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Assistive Technology: The Official Journal of RESNA Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/uaty20

Comparative Observations of Learning Engagement by Students With Developmental Disabilities Using an iPad and Computer: A Pilot Study a

a

Sajay Arthanat PhD OTR/L ATP , Christine Curtin MS OT & David Knotak MA MS OTR/L

b

a

College of Health and Human Services, University of New Hampshire, Occupational Therapy , Durham , New Hampshire b

Crotched Mountain Rehabilitation Center , Greenfield , New Hampshire Accepted author version posted online: 04 Jan 2013.Published online: 14 Oct 2013.

To cite this article: Sajay Arthanat PhD OTR/L ATP , Christine Curtin MS OT & David Knotak MA MS OTR/L (2013) Comparative Observations of Learning Engagement by Students With Developmental Disabilities Using an iPad and Computer: A Pilot Study, Assistive Technology: The Official Journal of RESNA, 25:4, 204-213, DOI: 10.1080/10400435.2012.761293 To link to this article: http://dx.doi.org/10.1080/10400435.2012.761293

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Assistive Technology® (2013) 25, 204–213 Copyright © 2013 RESNA ISSN: 1040-0435 print / 1949-3614 online DOI: 10.1080/10400435.2012.761293

Comparative Observations of Learning Engagement by Students With Developmental Disabilities Using an iPad and Computer: A Pilot Study SAJAY ARTHANAT, PhD, OTR/L, ATP1∗ , CHRISTINE CURTIN, MS OT1, and DAVID KNOTAK, MA, MS, OTR/L2

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1 2

College of Health and Human Services, University of New Hampshire, Occupational Therapy, Durham, New Hampshire Crotched Mountain Rehabilitation Center, Greenfield, New Hampshire

This study examined the use of the Apple iPad for learning by children with developmental disabilities (DD), including those on the autism spectrum. A single case design was used to record the participation of four students with DD when taught with their standard computer at baseline, followed by the introduction of the iPad. A six-component participation scale was developed to quantify observations of these students during the learning sessions. Visual analysis of data indicated no differences in participation with the iPad as compared to the computer for three of the four subjects. One subject appeared to have notably higher participation with the iPad. Individual variations were identified in each student along with some common concerns with attention, task persistence, and goal directed behavior with use of the iPad. Student academic scores improved during the course of iPad use. Nevertheless, the findings drawn from this pilot study do not justify the use of the iPad over the computer (and vice versa) for achieving academic goals in students with DD. The need to document best practices and barriers in use of emerging touch-tablet devices to support individualized education was clearly evident. Keywords: assistive technology, developmental disability, education, iPad, single subject design

Introduction There are approximately 6.5 million children (5 to 21 years of age) with a developmental disability (DD) in the United States (U.S. Census of Bureau, 2006), with an evergrowing incidence (1 in 110) of children with autism spectrum disorders (US Department of Health and Human Services, Center for Disease Control and Prevention, 2011). The Individuals with Disabilities Education Act of 1997 (U.S. Department of Education, 2004) mandates that these children be provided inclusive public education in a least restrictive environment through provision of needed technologies. Every child must have an individualized education program (IEP) with measurable goals outlined by an IEP team comprising teachers, therapists, and the child’s parents. In schools across the United States, computerized educational applications are being used in the IEP as an explorative and interactive means to facilitate learning. The iPad is a touch tablet computer recently developed by Apple, Inc. ( Cupertino, CA) with multiple audio-visual applications (apps). It is considered a ground-breaking educational tool and is anticipated to have wide-ranging academic implications for all children. The news media, including anecdotal reports, continue to highlight the potential of the iPad for children with ∗

Address correspondence to: Sajay Arthanat, College of Health and Human Services, University of New Hampshire, Occupational Therapy, 4 Library Way, Hewitt Hall, Durham, NH 03824, USA. Email: [email protected]

disabilities (Hu, 2011; Learmonth, 2010; Sughrue, 2011). Some recent studies have highlighted the scope of iPad for children with autism spectrum disorders in promoting social communication (Jowett, Moore & Anderson, 2012) and its use as a form of augmentative alternative communication (Flores et al., 2012). However, empirical evidence supporting the use of this novel touch screen tablet technology for education of children with DD is yet to emerge. The focus of this study is to investigate and compare the interaction of students with DD with the iPad and a traditional mouse-driven computer in selected academic areas.

