Improving Expository Text Comprehension in Adolescent Spanish–English Bilingual Learners With Learning Disabilities Using a Graphic Organizer

Abstract

The purpose of this study was to examine the efficacy of a graphic organizer for improving the expository text comprehension of adolescent Spanish–English bilingual students with learning disabilities. Students were two females and one male. Using a multiple baseline single case design, researchers taught students to create a funnel map graphic organizer for 10 descriptive text passages. Students’ performance was assessed on their ability to correctly create the funnel map (criterion variable) and to comprehend expository passages during baseline, intervention, and maintenance phases. Each participant learned to create an accurate funnel map within four sessions. Text comprehension scores began to increase within three sessions. Results showed the positive effect of using the funnel map for improving comprehension of expository texts. Individual Tau effect sizes (.81–.92) and overall Tau-U effect sizes (.86) and a Between Case-Standardized Mean Difference (BC-SMD) of 1.87 showed the intervention to be highly effective.

Keywords

reading single-subject methods research design or utilization instructional strategies diversity

The reading proficiency of Spanish–English bilingual learners with learning disabilities (LDs) is of high concern for both educators and researchers. According to the National Assessment of Education Progress (NAEP, 2019), 96% of bilingual learners (Note 1) and 91% of students with disabilities in eighth grade were reading below proficient levels. On the 2019 NAEP reading assessment, bilingual learners scored 221 and students with disabilities scored 229, with 280 considered “proficient.” While NAEP did not report the number of Spanish–English bilingual learners with LD reading at proficiency, they did report that 78% of Hispanic students were reading below proficient levels compared with 58% of their White peers.

Since 2000, the percentage of Spanish–English bilingual students in the United States has increased from 16% to 25% (National Center for Education Statistics [NCES], 2019b). In 2015, 4.9 million children whose heritage language was one other than English attended public schools in the United States and of that number, 77% spoke Spanish as their heritage language (NCES, 2019a). In the 2018 to 2019 school year, the number of Spanish–English bilingual learners in public schools who received special education services approached one million (NCES, 2020a, 2020b). Of these children, more than 740,000 were identified as having a specific LD.

Reading comprehension is arguably the most important skill for children to develop as they progress through their formal education. However, many adolescent bilingual students with LD struggle with reading comprehension in the late elementary and middle grades as they encounter different text structures (Lesaux & Kieffer, 2010; M. Li et al., 2020) and the demand for more complex oral language skills, vocabulary, and background knowledge increases (Farnia & Geva, 2013). Moreover, adolescent bilingual learners with LD often lag behind in the development of these complex skills in English (Grimm et al., 2018; Kieffer, 2012; Lesaux & Kieffer, 2010). Because many adolescent bilingual learners with LD have poor reading comprehension, they are at risk for academic failure (Faggella-Luby & Deshler, 2008; Richman et al., 1998) and at risk for dropping out of school (Vaughn et al., 2015).

This single-case design (SCD) study focused on a comprehension intervention using expository texts. Single-case designs provide a rigorous approach to evaluating educational interventions and have shown promise for identifying effective interventions by establishing a functional relation between the intervention and target skill or behavior (Klingbeil et al., 2017). In the present study, we sought to determine whether there was a functional relationship between teaching students to use a graphic organizer during the reading of expository texts (intervention) and text comprehension (target skill). Expository texts are more difficult to comprehend than narrative texts because they contain new and abstract concepts and discuss complex relationships among concepts (Coté et al., 1998; Kraal et al., 2018; Meyer & Ray, 2011). As students enter the middle grades, content area educators expect students to be able to understand complex expository texts; however, many bilingual students with LD struggle to comprehend these complex texts (Lesaux et al., 2010; Mancilla-Martinez & Lesaux, 2011; Swanson et al., 2017).

Although there is a great need for research-based reading comprehension interventions for bilingual students with LD, there are few studies with this population. We identified several studies that reported positive reading comprehension outcomes for bilingual learners and students with disabilities (Vaughn et al., 2009, 2010, 2011; Wanzek et al., 2011). Each study incorporated multiple components to improve reading comprehension. Within the components, a common tool included in these “packaged” interventions was the use of graphic organizers.

Graphic Organizers and Reading Comprehension

Graphic organizers are visual displays that help students construct meaning by organizing, clarifying, or simplifying complex information and by establishing relationships across concepts (Boyle, 2000; Kim et al., 2004). They use visual cues to represent conceptual information in an easy-to-understand format (Ciullo et al., 2015; Stull & Mayer, 2007). Graphic organizers can be used during the reading process to highlight key concepts, assist with note-taking (Dexter et al., 2011), and to support students with comprehension of different text structures (e.g. descriptive, cause and effect, problem and solution, classification, compare and contrast). Because of their versatility, graphic organizers can be used to build background knowledge (Dexter et al., 2011), vocabulary (Gallagher et al., 2019), and to support inference making (McCrudden & Rapp, 2017) and text structure understanding (Strong, 2020).

As students read, they rely on attention and working memory to process the meaning of text. Attention involves a student’s ability to focus on a message and process it using working memory (McCrudden & Rapp, 2017). Working memory provides temporary storage of information necessary to perform complex tasks such as comprehension, learning, and reasoning (Baddeley, 2010). When used during reading, a graphic organizer may improve a student’s processing efficiency by providing a permanent representation of the mental model of a text, by helping to organize important information, and by highlighting connections among concepts (McCrudden & Rapp, 2017). Moreover, a graphic organizer reduces the need to hold information in working memory while reading and reduces the need to search for information in the text.

According to two prior meta-analyses, students with LDs benefited from the use of graphic organizers for improving factual recall (Kim et al., 2004) and inferencing (Dexter et al., 2011). In a third meta-analysis on the effects of instructional strategies on the reading comprehension of English Learners, J. Li et al. (2021) found that graphic organizers provided bilingual learners with a “visual representation which helps them tangibly and systematically understand text concepts and link fragments of information together” (p. 13). Furthermore, Li et al. reported a large effect size for bilingual learners’ reading comprehension and the use of graphic organizers (g = .98).

Several studies have examined the effects of graphic organizers on the reading comprehension of students with LD. Boyle (1996) found significant between-group differences in a randomized control trial (RCT) matched pair design in favor of the treatment group (p = .006) and large effect sizes for both literal and inferential comprehension (literal $η_{p}^{2} = . 33$ ; inferential $η_{p}^{2} = . 21$ ) on proximal measures of reading comprehension when using a cognitive mapping strategy, a type of graphic organizer, on 30 monolingual English middle school students with LD. Using an RCT, Boyle (2000) also found significant between-group differences (p < .05) and large effect sizes for literal (d = 1.17) and relational (d = 0.87) comprehension in favor of the treatment group, but no significant differences for inferential comprehension (p > .05; d = 0.36) on proximal measures using a Venn diagram while reading compare and contrast texts with 24 monolingual English ninth- and 10th-grade students.

