The Importance of Reading Comprehension Intervention for Students with ASD

The Individuals with Disabilities Education Improvement Act (IDEA 2004) requires school personnel to provide students with disabilities access to the general education curriculum and interventions to address deficits in core academic areas such as reading. Consequently, an increasing number of students with disabilities, including those diagnosed with autism spectrum disorder (ASD) are partially or fully included in the general educational setting (O’Connor and Klein 2004). However, current research has indicated that general education teachers in inclusive classrooms are often uncertain how to effectively provide interventions for students with ASD to address difficulties with reading comprehension (Chiang and Lin 2007), a requisite skill that most teachers assume that their students possess. Learners with ASD have diverse needs and abilities, and many of these learners are included in academically focused curricula along with typically developing peers. For many students with ASD, expectations for academic progress, including reading comprehension, are similar to those set for their typically developing peers (El Zein et al. 2013).

Reading Comprehension Challenges in Students with ASD

Previous studies have repeatedly discussed a puzzling combination of average to above average word reading skills yet markedly poor reading comprehension among students with ASD (Chiang and Lin 2007; El Zein et al. 2013; Goldberg 1987; O’Connor and Hermelin 1994; O’Connor and Klein 2004, Patti and Lupinetti 1993). There is evidence that many students with ASD can read accurately, but even among these students, levels of reading comprehension are poor (Frith and Snowling 1983; Minshew et al. 1994; O’Connor and Klein 2004; Snowling and Frith 1986).

Explanations of the unique challenges faced by students with ASD in developing reading comprehension skills include difficulty in summarizing salient points (e.g., Happe 2005; Happe and Frith 2006; Williamson et al. 2009), and identifying different perspectives of characters represented in text (e.g., Baron-Cohen 1989; Frith 1989; Leslie 1987). The majority of the research efforts on reading comprehension in students with ASD have focused on describing the particular reading comprehension difficulties this population experiences and on explaining the cognitive profiles underlying those challenges. Additional research is needed to determine which aspects of reading interventions facilitate students with ASDs’ understanding of text.

The issue of providing effective reading comprehension instruction is further complicated by the unique and challenging behaviors often present for students with ASD during academic instruction (Goodman and Williams 2007; Marks et al. 2003). Students with ASD often typically display self-stimulatory behaviors, impaired communication and language skills, and resistance to participation in instructional activities. In addition, students with ASD often demonstrate difficulty with processing auditory information (Lincoln et al. 1995; Marco et al. 2011) with a tendency to focus only on selective parts of the message (Burke and Cerniglia 1990; Ploog 2010). Without the use of behavioral interventions and instructional modifications during academic instruction, these types of issues can often impede levels of on-task behavior and jeopardize student learning (Goodman and Williams 2007; Marks et al. 2003).

In a recent synthesis of research studies examining reading comprehension interventions with students with ASD, the authors found that many of the instructional interventions associated with improved comprehension for students with reading difficulties (e.g., identifying main idea, summarizing, questioning, self-monitoring, graphic organizers, and others) can be modified and implemented with students with ASD (El Zein et al. 2013). Additionally, results from a recent single-subject design demonstrated that implementation of modified strategy instruction (e.g., question development, anaphoric cuing) yielded positive reading comprehension outcomes in four elementary students with ASD (Solis et al. 2015)). Along the same line, researchers from the field of students’ with intellectual disabilities and low incidence populations have previously suggested that many of the effective intervention approaches used for other populations of students may also be effective for students with ASD (Browder et al. 2006; Mirenda 2003; Quill 1997).

The Use of Graphic Organizers

Studies conducted with students with learning disabilities (LD) have shown that the use of graphic organizers (e.g., semantic maps, cognitive maps, story maps, Venn diagrams) facilitate their learning and understanding of text through visual displays of content that assist readers as an organizational framework for relating prior knowledge to new information (e.g., Simmons et al. 1988). In a synthesis of research studies on reading comprehension interventions with students with LD, the authors found that visual displays of information such as those provided by graphic organizers (GOs) enhance the reading comprehension of students with LD (Kim et al. 2004). There is also evidence supporting the premise that students with ASD often demonstrate strengths in visual processing (Allen et al. 1991; Freeman et al. 1985; Rumsey 1992; Rumsey and Hamburger 1990; Yirmiya and Sigman 1991), which may lead to enhanced learning via GOs. Supporting this notion, a study by Van Riper (2010) suggested that the use of graphic organizers improved performance of students with ASD on reading comprehension measured through the qualitative reading inventory-4 (making predictions, literal and inferential questions). Based on existing evidence that the use of GOs was found to enhance reading comprehension in students with LD and on evidence that effective intervention approaches used for other populations of students may also be effective for students with ASD, we hypothesize that including graphic organizers within the present intervention may result in favorable reading comprehension outcomes for the participants.