Background The benefits of incorporating computerized learning for students with disabilities are widely documented. These benefits include, but are not limited to, facilitation of visual-spatial skills (Akhutina et al., 2003), reading (Mott, 2010), writing (Handley-More, Deitz, Billingsley, & Coggins, 2003), and social interaction (Jacklin & Farr, 2005). However, students with DD have been observed to have challenges in using a mouse-driven computer, including lack of adequate motor control to move the mouse, the coordination to perform clicks with precision, the necessary visual-spatial skills and sustained attention to track the cursor, and, above all, the cause-effect understanding to relate the movement of the mouse to the cursor (Hirofumi & McDonough, 2006). Shimizu, Yoon, and McDonough (2010) demonstrated that a structured training program involving facilitation of mouse movement, eye-hand coordination, and precision and timing of

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iPad Use by Students With Developmental Disabilities click-and-release was needed to increase efficiency (as measured by clicks, time taken, cursor movement, and prompting) in use of mouse-driven computer by children with DD. At the same time, the potential of touch screen interface for children with DD as a way to eliminate the complexities of traditional mouse interface has not been conclusively explored. In earlier research, Durfee and Billingsley (1999) employed a single case study approach and found that selections were faster on a touch screen monitor for matching five consecutive letters, while the accuracy was better (with 14% less error rate) when the mouse was used with an enlarged cursor. With no substantiated evidence thus far, the question arises whether more novel and popular touch tablet devices such as the iPad can replace or complement the use of mouse-driven computers by children with DD in classrooms across the United States. Technology analysts describe the iPad as an ideal tool for all levels of learning. Several schools across the nation have already introduced it in classrooms and students report wanting to participate in learning activities because of its novelty, audio-visual characteristics and ease of use (Learmonth, 2010). There are about 5,400 educational applications available for download into the iPad (Hu, 2011). The iPad can be used to create text, audio, or visual notes based on different learning styles. Students can store all of their educational materials in a digital portfolio. With the iPad, education can be taught through engaging and interactive games or animations. Disability advocates believe that the iPad’s light weight, portability, touch screen, large screen icons, speakers, voice over, zoom in, available closed captions, and cognitive simplicity are some of the characteristics that make it an accessible tool (Buchanan, 2010). The iPad’s touch screen eliminates the demands of using a mouse. Some recent articles have highlighted the iPad’s visual appeal and the intuitive touch interface as the key facilitators of learning for children with disabilities including those with autism (Gordon, 2011; Hager, 2010). Despite such assertions, there is no empirical evidence thus far to substantiate the interaction of children with DD with touch tablet devices and how that interaction may translate into academic performance. The broad objective of this study is to examine how students with DD in a classroom participate in learning using the iPad in comparison to a traditional mouse-interface computer. To this end, specific research questions are: (a) do students with DD interact more effectively with the iPad than a traditional computer; (b) what are specific strengths and concerns in their interaction with the iPad; and (c) does the interaction improve their academic performance (based on their established IEP criteria).

Methods This pilot study was conducted using a single subject design. Single case design allows researchers to make in-depth observations of each subject by examining the impact of the independent variable on one or more dependent variable/s (Betz Gooze, 1998; Kratochwill et al., 2010). The design involves consideration of each subject as his or her own control by tracking individual responses to an intervention across time. This design was deemed most appropriate for this study because of: (a) the vast variations observed in children with DD in terms of their physical, intellectual and behavior characteristics, and academic goals; and

205 (b) the available resources including equipment (iPads), funding, and time on the part of students and teachers. Specifically, a multiple baseline design was adopted to verify the comparative interaction of the students with the iPad and the computer in two academic areas (conditions). Promoting the intervention in two or more conditions within a specified number of sessions or trials allows for the verification of the effects of the interventions (Kratochwill et al., 2010). This design is a close approximation of an alternating baseline design (AB1 AB2 ), but was unique in that the conditions were introduced concurrently as opposed to being sequenced across time (i.e., the second A condition followed by the B1 condition). The participating students engaged in multiple academic areas each week, and such a design was adopted to fit with the school’s summer academic schedule. A pre/post-test design was also included to verify academic gains. Setting The study was conducted in a classroom setting at a special needs school located in southern New Hampshire. The school provides comprehensive individualized education for students with wide-ranging DD from elementary–12th grade level. The iPad was recently introduced at the school as an innovative learning modality. Participants The participants in this study were 4 students (boys, 11–13 years of age) diagnosed with a form of autism or intellectual disability. They were recruited by purposive sampling, wherein each participant is selected based on how he or she fulfills a specific eligibility criterion. In consideration of a broad educational criteria, each student in this study was chosen based on their unique individualized academic goals (shape and color recognition, math, reading, spelling, vocabulary, and money and coin recognition). The inclusion criteria for the students were that they: (a) have an IEP in at least two academic areas, (b) are already engaged in some form of learning using a computer, (c) have the basic skills to use the iPad (as determined by the teacher), (d) do not have any underlying visual perceptual deficits as reported by the IEP team, and (e) have an educational content that can be delivered using iPad’s apps. The case descriptions of each student are given below. To maintain participant anonymity, pseudonyms have been used and specific diagnostic details have not been disclosed. Participant 1 Brycen is a 12-year-old boy who enjoys puzzles and playing games on the computer. He has an autism spectrum disorder combined with a form of mental illness. He has decreased intellectual functioning, difficulty with communication, and a decreased attention span with high distractibility. Brycen is currently working on differentiating between colors and shapes and letter identification. He mostly uses flash cards and paper-pen worksheets for learning. He has often used the computer prior to this study for some academics including one with a touch screen monitor. He uses the iPad to play games during choice time.