Two additional studies used SCDs to investigate the effects of graphic organizers on the reading comprehension of upper elementary and middle school bilingual learners and students with LD. Calvin and Gray (2022) provided explicit instruction on the use of a graphic organizer of seventh- and eighth-grade Spanish–English bilingual students (n = 3) reading compare and contrast expository texts. The intervention took place over 12 one-hour sessions and was taught by trained undergraduate research assistants (RAs). Students learned to create a double-bubble map, a type of Venn diagram, while reading. After completing the double-bubble map, students answered comprehension questions related to the text using the graphic organizer. Across baseline and intervention phases, results suggested a large effect size on proximal measures of reading comprehension (p < .05; Tau-U = .94). Ciullo et al. (2015) examined the use of a graphic organizer on the social studies reading comprehension of fourth- and fifth-grade students with LD (n = 7) for 45-min sessions over a 6-week period. A certified teacher delivered the intervention. Students received a premade graphic organizer with information prefilled from the text. Every three sessions, two boxes were left blank for students to complete with the teacher’s assistance. After completing the graphic organizer, students reviewed the information with the teacher and then answered comprehension questions related to the passage. The researchers found a large effect size (PND = .96) across baseline and intervention phases.

Summary

When students enter intermediate and middle grades, the use of comprehension strategies can contribute to improved comprehension of written texts (Edmonds et al., 2009). Previous research has shown that many bilingual learners and students with LD benefit from strategy instruction to understand what they are reading. Interventions with the largest effects on reading comprehension for bilingual learners and students with LD involved multiple components including graphic organizers (Vaughn et al., 2009, 2011) or the use of graphic organizers alone (Boyle, 1996, 2000; Calvin & Gray, 2022; Ciullo et al., 2015). While these studies demonstrated efficacy, there were limitations. First, because most of the studies used multiple components, we do not know which active ingredients resulted in significant between-group differences. Second, the length of treatment in the multiple component interventions spanned several months to an entire school year—a significant investment of time and resources. If similar effects could be achieved with less resources, that is important to know. Finally, several of the multiple component interventions used classroom teachers as the interventionist which may be cost prohibitive for schools. Interventions that can be delivered by support personnel may be more feasible and cost-effective to deliver.

Purpose

The purpose of this study was to evaluate whether the use of a funnel map graphic organizer improved the reading comprehension of bilingual learners with LD (Note 2) when they were reading descriptive expository texts. The study addressed some of the limitations noted above. We investigated a single strategy that was delivered by trained RAs over 10 one-hour sessions. The intervention lessons were directly aligned with Common Core State Standards (CCSS; National Governors Association, 2010) literacy strands within content area standards. The intervention utilized explicit instruction to teach students to use a graphic organizer as a notetaking tool to aid in the comprehension of descriptive texts.

We hypothesized that the use of the funnel map would enable students to better comprehend expository texts because they help readers focus on key concepts and how they relate to other concepts in the text and reduce the need to hold information in working memory. The research questions were as follows:

Research Question 1. Are students able to independently draw and correctly label a funnel map within 10 sessions?

Research Question 2. Does explicit instruction on the use of the funnel map increase expository comprehension in students who are bilingual learners with LD?

Research Question 3. Does explicit instruction on the use of a funnel map have a bigger effect on students’ ability to answer literal versus inferential questions?

Research Question 4. Do students perceive the usefulness of the funnel map to support reading comprehension?

Method

Using an SCD, we followed the What Works Clearinghouse Handbook 4.1 Single Case Design guidelines (2020) to ensure that the study met standards without reservations. The study consisted of three phases: baseline, intervention, and maintenance and had five baseline data points, 10 intervention data points, and two maintenance data points with three replications. The study took place via Zoom, an online platform, which allowed students to participate in the intervention without in-person contact due to COVID-19 restrictions. All baseline, intervention, and follow-up sessions were delivered via Zoom in a 1:1 format with an RA.

Participants

Seventh- and eighth -grade students were recruited from 10 school districts in a southwestern U.S. state and through Facebook advertisements. Study procedures were approved by the university’s Institutional Review Board. Consent packets and questionnaires were provided to families in both Spanish and English. Parents completed a questionnaire to provide demographic information about their family and their child including race, ethnicity, and languages spoken in the home.

To qualify for inclusion in the study students met the following criteria: (a) enrolled in seventh or eighth grade; (b) started preschool or kindergarten speaking primarily Spanish per parent report; (c) achieved a standard score of 75 or higher on the matrices subtest of the Kaufman Brief Intelligence Test, Second Edition (KBIT-2; Kaufman & Kaufman, 2004); (d) standard score below 85 on the Woodcock Reading Mastery Test (WRMT) Passage Comprehension subtest (Woodcock, 2011); scaled score of 75 or above on the Test of Word Reading Efficiency (Torgesen, et al. 2012), Second Edition (TOWRE-2); and (f) score below 90% or below on baseline measures to ensure that students could demonstrate growth once the independent variable was implemented. While we were not able to verify with school districts if students had an individualized education plan for a LD, we chose the cut scores on the KBIT-2 Matrices subtest and WRMT Passage Comprehension subtest to be consistent with qualifying scores for special education services. We acknowledge that these may vary district to district and state to state; however, by ensuring that our participants met these criteria the study becomes more replicable.

Nine parents consented to their child’s participation. Of the nine students consented, two never responded to scheduling requests. Thus, seven students were administered the inclusionary measures and met the minimum criteria to enter the baseline phase. Three students were excluded because they achieved 100% on at least one baseline comprehension measure (testing). Of the four who continued in the study, one did not complete the sessions due to scheduling conflicts. Thus, three students completed the study. See Table 1 for descriptive statistics.

Table 1.

Descriptive Statistics.

Participant	Ethnicity	Gender	Grade	Age	KBIT-2Nonverbal IQ	WRMTPassage comprehension	TOWRE
Student 1	Hispanic	Female	7	12	121	80	83
Student 2	Hispanic	Female	8	13	118	81	79
Student 3	Hispanic	Male	7	12	81	75	71

Note. KBIT-2 = Kaufman Brief Intelligence Test, Second Edition (Kaufman & Kaufman, 2004; x = 100; SD = 15); WRMT = Woodcock Reading Mastery Test, Revised (Woodcock, 2011; x = 100; SD = 15); TOWRE: Test of Word Reading Efficiency (x = 100; SD = 15).

