those papers which used for dataset construction.

Keywords: reading strategy, reading comprehension, discourse comprehension, elaboration strategy, organization strategy, monitoring strategy, affective strategy

Citation: Sun Y, Wang J, Dong Y, Zheng H, Yang J, Zhao Y and Dong W (2021) The Relationship Between Reading Strategy and Reading Comprehension: A Meta-Analysis. Front. Psychol. 12:635289. doi: 10.3389/fpsyg.2021.635289

Received: 30 November 2020; Accepted: 31 May 2021; Published: 04 August 2021.

Reviewed by:

Copyright © 2021 Sun, Wang, Dong, Zheng, Yang, Zhao and Dong. 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: Yang Dong, yangdong3-c@my.cityu.edu.hk ; Jindao Wang, wangjindao@163.com

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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Levels of Reading Comprehension in Higher Education: Systematic Review and Meta-Analysis

Cristina de-la-peña.

1 Departamento de Métodos de Investigación y Diagnóstico en Educación, Universidad Internacional de la Rioja, Logroño, Spain

María Jesús Luque-Rojas

2 Department of Theory and History of Education and Research Methods and Diagnosis in Education, University of Malaga, Málaga, Spain

Associated Data

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Higher education aims for university students to produce knowledge from the critical reflection of scientific texts. Therefore, it is necessary to develop a deep mental representation of written information. The objective of this research was to determine through a systematic review and meta-analysis the proportion of university students who have an optimal performance at each level of reading comprehension. Systematic review of empirical studies has been limited from 2010 to March 2021 using the Web of Science, Scopus, Medline, and PsycINFO databases. Two reviewers performed data extraction independently. A random-effects model of proportions was used for the meta-analysis and heterogeneity was assessed with I 2 . To analyze the influence of moderating variables, meta-regression was used and two ways were used to study publication bias. Seven articles were identified with a total sample of the seven of 1,044. The proportion of students at the literal level was 56% (95% CI = 39–72%, I 2 = 96.3%), inferential level 33% (95% CI = 19–46%, I 2 = 95.2%), critical level 22% (95% CI = 9–35%, I 2 = 99.04%), and organizational level 22% (95% CI = 6–37%, I 2 = 99.67%). Comparing reading comprehension levels, there is a significant higher proportion of university students who have an optimal level of literal compared to the rest of the reading comprehension levels. The results have to be interpreted with caution but are a guide for future research.

Introduction

Reading comprehension allows the integration of knowledge that facilitates training processes and successful coping with academic and personal situations. In higher education, this reading comprehension has to provide students with autonomy to self-direct their academic-professional learning and provide critical thinking in favor of community service ( UNESCO, 2009 ). However, research in recent years ( Bharuthram, 2012 ; Afflerbach et al., 2015 ) indicates that a part of university students are not prepared to successfully deal with academic texts or they have reading difficulties ( Smagorinsky, 2001 ; Cox et al., 2014 ), which may limit academic training focused on written texts. This work aims to review the level of reading comprehension provided by studies carried out in different countries, considering the heterogeneity of existing educational models.

The level of reading comprehension refers to the type of mental representation that is made of the written text. The reader builds a mental model in which he can integrate explicit and implicit data from the text, experiences, and previous knowledge ( Kucer, 2016 ; van den Broek et al., 2016 ). Within the framework of the construction-integration model ( Kintsch and van Dijk, 1978 ; Kintsch, 1998 ), the most accepted model of reading comprehension, processing levels are differentiated, specifically: A superficial level that identifies or memorizes data forming the basis of the text and a deep level in which the text situation model is elaborated integrating previous experiences and knowledge. At these levels of processing, the cognitive strategies used, are different according to the domain-learning model ( Alexander, 2004 ) from basic coding to a transformation of the text. In the scientific literature, there are investigations ( Yussof et al., 2013 ; Ulum, 2016 ) that also identify levels of reading comprehension ranging from a literal level of identification of ideas to an inferential and critical level that require the elaboration of inferences and the data transformation.

