Scholarly Articles About Reading Levels in the United States

Introduction

Reading comprehension allows the integration of cognition 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 cocky-straight their academic-professional learning and provide critical thinking in favor of customs service (UNESCO, 2009). All the same, inquiry in recent years (Bharuthram, 2012; Afflerbach et al., 2015) indicates that a role of university students are not prepared to successfully bargain with academic texts or they take reading difficulties (Smagorinsky, 2001; Cox et al., 2014), which may limit academic preparation focused on written texts. This work aims to review the level of reading comprehension provided past studies carried out in unlike 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 near accepted model of reading comprehension, processing levels are differentiated, specifically: A superficial level that identifies or memorizes information forming the basis of the text and a deep level in which the text situation model is elaborated integrating previous experiences and cognition. At these levels of processing, the cerebral 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 disquisitional level that require the elaboration of inferences and the data transformation.

Studies focused on higher education (Barletta et al., 2005; Yáñez Botello, 2013) testify that academy 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 equally the enquiry on reading comprehension in the mother tongue in the university population. Bharuthram (2012) indicates that university students practice not access or develop effective strategies for reading comprehension, such as the chapters for abstraction and synthesis-analysis. Later, Livingston et al. (2015) find that first-year education students present express reading strategies and difficulties in understanding written texts. Ntereke and Ramoroka (2017) constitute that only 12.four% 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 instance, 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 adopt to read in print vs. digital texts. In reading the written text, metacognitive strategies are involved (Amril et al., 2019) only studies (Channa et al., 2018) seem to betoken that students do not use them for reading comprehension, specifically; Korotaeva (2012) finds that only seven% of students utilize them. Concerning the blazon 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 than difficult to read than narrative texts. Regarding the modality of the text, Mayer (2009) and Guo et al. (2020) bespeak that multimodal texts that contain images into the text positively amend reading comprehension. In a study of Kobayashi (2002) using open questions, shut, and multiple-option shows that the type and format of the reading comprehension assessment test significantly influence pupil operation and that more structured tests assist 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 ameliorate level of reading comprehension than men and with noesis related to reading (Perfetti et al., 1987). In this inquiry, it was controlled that all were printed and unimodal texts, that is, only text. This is essential considering the cerebral processes involved in reading comprehension tin 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 determinative 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 teaching; specifically, the proportion of university students who perform optimally at each level of reading comprehension. It is of import to note that there is not much information nigh the different levels in academy 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 academy system requires that students produce noesis 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 capacity or review books or publications; (b) articles in other languages; (c) studies of lower educational levels; (d) articles that practice not place the age of the sample; (due east) second language studies; (f) students with learning difficulties or other disorders; (g) publications that practice non indicate the level of reading comprehension; (h) studies that relate reading competence with other variables but practise not report reading comprehension levels; (i) pre-post plan application work; (j) studies with experimental and control groups; (k) articles comparing pre-academy stages or adults; (fifty) publications that use multi-texts; (m) studies that use some type of applied science (computer, hypertext, spider 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 inquiry (article, thesis, final caste/master'due south degree, or conference proceedings book); (b) university stage; (c) include data or some measure on the level of reading comprehension that allows calculating the outcome size; (d) written in English language or Spanish; (eastward) reading comprehension in the commencement language or mother tongue; and (f) the temporary period from Jan 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 language, such every bit 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 post-obit terms (titles, abstracts, keywords, and full text) are used to select the manufactures: Reading comprehension and higher education, academy students, in Spanish and English, combined with the Boolean operators AND and OR. In the last footstep, secondary sources, such as the Google search engine, Theseus, and references in publications, are explored.

The search reports four,294 publications (manufactures, 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 total text cannot be accessed (the authors were contacted just did not respond), the total text did not evidence 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 academy students. Information additional to those included in the articles were non 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 option of publications relevant to the subject is exposed (Figure 1).

Figure one. Flow diagram for the selection of articles.

Encoding Procedure

This research complies with what is established in the manual of systematic reviews (Higgins and Greenish, 2008) in which clear objectives, specific search terms, and eligibility criteria for previously defined works are established. 2 contained coders, reaching a 100% understanding, carry out the study search process. Subsequently, the research is codified, for this, a coding protocol is used as a guide to aid 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, state, research objective, sample size, age and gender, reading comprehension exam, other tests, and reading comprehension results were coded in percentages. All this information was subsequently systematized in Table 1.