Materials

Prior to the start of the study, 23 biographical reading passages were written at a sixth-grade level by the first author. This level was selected because students with LD typically read and comprehend text below grade level; therefore, we did not want them to become discouraged if they could not read or understand the texts. To further mitigate word reading difficulties, each RA read the same randomly assigned text during each baseline and intervention session while the student followed along using a written copy. Researcher-created texts were necessary because the number of equated expository instructional and assessment passages required for this study not available. Although equating across texts is very challenging, we used Coh-Metrix metrics (Graesser et al., 2011) to make the passages as similar as possible. Each passage was written to score within one standard deviation of the word length (M = 256; SD = .53), sentence length (M = 12.74; SD = .01), and grade-level (M = 6.5; SD = .06) mean for baseline passages and intervention passages. We anticipated that additional passage characteristics such as number of idea units and vocabulary, and the background knowledge of participants, could affect participant performance; therefore, once the passages were equated using Coh-Metrix, we randomly assigned them to a passage order then used for all participants.

We taught students to create a funnel map, to record handwritten notes about the details and to infer the main idea of each expository text (see Supplemental Appendix A). Students created the funnel map while following along as the RA read the passage. Each paragraph of text had a vertical flow where students listed key details of each paragraph. After identifying the key details, students reviewed the information and determined the main idea of the passage. The design of the map allowed students to see how details contributed to the main idea of the text and to record the key details without having to read back through the text to find information. Note that in Supplemental Appendix A, although three paragraphs are represented in the funnel map, some texts may have more or fewer than three paragraphs and some paragraphs had more or fewer details to provide varied practice.

Measures

Inclusionary Measures

All inclusionary measures were administered by trained RAs via zoom.

KBIT-2

The KBIT-2 was used a screening measure to ensure that students’ nonverbal IQ was 75 or higher. We chose the Matrices subtest to gain a more accurate assessment of cognitive ability should students have a language disorder. The Matrices subtest consists of 46 nonverbal measures composted of different types of items involving visual stimuli. The reliability for the KBIT-2 Matrices subtest is .88 and had correlational scores to the Wechsler Intelligence Scale for Children, Third Edition (WISC-III) and Wechsler Intelligence Scale for Children, Fourth Edition (WISC-IV) of .53 and .56.

TOWRE-2

The TOWRE-2 was administered to ensure that students were able to decode the reading passages written a sixth-grade level. Students completed the Sight Word Efficiency (SWE) and the Phonemic Decoding Efficiency (PDE) subtests which are timed tests. The TOWRE is a nationally normed measure with reliability above .90. The test–retest coefficients range from .83 to .96.

WRMT

The passage comprehension subtest of the WRMT was administered to better understand students’ ability to comprehend written text and ensure that students met the criteria of having an LD. The passage comprehension subtest uses a cloze procedure where a word(s) is omitted from a sentence. The student supplied a word that was appropriate for the sentence. Reliability for each of the clusters exceeded .80. Concurrent validity with the Woodcock-Johnson III passage comprehension was high (.68).

Baseline and Intervention Measures

Baseline and intervention measures assessed the student’s ability to correctly create the funnel map (our criterion variable) and to answer 10 comprehension questions about the text (see description below). Prior to beginning the study, from a pool of 23 researcher-created biographical texts, we randomly assigned a text and the corresponding reading comprehension questions to each baseline session, intervention session, data point assessments, and maintenance sessions. Thus, no text was repeated within sessions or assessments and each student had the same text at the same point in the study.

During baseline and intervention assessments, each RA read a new passage aloud to the student to ensure that reading decoding problems did not negatively impact the student’s understanding of the text and the student followed along with a written copy. The RA then reread the passage and asked the student to create a graphic organizer that included key details from each paragraph and the identification of the main idea. The RAs did not provide prompts or give support during the baseline and intervention sessions. After creating a graphic organizer, the student answered 10 comprehension questions related to the text. During the intervention phase, the assessment was administered at the end of the teaching session.

The funnel map served as the criterion variable (see Figure 1). The student received one point for each key detail listed. The total number of key details listed by the student were divided by the total number of correct details in the text to determine the percentage correct. For example, if a student listed seven details in the biographical text, but there were 10 details, the student received a score of 70%.

Figure 1.

Percentage Correct of Funnel Map and Reading Comprehension (RC) Means.

The student also received three points for correctly identifying the main idea. More points were awarded for the main idea because inferring the main idea requires a synthesis of key details, rather than identifying information explicitly stated in the text. The main idea was scored by trained RA using a rubric. Students earned three points if their response clearly synthesized information across the passage to form the main idea, two points if their response synthesized one or two details in the passage, one point if they retold information in the passage with no synthesizing, and zero points if they only stated the topic of the passage.

To calculate an overall score for the funnel map, percentages of the key details and main idea were averaged to determine the overall percentage. For example, in the previous example, if a student received 70% on key details and 100% on the main idea, the sum of the two scores is 170. This score would be divided by two for a total score of 85% on the funnel map.

For baseline and intervention phases, reading comprehension measures included six factual comprehension questions and four inferential questions. For the factual comprehension questions, the student was asked to recall information explicitly stated in the text. For inferential comprehension questions, the student had to infer the answer based on textual information.

The funnel map and reading comprehension measures were scored by the interventionist RA and independently scored by another RA. All assessments in each study phase were double-scored to calculate inter-rater reliability. Disagreements were resolved by consensus. The percentage of agreement was calculated by dividing the number of agreements by the number of agreements plus the number of disagreements and multiplying by 100. One hundred percent of assessments in each phase of the study was double-scored by a RA to calculate inter-rater agreement. A score of 92% was attained for funnel map measures and 100% for reading comprehension measures.

Descriptive Measures

Students completed a post-intervention survey to assess their beliefs about the efficacy of the intervention. The four multiple-choice questions asked whether students felt the use of the graphic organizer funnel map helped them in their understanding of biographical texts and whether they would use the funnel map in the future. Students chose one of four responses, “Strongly Disagree; Disagree, Agree, or Strongly Agree” with strongly disagree being scored as 1 point and strongly agree being scored as 4 points. We chose to include multiple-choice items in the social validity measure because it is easier to elicit responses from participants. However, we did include two additional open response questions that asked for specific feedback on what they liked and disliked about the graphic organizer intervention.

Procedures

Research Assistants

The RAs were undergraduate students in the Speech and Hearing Science Program with no prior teaching experience. The first author trained 14 RAs in a group format prior to study initiation. The training consisted of how to administer measures and deliver the interventions from start to finish with fidelity through Zoom. Before the RAs could work with students, they were required to teach two intervention lessons to the first author. A fidelity checklist was used to determine whether each assistant delivered the lessons as planned with 100% fidelity. All RAs met the training criteria to deliver the intervention with 100% fidelity on two separate checks.