Studies focused on higher education ( Barletta et al., 2005 ; Yáñez Botello, 2013 ) show that university students are at a literal or basic level of understanding, they often have difficulties in making inferences and recognizing the macrostructure of the written text, so they would not develop a model of a situation of the text. These scientific results are in the same direction as the research on reading comprehension in the mother tongue in the university population. Bharuthram (2012) indicates that university students do not access or develop effective strategies for reading comprehension, such as the capacity for abstraction and synthesis-analysis. Later, Livingston et al. (2015) find that first-year education students present limited reading strategies and difficulties in understanding written texts. Ntereke and Ramoroka (2017) found that only 12.4% of students perform well in a reading comprehension task, 34.3% presenting a low level of execution in the task.

Factors related to the level of understanding of written information are the mode of presentation of the text (printed vs. digital), the type of metacognitive strategies used (planning, making inferences, inhibition, monitoring, etc.), the type of text and difficulties (novel vs. a science passage), the mode of writing (text vs. multimodal), the type of reading comprehension task, and the diversity of the student. For example, several studies ( Tuncer and Bahadir, 2014 ; Trakhman et al., 2019 ; Kazazoglu, 2020 ) indicate that reading is more efficient with better performance in reading comprehension tests in printed texts compared to the same text in digital and according to Spencer (2006) college students prefer to read in print vs. digital texts. In reading the written text, metacognitive strategies are involved ( Amril et al., 2019 ) but studies ( Channa et al., 2018 ) seem to indicate that students do not use them for reading comprehension, specifically; Korotaeva (2012) finds that only 7% of students use them. Concerning the type of text and difficulties, for Wolfe and Woodwyk (2010) , expository texts benefit more from the construction of a situational model of the text than narrative texts, although Feng (2011) finds that expository texts are more difficult to read than narrative texts. Regarding the modality of the text, Mayer (2009) and Guo et al. (2020) indicate that multimodal texts that incorporate images into the text positively improve reading comprehension. In a study of Kobayashi (2002) using open questions, close, and multiple-choice shows that the type and format of the reading comprehension assessment test significantly influence student performance and that more structured tests help to better differentiate the good ones and the poor ones in reading comprehension. Finally, about student diversity, studies link reading comprehension with the interest and intrinsic motivation of university students ( Cartwright et al., 2019 ; Dewi et al., 2020 ), with gender ( Saracaloglu and Karasakaloglu, 2011 ), finding that women present a better level of reading comprehension than men and with knowledge related to reading ( Perfetti et al., 1987 ). In this research, it was controlled that all were printed and unimodal texts, that is, only text. This is essential because the cognitive processes involved in reading comprehension can vary with these factors ( Butcher and Kintsch, 2003 ; Xu et al., 2020 ).

The Present Study

Regardless of the educational context, in any university discipline, preparing essays or developing arguments are formative tasks that require a deep level of reading comprehension (inferences and transformation of information) that allows the elaboration of a situation model, and not having this level can lead to limited formative learning. Therefore, the objective of this research was to know the state of reading comprehension levels in higher education; specifically, the proportion of university students who perform optimally at each level of reading comprehension. It is important to note that there is not much information about the different levels in university students and that it is the only meta-analytic review that explores different levels of reading comprehension in this educational stage. This is a relevant issue because the university system requires that students produce knowledge from the critical reflection of scientific texts, preparing them for innovation, employability, and coexistence in society.

Materials and Methods

Eligibility criteria: inclusion and exclusion.

Empirical studies written in Spanish or English are selected that analyze the reading comprehension level in university students.

The exclusion criteria are as follows: (a) book chapters or review books or publications; (b) articles in other languages; (c) studies of lower educational levels; (d) articles that do not identify the age of the sample; (e) second language studies; (f) students with learning difficulties or other disorders; (g) publications that do not indicate the level of reading comprehension; (h) studies that relate reading competence with other variables but do not report reading comprehension levels; (i) pre-post program application work; (j) studies with experimental and control groups; (k) articles comparing pre-university stages or adults; (l) publications that use multi-texts; (m) studies that use some type of technology (computer, hypertext, web, psychophysiological, online questionnaire, etc.); and (n) studies unrelated to the subject of interest.

Only those publications that meet the following criteria are included as: (a) be empirical research (article, thesis, final degree/master’s degree, or conference proceedings book); (b) university stage; (c) include data or some measure on the level of reading comprehension that allows calculating the effect size; (d) written in English or Spanish; (e) reading comprehension in the first language or mother tongue; and (f) the temporary period from January 2010 to March 2021.