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Participant 2 Jake is a 12-year-old boy who enjoys music, animals, and doing puzzles. He is diagnosed with a form of autism. Jake is non-verbal; however, he can communicate through an augmentative alternative communication device in which he spells his responses. His academic goal is to expand his vocabulary and spelling to apply to his use of the communication device. He is also working on math consisting of adding single and two digit numbers. He uses paper-pen worksheets and cut out alphabet pieces for learning. He uses the computer to listen to music and the iPad only to play games. Participant 3 Neil is a 13-year-old boy who is fascinated by images and books. He is diagnosed with autism and observed to be a “tactile learner” who prefers to explore and learn by touching and feeling objects. He is working on coin and object recognition. His goal is to identify all of the coins, and to recognize what an object is based on a picture. He learns using real coins and paper-pen worksheets, as well as matching with flash cards. Participant 4 Evan is an 11-year-old boy who is interested in watching children’s programs on television. He also enjoys coloring. He is diagnosed with a rare genetic disorder that causes physical and intellectual delays in development. His academic goals relate to word recognition, counting, and telling time, specifically to identify words that match pictures, and to count by 2s, 5s and 10s. Human Subject Protection The study protocol was reviewed and approved by the Institutional Review Boards of the University of New Hampshire and the participants’ school. The parents/guardians of the selected students were contacted by respective teachers to obtain verbal consent for the study. Due to the inclusion of minors, parental written consent followed by assent from the participants was obtained prior to the protocol. Variables and Instruments The outcome variables and corresponding instruments for this study included the following: • The student’s participation in the learning as defined by the ability of students to effectively interact with the device and engage in the learning activity- To quantify this outcome variable, an observational tool (see Table 1) was developed to record any problem that may have affected the students’ participation. The tool consisted of six participation variables specifically tailored to the learning intervention and the behavior and intellectual skills of the students. As listed in Table 1, it has been conceptualized and linked to the two domains (General tasks and demands and Focusing attention) under the Activities and Participation component of the International Classification for Functioning, Disability, and Health (World Health Organization, 2001). These skills were further expanded and operationalized specific to the study by observing videos of the students participating in trial learning

Arthanat et al. sessions using the iPad and the computer and identifying the quantifiable behavioral attributes. For scoring, a rating of 1–4 was assigned to each variable as indicated by the frequency with which a problem was apparent during each learning session (See Table 2). The ratings on the variables were aggregated and averaged to yield a participation score for each session. • The change in academic performance of the students as a result of their participation in each form of learning intervention (computer and the iPad). A 10-question multiple choice test in accordance with the IEP goals was developed for each student in consultation with their teachers. A point was assigned for each correct response and half a point was given if the student partially answered and required prompting by the teacher to complete the answer. Intervention The study lasted 10 weeks. The learning sessions were scheduled for about 25 minutes 4 times a week for each student. In the first 4 weeks, the students were observed using their standard mousedriven desktop computers in individualized learning activities, considered as the baseline phase of the study. The iPad was introduced at the fifth week of the study. In order to accustom the students to the learning apps on the iPad, they were allowed to explore it with no formal structure for a week. The actual learning intervention and observations began at week 6 and continued for the remainder of the study. The learning sessions in the two academic areas (B1 and B2 ) were alternated in these last 4 weeks. Table 3 lists the iPad apps that were selected based on the individual student’s IEP goals and teacher input. All learning sessions were one-on-one and conducted by a trained occupational therapy student intern under the supervision of the teachers. Data Collection For each student, two learning sessions per week were scheduled to be captured on video. The camera was positioned on a small tripod at a diagonal angle that captured a full view of the student but away from the line of sight. To support the analysis, the observer also used a log sheet to note specific behavior during the course of the activity. The 10-question individualized academic test was given to each student 3 times: at the end of the baseline phase, following the intervention with the iPad, and a month following the completion of the study to examine learning retention. In order to avoid practice effect, the questions were revised (e.g., the answer choices), but the content, format, and level of difficulty remained the same. The teachers administered the academic test a month following the intervention, and reported about the continued usage of the iPad by the students. Data Analysis Four videos of learning sessions were visually analyzed within each phase of the two AB design. Note here that each student was absent 1–2 sessions when the video capture was scheduled. A minimum of three repeated observations is recommended in single subject case studies for visual analysis of trends in

iPad Use by Students With Developmental Disabilities

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Table 1. Operationalization of the observation tool from the ICF. Activity & participation domains (WHO, 2001)