Baseline Phase

Seven students entered the baseline phase simultaneously. Baseline data were collected on multiple consecutive days to determine which students had a stable baseline. During the baseline phase, the RA read the randomly assigned descriptive text while the student followed along with a written copy and then instructed them to use a blank piece of paper to create a graphic organizer as a notetaking tool during a second reading of the text. The creation of the graphic organizer served as the funnel map measure, our criterion variable. At the end of the reading, the RA administered the reading comprehension measure (see description below).

After five baseline data points, three of the seven students scored 100% on at least one reading comprehension measure. Thus, they were not included in the study. Therefore, four students continued in the baseline phase. Of the four students left in baseline, one dropped out of the study because of scheduling conflicts. Of the three remaining students, one was male and two were female (see Table 1).

From all students with a stable baseline trend on the funnel map measure over five data points, one was randomly selected to enter the intervention phase first. What Works Clearninghouse requires at least five stable baseline data points prior to students moving into the intervention phase to meet standards without reservation. Baseline stability was determined by an outside person who was not informed of the study’s purpose and who could evaluate the data without bias. Baseline data were collected on the remaining students 3 days (three data points) just prior to the time the next randomly selected student was to enter intervention, at which time a series of three baseline measures over 3 days were administered to determine stability.

We measured students’ performance on the creation of the funnel map because this graphic organizer formed the basis of our treatment approach. We tracked how quickly students learned to create the map in response to reading a biographical text. When the first student in the intervention phase demonstrated a positive growth trend on at least three funnel map measures between baseline and intervention, an experimental effect was considered established (Cuillo et al., 2017) and the next randomly selected student entered intervention. We followed the same procedure for the entrance of all subsequent students.

Intervention Phase

During the intervention phase, each student worked with their assigned RA for two 1-hr sessions per week over 5 weeks. Each RA taught the same student throughout the intervention phase. The RA delivered scripted lessons using a direct instruction teaching method (Archer & Hughes, 2011). Instruction focused on the development of the funnel map, identifying the main idea, and supporting details of a text, and practice answering comprehension questions. The RA and student spent 5 min setting the stage for the lesson, 15 min each for I Do, We Do, You Do sections of the lesson (described below), and 5 min for closure.

During each lesson, the RAs followed a scripted regimen of activities that includes Setting the Stage, I do, We do, You do, and Closure. During Setting the Stage, the RAs reviewed the previous lesson, explained what the students would be doing during that session and briefly reviewed key vocabulary in the text. As the lesson transitioned to the I do stage, RAs modeled reading the text, creating a funnel map, added key details from the text to the map, synthesized across the key details to determine the main idea, and practiced answering comprehension questions using information from the funnel map. When students enter the We do (guided practice) phase, the RAs continued to lead the lesson, checked for understanding, prompted students if they missed a key detail, provided feedback, and helped students practice the new skills with support. During the You do (independent practice) stage, the students practiced creating a funnel map with the modeled passage by listing key details, synthesizing the main idea, and answering reading comprehension questions while the RA monitored their work. If the student missed a key detail, the RA prompted the student to verify that all key details were listed. If the student continued to leave out key details, the RA shared the missing detail. During Closure, the RAs or students synthesized what they learned that session.

To assess treatment fidelity, one of three trained RAs observed each intervention session in addition to the interventionist. The RAs used a rubric to determine whether each of the planned instructional steps were delivered. Treatment fidelity was calculated by adding the total number of earned points and then dividing it by the 20 possible points. A fidelity implementation score of 98.6% was attained (range = 96%–100%).

Maintenance Phase

Two assessment sessions were conducted during the maintenance phase; the first approximately 1 week after the intervention ended and the second about 4 weeks after the intervention had ended. During these sessions, the RA administered both a funnel map measure and a reading comprehension measure the same as the baseline and intervention measures.

Analytic Approach

Each student’s data were evaluated using a visual analysis to compare the effects of the independent treatment variable on the outcome variables. Both the Tau-U (Parker et al., 2011) and the Between Case-Standardized Mean Difference (BC-SMD; Valentine et al., 2016) were used to calculate an effect size for each dependent variable.

Visual Analysis

To determine whether students were able to correctly draw and label a funnel map within 10 sessions and whether the use of the funnel map had an effect on reading comprehension, we examined within-phase and between-phase data for each dependent variable. The visual analyses were based on the observed data within the baseline, intervention, and follow-up phases. The observed data within each phase was evaluated based on the features of (a) level (mean), (b) trend (best-fitting line slope), (c) variability (variation of data from the mean), (d) immediacy of effect (the change in the last three baseline data points and the first three intervention data points), (e) overlap (proportion of overlapping data points between baseline and intervention), and (f) consistency of data in similar phases. Data patterns across phases were investigated for (a) the visible distinction between the data features of the baseline data points and the intervention data points and (b) the percentage of data points overlapping between the baseline phase and the intervention phase with low overlapping suggesting larger treatment effect sizes (Horner et al., 2012; Lenz, 2013; WWC, 2020).

Tau-U

The Tau-U analysis, a nonoverlapping index of effect, was used to examine group treatment effects between the baseline phase and the intervention phase. Tau-U is well suited for the small data sets in single-case design and provides p values for statistical significance (Parker et al., 2011). An individual Tau contrast was calculated for the funnel map criterion variable and for the reading comprehension dependent variable, for each student. In addition, a weighted Tau-U contrast was calculated for an overall treatment effect. The weighted Tau-U is a calculation of each student’s phase contrasts between baseline and treatment for the dependent to give an overall intervention effect. Tau-U effect scores range from 0 to 1 with weak to small effect sizes specified by .65 or less, medium to high effect sizes specified by .66 to .92, and large or strong effect sizes specified by .93 or greater (Rakap, 2015).

Between Case-Standardized Mean Difference

The BC-SMD was used to calculate an across-student effect size that measured the effectiveness of the intervention. The BC-SMD estimates the same effect size as in between-case experimental designs, using data from a single-case design (Hedges et al., 2013; Pustejovsky et al., 2014; Shadish et al., 2014). The BC-SMD was chosen because it offers an effect size that is comparable with group design studies and can be interpreted like Cohen’s d for single-case design studies (Ruiz et al., 2018). We used a web-based calculator to generate the BC-SMD for single-case design research that includes a correction for small sample sizes, uses the restricted maximum likelihood estimator, and provides an effect size, standard error, confidence intervals, and auto-correlations (Pustejovsky et al., 2021). For the dependent variable (reading comprehension), we used a model that included a stable baseline trend and a change in level for the intervention phase.