Search Strategies

A three-step procedure is used to select the studies included in the meta-analysis. In the first step, a review of research and empirical articles in English and Spanish from January 2010 to March 2021. The search is carried out in online databases of languages in Spanish and English, such as Web of Science (WoS), Scopus, Medline, and PsycINFO, to review empirical productions that analyze the level of reading comprehension in university students. In the second step, the following terms (titles, abstracts, keywords, and full text) are used to select the articles: Reading comprehension and higher education, university students, in Spanish and English, combined with the Boolean operators AND and OR. In the last step, secondary sources, such as the Google search engine, Theseus, and references in publications, are explored.

The search reports 4,294 publications (articles, theses, and conference proceedings books) in the databases and eight records of secondary references, specifically, 1989 from WoS, 2001 from Scopus, 42 from Medline, and 262 of PsycINFO. Of the total (4,294), 1,568 are eliminated due to duplications, leaving 2,734 valid records. Next, titles and abstracts are reviewed and 2,659 are excluded because they do not meet the inclusion criteria. The sample of 75 publications is reduced to 40 articles, excluding 35 because the full text cannot be accessed (the authors were contacted but did not respond), the full text did not show specific statistical data, they used online questionnaires or computerized presentations of the text. Finally, seven articles in Spanish were selected for use in the meta-analysis of the reading comprehension level of university students. Data additional to those included in the articles were not requested from the selected authors.

The PRISMA-P guidelines ( Moher et al., 2015 ) are followed to perform the meta-analysis and the flow chart for the selection of publications relevant to the subject is exposed (Figure 1) .

Flow diagram for the selection of articles.

Encoding Procedure

This research complies with what is established in the manual of systematic reviews ( Higgins and Green, 2008 ) in which clear objectives, specific search terms, and eligibility criteria for previously defined works are established. Two independent coders, reaching a 100% agreement, carry out the study search process. Subsequently, the research is codified, for this, a coding protocol is used as a guide to help resolve the ambiguities between the coders; the proposals are reflected and discussed and discrepancies are resolved, reaching a degree of agreement between the two coders of 97%.

For all studies, the reference, country, research objective, sample size, age and gender, reading comprehension test, other tests, and reading comprehension results were coded in percentages. All this information was later systematized in Table 1 .

Results of the empirical studies included in the meta-analysis.

In relation to the type of reading comprehension level, it was coded based on the levels of the scientific literature as follows: 1 = literal; 2 = inferential; 3 = critical; and 4 = organizational.

Regarding the possible moderating variables, it was coded if the investigations used a standardized reading comprehension measure (value = 1) or non-standardized (value = 0). This research considers the standardized measures of reading comprehension as the non-standardized measures created by the researchers themselves in their studies or questionnaires by other authors. By the type of evaluation test, we encode between multiple-choice (value = 0) or multiple-choices plus open question (value = 1). By type of text, we encode between argumentative (value = 1) or unknown (value = 0). By the type of career, we encode social sciences (value = 1) or other careers (health sciences; value = 0). Moreover, by the type of publication, we encode between article (value = 1) or doctoral thesis (value = 0).

Effect Size and Statistical Analysis

This descriptive study with a sample k = 7 and a population of 1,044 university students used a continuous variable and the proportions were used as the effect size to analyze the proportion of students who had an optimal performance at each level of reading comprehension. As for the percentages of each level of reading comprehension of the sample, they were transformed into absolute frequencies. A random-effects model ( Borenstein et al., 2009 ) was used as the effect size. These random-effects models have a greater capacity to generalize the conclusions and allow estimating the effects of different sources of variation (moderating variables). The DerSimonian and Laird method ( Egger et al., 2001 ) was used, calculating raw proportion and for each proportion its standard error, value of p and 95% confidence interval (CI).

To examine sampling variability, Cochran’s Q test (to test the null hypothesis of homogeneity between studies) and I 2 (proportion of variability) were used. According to Higgins et al. (2003) , if I 2 reaches 25%, it is considered low, if it reaches 50% and if it exceeds 75% it is considered high. A meta-regression analysis was used to investigate the effect of the moderator variables (type of measure, type of evaluation test, type of text, type of career, and type of publication) in each level of reading comprehension of the sample studies. For each moderating variable, all the necessary statistics were calculated (estimate, standard error, CI, Q , and I 2 ).