Strategy Instruction- Identifying Main Idea

In a synthesis of 20 years of intervention studies with elementary students who were struggling in reading, Wanzek et al. (2010) found that comprehension practices that provided opportunities for students to preview text and connect with their knowledge, identify main ideas, and summarize what they are learning were associated with positive outcomes. In a separate synthesis, Solis et al. (2012) identified strategy instruction in general, and main idea/summarization in particular, as the reading comprehension intervention most supported by both experimental and single subject studies. Based on findings from the only text reading comprehension synthesis within the body of literature (El Zein et al. 2013) and a recent single-subject design study (Solis et al. 2015), strategy instruction was found to be a promising intervention approach for enhancing reading comprehension outcomes in students with ASD. From here, we hypothesize that including strategy instruction (i.e., identifying main idea) within the present multi-component intervention may improve reading comprehension performance in the participants of this study.

The Use of Token Economy Systems

Research with developmental disabilities (DD), particularly intellectual disabilities and ASD, has a history of broad applications of Applied Behavior Analysis (ABA) techniques (Chung et al. 2007; Lancioni et al. 2007; Matson 2007; Plant and Sanders 2007; Vedora and Stromer 2007). The application of specific principles of ABA, specifically stimulus control and reinforcement techniques, have been consistently and systematically implemented and documented as evidence-based instructional approaches in educating students with ASD (Heflin and Alberto 2001; Jacobsen et al. 2005). The use of token economy systems have been described as an effective behavioral intervention that is based on the principle of positive reinforcement and is commonly used with students with ASD (Charlop-Christy and Haymes 1998; Matson and Boisjoli 2009). In a review of the literature, Matson and Boisjoli (2009) reported that the use of token economy has been shown to be an effective intervention for children with DD, and has been documented as a treatment that is worthy of the current day practitioner and researcher attention for further investigation (Matson and Boisjoli 2009). Tokens are secondary reinforcers (e.g., stickers, chips, tickets) that acquire their reinforcing value through association with backup or primary reinforcers. Token systems are widely utilized in educational programs because they can be easily used and teachers do not need special training in ABA principles to successfully implement them (Charlop-Christy and Haymes 1998).

The Use of the iPad® Assisted Versus Teacher Directed Instruction

Recently, iPads® have been widely utilized in educational programs for individuals with ASD and other developmental disabilities (Kagohara et al. 2013; Neely et al. 2013). Researchers have documented that embedding the use of iPads® into educational programs have some advantages including the availability of various educational applications (Kagohara et al. 2012; Kagohara et al. 2013; Neely et al. 2013), the portable feature of the devices (Neely et al. 2013; van Laarhoven et al. 2009) and the possible positive impact this device has on the motivation and engagement of students with ASD (Neely et al. 2013). Most iPad research with individuals who have ASD and other developmental disabilities has targeted social, functional, and adaptive skills such as teaching communication (e.g., Flores et al. 2012; van der Meer et al. 2012), employment skills (e.g. van Laarhoven et al. 2009), or leisure activities (e.g., Hammond et al. 2010). However, knowing that this population has unique challenges related to academic engagement and performance, research on the use of iPads® to teach academic skills is limited, and hence highly warranted (Kagohara et al. 2013).

Within academic areas, recent studies have examined the effects of incorporating iPads® into spelling (Kagohara et al. 2012) mathematics (Burton et al. 2013; Jowett et al. 2012; Neely et al. 2013) and color matching (Neely et al. 2013) instructional programs for students with ASD. The effects of utilizing iPads® during reading comprehension instruction with this population has not been explored by researchers yet. Given the findings that describe reading comprehension as the most prevalent are of academic difficulty for students with ASD (Jones et al. 2009), examining the impact of incorporating iPads® within reading instruction is warranted. Findings from previous related studies suggest that although incorporating iPads® into academic instruction has the potential to increase engagement and motivation, without careful educational planning, it is possible that the use of such devices could hinder academic achievement (Northrop and Killeen 2013). Northrop and Killeen (2013) argue that children may be more proficient with the technology than with the targeted literacy concepts, and may not be effectively learning the literacy skills targeted to their individual instructional level. To further investigate such argument, research is needed to demonstrate whether iPad® assisted instruction (IAI) is, or is not, less effective than teacher directed instruction (TDI) as a primary method for instructional delivery. Because the use of iPads® is widely used among this population, it is particularly important to specifically examine how IAI and TDI methods compare in terms of their effects on performance in reading comprehension skills and academic engagement in students with ASD.