Results

A summary of observed means, range, individual Tau-U, and BC-SMD is presented in Table 2. Individual baseline and intervention graphs are presented in Figure 1.

Table 2.

Funnel Map and Reading Comprehension Outcome Variables and Individual Effect Sizes.

	Funnel map				Reading comprehension
Participant	BLM (range)	INTM (range)	MAIN.M (range)	Tau	BLM (range)	INTM (range)	MAIN.M (range)	Tau
Student 1	0 (0)	85.5 (54–95)	91.75 (86–97.5)	094**	62 (40–80)	91 (70–100)	95 (90–100)	.92**
Student 2	0 (0)	94.3 (89–100)	92.5 (90.5–94.5)	096**	66.25 (40–90)	94 (70–100)	90 (90)	.81**
Student 3	0 (0)	59.8 (18–77.5)	62.5 (62–63)	.09**	54 (30–80)	86 (70–100)	75 (70–80)	.85**

Note. Table outcomes reflect measures specifically created for this study, Tau individual effect size. BL = baseline mean; INT = intervention mean; MAIN = maintenance mean.

p ≤ .01.

Funnel Map Results

Data points were collected on the funnel map during the intervention phase beginning in the first treatment session. All three students demonstrated an increase in level, trend, and immediacy of effect from baseline to intervention phase on funnel map assessments, thus demonstrating an understanding of the concept of the funnel map by listing key details for each paragraph and attempting to identify the main idea after one session. While Participant 2 demonstrated the ability to accurately create a funnel map with key details and the main idea with 90% accuracy after one session, Participant 1 showed steady growth over four data points in creating a funnel map to 90% accuracy and Participant 3 struggled with the mastery of the funnel map. While Participant 3 demonstrated the ability to identify most of the key details in each paragraph, the synthesizing of the key details to identify the main idea never fully materialized. However, when comparing the effects from baseline to intervention, the positive response of data patterns and replications across participants indicated a positive experimental effect, which is supported by Tau-U and BC-SMD (Tau-U = 1.0; p < .01; BC-SMD = 1.71).

Maintenance-phase data points were collected 2 and 4 weeks post intervention. Participant 1 scored 97.5% and 86% on the funnel map measure for first and second post-intervention data points, respectively, while Participant 2 scored above 90% on the funnel map during the 2- and 4-week maintenance check. Participant 3 scored 62% and 63% on the funnel map measure for first and second post-intervention data points.

Comprehension Results

During baseline, students demonstrated variability on the comprehension measures. Participants 1 and 3 showed the least variability and ranged from scoring 40% to 80%, whereas Participant 2 showed greatest variability and ranged from 40% to 90%. However, variability decreased after the introduction of the independent variable (funnel map).

All students showed a positive response to the intervention based on these measures. After two sessions, Participant 1 demonstrated an increase in level and trend with scores of 90% or 100% for Sessions 3 through 10 and an individual Tau effect size of .92 (p < .001). Participant 2 consistently scored between 90% and 100% on the comprehension measures until the last session with an individual Tau effect size of .81 (p < .001) and demonstrated an increase in level, but a slightly negative trend, due to one low score. Participant 3 was slower to respond to the intervention, but showed an increase in level and trend. After four intervention sessions, he showed a response to the independent variable with scores between 90% and 100% on the comprehension measures in Sessions 5 through 10 with a medium individual Tau effect size (Tau = .85; p < .001). However, when comparing the effects from baseline to intervention, the positive response of data patterns and replications across participants indicated a positive experimental effect, which is supported by Tau-U and BC-SMD (Tau-U = .86; p < .01; BC-SMD = 1.87). See Table 2 for baseline and intervention reading comprehension measures and individual effect sizes.

Maintenance-phase data points were collected 2 and 4 weeks post intervention. Participant 1 scored 90% and 100% on the comprehension measure for both post-intervention data points, respectively. Participant 2 scored 90%% on both comprehension measures for the 2-week maintenance check. Both students demonstrated consistency with their performance as compared with the intervention phase. Participant 3 scored 70% and 80% on the comprehension measure for first and second post-intervention data points, which is lower than the last six data points in the intervention phase.

Literal Comprehension Questions

Each comprehension measure contained six literal comprehension questions. We found that Participant 1 (Tau: .92, p < .001) and Participant 2 (Tau: .90, p < .001) had large individual Taus, whereas Participant 3 demonstrated a medium effect (Tau: .68, p < .01). Overall, between cases, there was a medium effect on literal comprehension (Tau-U: .83, p < .001; BC-SMD: 1.83).

Inferential Comprehension Questions

Each comprehension measure contained four inferential comprehension questions. We found that Participant 1 (Tau: .48, p = .14) and Participant 2 (Tau: .41, p = .14) had small, but nonsignificant individual Taus, whereas Participant 3 demonstrated a significant medium effect (Tau: .61, p < .01). Overall, between cases, there was a small effect on inferential comprehension (Tau-U: .50, p < .001; BC-SMD: 1.16).

Social Validity

At the conclusion of the intervention, each participant completed a post-intervention survey. All three students strongly agreed that the funnel map helped them understand and remember what they read. Participants 1 and 2 strongly agreed that they would use the funnel map in classes. Participants 1 and 3 stated that they liked using the graphic organizer because it made it easier to find information rather than reading back through the text. Participant 2 stated that she liked listing the key details of each paragraph and then referring back to the funnel map when answering questions because it made remembering what was read easier. Participant 1 stated that the amount of writing that went into building the funnel map was tiring. In a similar vein, Participant 3 felt that it took a long time to build the funnel map. Overall, the students found the intervention helpful and beneficial to the reading of descriptive texts.

Discussion

Results from this study show that Spanish–English bilingual students with LDs benefited from learning to use the funnel map to help comprehend descriptive expository texts. Moreover, in a relatively short period of time, students were able to use the funnel map to respond correctly to comprehension questions about the text. Two students quickly grasped the concept of the funnel map which had a direct impact on their comprehension scores. While the third student took longer, his comprehension scores began to improve by the fifth session. Furthermore, using the funnel map, two participants were able to accurately synthesize key details to correctly identify the main idea within two sessions. These improvements in identification of the main idea and reading comprehension scores likely occurred because the funnel map allowed students to see the key details from text all together in the graphic organizer. Results indicated that each of the students made modest increases in comprehension from the baseline phase through the intervention phase. Medium Tau-U effects sizes were observed for the three participants on the reading comprehension measures. Even though some students demonstrated high baseline scores, we saw positive changes in their comprehension scores after the intervention was implemented.