To compare the effect sizes of each level (literal, inferential, critical, and organizational) of reading comprehension, the chi-square test for the proportion recommended by Campbell (2007) was used.

Finally, to analyze publication bias, this study uses two ways: Rosenthal’s fail-safe number and regression test. Rosenthal’s fail-safe number shows the number of missing studies with null effects that would make the previous correlations insignificant ( Borenstein et al., 2009 ). When the values are large there is no bias. In the regression test, when the regression is not significant, there is no bias.

The software used to classify and encode data and produce descriptive statistics was with Microsoft Excel and the Jamovi version 1.6 free software was used to perform the meta-analysis.

The results of the meta-analysis are presented in three parts: the general descriptive analysis of the included studies; the meta-analytic analysis with the effect size, heterogeneity, moderating variables, and comparison of effect sizes; and the study of publication bias.

Overview of Included Studies

The search carried out of the scientific literature related to the subject published from 2010 to March 2021 generated a small number of publications, because it was limited to the higher education stage and required clear statistical data on reading comprehension.

Table 1 presents all the publications reviewed in this meta-analysis with a total of students evaluated in the reviewed works that amounts to 1,044, with the smallest sample size of 30 ( Del Pino-Yépez et al., 2019 ) and the largest with 570 ( Guevara Benítez et al., 2014 ). Regarding gender, 72% women and 28% men were included. Most of the sample comes from university degrees in social sciences, such as psychology and education (71.42%) followed by health sciences (14.28%) engineering and a publication (14.28%) that does not indicate origin. These publications selected according to the inclusion criteria for the meta-analysis come from more countries with a variety of educational systems, but all from South America. Specifically, the countries that have more studies are Mexico (28.57%) and Colombia, Chile, Bolivia, Peru, and Ecuador with 14.28% each, respectively. The years in which they were published are 2.57% in 2018 and 2016 and 14.28% in 2019, 2014, and 2013.

A total of 57% of the studies analyze four levels of reading comprehension (literal, inferential, critical, and organizational) and 43% investigate three levels of reading comprehension (literal, inferential, and critical). Based on the moderating variables, 57% of the studies use standardized reading comprehension measures and 43% non-standardized measures. According to the evaluation test used, 29% use multiple-choice questions and 71% combine multiple-choice questions plus open questions. 43% use an argumentative text and 57% other types of texts (not indicated in studies). By type of career, 71% are students of social sciences and 29% of other different careers, such as engineering or health sciences. In addition, 71% are articles and 29% with research works (thesis and degree works).

Table 2 shows the reading comprehension assessment instruments used by the authors of the empirical research integrated into the meta-analysis.

Reading comprehension assessment tests used in higher education.

Meta-Analytic Analysis of the Level of Reading Comprehension

The literal level presents a mean proportion effect size of 56% (95% CI = 39–72%; Figure 2 ). The variability between the different samples of the literal level of reading comprehension was significant ( Q = 162.066, p < 0.001; I 2 = 96.3%). No moderating variable used in this research had a significant contribution to heterogeneity: type of measurement ( p = 0.520), type of test ( p = 0.114), type of text ( p = 0.520), type of career ( p = 0.235), and type of publication ( p = 0.585). The high variability is explained by other factors not considered in this work, such as the characteristics of the students (cognitive abilities) or other issues.

Forest plot of literal level.

The inferential level presents a mean proportion effect size of 33% (95% CI = 19–46%; Figure 3 ). The variability between the different samples of the inferential level of reading comprehension was significant ( Q = 125.123, p < 0.001; I 2 = 95.2%). The type of measure ( p = 0.011) and the type of text ( p = 0.011) had a significant contribution to heterogeneity. The rest of the variables had no significance: type of test ( p = 0.214), type of career ( p = 0.449), and type of publication ( p = 0.218). According to the type of measure, the proportion of students who have an optimal level in inferential administering a standardized test is 28.7% less than when a non-standardized test is administered. The type of measure reduces variability by 2.57% and explains the differences between the results of the studies at the inferential level. According to the type of text, the proportion of students who have an optimal level in inferential using an argumentative text is 28.7% less than when using another type of text. The type of text reduces the variability by 2.57% and explains the differences between the results of the studies at the inferential level.

Forest plot of inferential level.