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General tasks and demands d210: Undertaking a single task

Participation variables

Conceptual definition “Carrying out simple or complex and coordinated actions related to the mental and physical components of a single task such as initiating a task, organizing time, space and materials for a task, pacing task performance, and carrying out, completing, and sustaining a task” (WHO, 2001, p.129)

Operational definition

Initiation

The ability to commence the learning task in a reasonable amount of time or as expected.

Pace

The ability to carry on with the steps in the learning task in a reasonable pace without pausing or delays. Carrying out the learning task without the need for prompting (verbal or physical). Sustaining focus on the learning task.

Persistence

Learning and applying knowledge d160: Focusing attention

“Intentionally focusing on specific stimuli, such as filtering out distracting noises” (WHO, 2001, p. 126)

Attention

Temperament

Carrying out the learning task without any maladaptive behavior. Carrying out the learning task without impulsive (self-stimulating) stereotypical actions.

Goal-directed

Table 2. Scoring student participation using the observational tool. Rating

Participation variable

Profound (0) Problem led to incompletion of the task

Severe (1) Problem apparent for 75% of the task

Moderate (2) Problem apparent for 50% of the task

Mild (3) Problem apparent for 25% of the task

No limitation (4) Problem not apparent throughout the task

Initiation Attention Temperament Pace Goal-Directed Actions Persistence

0 0 0 0 0 0

1 1 1 1 1 1

2 2 2 2 2 2

3 3 3 3 3 3

4 4 4 4 4 4

intervention outcome (Betz, 1998). For each student, the video files were grouped as those from the computer sessions and the iPad sessions and then organized based on the academic areas to ensure that the comparison of student participation in the learning activities between the computer and the iPad was made for the same academic area. Two reviewers (one of the investigators and an independent trained reviewer) carried out the visual analyses. The reviewers first established a clear understanding of the variables associated with participation of the students in the learning sessions. The

reviewers then viewed and analyzed the videos independently. Subsequently, debriefing sessions were conducted between the reviewers to verify the analyzed scores for reliability and agreement. The percentage agreement on the observations between the reviewers was calculated. For the 4 students, the two reviewers independently viewed 62 learning sessions. Note here that Neil and Evan were present only for three videos in one of the intervention phases with the iPad. For each session, the reviewers rated 6 participation variables for a total of 372 ratings. The independent observations of

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Arthanat et al. Table 3. iPad learning apps selected for each student. Student

Academic areas

iPad apps used

Brycen

Shape and color recognition

Jake Neil Evan

Counting and spelling Money management and reading Reading and counting

Abby Train colors,a ABC Letters, Numbers, Shapes and Colorsb Kids can spell,c Puzzle mathd Play words,e Jungle Coinsf Play words, Jungle Coins

a 22

Learn LLC. Learn.com and CFC, s.r.o. c Kids Best Place 2011. d Bonrac 2012. e Pocketglow Inc 2011–2013. f Andrew Short 2010–2013.

whether the outcome scores between baseline and intervention are considerably different in drawing a cause-effect relation. Finally, consistency involves linking the data points in each phase to determine whether the patterns in outcome scores are the same for baseline and intervention. These data points were plotted manually using the drawing tool in Microsoft Excel program. The data patterns further verifies the projected similarities or differences in the outcome between baseline and intervention. (Kratochwill et al., 2010).

Results Participant 1 Brycen used the computer and the iPad to learn color and shape recognition. As seen in Figure 1, the trend lines for the iPad had an upward slope in both phases compared to a slightly downward slope for the computer. However, there were no major differences