Several factors may have contributed to the variability in baseline scores. First, students’ background knowledge likely played a role given that background knowledge is a strong predictor of reading comprehension (Cromley & Azevedo, 2007; O’Reilly et al., 2019; Oakhill & Cain, 2012; Scarborough, 2001). We anticipated that background knowledge would vary by passage topic. To address this, we randomly assigned the passages to each baseline, treatment, and post-intervention session. Another factor is that comprehension questions vary in difficulty. For example, on two passages (Sojourner Truth and William Wilberforce) students scored higher on the inferential questions than the literal questions, which typically would be more difficult to answer.

Importantly, however, from the baseline phase through the intervention phase, the variability in comprehension scores decreased substantially. Students 1 and 2 had much more stable scores in the intervention phase, which may be a direct result of learning to use the funnel map while reading descriptive texts and using it to answer comprehension questions. This suggests that when students have a visual display of information read in a passage, they may not need to rely as heavily on their background knowledge or memory to answer comprehension questions. Student 3 showed variability in the initial sessions of intervention phase. However, at Session 5, he began to grasp the concept of the funnel map. After Session 4, he maintained stable scores on the comprehension measures.

Another interesting observation was the differential effects of the funnel map on literal and inferential questions. The intervention had a larger effect on literal than inferential questions, but we expected the opposite. Inferential comprehension requires the reader to draw upon prior knowledge and integrate that knowledge with relevant information presented in the text. We were encouraged to find a small, but significant effect from baseline to intervention for inferential comprehensions, leading us to believe that the funnel map supported both literal and inferential comprehension.

Implications for Practice

Interventionists and teachers of bilingual students with reading difficulties need strategies to increase students’ comprehension. This study contributes to the research literature by examining the use of the funnel map to enhance comprehension of descriptive text structures. The results of this study show that explicit instruction in the use of the funnel map when reading descriptive texts was beneficial for all students in the study and offered initial evidence that the funnel map may be effective at improving comprehension for Spanish–English bilingual students with LD. This study builds on the previous single-case design study by Calvin and Gray (2022) that demonstrated the efficacy of using of a double-bubble map graphic organizer to improve reading comprehension of compare/contrast expository texts in Spanish–English bilingual students with LD. Together, these two studies provide causal evidence that graphic organizers can improve students’ comprehension of expository texts.

An advantage of this intervention was that it was implemented with fidelity by undergraduate students with no teaching experience. The use of scripting for lessons makes it possible for trained tutors or teaching assistants to deliver the intervention to students. In addition, the treatment effect occurred quickly, showing the efficiency of the intervention.

A next step is to determine whether teachers and reading interventionists could incorporate graphic organizers into their classroom instruction with good effect and whether students who learn to use graphic organizers can continue to do so for expository texts in all of their classes.

Study Strengths and Limitations

One of the strengths of this study is that fidelity of implementation was high. This was achieved through a scripted lesson plan that RAs followed for all intervention sessions. A second strength was the use of an independent analyst, who was not aware of the study’s purpose, to determine a stable baseline and growth during the intervention phase. Third, this study met criteria established by the WWC (2020) for single-case designs. We demonstrated three replications of results across phases and five data points in each phase. Finally, the intervention proved to be economical in terms of how quickly participants learned to use the funnel map. One participant successfully created a funnel map after only one session and the other two participants achieved 80% accuracy or higher after four sessions. In addition, as the accuracy of the funnel map increased, scores on the comprehension measures increased, indicating that this intervention was effective for all participants.

One limitation of this study is that we used researcher-developed reading passages and measures. While the reading passages were leveled and the complexity was standardized, we did not test the relative equivalence of the measures. To help avoid a systematic effect of difficulty, we randomly assigned reading passage order across participants. Another limitation of the study was the online delivery due to COVID-19. While participants had experience with online learning for 18 months preceding the study, some students may have benefited more from face-to-face explicit instruction.

Conclusion

This study provided efficacy data for an instructional method to improve the comprehension of Spanish–English bilingual learners with LDs. Based on the Tau-U effect size, the effects of the funnel map on the overall comprehension benefited all students. The Tau-U effect size also showed a benefit to both literal and inferential comprehension. Thus, the general use of the funnel map when reading descriptive text structures may prove beneficial to many students, including bilingual students with LDs.

Supplemental Material

sj-docx-1-ldq-10.1177_07319487231176780 – Supplemental material for Improving Expository Text Comprehension in Adolescent Spanish–English Bilingual Learners With Learning Disabilities Using a Graphic Organizer

Supplemental material, sj-docx-1-ldq-10.1177_07319487231176780 for Improving Expository Text Comprehension in Adolescent Spanish–English Bilingual Learners With Learning Disabilities Using a Graphic Organizer by Kristie L. Calvin and Shelley Gray in Learning Disability Quarterly

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

This research was funded in part by a grant to the first author by Arizona State University’s Graduate Professional Student Association.

Supplemental Material

Supplemental material for this article is available at .

Notes

References

Archer

Hughes

(2011). Explicit instruction: Effective and efficient teaching. The Guilford Press.

Baddeley

(2010). Working memory. Current Biology, 20(4), R136–R140. https://doi.org/10.1016/j.cub.2009.12.014

Baker

Jones

S. P.

(1998). Encyclopedia of bilingualism and bilingual education. Multilingual Matters.

Boyle

J. R.

(1996). The effects of a cognitive mapping on the literal and inferential comprehension of students with mild disabilities. Learning Disability Quarterly, 19(2), 5–13. https://doi.org/10.2307/151125

Boyle

J. R.

(2000). The effects of a Venn diagram strategy on the literal, inferential, and relational comprehension of students with mild disabilities. Learning Disabilities, 10(1), 86–98. https://doi.org/10.1016/B978-0-12-388409-1.00007-2

Calvin & Gray. (2022). Double-bubble thinking maps and their effect on reading comprehension in Spanish-English bilingual middle school students with learning disabilities. Learning Disability Quarterly, 45(3), 212–224. https://doi.org/10.1177/0731948720958644

Ciullo

Falcomata

Vaughn

(2015). Teaching social studies to upper elementary students with learning disabilities: Graphic organizers and explicit instruction. Learning Disability Quarterly, 38(1), 15–26. https://doi.org/10.1177/0731948713516767

Coté

Goldman

Saul

(1998). Students making sense of informational text: Relations between processing and representation. Discourse Processes, 25(1), 1–53. https://doi.org/10.1080/01638539809545019

Cromley

Azevedo

(2007). Testing and refining the direct and inferential mediation model of reading comprehension. Journal of Educational Psychology, 99(2), 311–325. https://doi.org/10.1037/0022-0663.99.2.311

10.