Purpose of This Study

The present study examined the effects of a multicomponent reading comprehension intervention on reading comprehension performance and task refusal behavior of three elementary students with ASD. This study also sought to compare the effects of delivering the multicomponent intervention through TDI versus using IAI as the primary mode of instructional delivery on the same outcomes. The multicomponent intervention during the TDI treatment consisted of teaching text previewing strategy (i.e., looking at text and picture, making predictions), identifying the main idea of each paragraph using a graphic organizer, and the use of a token economy system. The multicomponent intervention during the IAI treatment sessions consisted of the use of an iPad® application that focused on identifying main idea paired with implementing a token economy system for task completion. The present study sought to answer the following research questions:

  1. 1)

    Which treatment condition (TDI or IAI) is associated with higher reading comprehension outcomes?

  2. 2)

    Which treatment condition (TDI or IAI) is associated with lower levels of task refusal behavior?

Method

Participants

To be included in this study, potential participants had to meet the following criteria: (a) had a diagnosis of an ASD, (b) was between the ages of 9 and 12 years old, (c) could speak in full sentences and answer orally presented simple questions, (d) could decode reading passages on a 2nd grade level or greater, (e) could hand copy and write words, (f) had prerequisite attentive skills (e.g., sitting at a desk and attending to a conversation), and (g) did not exhibit challenging behaviors that are profound enough to impede learning of others in the same setting (e.g., aggressive and/or self-injurious behavior). A flyer describing the purpose of the study as well as eligibility criteria for participation was distributed to nearby schools and autism clinics. Six potential participants went through an interviewing process for the purpose of confirming eligibility. Two of the six potential participants were excluded because they exhibited severe challenging behavior which included noncompliance and physical aggression. One of the six who were interviewed did not demonstrate the ability to decode text on a second grade level or greater. Three elementary male students met the previously listed criteria (Alex, Arturo, Rafael) and participated in the study. Although DSM-V had just changed diagnostic criteria for ASD at the time of the study, one participant was diagnosed with Asperger Syndrome (Rafael) and the remaining two were diagnose with autism.

A week prior to the beginning of the study, screening from Read Naturally (Ihnot et al. 1992) was administered to the students to estimate reading levels. Informal observations of behavioral challenges related to academic task demands and vocal speech capabilities were also conducted during the assessment session. Parents were interviewed and provided information about their students regarding current educational setting, school reported grade level achievement in reading and writing, behavioral challenges, and the use of reinforcement systems or other behavioral intervention techniques.

Alex was a 9.5-year-old Caucasian male who was entering 4th grade and read on a 3rd grade instructional reading level. Alex had been homeschooled by his mother for the past 2 years, and had previously been in inclusive settings. His mother reported that he sometimes tried to avoid academic tasks (especially writing) by crying or throwing himself on the floor. She noted that he had experience with token systems, but because of his low muscle tone he often protested less when allowed to do academic work lying down on the floor.

Arturo was a Hispanic (9.11-year-old at the start of the study) student entering 5th grade. During the school year he was educated in a general education classroom with push-in special education supports. Arturo was reading on a 2nd grade instructional level. His mother noted that he sometimes tried to avoid work by protesting vocally, banging on his chest, or biting his shirt. She also reported he had experience using a token system.

Rafael was a Hispanic student, who was 10.11 years old at the start of the study. He was entering 6th grade, and read on a 4th grade instructional reading level. Rafael’s school setting was a general education classroom with push-in special education supports. His mother reported that he occasionally vocally protested or put his head down to avoid academic work. Similar to the other participants, Rafael was reported to have had prior success using token systems.

Setting

All sessions took place in an assistive technology (AT) lab during a 4-week academic summer camp held at a major university. The AT lab was set up like a classroom with desks, a carpet area, and various learning stations. The lab was divided into two different teaching areas during the camp. On one side of the room the participants in this study were instructed by two graduate students and one doctoral level researcher. On the other side of the room, three other students with learning disabilities who did not participate in this study, were instructed by three additional graduate students and observed by a professor/researcher. Two participants (Alex and Rafael) sat in desks next to each other and directly across from their instructor. Alex was also permitted to do some academic work using a clipboard while lying on a carpeted area behind the desks. Arturo sat at his own desk and instructors sat directly next to him. The instructor who carried out the sessions with the three participants was a graduate student with extensive background in techniques of ABA, a master’s degree in education, and 3 years of teaching experience focused on providing services to students with ASD.