The critical level has a mean effect size of the proportion of 22% (95% CI = 9–35%; Figure 4 ). The variability between the different samples of the critical level of reading comprehension was significant ( Q = 627.044, p < 0.001; I 2 = 99.04%). No moderating variable used in this research had a significant contribution to heterogeneity: type of measurement ( p = 0.575), type of test ( p = 0.691), type of text ( p = 0.575), type of career ( p = 0.699), and type of publication ( p = 0.293). The high variability is explained by other factors not considered in this work, such as the characteristics of the students (cognitive abilities).

Forest plot of critical level.

The organizational level presents a mean effect size of the proportion of 22% (95% CI = 6–37%; Figure 5 ). The variability between the different samples of the organizational level of reading comprehension was significant ( Q = 1799.366, p < 0.001; I 2 = 99.67%). The type of test made a significant contribution to heterogeneity ( p = 0.289). The other moderating variables were not significant in this research: type of measurement ( p = 0.289), type of text ( p = 0.289), type of career ( p = 0.361), and type of publication ( p = 0.371). Depending on the type of test, the proportion of students who have an optimal level in organizational with multiple-choices tests plus open questions is 37% higher than while using only multiple-choice tests. The type of text reduces the variability by 0.27% and explains the differences between the results of the studies at the organizational level.

Forest plot of organizational level.

Table 3 shows the difference between the estimated effect sizes and the significance. There is a larger proportion of students having an optimal level of reading comprehension at the literal level compared to the inferential, critical, and organizational level; an optimal level of reading comprehension at the inferential level vs. the critical and organizational level.

Results of effect size comparison.

Analysis of Publication Bias

This research uses two ways to verify the existence of bias independently of the sample size. Table 4 shows the results and there is no publication bias at any level of reading comprehension.

Publication bias results.

This research used a systematic literature search and meta-analysis to provide estimates of the number of cases of university students who have an optimal level in the different levels of reading comprehension. All the information available on the subject at the international level was analyzed using international databases in English and Spanish, but the potentially relevant publications were limited. Only seven Spanish language studies were identified internationally. In these seven studies, the optimal performance at each level of reading comprehension varied, finding heterogeneity associated with the very high estimates, which indicates that the summary estimates have to be interpreted with caution and in the context of the sample and the variables used in this meta-analysis.

In this research, the effects of the type of measure, type of test, type of text, type of career, and type of publication have been analyzed. Due to the limited information in the publications, it was not possible to assess the effect of any more moderating variables.

We found that some factors significantly influence heterogeneity according to the level of reading comprehension considered. The type of measure influenced the optimal performance of students in the inferential level of reading comprehension; specifically, the proportion of students who have an optimal level in inferential worsens if the test is standardized. Several studies ( Pike, 1996 ; Koretz, 2002 ) identify differences between standardized and non-standardized measures in reading comprehension and a favor of non-standardized measures developed by the researchers ( Pyle et al., 2017 ). The ability to generate inferences of each individual may difficult to standardize because each person differently identifies the relationship between the parts of the text and integrates it with their previous knowledge ( Oakhill, 1982 ; Cain et al., 2004 ). This mental representation of the meaning of the text is necessary to create a model of the situation and a deep understanding ( McNamara and Magliano, 2009 ; van den Broek and Espin, 2012 ).

The type of test was significant for the organizational level of reading comprehension. The proportion of students who have an optimal level in organizational improves if the reading comprehension assessment test is multiple-choice plus open questions. The organizational level requires the reordering of written information through analysis and synthesis processes ( Guevara Benítez et al., 2014 ); therefore, it constitutes a production task that is better reflected in open questions than in reproduction questions as multiple choice ( Dinsmore and Alexander, 2015 ). McNamara and Kintsch (1996) identify that open tasks require an effort to make inferences related to previous knowledge and multidisciplinary knowledge. Important is to indicate that different evaluation test formats can measure different aspects of reading comprehension ( Zheng et al., 2007 ).