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 equally follows: i = literal; 2 = inferential; iii = 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 not-standardized measures created by the researchers themselves in their studies or questionnaires by other authors. By the type of evaluation exam, we encode between multiple-selection (value = 0) or multiple-choices plus open up 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 = i) or other careers (wellness sciences; value = 0). Moreover, by the type of publication, we encode betwixt commodity (value = 1) or doctoral thesis (value = 0).

Upshot Size and Statistical Analysis

This descriptive written report with a sample k = 7 and a population of i,044 university students used a continuous variable and the proportions were used equally the effect size to clarify 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 issue size. These random-effects models have a greater capacity to generalize the conclusions and let estimating the effects of different sources of variation (moderating variables). The DerSimonian and Laird method (Egger et al., 2001) was used, computing raw proportion and for each proportion its standard mistake, value of p and 95% confidence interval (CI).

To examine sampling variability, Cochran's Q test (to test the nada hypothesis of homogeneity between studies) and I ² (proportion of variability) were used. According to Higgins et al. (2003), if I ^two reaches 25%, it is considered depression, if it reaches 50% and if information technology exceeds 75% it is considered loftier. A meta-regression analysis was used to investigate the issue of the moderator variables (type of measure, blazon of evaluation test, blazon of text, blazon 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, disquisitional, and organizational) of reading comprehension, the chi-foursquare test for the proportion recommended past Campbell (2007) was used.

Finally, to analyze publication bias, this study uses two ways: Rosenthal'south fail-safe number and regression test. Rosenthal'south fail-condom number shows the number of missing studies with nix effects that would make the previous correlations insignificant (Borenstein et al., 2009). When the values are large in that location is no bias. In the regression exam, 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.

Results

The results of the meta-analysis are presented in 3 parts: the full 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 area published from 2010 to March 2021 generated a small number of publications, considering it was express to the higher teaching stage and required clear statistical data on reading comprehension.

Table one presents all the publications reviewed in this meta-assay 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. Virtually of the sample comes from academy degrees in social sciences, such as psychology and teaching (71.42%) followed by health sciences (xiv.28%) engineering science and a publication (14.28%) that does non signal origin. These publications selected co-ordinate to the inclusion criteria for the meta-analysis come from more countries with a variety of educational systems, simply all from Due south America. Specifically, the countries that take more studies are Mexico (28.57%) and Colombia, Republic of chile, Republic of bolivia, Peru, and Republic of ecuador with xiv.28% each, respectively. The years in which they were published are two.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, disquisitional, 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% not-standardized measures. Co-ordinate to the evaluation test used, 29% use multiple-selection 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). Past type of career, 71% are students of social sciences and 29% of other different careers, such as engineering science or wellness sciences. In improver, 71% are articles and 29% with enquiry works (thesis and degree works).

Tabular array 2 shows the reading comprehension assessment instruments used by the authors of the empirical enquiry integrated into the meta-analysis.

Table 2. Reading comprehension cess tests used in college education.

Meta-Analytic Analysis of the Level of Reading Comprehension

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

Effigy 2. Woods plot of literal level.

The inferential level presents a hateful proportion effect size of 33% (95% CI = 19–46%; Figure iii). The variability between the different samples of the inferential level of reading comprehension was pregnant (Q = 125.123, p < 0.001; I ² = 95.2%). The blazon 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 blazon of measure, the proportion of students who have an optimal level in inferential administering a standardized test is 28.7% less than when a not-standardized test is administered. The blazon of measure reduces variability by 2.57% and explains the differences between the results of the studies at the inferential level. According to the blazon of text, the proportion of students who have an optimal level in inferential using an belligerent text is 28.vii% less than when using another type of text. The type of text reduces the variability by two.57% and explains the differences between the results of the studies at the inferential level.

Figure 3. Forest plot of inferential level.

The disquisitional level has a mean effect size of the proportion of 22% (95% CI = ix–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 ^two = 99.04%). No moderating variable used in this research had a meaning 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 loftier variability is explained past other factors not considered in this piece of work, such equally the characteristics of the students (cerebral abilities).