Materials

iPads®

Three iPads® with the applications Space Voyage (Teacher Created Resources 2012) were used for this study. The selection of this application allowed for the closest approximation of tasks presented during TDI (i.e., practice identifying the correct main idea of a passage after reading it). Space Voyager provides a video game of a distant galaxy where the player has to read a paragraph and answer questions that require correct identification of the paragraph’s main idea. The application keeps track of the player’s responses and provides immediate feedback through moving the player’s spaceship in a fashion similar to a board game. Alex and Arturo used the Grades 2–3 levels, and Rafael used the Grades 4–5 levels.

Space Voyager game includes visual and audio effects related to the theme of the game (i.e., outer space). Players can pick to play against the computer or against other players; however, for the purpose of this study, the participants selected the option of playing against the computer. When it was the participant’s turn, he had to read a short paragraph that was followed by a multiple choice question about the main idea with three answer choices. The game provided the player with immediate feedback. If the player answered correctly, he rolled a dice on the screen and the spaceship would move spaces accordingly.

Several games such as Minecraft (Mojang 2013) and Angry Birds (Rovio 2013) were also downloaded and available on the iPads® for use during breaks. Each iPad® also had a set of headphones. These games were used as a reward option within the token economy system and were utilized during the TDI and the IAI conditions.

Passages

Grade-level text was selected from Read Naturally published reading passages that include grade-level, expository, high interest text consisting of several paragraphs. Topics of the passages were animals, historic figures, and mysterious events. The reading passages have previously been used in a pilot study conducted by Reutebuch and her colleagues that examined the effects of Collaborative Strategic Reading- High School (CSR-HS) on reading and behavioral outcomes of secondary students with ASD (Reutebuch et al. 2015).

Other Instructional and Behavior Management Materials

A graphic organizer was provided for each student during TDI instruction. This main idea graphic organizer (see Fig. 1) was adapted from a previous reading comprehension intervention study conducted with students with ASD (Solis et al. in review). The graphic organizer consists of boxes labeled as follows: a) who or what it’s about, b) what’s the most important thing about that who/what, and c) main idea statement. A visual support that consisted of a picture related to the topic of reading was provided and used during the previewing phase of each passage.

Fig. 1
figure 1

Main idea graphic organizer

Full size image

For the token economy system, each student had a board consisting of 12 laminated pictures of preferred characters (Angry Birds) that could be removed or attached to the board using Velcro. In addition to games on the iPad®, snacks, juice, small toys sent in by parents, and the AT devices in the lab were also available as materials to be used as reinforcers. The mentioned reinforcers were identified through an informal interview with each student prior to implementation phase.

Experimental Design

An alternating treatments design (Kennedy 2005) was implemented in an attempt to demonstrate experimental control within each participant’s data set. Each day the participants had one 35-min session that focused on identifying the main idea of a paragraph on their instructional reading level (included instructional routine and probe administration time). The alternating treatments design aimed to compare student performance on CBM probes between the two conditions (i.e., TDI and IAI). The TDI and IAI conditions were counterbalanced across 16 days, with one condition never occurring for more than three consecutive sessions.

Dependent Variables

Reading Comprehension

Proximal reading comprehension outcomes were measured through curriculum-based measure probe. Each probe consisted of four main idea questions that involved reading a paragraph and identifying the correct main idea from three response choices. The student’s independent answers (not corrected or prompted answers completed with instructor on TDI days) were scored. Probe items were multiple choice questions, and each item was worth one point. Probe scores were determined by dividing the number of correct responses by the maximum score (4) and multiplying by 100. Possible CBM probe scores were 0 %, 25 %, 50 %, 75 %, or 100 %.

Task Refusal Measure

Frequency counts of vocal protest (e.g., no, it’s too hard, I do not want to), physical task refusal (physical behaviors that competed with beginning the task, such as pushing paper away or putting head down), or task refusal without vocal or physical protesting (i.e., no response 10 s after one verbal redirection) were recorded. The total frequency of all task refusal behaviors was summed for each session (including both lesson and CBM administration).