The type of text significantly influenced the inferential level of reading comprehension. The proportion of students who have an optimal level in inferential decreases with an argumentative text. The expectations created before an argumentative text made it difficult to generate inferences and, therefore, the construction of the meaning of the text. This result is in the opposite direction to the study by Diakidoy et al. (2011) who find that the refutation text, such as the argumentative one, facilitates the elaboration of inferences compared to other types of texts. It is possible that the argumentative text, given its dialogical nature of arguments and counterarguments, with a subject unknown by the students, has determined the decrease of inferences based on their scarce previous knowledge of the subject, needing help to elaborate the structure of the text read ( Reznitskaya et al., 2007 ). It should be pointed out that in meta-analysis studies, 43% use argumentative texts. Knowing the type of the text is relevant for generating inferences, for instance, according to Baretta et al. (2009) the different types of text are processed differently in the brain generating more or fewer inferences; specifically, using the N400 component, they find that expository texts generate more inferences from the text read.

For the type of career and the type of publication, no significance was found at any level of reading comprehension in this sample. This seems to indicate that university students have the same level of performance in tasks of literal, critical inferential, and organizational understanding regardless of whether they are studying social sciences, health sciences, or engineering. Nor does the type of publication affect the state of the different levels of reading comprehension in higher education.

The remaining high heterogeneity at all levels of reading comprehension was not captured in this review, indicating that there are other factors, such as student characteristics, gender, or other issues, that are moderating and explaining the variability at the literal, inferential, critical, and organizational reading comprehension in university students.

To the comparison between the different levels of reading comprehension, the literal level has a significantly higher proportion of students with an optimal level than the inferential, critical, and organizational levels. The inferential level has a significantly higher proportion of students with an optimal level than the critical and organizational levels. This corresponds with data from other investigations ( Márquez et al., 2016 ; Del Pino-Yépez et al., 2019 ) that indicate that the literal level is where university students execute with more successes, being more difficult and with less success at the inferential, organizational, and critical levels. This indicates that university students of this sample do not generate a coherent situation model that provides them with a global mental representation of the read text according to the model of Kintsch (1998) , but rather they make a literal analysis of the explicit content of the read text. This level of understanding can lead to less desirable results in educational terms ( Dinsmore and Alexander, 2015 ).

The educational implications of this meta-analysis in this sample are aimed at making universities aware of the state of reading comprehension levels possessed by university students and designing strategies (courses and workshops) to optimize it by improving the training and employability of students. Some proposals can be directed to the use of reflection tasks, integration of information, graphic organizers, evaluation, interpretation, nor the use of paraphrasing ( Rahmani, 2011 ). Some studies ( Hong-Nam and Leavell, 2011 ; Parr and Woloshyn, 2013 ) demonstrate the effectiveness of instructional courses in improving performance in reading comprehension and metacognitive strategies. In addition, it is necessary to design reading comprehension assessment tests in higher education that are balanced, validated, and reliable, allowing to have data for the different levels of reading comprehension.

Limitations and Conclusion

This meta-analysis can be used as a starting point to report on reading comprehension levels in higher education, but the results should be interpreted with caution and in the context of the study sample and variables. Publications without sufficient data and inaccessible articles, with a sample of seven studies, may have limited the international perspective. The interest in studying reading comprehension in the mother tongue, using only unimodal texts, without the influence of technology and with English and Spanish has also limited the review. The limited amount of data in the studies has limited meta-regression.

This review is a guide to direct future research, broadening the study focus on the level of reading comprehension using digital technology, experimental designs, second languages, and investigations that relate reading comprehension with other factors (gender, cognitive abilities, etc.) that can explain the heterogeneity in the different levels of reading comprehension. The possibility of developing a comprehensive reading comprehension assessment test in higher education could also be explored.

This review contributes to the scientific literature in several ways. In the first place, this meta-analytic review is the only one that analyzes the proportion of university students who have an optimal performance in the different levels of reading comprehension. This review is made with international publications and this topic is mostly investigated in Latin America. Second, optimal performance can be improved at all levels of reading comprehension, fundamentally inferential, critical, and organizational. The literal level is significantly the level of reading comprehension with the highest proportion of optimal performance in university students. Third, the students in this sample have optimal performance at the inferential level when they are non-argumentative texts and non-standardized measures, and, in the analyzed works, there is optimal performance at the organizational level when multiple-choice questions plus open questions are used.

The current research is linked to the research project “Study of reading comprehension in higher education” of Asociación Educar para el Desarrollo Humano from Argentina.

Data Availability Statement

Author contributions.

