Applying High Leverage Practices to Increase Active Engagement and On-task Behavior of Students with Intellectual Disabilities during Literacy Activities

Abstract

The high leverage practices of promoting active student engagement and using assistive and instructional technology can be implemented simultaneously in resource settings. The purpose of the study was to compare two commonly used methods of engagement, hand-raising and digital response cards, to determine their effect on students’ active engagement, on-task behavior, and reading comprehension. An ABAB design was used to evaluate the effects among high school students with intellectual disabilities during reading lessons. The results indicated there was a positive correlation associated with digital response cards on the level of active engagement, on-task behavior and skill acquisition as evidenced by whole group means.

Keywords

intellectual disability reading digital response cards active engagement high school

The Every Student Succeeds Act (2015) renewed the focus of academic achievement for students with intellectual disabilities and increased the expectations that all individuals, regardless of their abilities, will be educated using the most effective methods available. The renewed focus on academic achievement highlighted the need for intentional, instructional practices that facilitate student growth both academically and behaviorally. The call was met by the Council for Exceptional Children (CEC) with the identification of high leverage practices (McLeskey et al., 2017) that have a wide body of research to demonstrate their effectiveness in educating students with and without disabilities. These high leverage practices are integral to effective teaching and have a positive impact on student behavior and learning.

One such practice is the CEC High Leverage Practice 18, using strategies to promote active student engagement (McLeskey et al., 2017). Active student engagement is commonly associated with opportunities to respond. Traditionally, educators check for understanding by offering students an opportunity to respond to a teacher directed question throughout the delivery of instruction. These opportunities can be prompted by the teacher (e.g., choral responses, individual responses) or peers (e.g., peer-to-peer responses; McLeskey et al., 2017). The types of responses can vary from performing a skill or answering a question to responding to a task direction (Ault & Horn, 2018). Students can respond verbally, through a physical gesture (e.g., response cards), or through an electronic system (e.g., Plickers; Common et al., 2020).

Although checking for understanding is imperative to the overall effectiveness of any lesson, it is frequently implemented inconsistently in classrooms for students with intellectual disabilities (Pennington & Courtade, 2015) or in a manner that reduces students’ opportunities to participate by only allowing one individual to respond at a time (e.g., individual response through hand-raising). Identifying strategies that promote the active engagement of all learners simultaneously (i.e., choral responding) has been associated with greater frequencies of on-task behavior (Haydon et al., 2013) and academic success (Brophy & Good, 1986; McLeskey et al., 2019) and decreased behavioral concerns (Berrong et al., 2007). Allowing all individuals the opportunity to respond simultaneously may also reduce the anxiety associated with being the lone individual called upon to respond to the teacher posed question (Menzies et al., 2017). Whole class active engagement strategies may be a more efficient manner for educators to access formative assessment data that can be used to modify instruction and provide immediate feedback on behavioral and academic performance, two areas which are of particular importance when educating students with disabilities.

One method that used to increase opportunities to respond and engage multiple students during a lesson is the use of response cards. Response cards are signs or cards that are typically held up by all students participating in the lesson to show the teacher their response to a question or direction (Ault & Horn, 2018). Response cards come in a variety of formats and occur along the assistive technology continuum. Some low-tech examples of student response systems include printed pictures or words, whiteboards, yes/no paddles, and students holding thumbs up or down. These are easy to implement, inexpensive, and increase engagement. However, low tech response cards can be harder to differentiate due to the limited methods of responding they allow (Ault & Horn, 2018). Additionally, low-tech response cards require teachers to manually record student responses to the questions they pose which can negatively impact the pace of instruction. The implementation of traditional response cards provides the opportunity for all students to respond simultaneously during the instructional session providing the teacher with immediate feedback on all students’ performance (Schnorr et al., 2016; Sutherland et al., 2003). The use of response cards lends itself to the CEC High Leverage Practices 8 and 22 that encourage educators to provide timely, positive behavior specific feedback to acknowledge and guide students’ learning and behavior (McLeskey et al., 2017). The consistent use of response cards provides students with multiple opportunities to respond and teachers with many opportunities to provide high rates of feedback embedded in an efficient manner.