4.00 Participation Score

the reviewers were consistent for 307 of these ratings indicating an 82% agreement. The remaining 65 inconsistent ratings warranted a combined observation of the video between the reviewers in order to arrive at an agreed upon participation score. The participation scores for each student were plotted on a chart for visual analysis using Microsoft Excel program. In order to verify causal relationship (i.e., whether the iPad caused a change in student participation) in the visual analysis, we adopted a six-feature criteria proposed by single subject design methodologists: Standards for demonstrating evidence of a relation between an independent variable and outcome variable (Kratochwill et al., 2010). The design phases in the student charts (both within and between phases) were examined in terms of trend, level, variability, immediacy of the effect, overlap, and consistency of data patterns across similar phases. Trend refers to the slope represented by a line that best coincides with the data points in each phase of baseline and intervention. These trend lines were generated in the charts using Microsoft Excel program. Level is the mean scores of data points in each phase, while variability is the standard deviation of the data points. In order to draw meaningful conclusion in this study, we estimated a one-point difference in the mean scores (signifying problems in participation for 25% of the session) to be a compelling indication of the higher or lower participation between the iPad and the computer. Examining trend, level and variability is essential to effectively extrapolate that the data points within the baseline and intervention phases will continue in the same trajectory. In addition, analyzing the immediacy, overlap, and consistency between the data points in baseline and intervention phases is important in substantiating the causal relationship in single subject design (Kratochwill et al., 2010). Immediacy of the effect is defined as the change in level in the last three data points in one phase to the first three data points of the next (baseline to intervention and intervention to baseline). An immediate change here will support a compelling inference that change in the outcome measure was due to manipulation of the independent variable, although in some interventions the effects may be delayed. Here again, we chose a one-point difference between the phases to reflect a major change in participation between the use of the computer and iPad. Overlap is determined by the proportion of data points from one phase that overlaps with data from the previous phase. This estimation visually verifies

Counting

3.00 2.00 Weeks 6 to 10

Weeks 1 to 4

1.00 0.00 1

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5

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8

4.00 Participation Score

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b 22

Shape Recognition

3.00 2.00 1.00

Weeks 6 to 10

Weeks 1 to 4

0.00 1

2

3

4

5

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7

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Trials Computer

iPad

Fig. 1. Brycen’s participation with computer and iPad: Counting and shape recognition (color figure available online).

Color Recognition

4

4.00

Shape Recognition

3 2 1 0

209

Init. Att. Temp. Pace G.D Pers Init. Att. Temp. Pace G.D Pers Participation variables

Counting

Participation Score

Avg.Participation ratings

iPad Use by Students With Developmental Disabilities

3.00

2.00

1.00

Weeks 6 to 10

Weeks 1 to 4

0.00 1

in participation scores in terms of level and variability. For the four baseline trials involving color recognition, his mean participation score was 2.67 (Std = 0.45), slightly higher than that with the iPad (Avg = 2.58, Std = 0.52). While learning shapes, his participation score with the computer decreased (Avg = 2.13, Std = 0.48), but peaked again (Avg = 2.71, Std = 0.53) while using the iPad for the same learning activity. As measured by immediacy, these changes were not rapid as he switched from the computer to the iPad and vice versa. The similarities in the linked data pattern (note the oval shape) along with the relatively same standard deviations suggest consistency in the participation trajectory in all phases. A major proportion of the data points also overlapped other than in the three trials (trial eight for counting, and trials six and eight for shape recognition) indicating that there were no overall differences in Brycen’s participation with both devices. The observer noted that Brycen participated somewhat better in shape recognition tasks while using the iPad (as seen in the 6th and 8th trials). His average ratings on the six participation variables (initiation, attention, temperament, pacing, goal directed behavior, and persistence) for each academic area are displayed in Figure 2. Although he initiated the learning, he had difficulties sustaining his attention. The observer noted that he “at times stared off into space or physically got up and walked away from the session during two separate trials” one involving the iPad and the other the computer. His impulsiveness to play games on the iPad and computer undermined his goal directed actions during the sessions. At times, he responded to questions aimlessly even when he knew the correct answer and had to be frequently prompted to listen carefully to questions. Following the intervention, Brycen continued to use a computer with a touch screen monitor with his teachers on a daily basis. Despite the lack of any observed differences in his participation, his academic scores increased progressively from 35% while using the computer to 50% with the iPad and 60% during follow-up. Participant 2 Jake’s participation in the learning sessions with the iPad was noticeably better than with the computer (see Figure 3). The trend lines displaying the participation in both intervention phases were comparatively at higher levels while using the iPad- going from mean scores of 2.00 (Std = 0.47) to 3.00 (Std = 0.14) when learning to count; and then from 2.29 (Std = 0.08) to 3.42 (Std = 0.29) while learning to spell. The change in participation scores

2

3

4

5

6

7

8

4.00 Participation Score

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Fig. 2. Brycen’s participation using the iPad (color figure available online).