Cd-l-P had the idea for the article and analyzed the data. ML-R searched the data. Cd-l-P and ML-R selected the data and contributed to the valuable comments and manuscript writing. All authors contributed to the article and approved the submitted version.

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.

The handling editor declared a shared affiliation though no other collaboration with one of the authors ML-R at the time of the review.

Publisher’s Note

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.

Funding. This paper was funded by the Universidad Internacional de la Rioja and Universidad de Málaga.

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• Group B2: Master's Thesis Students

Final round

Thursday, April 11, 2024, at 7 p.m. in the Wells Fargo Auditorium (MIKC 124)

In the final round you'll compete against the eight finalists at your degree level:

• Group A — Doctoral Students (Four students from A1 and four students from A2)
• Group B — Master's Students (Four students from B1 and four students from B2)

Award amounts

Winners from each group of the final round will be awarded as follows:

• First Place: $1,000
• Second Place: $600
• Third Place: $400
• Peoples' Choice: $500

Deadline and application form

Applications are due February 29 by 11:59 p.m.

Preliminary submission form

Competition rules and terms

Presentation:.

• A single, static PowerPoint slide in 16x9 format is required (pdfs not allowed).
• Include your presentation title, full name, and graduate program on the slide.
• First-place winners from the last year's 3MT competition are ineligible to compete, however, last year's second- and third-place winners are eligible to compete.
• No slide transitions, animations or on-screen movement of any description are allowed.
• The slide is to be presented from the beginning of the oration.
• No additional electronic media (e.g. sound and video files) are permitted.
• No additional props (e.g. costumes, musical instruments, laboratory equipment) are permitted.
• Presentations are limited to three minutes maximum; competitors exceeding three minutes are disqualified.
• Presentations are to be spoken word (e.g. no poems, raps or songs).
• Presentations are to commence from the stage.
• Presentations are considered to have commenced when a presenter starts their presentation through either movement or speech.
• The decision of the adjudicating panel is final.
• All monetary awards for both preliminary and final rounds are pre-tax amounts.
• Abstracts are limited to 250 words.
• Students must be graduate students to enter the competition.
• While advancement to candidacy is not required, students must have made significant progress towards completion of their dissertation, thesis, or professional project in order to enter the competition.
• Winners will be announced approximately one week after the competition.
• You will be asked to sign a photo-video release at the event to allow the University of Nevada, Reno to use your likeness in photos/videos of the competition.

Judging criteria

Comprehension & content.

• Did the presentation provide an understanding of the background to the research question being addressed and its significance?
• Did the presentation clearly describe the key results of the research including conclusions and outcomes?
• Did the presentation follow a clear and logical sequence?
• Was the thesis topic, key results and research significance and outcomes communicated in language appropriate to a non-specialist audience?
• Did the speaker avoid scientific jargon, explain terminology and provide adequate background information to illustrate points?
• Did the presenter spend adequate time on each element of their presentation - or did they elaborate for too long on one aspect or was the presentation rushed?

Engagement & Communication

• Did the oration make the audience want to know more?
• Was the presenter careful not to trivialize or generalize their research?
• Did the presenter convey enthusiasm for their research?
• Did the presenter capture and maintain their audience's attention?
• Did the speaker have sufficient stage presence, eye contact and vocal range; maintain a steady pace, and have a confident stance?
• Did the PowerPoint slide enhance the presentation - was it clear, legible, and concise?

View past Three Minute Thesis winners

View the winners of each year since 2014!

View past winners

2022-2023 Finalists and winners

Doctoral category

First place: cody cris.

• Graduate program:  Cell and Molecular Biology
• Title:  Lighting the way: Tools to prepare for future pandemics
• Faculty advisor:  Subhash Verma

SECOND PLACE: Anithakrithi Balaji

• Graduate program: Biomedical Engineering
• Title: Electrifying the fight-or-flight response: Nanosecond electric pulses for neuromodulation
• Faculty advisor: Jihwan Yoon

THIRD PLACE: Noah Nieman

• Graduate program:  Civil and Environmental Engineering
• Title:  Accelerating bridge construction connections behavior during near fault motions
• Faculty advisor: Floriana Petrone

2024 Finalists:

Francisco calderon abullarade.