The research associated with response cards has consistently demonstrated that response cards result in higher rates of active engagement and on-task behavior for students in preschool through post-secondary educational environments and with students who are neurotypical, have mild to severe intellectual disabilities, as well as learners with emotional behavior disorders (Berrong et al., 2007; Bolt et al., 2019; Bondy & Tincani, 2018; Cakirglu, 2014; Didion et al., 2020; George, 2010; Godfrey et al., 2003). The effectiveness of response cards coupled with CEC High Leverage Practice 19, the use of assistive and instructional technologies, has created a unique opportunity to combine two highly effective strategies to promote positive academic and behavior outcomes for students with disabilities (McLeskey et al., 2017). Digital response cards (DRC) are tablet devices that all students utilize to formulate a response to a whole class question posed by the teacher. DRC offer students and teachers the same benefits associated with traditional response cards with one unique advantage, which is that a tablet device allows students to respond using accessibility features inherent to the device. Students can use the speech to text software, provide a visual representation of their response, or access word prediction software to aid in conveying their knowledge. DRC are an alternative for choral responding that capitalize on the benefits associated with traditional response cards (Ault & Horn, 2018). Although Haydon et al. (2013) concluded that choral responding is more effective than individual responding in engaging students with disabilities during whole group instruction, it was also noted that additional research was necessary.

The benefits associated with traditional response cards coupled with the advantages associated with choral responding which has been proven to be more effective than individual responding techniques during whole group instruction provides a unique opportunity to pair two effective strategies into one intervention package. Therefore, the present study aimed to determine the differential effects of individual responding through hand-raising and choral responding through DRC on active engagement and on-task behaviors of students with intellectual disabilities during whole group reading lessons in a resource classroom. In addition, the collateral effects of the DRC condition on reading comprehension were assessed. The following research questions guided the investigation:

What are the differential effects of hand-raising versus digital response cards on the level of active engagement for high school students with disabilities during literacy activities?

What are the differential effects of hand-raising versus digital response cards on the level of on-task behavior for high school students with disabilities during literacy activities?

What are the effects of digital response cards on the acquisition of lesson content?

Method

Participants

The investigation included students with identified intellectual disabilities enrolled in a rural public high school in a southeastern state in the United States. Nine students (five males and four females) ranging in age from 16 years 4 months to 20 years 1 month participated in the study. All students received services in the resource classroom for students with disabilities for at least 70% of the school day. Seven of the students were Caucasian, one was African-American, and one was Asian. The students had previously documented IQ scores from the Weschler Intelligence Scale for Children (2014) between the range of 48–60 and each had a current individualized education program (IEP). All students participated in their state’s alternate assessment. Each student is described using a pseudonym.

Salmon was a male student, aged 16 years 11 months, who was identified with a mild intellectual disability. He was below grade level across all academic areas and had vocational, reading, written expression, and math objectives on his IEP.

Skylar was a female student, aged 16 years 3 months, who was identified as having autism spectrum disorder and attention deficit disorder. She had functional reading, writing, math, and daily living goals on her IEP. Skylar also had a behavior intervention plan (BIP) for decreasing the occurrence of self-injurious behavior and received occupational therapy to increase her fine motor abilities.

Caleb was a male student, aged 16 years 6 months, who was identified with a mild mental intellectual disability and osteogenesis imperfecta. He was below grade level across all academic areas, and had reading, written expression, math, and vocational goals. Caleb received physical and occupational therapy for gross and fine motor abilities.