Procedures

TDI Lessons

TDI lessons were designed to last about 20 min. Prior to reading, the students were provided with a picture that represented the topic of the passage. The instructor asked, “What do you know about ___?” The students then shared what they knew and made a prediction about what they thought the passage would be about. The students were provided with the main idea graphic organizer, and the instructor began the lesson by reviewing what the boxes within the graphic organizer represented. For example, the instructor would say, “When we read, we always think about the most important who or what in the passage. We also try to remember what the most important thing we learned about that who or what was. When we combine these two pieces of information together, we get a good main idea statement. This statement tells us what the passage is mostly about.” The instructor then asked the students to begin reading and prompted them to fill out the graphic organizer as they worked. Whenever the students provided the correct information, they were verbally praised by the instructor. Whenever they gave incorrect information, the instructor provided corrective feedback and utilized a least-to-most prompting technique, where the least prompt was reposing the question, and the most prompt was dictating the correct answer to the student.

IAI Lessons

During the 20-min lesson, the instructor provided the students with a picture that represented the topic of the passage. The instructor listed to the students the steps involved in Space Voyage game application. For example, the instructor would state, “first, you will read the text, then you will be given several answer choices”. The students are instructed to select the answer choice that represents the best “main idea” for the text they just read. The instructor explains what “main idea” is by mentioning, “A main idea is the statement that tells you the most important thing you learned about in the text”. As noted previously, Alex and Arturo used the Grades 2–3 application; Rafael used the Grades 4–5 application. The instructor gave brief directions and/or reminders on how to use the app and provided prompts to encourage student engagement as needed (e.g., “Look for an answer,” “It’s time to roll the dice,” “Press the back button”). No instruction or assistance in answering the questions was provided. When students asked for instructional assistance, they were reminded that this was an independent activity. When the student selects a correct response, the app provided the students with a praise statement and positive picture (e.g., “well done!”; “This is correct!” etc.) and an encouraging “try again” feedback upon selecting an incorrect response.

CBM Probe Administration Procedures

Main idea multiple choice questions were adapted from a question bank website, www.helpteaching.com, which categorized questions based on targeted skill and grade level. These questions were used to create probes that served as the study’s CBMs. Students received fiction and non-fiction passages, counterbalanced across sessions and conditions. Based upon the instructional reading level assessment, Arturo’s passages were written at a 2nd grade level, Alex’s passages were written at a 3rd grade reading level, and Rafael’s passages were written at a 4th grade level. On both IAI and TDI session days, students completed the researcher-developed probe that consisted of four main idea questions. Each question consisted of a paragraph with a multiple choice question: “What is the main idea of this paragraph?” The students were instructed to read the paragraphs within the assessment and circle the correct main idea for each paragraph from among three response choices. They were given up to 20 min to complete the assessment. If the students asked for assistance, they were told that this was a chance for them to show us what they could do on their own, and they should try their best; but they could write “I do not know” if they could not find an answer. Students were only given brief verbal prompts to remain on task. On TDI days, unlike IAI days, students were also given the main idea graphic organizer and reminded that they could use it to help them answer the questions.

Behavior Management and Reinforcement Procedures

All participants used a token board with 12 tokens. On IAI days, up to six tokens were given on a variable interval schedule for Alex and Rafael contingent upon active engagement (i.e., looking at iPad® and selecting answers) with the instructional iPad® games. Arturo received two tokens for every 3 min of active engagement with the instructional games (up to eight tokens total). For Alex and Rafael, the six remaining tokens were given upon answering each CBM question (not contingent upon correct responses). For Arturo, the four remaining tokens were given for circling an answer on his multiple choice questions or writing, “I do not know” (not contingent on correct responses).

On TDI days, for Alex and Rafael up to six tokens were given on a variable interval schedule contingent upon following directions during the lesson. Following session directions included finding the part of the story that answered the question and writing the answer (not contingent on correct responses). Up to six additional tokens were given for responding to each CBM question (not contingent upon correct responses). For Arturo, a total of eight tokens were available on a fixed ratio schedule during the TDI lesson (i.e., two tokens after listening to story section and answering each question). Arturo received up to four additional tokens during the CBM every time he demonstrated active engagement behavior. All participants were given the choice of a reinforcement activity after completion of the entire token board. After the first session, Arturo was also given the option to take a 1-min break (choice of item or activity) after every two tokens earned.