Dexter

Park

Hughes

(2011). A meta-analytic review of graphic organizers and science instruction for adolescents with learning disabilities: Implications for the intermediate and secondary science classroom. Learning Disabilities Research & Practice, 26(4), 204–213. https://doi.org/10.1111/j.1540-5826.2011.00341.x

11.

Edmonds

M. S.

Vaughn

Wexler

Reutebuch

Cable

Tackett

K. K.

Schnakenberg

J. W.

(2009). A synthesis of reading interventions and effects on reading comprehension outcomes for older struggling readers. Review of Educational Research, 79(1), 262–300. https://doi.org/10.3102/0034654308325998

12.

Faggella-Luby

Deshler

D. D.

(2008). Reading comprehension in adolescents with LD: What we know; what we need to learn. Learning Disabilities Research & Practice, 23(2), 70–78. https://doi.org/10.1111/j.1540-5826.2008.00265.x

13.

Farnia

Geva

(2013). Growth and predictors of change in English language learners’ reading comprehension. Journal of Research in Reading, 36(4), 389–421. https://doi.org/10.1111/jrir.1200

14.

Gallagher

M. A.

Barber

A. T.

Beck

J. S.

Buehl

M. M.

(2019). Academic vocabulary: Explicit and incidental instruction for students of diverse language backgrounds. Reading & Writing Quarterly: Overcoming Learning Difficulties, 35(2), 84–102. https://doi.org/10.1080/10573569.2018.1510796

15.

Graesser

McNamara

Kulikowich

(2011). Coh-Metrix: Providing multilevel analyses of text characteristics. Educational Researcher, 40(5), 223–234. https://doi.org/10.3102/0013189X11413260

16.

Grimm

Solari

Gerber

(2018). A longitudinal investigation of reading development from kindergarten to grade eight in a Spanish-speaking bilingual population. Reading and Writing, 31(3), 559–581. https://doi.org/10.1007/s11145-017-9798-1

17.

Hedges

L. V.

Pustejovsky

J. E.

Shadish

W. R.

(2013). A standardized mean difference effect size for single case designs. Research Synthesis Methods, 3(3), 224–239. https://doi.org/10.1002/jrsm.1052

18.

Horner

Swaminathan

Sugai

Smolkowski

(2012). Considerations for the systematic analysis and use of single-case research. Education and Treatment of Children, 35(2), 269–290. https://doi.org/10.1353/etc.2012.0011

19.

Kaufman

A. S.

Kaufman

N. L.

(2004). Kaufman Brief Intelligence Test (2nd ed.). Pearson.

20.

Kieffer

(2012). Early oral language and later reading development in Spanish-speaking English language learners: Evidence from a nine-year longitudinal study. Journal of Applied Developmental Psychology, 33(3), 146–157. https://doi.org/10.1016/j.appdev.2012.02.003

21.

Kim

Vaughn

Wanzek

Shangjin

(2004). Graphic organizers and their effects on the reading comprehension of students with LD: A synthesis of research. Journal of Learning Disabilities, 37(2), 105–118. https://doi.org/10.1177/00222194040370020201

22.

Klingbeil

Renshaw

T. L.

Willenbrink

J. B.

Copek

R. A.

Chan

K. T.

Haddock

Yassine

Clifton

(2017). Mindfulness-based interventions with youth: A comprehensive meta-analysis of group-design studies. Journal of School Psychology, 63, 77–103. https://doi.org/10.1016/j.jsp.2017.03.006

23.

Kraal

Koornneef

Saab

van den Broek

(2018). Processing of expository and narrative texts by low- and high-comprehending children. Reading & Writing, 31(9), 2017–2040. https://doi.org/10.1007/s11145-017-9789-2

24.

Lenz

(2013). Calculating effect size in single-case research: A comparison of nonoverlap methods. Measurement and Evaluation in Counseling and Development, 46(1), 64–73. https://doi.org/10.1177/07481756124564

25.

Lesaux

Crosson

Kieffer

Pierce

(2010). Uneven profiles: Language minority learners’ word reading, vocabulary, and reading comprehension skills. Journal of Applied Developmental Psychology, 31(6), 475–483. https://doi.org/10.1016/j.appdev.2010.09.004

26.

Lesaux

Kieffer

(2010). Exploring sources of reading comprehension difficulties among language minority learners and their classmates in early adolescence. American Educational Research Journal, 47, 596–632. https://doi.org/10.3102/0002831209355469

27.

Tong

Irby

B. J.

Lara-Alecio

Rivera

(2021). The effects of four instructional strategies on English learners’ English reading comprehension: A meta-analysis. Language Teaching Research. Advance online publication. https://doi.org/10.1177/1362168821994133

28.

Koh

P. W.

Geva

Joshi

R. M.

Chen

(2021). The componential model of reading in bilingual learners. Journal of Educational Psychology, 112(8), 1532–1545. https://doi.org/10.1037/edu0000459

29.

Maki

K. E.

Adams

S. R.

(2019). Specific learning disabilities identification: Do the identification methods and data matter? Learning Disability Quarterly, 43, 63–74. https://doi.org/10.1177/0731948719826296

30.

Maki

K. E.

Burns

M. K.

Sullivan

A. L.

(2018). School psychologists’ confidence in learning disability identification decisions. Learning Disability Quarterly, 4, 243–256. https://doi.org/10.1177/0731948718769251

31.

Maki

K. E.

Floyd

R. G.

Roberson

(2015). State learning disability eligibility criteria: A comprehensive review. School Psychology Quarterly, 30, 457–469. https://doi.org/10.1037/spq0000109

32.

Mancilla-Martinez

Lesaux

(2011). The gap between Spanish speakers’ word reading and word knowledge: A longitudinal study. Child Development, 82(5), 1544–1560. https://doi.org/10.1111/j.1467-8624.2011.01633.x

33.

McCrudden

Rapp

(2017). How visual displays affect cognitive processing. Educational Psychology Review, 29(3), 623–639. https://doi.org/10.1007/s10648-015-9342-2

34.

Meyer

Ray

(2011). Structure strategy interventions: Increasing reading comprehension of expository text. International Electronic Journal of Elementary Education, 4(1), 127–152.

35.

National Assessment for Education Progress. (2019). Indicator 1: Population distribution. https://nces.ed.gov/programs/raceindicators/indicator_RAA.asp

36.

National Center for Education Statistics. (2019a). Indicator 1: Population distribution. https://nces.ed.gov/programs/raceindicators/indicator_RAA.asp

37.

National Center for Education Statistics. (2019b). Indicator 8: English language learners in public schools. https://nces.ed.gov/programs/raceindicators/indicator_RBC.asp

38.