Maverick was a male student, aged 17 years 3 months, who was identified as having autism spectrum disorder and attention deficit disorder. Maverick had functional vocational, reading, written expression, and math objectives on his IEP. Additionally, he received speech therapy once a week for expressive language skills. Maverick also had a BIP to increase on-task behavior and task completion.

Jonah was a 16-year-old male student who was identified with other health impairment. He had a mild intellectual disability, a seizure disorder and attention deficit disorder. Jonah had reading, written expression, and functional math goals on his IEP. He also had a BIP to reduce the occurrence of talk outs during instructional activities.

Susan was a female student, aged 16 years 7 months, who was identified as having a mild intellectual disability. Her IEP contained goals for reading, math, and written expression skills. Susan received speech therapy for receptive language skills.

Body was a male student, aged 20 years 1 month, diagnosed with a moderate intellectual disability and Down syndrome. Body’s IEP contained functional academic skills in the area of reading and math. Body received physical therapy to increase gross motor capabilities.

Elenore was a female student, aged 19 years 2 months, with a mild intellectual disability who was also an English Language Learner. She had objectives related to reading, written expression, math, and vocational training skills.

Tatum was a female student, aged 18 years 4-month old, with a mild intellectual disability and a Down syndrome diagnosis. Tatum’s IEP contained functional academic goals associated with reading, math, and vocational training.

The participants’ special education teacher conducted all sessions. She had a Master’s degree in special education, a teaching license in moderate to severe disabilities (K–12), and 21 years teaching experience. Although two paraeducators were present during the study, they were assigned administrative tasks to complete during the study sessions and were not actively engaged with students.

The data collectors were the first and third author, the first of whom held a Ph.D. in special education and was the primary data collector. The third author, who was obtaining a Master’s degree in Applied Behavior Analysis was the reliability data collector.

Instructional Setting and Arrangement

The setting was a rural public high school in a resource classroom. Sessions occurred during a time that the teacher was typically teaching language arts. Along with the nine participants, the teacher, and the paraprofessionals, there were three peer tutors in the room during the language arts sessions. Participants were seated at two large group tables facing the teacher and a Smartboard.

Materials/Equipment

The teacher downloaded passages from Don Johnston’s Start to Finish Online Accessible Library (Don Johnston Human Learning Tools, 2020). The Don Johnston Start to Finish reading program is a commercially available product that adapts high school literature to an elementary reading level. The literature is professionally narrated, utilizing age appropriate language and offers word highlighting while the passage is visually displayed on the Smartboard. The teacher provided each student with a 21.59 × 27.94 cm black and white photocopy of the page being displayed on the Smartboard and allocated 2 min for each student to position the page in their spiral bound notebook. The photocopy aligned directly with the information being displayed on the Smartboard. The books (e.g., Journey to the Center of the Earth and Percy Jackson: Lightning Thief) used in the study were selected by the teacher. During all sessions, the participants had access to the page being read and materials to highlight or underline important information from the passage. During the DRC condition, the participants had access to an iPad. Students used the Doodle Buddy whiteboard application that had been downloaded on each device (Pinger, Inc., 2010). Doodle Buddy is a free drawing app that allows users to select tools and colors to write on the iPad screen during the intervention condition. The participants also were assigned a Plickers card (Kent, 2019). Plickers are individualized QR codes that allow educators to immediately collect multiple choice formative assessment data to teacher directed questions. The Plickers were copied on 21.59 × 27.94 cm pieces of cardstock and contained a black QR code. Plickers were used by all participants to respond during pre- and post-tests to measure academic achievement. The researcher collected academic responses from the QR codes by scanning the code displayed by each participant with the Plickers application downloaded on an iPhone. Data sheets were used by the observers for interobserver agreement of on-task and hand raising, and to measure procedural fidelity. MotivAiders® (https://www.habitchange.com) were used to signal observers as to the beginning and end of each scoring interval for on-task behavior.