Spelling

3.00 2.00 Weeks 6 to 10

Weeks 1 to 4

1.00 0.00 1

2

3

4

5

6

7

8

Trials Computer

iPad

Fig. 3. Jake’s participation with the computer and iPad: Counting and spelling (color figure available online).

going from computer to the iPad was also rapid (mean score >1) as highlighted by immediacy between baseline to intervention for both learning activities. The data patterns between the phases also remained consistent (except in Trial 3 for counting) as denoted by the similar oval shapes in the linked data points. Importantly, the lack of any overlap between the data points of the baseline and the intervention phases conclusively indicate Jake’s higher participation with the iPad compared to the computer. Summarizing the observer’s notes, Jake was distracted and disinterested for about 50–75% of the time while completing the counting task on the computer and often did not comply to prompting. He refused to continue the task and walked away from the computer on one occasion. On the other hand, he remained focused on the task while using the iPad and at times “yelled in excitement” when he answered correctly. As noted in Figure 4, the noted concerns were with his goal directed behavior and persistence with the counting task. He intentionally tapped on the wrong answer frequently to elicit the audible beep and required frequent prompting, which resulted in a decline in his participation towards the third trial. Jake was actively engaged with the spelling task in all three trials considerably more with the iPad than with the computer. He was distracted 50–75% of the time while on his computer and was observed “staring at others” and disconnected himself from the task by “sitting with his arms crossed.” This behavior was not evident when he used the iPad for spelling. As reported by his teachers, Jake continued to show an active interest in the iPad even after the intervention phase. His academic performance noticeably increased from 40% at baseline to a 100% when measured at follow-up.

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Arthanat et al. Spelling

4 3 2 1 0

Init.

Att. Temp. Pace

G.D Pers Init. Att. Temp. Pace Avg. Participation Ratings

G.D

Pers

Fig. 4. Jake’s participation with the iPad (color figure available online).

Participant 3

Participant 4

Participation Score

Coin Counting

3.00 2.00

1

2

3

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5

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8

Trials

4.00

Word Finding

3.00 2.00 Weeks 6 to 10

Weeks 1 to 4

1.00 0.00 1

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Trials iPad

Computer

Fig. 5. Neil’s participation with the computer and the iPad: Coin counting and word finding (color figure available online). Coin Counting

4

Word Finding

3 2 1 0 Init.

Evan’s learning sessions were focused on counting using coins and reading by word recognition. He participated better in the learning sessions for word recognition as opposed to counting. However, the visual analysis showed no notable differences in his participation with the computer and the iPad. The trend lines for participation were pointing downward for the computer in both learning activities, while it was the same for the iPad for counting. The participation level and variability were relatively the same, and the immediacy, consistency and overlap of data patterns indicated no categorical differences while learning with both devices (see Figure 7).

Weeks 6 to 10

Weeks 1 to 4

1.00 0.00

Participation Score

Neil used the computer and the iPad for money math and reading (i.e., word finding). The visual analysis revealed no remarkable differences in his participation with the iPad and the computer in terms of the six-feature criteria (see Figure 4). In fact, the participation trend was slightly downward with the iPad in both phases. This trend was evident in the slightly lower mean scores of participation (level) with the iPad (2.83) in both phases compared to that of the computer (2.96 and 3.17, respectively). However, the immediacy differences between the last three trials with the computer and the first three trials with the iPad were not found to be convincing. The consistency and major overlap among the data patterns between baseline and intervention also support that Neil’s participation scores with both devices were not distinct. The observations revealed that he demonstrated more or less the same levels of attention and interest in tasks involving both devices. However, his lack of goal directed actions (75% in 2 trials) and the frequent need for prompting (50–75% of the time) undermined his learning with the use of the iPad (see Figure 5). His tendency to respond inappropriately to the visual and auditory cues of the iPads was quite evident. The observer noted that “he gets distracted by certain visuals and got disengaged from the task by wanting to tap on them.” On the other hand, no such issues with goal directed behavior were noted when he was using the computer. Neil did not correctly answer any of his questions on the baseline academic test, but responded 30% correctly following intervention. Unfortunately, Neil was unavailable at school during the follow-up phase and the academic test could not be administered to him a third time.

4.00

Participation Variables

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Participation variables

Counting

Att. Temp. Pace G.D

Pers Init.

Att. Temp. Pace G.D

Pers

Avg. Participation Ratings

Fig. 6. Neil’s participation with the iPad (color figure available online).

As observed specifically, Evan was less interested in the counting activity and often wanted to skip out of the application to play games especially during Trial 3 for counting using the computer. He appeared too impulsive and hasty to finish the task in all three trials that his actions were misdirected and required

iPad Use by Students With Developmental Disabilities

211 Discussion

4.00 Participation Score

Time telling

3.00

2.00

1.00

Weeks 6 to 10

Weeks 1 to 4

0.00 1

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3

Participation Score

5

6

7

Word Recognition

3.00 2.00 Weeks 1 to 4

1.00

Weeks 6 to 10

0.00 1

2

3

4

5

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7

8

Trials iPad

Computer

Fig. 7. Evan’s participation with the computer and the iPad: Time telling and word recognition (color figure available online).