Procedural Integrity

Data on procedural integrity was taken by a trained observer during four IAI sessions (25 % of total number of IAI sessions across participants) and four TDI sessions (25 % of total number of TDI sessions across participants). The first author provided the observers with a three hour training session on the procedures involved in scoring reading comprehension probes and in task refusal data collection with detailed information regarding the operational definitions of “correct responding” and “task refusal”. The selection of sessions was not completely random as it was dependent on the availability of the observer. The trained observer utilized a researcher-devised procedural integrity (i.e., fidelity) form that provided a description of five main components of each session including lesson and CBM administration procedures (e.g., “Instructor reviews the different sections of the main idea graphic organizer,” “Instructor provides oral directions for completing the probe”). For each component, the observer used a rating scale (1 to 4) to indicate fidelity of implementation (e.g., 1 being poor fidelity, 4 being excellent fidelity). Observers received instructions on how to rate each component through a training conducted by the first author (i.e., developer of the scale) using case studies. For example, when the instructor provides no oral directions for completing a probe, he/she receives a score of 1 on this component. If the instructor provides parts of the directions, he/she receives a score of 2 or 3 (depending on how many directions are missing). A score of 4 s given when the instructor provides all oral directions prior to starting the probe. An overall rating (1 to 4) for procedural integrity across the session was also given and all scores were summed together. The procedural integrity score was determined by dividing the summed score by the maximum score (24) and multiplying by 100. The mean procedural integrity score was 96 %.

Inter-Observer Agreement

Inter-Observer Agreement (IOA) for CBM Scores

To assess the accuracy of CBM scoring, permanent products from two randomly-selected TDI CBMs and two randomly selected IAI CBMs (i.e., 25 % of total CBMs) for each participant were independently scored by two raters. For each product, IOA was calculated by using the formula agreements/agreements + disagreements × 100 %. Mean IOA scores were 100 % for the three participants.

Inter-Observer Agreement (IOA) for Task Refusal Measure

IOA for task refusal was taken by a trained observer during four IAI sessions (25 % of total number of IAI sessions across participants) and four TDI sessions (25 % of total number of TDI sessions across participants). The selection of sessions was not completely random as it was dependent on the availability of the observer. For each session IOA was calculated using the formula agreements/agreements + disagreements × 100 %. Mean IOA for protesting behavior across participants was 93.75 % (range 75 to 100 %).

Results

Performance on CBM Probes

Data for the three participants’ CBM scores are illustrated in Fig. 2 (Rafael), 4 (Alex), and 6 (Arturo). Visual analysis of the graphs reveals ascending trends in performance during both treatment conditions for the three participants. Mean CBM scores for the three participants are reported in Table 1. All three participants had higher mean scores on CBM probes that were completed after TDI as compared to IAI. Although clear differentiation was observed initially between the scores during the two treatments and the difference in overall means suggested that TDI was more effective for the three participants, it should be noted that their scores during the IAI treatment increased during the course of the evaluation with comparable performance observed during the final session of each treatment. Overall, Rafael’s scores on CBM probes were higher during the TDI treatment (M = 89.3 %) relative to his scores during the IAI treatment (M = 75 %). His scores during the TDI treatment ranged between 75 and 100 %; his scores during the IAI treatment varied from 50 to 100 %. Similarly, Alex’s mean CBM scores during the TDI treatment (M = 85.7 %) was higher than that during IAI sessions (M = 67.8 %). His scores during TDI ranged from 75 to 100 %; Alex’s scores during IAI sessions ranged from 25 to 100 %. Arturo’s CBM data demonstrate a pattern similar to those observed for Alex and Rafael. Arturo’s mean CBM scores during the TDI treatment (M = 89.3 %) was higher than that obtained during the IAI treatment (M = 42.6 %). His scores during the TDI treatment ranged from 25 to 100 %; his scores during the IAI treatment ranged from 0 to 75 %.

Fig. 2
figure 2

Rafael’s percentage correct on CBM reading probes

Full size image
Table 1 Results as mean CBM scores and mean task refusal results
Full size table

In both treatment conditions, Arturo started with low scores (i.e., 25 %) and showed consistent increase in scores to reach 100 % during the last TDI session and 50 % during the last IAI session. Similarly, Rafael’s scores demonstrated an ascending trend from 75 % to 100 % in the TDI treatment and 50 % to 75 % during the IAI treatment. Even though Alex’s graph illustrates an ascending trend in performance during the IAI treatment, his first and last IAI scores were 75 %. Alex’s score during the first TDI session was 75 % and his score during the last TDI session was 100 %.

Task Refusal

Data for the three participants’ task refusal behavior during TDI and IAI treatments are illustrated in Figs. 3, 4, 5, 6 and 7 (Rafael), 5 (Alex), and 7 (Arturo). Visual analysis of the graphs reveals descending trends in task refusal during both treatment conditions for the three participants. Mean frequency of task refusal for the three participants are reported in Table 1 below. All three participants had fewer occurrences of task refusal during IAI as compared to TDI treatment. Although clear differentiation was observed initially between occurrences of task refusal during the two treatments and the difference in overall means suggested that IAI was associated with fewer task refusal behavior for the three participants, it should be noted that task refusal incidences in the TDI treatment decreased during the course of the evaluation with zero to near zero incidences observed during the final sessions of each treatment.