National Center for Education Statistics. (2020a). Children 3 to 21 years old served under Individuals with Disabilities Education Act (IDEA), Part B, by age group and sex, race/ethnicity, and type of disability: 2018-19. https://nces.ed.gov/programs/digest/d19/tables/dt19_204.50.asp

39.

National Center for Education Statistics. (2020b). Students with disabilities. https://nces.ed.gov/programs/coe/indicator_cgg.asp

40.

National Governors Association Center for Best Practices, Council of Chief State School Officers. (2010). Common core state standards: Science and technical subjects grades 6-8.

41.

Nitido

Plante

(2020). Diagnosis of developmental language disorder in research studies. Journal of Speech, Language, and Hearing Research, 8, 2777–2788. https://doi.org/10.1044/2020_JSLHR-20-00091

42.

Oakhill

J. V.

Cain

(2012). The precursors of reading ability in young readers: Evidence from a four-year longitudinal study. Scientific Studies of Reading, 16(2), 91–121. https://doi.org/10.1080/10888438.2010.529219

43.

O’Reilly

Wang

Sabatini

(2019). How much knowledge is too little? When a lack of knowledge becomes a barrier to comprehension. Psychological Science, 30(9), 1344–1351. https://doi.org/10.1177/0956797619862276

44.

Parker

R. I.

Vannest

K. J.

Davis

J. L.

Sauber

S. B.

(2011). Combining non-overlap and trend for single case research: Tau-U. Behavior Therapy, 42, 284–299. https://doi.org/10.1016/j.beth.2010.08.006

45.

Pustejovsky

J. E.

Chen

Hamilton

(2021). scdhlm: A web-based calculator for between-case standardized mean differences (Version 0.5.2) [Web application]. https://jepusto.shinyapps.io/scdhlm

46.

Pustejovsky

J. E.

Hedges

Shadish

(2014). Design-comparable effect sizes in multiple baseline designs: A general modeling framework. Journal of Educational and Behavioral Statistics, 39(5), 368–393. https://doi.org/10.3102/1076998614547577

47.

Rakap

(2015). Effect sizes as result interpretation aids in single-subject experimental research: Description and application of four nonoverlap methods. British Journal of Special Education, 42(1), 11–33. https://doi.org/10.1111/1467-8578.12091

48.

Richman

J. M.

Rosenfeld

L. B.

Bowen

G. L.

(1998). Social support for adolescents at risk of school failure. Social Work, 43(4), 309–323. https://doi.org/10.1093/sw/43.4.309

49.

Ruiz

Flórez

García-Martín

Monroy-Cifuentes

Barreto-Montero

García-Beltrán

Riaño-Hernández

Sierra

Suárez-Falcón

Cardona-Betancourt

Gil-Luciano

(2018). A multiple-baseline evaluation of a brief acceptance and commitment therapy protocol focused on repetitive negative thinking for moderate emotional disorders. Journal of Contextual Behavioral Science, 9, 1–14. https://doi.org/10.1016/j.jcbs.2018.04.004

50.

Scarborough

H. S.

(2001). Connecting early language and literacy to later reading (dis)abilities: Evidence, theory, and practice. In Neuman

Dickinson

(Eds.), Handbook for research in early literacy (pp. 97–110). Guilford Press.

51.

Shadish

Hedges

Pustejovsky

(2014). Analysis and meta-analysis of single-case designs with a standardized mean difference statistic: A primer and applications. Journal of School Psychology, 52(2), 123–147. https://doi.org/10.1016/j.jsp.2013.11.005

52.

Strong

J. Z.

(2020). Investigating a text structure intervention for reading and writing in grades 4 and 5. Reading Research Quarterly, 55, 545–551. https://doi.org/10.1002/rrq.356

53.

Stull

A. T.

Mayer

R. E.

(2007). Learning by doing versus learning by viewing: Three experimental comparisons of learner-generated versus author-provided graphic organizers. Journal of Educational Psychology, 99(4), 808–820. https://doi.org/10.1037/0022-0663.99.4.808

54.

Swanson

Wanzek

Vaughn

Fall

Roberts

Hall

Miller

V. L.

(2017). Middle school reading comprehension and content learning intervention for below-average readers. Reading & Writing Quarterly: Overcoming Learning Difficulties, 33(1), 37–53. https://doi.org/10.1080/10573569.2015.1072068

55.

Torgesen

J. K.

Wagner

R. K.

Rashotte

C. A.

(2012). Test of Word Reading Efficiency (2nd ed.). Pro-Ed.

56.

Valentine

Tanner-Smith

E. E.

Pustejovsky

J. E.

Lau

T. S.

(2016). Between-case standardized mean difference effect sizes for single-case designs: A primer and tutorial using the scdhlm web application. Campbell Systematic Review, 12(1), 1–31. https://doi.org/10.4073/cmdp.2016.1

57.

Vaughn

Cirino

Wanzek

Wexler

Fletcher

Denton

Barth

Romain

Francis

(2010). Response to intervention for middle school students with reading difficulties: Effects of a primary and secondary intervention. School Psychology Review, 39(1), 3–21. https://doi.org/10.1080/02796015.2010.12087786

58.

Vaughn

Martinez

L. R.

Linan-Thompson

Reutebuch

C. K.

Carlson

C. D.

(2009). Enhancing social studies vocabulary and comprehension for seventh-grade English language learners: Findings from two experimental studies. Journal of Research on Educational Effectiveness, 2(4), 297–324. https://doi.org/10.1080/19345740903167018

59.

Vaughn

Roberts

Schnakenberg

Fall

Vaughn

Wexler

(2015). Improving reading comprehension for high school students with disabilities: Effects for comprehension and school retention. Exceptional Children, 82(1), 117–131. https://doi.org/10.1177/0014402915585478

60.

Vaughn

Wexler

Roberts

Barth

Cirino

Romain

Francis

Fletcher

Denton

(2011). Effects of individualized and standardized interventions on middle school students with reading disabilities. Exceptional Children, 77(4), 391–407. https://doi.org/10.1177/001440291107700401

61.

Wanzek

Vaughn

Roberts

Fletcher

J. M.

(2011). Efficacy of a reading intervention for middle school students with learning disabilities. Exceptional Children, 78(1), 73–87. https://doi.org/10.1177/001440291107800105

62.

What Works Clearinghouse. (2020). What works clearinghouse standards handbook (Version 4.1). U.S. Department of Education, Institute of Education Sciences, National Center for Education Evaluation and Regional Assistance. https://ies.ed.gov/ncee/wwc/handbooks

63.

Woodcock

R. W.

(2011). Woodcock Reading Mastery Tests (3rd ed., WRMT-III). Pearson.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.16 MB