Figure four. Wood 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 blazon of test fabricated a significant contribution to heterogeneity (p = 0.289). The other moderating variables were not significant in this research: type of measurement (p = 0.289), blazon 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% college than while using but multiple-choice tests. The type of text reduces the variability by 0.27% and explains the differences betwixt the results of the studies at the organizational level.

Figure 5. Forest plot of organizational level.

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

Table 3. Results of effect size comparing.

Analysis of Publication Bias

This research uses 2 ways to verify the being of bias independently of the sample size. Table iv shows the results and there is no publication bias at whatever level of reading comprehension.

Table 4. Publication bias results.

Give-and-take

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 data available on the field of study at the international level was analyzed using international databases in English language and Castilian, but the potentially relevant publications were express. Just seven Spanish language studies were identified internationally. In these vii studies, the optimal performance at each level of reading comprehension varied, finding heterogeneity associated with the very loftier estimates, which indicates that the summary estimates take to be interpreted with caution and in the context of the sample and the variables used in this meta-assay.

In this inquiry, the effects of the type of mensurate, type of test, type of text, type of career, and type of publication accept been analyzed. Due to the limited information in the publications, information technology was non possible to assess the result of any more moderating variables.

We constitute that some factors significantly influence heterogeneity according to the level of reading comprehension considered. The type of mensurate 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 (Freeway, 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 considering each person differently identifies the relationship betwixt the parts of the text and integrates it with their previous noesis (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 agreement (McNamara and Magliano, 2009; van den Broek and Espin, 2012).

The blazon 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-option 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 ameliorate reflected in open questions than in reproduction questions as multiple option (Dinsmore and Alexander, 2015). McNamara and Kintsch (1996) identify that open tasks require an effort to brand inferences related to previous noesis and multidisciplinary cognition. Important is to indicate that different evaluation exam formats tin measure different aspects of reading comprehension (Zheng et al., 2007).

The blazon of text significantly influenced the inferential level of reading comprehension. The proportion of students who have an optimal level in inferential decreases with an belligerent 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 contrary management to the written report 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. Information technology is possible that the argumentative text, given its dialogical nature of arguments and counterarguments, with a bailiwick unknown by the students, has determined the decrease of inferences based on their scarce previous knowledge of the subject, needing assistance 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, co-ordinate to Baretta et al. (2009) the unlike types of text are processed differently in the brain generating more than or fewer inferences; specifically, using the N400 component, they find that expository texts generate more inferences from the text read.

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

The remaining high heterogeneity at all levels of reading comprehension was non captured in this review, indicating that at that place are other factors, such every bit 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 betwixt the dissimilar levels of reading comprehension, the literal level has a significantly college proportion of students with an optimal level than the inferential, disquisitional, 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 Pine-Yépez et al., 2019) that signal 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 practise 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 brand a literal assay of the explicit content of the read text. This level of agreement tin 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 past 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 operation 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 take data for the dissimilar levels of reading comprehension.

Limitations and Decision

This meta-assay can be used equally a starting point to report on reading comprehension levels in higher teaching, 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 7 studies, may accept limited the international perspective. The involvement in studying reading comprehension in the female parent tongue, using just unimodal texts, without the influence of applied science 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 inquiry, broadening the study focus on the level of reading comprehension using digital engineering, experimental designs, second languages, and investigations that relate reading comprehension with other factors (gender, cerebral 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 means. In the commencement place, this meta-analytic review is the only one that analyzes the proportion of academy students who have an optimal operation in the unlike levels of reading comprehension. This review is made with international publications and this topic is mostly investigated in Latin America. Second, optimal operation tin 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 take optimal performance at the inferential level when they are non-argumentative texts and non-standardized measures, and, in the analyzed works, there is optimal functioning at the organizational level when multiple-choice questions plus open up questions are used.

The current enquiry is linked to the research projection "Report of reading comprehension in higher education" of Asociación Educar para el Desarrollo Humano from Argentina.

Data Availability Statement

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

Writer Contributions

Cd-l-P had the idea for the article and analyzed the data. ML-R searched the data. Cd-50-P and ML-R selected the data and contributed to the valuable comments and manuscript writing. All authors contributed to the commodity and approved the submitted version.

Funding

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

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 fourth dimension of the review.

Publisher'south 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 exist evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed past the publisher.

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