Fig. 3
figure 3

Rafael’s task refusal occurrences

Full size image
Fig. 4
figure 4

Alex’s percentage correct on CBM reading probes

Full size image
Fig. 5
figure 5

Alex’s task refusal occurrences

Full size image
Fig. 6
figure 6

Arturo’s percentage correct on CBM reading probes

Full size image
Fig. 7
figure 7

Arturo’s task refusal occurrences

Full size image

Overall, Alex’s mean occurrences of task refusal was lower during the IAI treatment (M = 0.7) relative to that during TDI treatment (M = 3.7). Occurrences of Alex’s task refusal during the IAI sessions ranged from zero to two, while occurrences during the TDI treatment varied from zero to eight. Similarly, Rafael’s mean occurrences of task refusal behavior during the IAI treatment (M = 0.7) was lower than that during TDI sessions (M = 2). Rafael’s task refusal ranged from zero to two incidences during the IAI treatment, while similar occurrences during TDI sessions ranged from zero to nine. Arturo’s task refusal data demonstrate a pattern similar to that observed for Alex and Rafael. Arturo’s task refusal was lower during the IAI treatment (M = 2.9) relative to TDI treatment (M = 5.6). Occurrences of Arturo’s task refusal behavior during the IAI sessions ranged from zero to seven while occurrences during the TDI treatment varied from 0 to 13.

Discussion

In this study, we examined the effects of a multicomponent reading comprehension intervention (e.g., previewing text, identifying main idea, the use of graphic organizer, and the use of a token economy system) on reading comprehension performance on a researcher-developed measure and on task refusal behavior of three elementary students with ASD. Another purpose of this study was to compare the effects of delivering the multicomponent intervention through TDI versus using IAI as the primary mode of instructional delivery on the same outcomes.

As stated in the results section, the three participants had higher average scores on reading comprehension CBM probes during the TDI treatment condition in comparison to the IAI condition. Additionally, data for all three participants demonstrated ascending trends during both conditions with greater growth during the TDI treatment. These findings suggest that the multicomponent intervention implemented during both conditions was associated with improved performance on CBM probes during TDI and IAI treatments, with an indication that the TDI treatment was more effective in increasing accuracy of responding on CBM probes in comparison to the IAI condition. Knowing that the CBM probes were highly proximal to the skills taught through the lessons (i.e., all probe items targeted the skill of identifying main idea), evidence from this study is insufficient to draw a definitive conclusion regarding the effectiveness of the multicomponent intervention in improving reading comprehension overall. On the other hand, with ascending trends in scores across participants and treatment conditions, we can make the statement that one or both treatments were associated with improvement in the skill of identifying the main idea of a paragraph after reading it.

Task refusal data for the three participants demonstrated positive results during the TDI treatment (i.e., reduction in occurrences of task refusal behavior). During the IAI treatment condition, Arturo started with a high level of task refusal that dropped to zero at the end of the treatment sessions. Rafael and Alex did not exhibit any task refusal behavior throughout the IAI sessions (i.e., from the first session through the last one). Averages of task refusal occurrences were higher during the TDI treatment condition for the three participants.

Even though students with ASD may appear highly engaged and exhibit fewer challenging behaviors while using the iPads®, findings from this study support considering the use of TDI when teaching novel skills through multicomponent intervention that involves strategy instruction (e.g., previewing and main idea), the use of visual support (e.g., graphic organizer and picture), and a behavior management system such as a token economy.

Component Effects

The consistently higher average of CBM scores during the TDI condition across all three participants supports the conclusion that the mentioned treatment was more effective than the IAI treatment in increasing accuracy of responding to CBM probes. As a possible explanation for the growth in performance observed during both conditions, the skills taught during the TDI sessions may have been successfully generalized or carried over to show positive effects on the CBM probes administered during the IAI sessions. Even though a component analysis was not part of the present study, anecdotal data suggest that tailoring intervention components to specific needs of the students had the positive impact observed during the TDI condition. The three participants were observed using the main idea graphic organizer while completing CBM probes following TDI lessons. They were also observed looking back for information in the paragraph while answering the probe items following TDI lessons; not to mention the longer period of time it took the three participants to complete the probes during the TDI condition as opposed to the IAI condition. An assumption can be made here that the students were following the steps taught during the lesson (i.e., the use of reading comprehension strategies taught through modeling). Such evidence is consistent with previous research that supports the use of graphic organizers (Flores and Ganz 2007, 2009; Stringfield et al. 2011), and strategy instruction (Stringfield et al. 2011; Whalon and Hanline 2008) for teaching reading comprehension skills to students with ASD. Findings from the present study are also in-line with existing research that highlights the effectiveness of using token economy systems in educating students with ASD (Charlop-Christy and Haymes 1998; Matson and Boisjoli 2009).