Experimental Design

An ABAB withdrawal design (Gast et al., 2018) was used to analyze the effects of the HR and DRC conditions on the active engagement and on-task behaviors as well as the academic achievement of all students in the class. The design was conducted based on the structure of the classroom. The first condition was the HR condition, which was business as usual in the classroom. In this condition, the teacher presented literature to the whole class and then asked students to raise their hand to answer comprehension questions. In the DRC condition, each student had an iPad. The teacher asked comprehension questions and directed students to use their iPad to respond and then show their response by holding it up with the screen in her direction. The implementer was the classroom teacher and the sessions took place during the students’ regularly scheduled literacy block, promoting generalization and ecological validity. Experimental control is established when a change in behavior occurs only in the intervention conditions (i.e., DRC conditions) and not in the baseline conditions (i.e., HR conditions).

General Procedures

Sessions were conducted one time a day, Monday through Thursday, during the 40 min language arts class that occurred at 12:20 PM within a whole class instructional arrangement. The study was conducted within the context of the ongoing classroom structure that was in place prior to the start of the study. The teacher greeted students individually as they transitioned into the classroom from lunch and instructed them to gather their language arts materials and find their seat. Once all students had transitioned and were positioned in their assigned seat, the teacher provided an attentional cue similar to “Now let’s get to reading.” The teacher would then display the literature on the SmartBoard and each word was highlighted as the computer program read it to the group. The teacher paused the recording after every paragraph and asked comprehension questions to the whole class in which students would respond.

Data Collection

The two dependent variables throughout all experimental conditions were (a) active engagement and (b) on-task behavior. Data were collected daily. Academic achievement data were collected prior to and at the conclusion of instruction on each chapter across each condition. Each chapter assessment included a pre and post assessment and two separate chapters were assessed during each condition.

Active engagement

Active engagement in the HR condition was defined as students raising hands at or above shoulder level within 5 s of the teacher asking the question. Active engagement in the DRC condition was defined as a student writing on the iPad and holding the iPad at or above shoulder level within 5 s of the teacher asking the question. The percentage of active engagement for the entire group was calculated by totaling the number of students actively responding, dividing by the total number of students given an opportunity to respond, and multiplying by 100. To collect data on active engagement, for each question presented by the teacher, the observers scored the occurrence or nonoccurrence of responding (i.e., raising hand during the hand raising condition or responding using the iPad in the DRC condition).

On-task behavior

On-task behaviors were defined as looking at the teacher when she was speaking, looking at another student when they were speaking, looking at another student when they were responding, talking to another student or another teacher/peer tutor about the content of the class and completing any task specifically requested by the teacher or paraprofessional. To record on-task behavior, researchers used a 60 s momentary time sampling data recording system (Cooper et al., 2020). At the end of each 60 s interval, the researcher scored an occurrence or nonoccurrence of on-task behavior for all students by scanning from right to left beginning in the back of the classroom and moving forward. For each session, the number of occurrences of on-task intervals for the nine students was divided by the total number of intervals observed and multiplied by 100 to derive the percent of intervals of on-task behavior. To collect reliability for on-task behavior, the observers synchronized two MotivAider® devices (https://www.habitchange.com) so that each signaled the end of 60 s intervals. The on-task behavior for all students was scored at the end of each interval.

Academic achievement

Academic achievement data during all experimental conditions were collected using the Plickers application during pre and post-tests for each chapter. Pre-tests were administered immediately prior to starting each chapter and post-tests were administered immediately following the conclusion of the chapter. Five questions (who, what, when, where, and why) were created by the reliability observer and approved by the primary data collector and the classroom teacher as being of equal difficulty for each chapter. The questions were presented one at a time on the SmartBoard with four multiple choice options. Each participant had a Plicker containing a QR code assigned to them and had been previously taught to display their desired response by positioning the Plicker card so their response option was displayed at the top of the Plicker and faced away from the student’s body. The students would display their response at or above shoulder level facing the researcher. The researcher then used an iPhone with the Plickers application downloaded to scan the students’ Plickers, capturing their answers.