• Graduate program: Ph.D. History
• Title: Creating the Enemy: The origins of the inter-american cold war in the 1940s
• Faculty advisor: Renata Keller

Anithakrithi Balaji

• Graduate program: Ph.D. Biomedical Engineering
• Title: Electrifying the fight-or-flight response: Nanosecond electric pulses for neuromodulation 

Monika Bharti

• Graduate program: Ph.D. Education - Literacy Studies
• Title: P re-service teachers experiences teaching K-8 Multilingual Students' (MLS) writing
• Faculty advisor: Rachel Salas and Fares Karam

Cossette Canovas

• Graduate program: Ph.D. Clinical Psychology
• Title: Identifying predictors of racial trauma to inform treatment development 
• Faculty advisor: Lorraine Benuto
• Graduate program: Ph.D. Cell and Molecular Biology
• Title:   Lighting the way: Tools to prepare for future pandemics 
• Faculty advisor: Subhash Verma

Kaashifah 

• Graduate program: Ph.D. Education - Equity, Diversity and Language
• Title: Bridging  the gaps: Evaluating the intervention programs to overcome academic disparities 
• Faculty advisor: Donald Easton-Brooks

Noah Nieman

• Graduate program: Ph.D. Civil and Environmental Engineering
• Title: Accelerating bridge construction connections behavior during near fault motions 

Sanjeevan Pradhan

• Graduate program: Ph.D. Political Science
• Title: Tough sell: Rising powers, domestic legitimation and costly international initiatives 
• Faculty advisor: Xiaoyu Pu

Patricia Berninsone People's Choice Award

Abdulwarith kassim.

• Graduate program: Chemistry
• Title: Chemically recyclable dithioacetal polymers
• Faculty advisor:  Ying Yang

Master's category

First place: abdulwarith kassim.

• Faculty advisor: Ying Yang

SECOND PLACE (TIE): 

• Name:  Elizabeth Everest
• Graduate program: Ecology, Evolution and Conservation Biology
• Title: Sustaining the beating heart of Cambodia: Fisheries management in southeast Asia's largest lake
• Faculty advisors: Zeb Hogan, Sudeep Chandra, Ken Nussear
• Name:  Cathy Silliman
• Title: Winterfat restoration in a changing climate
• Faculty advisor: Elizabeth Leger 

Samantha DeTiberiis

• Graduate program: M.A. Criminal Justice 
• Title: What do our phones teach us about incarceration? A social media content analysis 
• Faculty advisor: Jennifer Lanterman

Elizabeth Everest 

• Graduate program: M.S. Ecology, Evolution and Conservation Biology 
• Title:   Sustaining the beating heart of Cambodia: Fisheries management in southeast Asia's largest lake 
• Faculty advisor: Zeb Hogan, Sudeep Chandra, Ken Nussear

Carolynn Fedarko 

• Title: Zeroing in on gun violence
• Faculty advisor: Weston Morrow

Shipra Goswami

• Graduate program: M.S. Biochemistry
• Title: May the pericytes be with you: Transport engineers you never knew existed!
• Faculty advisor: Albert Gonzales
• Graduate program: M.S. Chemistry 

Anthony Michell

• Graduate program: M.A. History
• Title: Pushed to the limit: How the 1998 China floods revolutionized the relationship between China and the natural world
• Faculty advisor: Hugh Shapiro

Elizabeth Morgan

• Graduate program: M.S. Teaching History (M.A.T.H.)
• Title: Dust in the wind dude: The Owens Valley everywhere except, in the Owens Valley
• Faculty advisor: Edward Schoolman

Cathy Silliman

• Graduate program: M.S. Ecology, Evolution and Conservation Biology
• Faculty advisor: Elizabeth Leger

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The Princess Bride by William Goldman Reading Comprehension Worksheet

Subject: English

Age range: 14-16

Resource type: Worksheet/Activity

Last updated

2 September 2024

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We are pleased to present this comprehensive teaching resource for “The Princess Bride” by William Goldman. This Reading Comprehension Worksheet is meticulously designed to enhance various skills essential for academic success. The resource focuses on developing a range of skills including word meaning, inferences, summaries, analysis and evaluation, content structure and quality, retrieval, predicting, explaining and exploring, comparison and synthesis.

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Don’t miss out on this opportunity to incorporate a high-quality teaching resource into your curriculum. Download the worksheet today and empower your students to explore the enchanting world of “The Princess Bride” in an engaging and educational manner.

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