Participation Variables

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4.00

4

Counting

Word Recognition

4 3 2 1 0 Init.

Att. Temp. Pace G.D

Pers Init.

Att. Temp. Pace G.D

Pers

Avg. Participation Ratings

Fig. 8. Evan’s participation with the iPad (color figure available online).

prompting for about 75% of the time to answer correctly. He seemed relatively more interested in word finding with none to fewer problems being observed in initiation, sustained attention and temperament. However, he did require some level of verbal prompting at the end of each task to pick the right answer. His impulsivity was greater with the iPad (at times, 75% of the time) as observed by his purposeful selection of wrong answers to finish the task quickly, frequent attempts to switch to another application and “tapping aimlessly” to evoke the audible error feedback. On the other hand, his impulsivity with the computer was lesser and limited to him choosing answers too quickly without paying attention to the task. Evan’s teacher reported that his use of the iPad following the intervention period was solely for leisure. He had discontinued the use of the academic apps and was only interested in the gaming apps. Although his academic scores improved subsequent to the introduction of the iPad (30–80%), it had declined following a month (55%) since its discontinuation.

The study findings clarified the three research questions. With respect to student participation in learning, there was no distinguishing trend in three out of the four students to conclusively indicate any difference in their interaction between the iPad and the computer. Only one student, Jake, interacted clearly better with the iPad than with the computer in both academic areas. Overall, the participation patterns and associated processing and behavioral problems were similar in these students while using the computer and the iPad. Table 4 summarizes comparative participation of each student in learning sessions using the iPad and the computer, their noted strengths and concerns in their interaction with the iPad and change in academic scores following the trials with the device. The observation tool that was specifically developed for this study allowed us to analyze the stated behavioral attributes that contributed to or hindered the student’s participation. In regard to the iPad, there was no limitation in initiation. All of the students were eager to use the iPad and commenced their tasks immediately. For the most part, the iPad did not pose a problem to the students’ temperament as all of them performed the tasks with little to no maladaptive behavior. Additionally, the students maintained a generally consistent pace in the majority of their learning sessions. Nonetheless, the behavioral variables that were of concern were attention, goal-directed actions and persistence with the task. All four students were found to have difficulties sustaining their attention throughout the learning session. This in turn led to decreased persistence and a need to be verbally, and at times physically, re-directed to the learning task. In comparison, as noted especially with Neil and Evan, students demonstrated a higher level of goal directed behavior when using the computer. This difference may be attributed to the fact that students, as seemingly interested in the novelty of the iPad, were eager to explore and switch to different applications on the iPad. The touch screen interface may have stimulated the non-goal directed behavior because of the ease with which the students had access to other applications. In addition, the students seemed to get compulsively preoccupied on the visual and auditory feedback on the iPad apps (and at times the computer) that on many instances undermined their goal directed actions. These findings reflect the importance for teachers to have a clear understanding of the process skills and behavioral attributes of their students, and to be accordingly mindful of the graphical interface and interactive elements of the learning apps. The participation patterns for two students (Brycen and Neil) were relatively similar for the two academic areas while they were distinct for the other students suggesting that the interaction may be dictated by students’ learning interests, as well as the audio-visual layout and features of the apps. The academic scores for the students increased in varying percentages following the introduction of the iPad by 15% (with Brycen) to 60% (with Jake). The student who participated at the highest level (Jake) demonstrated the highest gain in knowledge. Out of the three students who completed the test following a month, two who continued with their scheduled learning sessions on the iPad showed further improvement in their academic scores. Based on teacher report, Evan, who was continuing to use

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Table 4. Comparative summary of student participant in learning with iPad versus computer.

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Comparative Participation as per visual analysis and observation

Students

iPad/computer/no Difference

Brycen

Observed strengths in use of the iPad

Observed concerns in use of the iPad

No Difference

Initiation and temperament “Started the sessions with no delays and displayed no maladaptive behavior”

Jake

iPad

Initiation, pacing, temperament and attention “Showed an active interest in the apps throughout the task”

Neil

No Difference

Initiation and pacing “Initiated tasks well, and maintained attention through the activity”

Evan

No Difference

Initiation, pacing and attention “Initiated tasks immediately, did very well answering questions correctly when focused, able to maintain attention throughout task”