Limitations, Implications, and Direction for Future Research

The present study was limited by the lack of component analysis, which may have assisted in identifying the components responsible for the positive effects observed. Without component analysis it is difficult to specify which component or combination of components was responsible for the increase in CBM scores during the TDI treatment (e.g. previewing strategy, main idea identification, the use of visual such as the graphic organizer, or the use of a token economy system. Additionally, as mentioned earlier, one possible explanation why the growth in performance were observed during both conditions is that the skills taught during the TDI sessions may have been successfully generalized or carried over to show positive effects on the CBM probes administered during the IAI sessions. Thus, it would have been ideal if a follow-up phase was implemented in which only the strongest treatment was used in isolation. Another limitation of the present study was the relative short period of time during which the course of evaluation occurred. While the overall results of this study may suggest that the TDI multi-component intervention may have positive effects on successful identification of main ideas from instructional level text, greater social validity would have been attained by implementing the intervention over a longer period of time. Another addition that would have been helpful in increasing social validity is conducting post-intervention interviews with parents to assess treatment acceptability. Furthermore the short time frame of the study resulted in limited descriptive information about the participants. For instance, we used parent and school reports to gather data that guided us in recruiting participants who met the previously described criteria. However, additional IQ and reading assessments may have been of value to the recruitment process and the participants’ demographic information. Similarly, even though overall behavioral characteristics observed during the course of the study were consistent with characteristics of individuals who are on the higher-functioning end of the autism spectrum, no formal assessment of autism severity was conducted. From here, replication of the present study in different educational setting, for a longer course of evaluation, and using standardized measures, is warranted for further investigation..

Despite these limitations, this study provides several important implications for practice, future research, and for developers of educational applications. Findings from the present study provide additional support for the value of strategic instruction delivered in one-on-one sessions tailored to meet the needs of students with ASD in order to fill gaps necessary to enhance their reading comprehension performance. Based on the findings of this study, educators are encouraged to consider using graphic organizers, token economy systems, and strategy instruction when teaching reading comprehension skills to students with ASD. A careful assessment of different applications should be conducted to determine what additional elements derived from more traditional TDI methods may need to be added where iPad® applications are lacking (e.g., additional visual supports, more specific strategy instruction, response contingent reinforcement and feedback). It could be that a third option, a combination of IAI and TDI, may provide even more positive results.

After comparing the effects of TDI and IAI, results demonstrated that TDI was associated with better scores on reading comprehension probes yet higher occurrences of task refusal behavior than IAI treatment. Hence, teachers should consider using iPads® to practice and maintain reading skills that were previously taught through TDI. Additionally, if the iPad® was identified as a potential reinforcer for a student, it may be beneficial to use it as part of an individualized behavior management plan. Educators should be cautious not to overly on utilizing the iPad® as a primary source for instructional delivery. This is consistent with findings from previous research which highlights that while incorporating iPads® into academic instruction has the potential to increase engagement and motivation, without careful educational planning, it is possible that the use of such devices could hinder academic achievement (Northrop and Killeen 2013).

Findings from this study have practical implications that may be helpful for developers of reading-related iPad® applications. It seems that all available applications focus on practicing reading comprehension skills (e.g., identifying main idea) rather than teaching the skill in an explicit fashion. From here, we suggest that there is a need for developing an iPad® application that focuses on teaching students skills that would aid in enhancing their reading comprehension (e.g., main idea, inference making, questioning etc.). Embedding teaching methods such as modeling, prompting, visual supports, and positive reinforcement within the reading applications is warranted and seem to be promising for enhancing reading comprehension in this population.

The present study provides preliminary evidence that despite the high levels of engagement and low levels of challenging behaviors students with ASD exhibited when participating in IAI, educators need to be aware that TDI may be more effective in teaching these students specific reading comprehension skills needed to improve their overall reading for meaning. Using the reading instruction iPad applications the way they presently exist (i.e., practice drills with motivating visual and audio effects) is insufficient for teaching students with ASD how to read for meaning. However, pairing their use with strategic reading instruction may maximize student engagement and thus produce more positive reading and behavioral outcomes.