Experimental Conditions

Hand Raise Condition

Prior to the start of each session, the teacher reminded the students to answer questions by raising their hands, she did this through the use of a verbal prompt paired with a physical model. During the hand raise (HR) condition a portion of a chapter from the selected book was read by the computer program while being displayed on the SmartBoard. The teacher would pause the computer program after each paragraph and ask a minimum of two or a maximum of three questions pertaining to the material previously presented. Questions consisted of true/false, yes/no format, with one short answer question pertaining to the students’ thoughts or feelings on the information presented. After the entire chapter had been read, the teacher reviewed the chapter and embedded a minimum of four and a maximum of five questions into her review. True/false, yes/no, or multiple-choice questions with four possible response options were asked. The data collector recorded active engagement following each question by recording the occurrence or non-occurrence of each participant raising their hand within 5 s of the question being asked. Only one participant who raised a hand was called on by the teacher to answer the question. If the participant answered correctly, the teacher delivered descriptive verbal praise. If the participant answered incorrectly, the teacher called on another participant that also had a hand raised. Five sessions were conducted in each HR condition.

Digital Response Card Condition

Similar to HR conditions, after the chapter was read the teacher reviewed the chapter and embedded questions into her review. Prior to the first question being asked, the teacher told the students they were using iPads to answer her questions and to write T/F, Y/N, or A, B, C, or D as a response. The data collector recorded active engagement following each question by recording the occurrence or non-occurrence of each student using their iPad to respond to the question within 5 s of the question being asked. The teacher then provided descriptive verbal praise for correct responses and corrective feedback for incorrect response to the whole group. Five intervention sessions were conducted in each condition.

Reliability

Interobserver agreement data for student active engagement and on-task behaviors were collected for 25% of the sessions and at least once in each condition. Interobserver agreement was gathered by having a second observer independently score active engagement and on-task behaviors. Two individuals served as reliability observers. The first was the third author who collected reliability data when the primary data collector was present. The second was a peer tutor in the classroom who had been trained and collected reliability data when the first author was unavailable.

Active Engagement

For each question asked, researchers scored active responding for all students and point-by-point agreement was calculated using the same point-by-point formula described in the on-task section. The overall mean interobserver agreement was 100%.

On-task Behavior

A point-by-point formula was used to calculate interobserver agreement in which the number of agreements was divided by the number of agreements plus disagreements and multiplied by 100 (Ledford & Gast, 2018). The overall mean interobserver agreement was 92% (range, 88%–100%).

Procedural Reliability

Procedural reliability data were collected during 30% of all sessions. During the first HR condition, procedural reliability data were collected during 40% of sessions. During subsequent conditions data were collected 40% of the first DRC condition, 20% of the second HR condition, and 20% of the second DRC condition. For each condition, the researcher recorded the teacher’s correct implementation of six procedural steps in each condition. The researcher scored the occurrence of the following teacher behaviors: materials prepared, attentional response provided to entire group describing the condition in effect, question provided, 5 s wait response time provided, individual student called on (HR condition) or cue provided for all students to respond (DRC condition), correct consequences provided, and a minimum number of questions asked. The number of questions asked could range from a minimum of 6 to a maximum of 17 depending on the number of paragraphs read and if the chapter concluded during the session. The number of teacher behaviors observed was divided by the number of teacher behaviors that were planned and multiplied by 100 (Billingsley et al., 1980). All procedural reliability percentages were 100%.

Results

The following questions were addressed in this study: When used with high school aged students with intellectual disabilities in a whole group resource setting, what are the differential effects of hand raising and digital response cards on (a) active engagement, (b) on-task behavior, and (c) the acquisition of lesson content?