Attention, pacing, persistence and goal directed behavior “Distracted by wanting to switch to game apps;” “Pausing and slowing down;” “At times answered impulsively in a rush and needed a lot of prompting to stay on the task.” Attention, goal directed actions and persistence during counting task “Frequently ‘stimmed’ off of on auditory feedback in apps which led to him not focusing on answering correctly” Attention, goal directed actions and persistence “Eager to explore the iPad, distracted by negative auditory feedback in second iPad app that required a good deal of verbal prompting” Temperament, goal directed actions and persistence “Eager to earn choice (games) and therefore often rushed through the activities, needed verbal prompting to slow down, yelling when prompted, and distracted by negative auditory feedback”

the iPad solely for leisure, recorded decreased scores at followup from 80% to 55%. These follow-up scores in conjunction with teacher report were received outside of the experimental period of the study. Although a causal-effect interpretation cannot be made, the follow up academic score tests provide some insight as to how continuing use of the iPad or other touch screen technologies may influence academic performance. It could also be argued that the learning potential from use of the touch can only be maximized through the regular use of the technology in the classroom as opposed to a short-term intervention. The study has implications in the use and implementation of touch screen tablet devices for learning by students with various developmental disabilities. Although the students demonstrated academic gains during and after the use of the iPad, conclusive evidence may only be reached through long-term research and control of confounding learning activities. The touch interface may also prove counter productive in terms of the student’s participation due to concerns with sustaining attention and goal directed actions with the learning application. This is an important consideration as iPads continue to be purchased and promoted in schools across the country. Concurrently, teachers also need to become familiarized with strategies and best practices by which the technology can be utilized in accordance to the wide-ranging learning needs and skills of students. This study underscored major as well as subtle

Academic performance following use of the iPad Increased (15%)

Increased (60%)

Increased (50%)

Increased (30%)

behavioral aspects and processing skills that are critical to the selection of iPad learning applications for students with DD including autism. The observational tool used in this study could assist teachers as a guide to monitor student behavior when technologies are incorporated into learning. Limitations This was a preliminary empirical study to examine the potential of iPad as a learning tool. However, this pilot study was limited by time, personnel and funding. Due to the nature of single subject design, limited data points and participant variability, the findings of the study can be argued as having limited generalizability. As mentioned previously, due to logistical difficulties, the study did not employ a standard time-sequenced ABAB design. Nonetheless, the use of AB design at two concurrent levels allowed for verification of trends within two exclusive baselines and interventions. A longitudinal study may be warranted to effectively validate the scope of the iPad in accomplishment of academic goals. Specifically, a large-sample, quasi-experimental study that employs a time-tested, repeated measures design with multiple data points for both the computer and iPad may better clarify the causal interpretation in the outcome variables. Because of the limited timeframe and concern with practice effect, the academic

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iPad Use by Students With Developmental Disabilities tests were given only once during baseline. Use of multiple baseline academic tests in broader intervals would have further corroborated the change in academic performance as exclusively attributed to the use of the iPad. In addition, the complexities in conducting experimental intervention studies in classrooms were evident. Students in the study were undergoing other forms of learning throughout the course of the study, which could not be withheld for ethical reasons. In particular, the follow-up phase of the study lacked experimental control and the academic scores collected at this time may have been confounded by other learning interventions. Some participants had prior exposure to the learning applications on the computer as opposed to those on the iPad, and this familiarity would have confounded their interaction with both devices. In terms of instrumentation, the observational tool was developed specifically for the study and no psychometric evaluation has been conducted to support its use in measuring student participation. All study participants were males. The majority of students in the school with DD and autism were boys and the fewer female students somehow did not fit the purposive sampling criteria. Finally, the selection of apps for intervention was based on the individual learning goals of the students as opposed to their behavior and process skills. The graphical interface, feedback and content of the apps may have very well influenced the participation and learning of each student.

Conclusion Touch tablet devices are rapidly gaining popularity in pubic schools across the United States. However, it should not be treated as a prescriptive tool in that the engagement and learning outcomes in each student may considerably vary depending on his/her motor, process and behavioral skills in combination with the complexity of the learning applications. The findings also do not imply the substitution of desktop computers in schools with the iPad. Rather, the iPad may be a complimentary educational tool for students based on their academic goals, skills, and interests. The instructional potential of touch tablet devices for students with inclusive education needs must be further investigated through long-term research and large-sample, controlled, experimental studies. Currently, there are no specific evaluation process, guidelines, and best practices to support the use of iPad for students with wide-ranging disabilities. Future work is required to support teachers in the systematic selection and use of touch tablet learning applications for students with individualized educational needs.

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Comparative observations of learning engagement by students with developmental disabilities using an Ipad and computer: a pilot study.

This study examined the use of the Apple iPad for learning by children with developmental disabilities (DD), including those on the autism spectrum. A...
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