Active Engagement

The overall mean percentages of active engagement for the whole group are shown in Figure 1. The mean percentage of active engagement across all participants during the first HR condition was 19.2% (range, 15%–23%) with a stable trend. In the first DRC condition, the mean percentage of active engagement across all participants was 82% (range, 69%–100%) with an accelerating trend. The second HR condition had a mean percentage of 17.6% (range, 14%–22%) and stable trend for active engagement across all participants. In the second DRC condition, the mean percentage of active engagement across all participants was 99.4% (range, 98%–100%) with an accelerating trend. Active engagement means were significantly higher for the whole group during DRC conditions as opposed to HR conditions. Using visual analysis, an immediate change in level is indicated upon introduction of the two DRC conditions. There is 100% nonoverlapping data (PND) between conditions. Results for active engagement are provided as a group mean to combat absenteeism.

Figure 1.

Mean percentage of active engagement.

On-Task Behavior

The overall mean percentages of on-task behavior for the whole group are shown in Figure 2. The mean percentage of on-task behavior across all participants for the first HR condition was 49.4% (range, 49%–58%) and presented with a decelerating trend. In the first DRC condition, the mean percentage of on-task behavior across all participants was 62.6% (range, 31%–86%) and a clear accelerating trend. In the second HR condition, the mean percentage of on-task behavior across all participants was 47% (range, 21%–70%) and again presented a decelerating trend. The final DRC condition had a mean percentage of 84.2% (range, 80%–88%) with a stable trend for on-task behavior across all participants. Overall, students demonstrated greater frequency of on-task behavior during the DRC condition as opposed to the HR condition. Using visual analysis, an immediate change in level is indicated upon introduction of the two DRC conditions. There is 60% PND between conditions. Results for on task behavior are presented as a group mean due to absenteesism.

Figure 2.

Mean percentage of on-task behavior.

Pre- and Post-Tests of Reading Comprehension

Individual means for all participants were calculated for both pre- and post-tests, and these data are reported in Tables 1 and 2. Pre- and post-tests were conducted for each of eight book chapters presented during the literacy activities (i.e., two chapters per condition). The mean percentage of pretest scores across all participants was 30.9% (range, 16%–39%). The mean percentage or post-test scores across all participants was 54.8% (range, 47%–69%). Pre- and post-tests for Chapters 4, 5, 8, and 9 were done in the HR condition. The pre- and post-tests for Chapters 6, 7, 10 and 11, were done in the DRC condition. The average pretest score for HR conditions across all students was 35.3% (range, 30%–39%). The average post-test score for HR conditions across all students was 50.3% (range, 47%–56%). For DRC conditions, the average pretest score across all participants was 26.5% (range, 16%–35%) and the average post-test score across all participants was 59.3% (range, 56%–69%).

Table 1.

Mean Percentage of Academic Achievement in HR Condition.

HR 1				HR 2
	Pre	Post	Mean difference		Pre	Post	Mean Difference
Chap 4	36	47	+11%	Chap 8	39	58	+19%
Chap 5	36	47	+11%	Chap 9	30	49	+19%

Table 2.

Mean Percentage of Academic Achievement in DRC Condition.

DRC 1				DRC 2
	Pre	Post	Mean Difference		Pre	Post	Mean Difference
Chap6	35	56	+21%	Chap 10	27	69	+42%
Chap7	28	56	+28%	Chap 11	16	56	+40%

Discussion

The study assessed effects of DRC on active student engagement, on-task behavior, and academic achievement for high school students with intellectual disabilities during literacy activities. Based on the data that were collected, several statements can be made. First, there was a substantial change in regard to active engagement between conditions with a clear increase in the frequency of active engagement during the DRC conditions. During the first HR condition, the group responding rate ranged from 15% to 23%. The second HR condition rate ranged from 14% to 22% for the group as compared to the DRC conditions which initially ranged from 69% to 100% during the first condition and increased to 98% to 100% during the final condition. Overall, the use of DRC increased the frequency of active responding for the whole group.

Second, there was a noticeable increase in the students’ on-task behavior during the DRC conditions as opposed to the HR conditions. During the first HR condition, the group mean of on-task behavior ranged from 49% to 58%. The second HR condition ranged from 21% to 70% for the group. As compared to the mean on-task behavior for the group during the DRC conditions which initially ranged from 31% to 86% and increased to 80% to 88% during the final condition. Overall, the use of DRC increased the frequency of on-task behavior for the whole group.

Third, when comparing the differences in means associated with pre and post assessment measures of comprehension completed during each condition of the study, a positive correlation between a higher mean score and DRC condition was noted. During the first HR condition the difference in mean scores from pre to post measures for Chapters 4 and 5 were 11%. The second HR condition evidenced a difference in means scores from pre to post assessment measures for Chapters 8 and 9 to be 19% for both chapters, compared to the difference in means scores for the first DRC condition which ranged from 21% for Chapter 6 to 28% for Chapter 7. Additionally, Chapters 10 and 11 had a mean difference between pre and post assessment measures that ranged between 42% to 40% respectively. Overall, the use of DRC had a positive impact on group means associated with academic achievement data.

Interestingly, the data for both active engagement and on-task behavior reflect even greater frequency during the second DRC condition. This finding may indicate that as the novelty of using technology (i.e., iPad) wears off and the students become more accustomed to using technology for learning, their engagement and on-task behavior will increase. The students often commented during the study that they enjoyed using the iPads with one participant commenting “It is so much more fun when we have iPads.”

Embedding technology into instruction is a high leverage practice that can be used to support students’ needs and enable them to participate more fully in learning activities. In regard to the collateral effects of the HR and DRC conditions on the acquisition of lesson content, the results indicate that higher percentage increases from pre- to post-tests when students were asked to chorally respond during the DRC condition. The greatest percentage change 42% occurred during the second DRC condition. This is a significant finding in that once the students had mastered the use of the technology and the novelty of using the technology during a learning trial had worn off, the students were able to successfully retain the information to a marked degree increase over business as usual instruction (i.e., HR) in the classroom.

Limitations and Directions for Future Research

Several limitations of this study must be discussed. First, this study did not include counterbalancing of the conditions across participants. Counterbalancing conditions across participants would have minimized the threat to internal validity and would have minimized sequencing effects. Future research should utilize counterbalancing of the conditions. Second, active engagement in the HR condition and the DRC condition varied slightly in that during the DRC condition, the participant needed to raise the iPad to shoulder height. This variance could introduce a threat to internal validity. Third, social validity data was not gathered. Social validity data would have provided additional information regarding the acceptability of the goals, procedures, and outcomes. The students indicated their enjoyment of the DRC condition through comments during the study, but no formal data were gathered. However, future research should include a social validity measure that assesses the teachers’ and students’ perceptions of the intervention.

While increases in frequency of active engagement and on-task behavior were indicated in both DRC conditions, the level was greatly increased in the second DRC condition. Future research could continue a “best alone” condition to further strengthen the results. Additionally, assessing the generalization of digital response cards across settings could provide information on strategies to support students with intellectual disabilities in collaborative settings.

Implications for Practice

The results of this study provide direction for practice in the field. Through applying two high leverage practices, engagement strategies and technology, students with intellectual disabilities increased their active engagement, displayed higher levels of on-task behavior, and acquired more content knowledge. Teachers should be aware of and implement these high leverage practices in their classrooms. By utilizing choral responding through DRC, the teacher in this study was able to increase her students’ active engagement, on-task behavior, and acquisition of content. This condition required each student to have access to technology (e.g., iPad), which could be a barrier for districts that do not have one-one technology. Additionally, teachers must also be prepared to troubleshoot the technology, keep the devices in working order, and provide for an alternative response format if the technology fails. However, the impact on student engagement and learning are worth the increased effort.

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

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Channon K. Horn

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