Examining the Effect of Using iPad Apps for Self-Monitoring of Target Behaviors for People with Autism Spectrum Disorder

Running head: IPAD APPS FOR SELF-MONITORING

Examining the Effect of Using IPad Apps for Self-Monitoring of Target Behaviors

for People with Autism Spectrum Disorder

Sarah K. Conway

A Capstone Presented to the Teachers College Faculty

of Western Governors University

in Partial Fulfillment of the Requirements for the Degree

Master of Education in Learning and Technology

December 29, 2013

Student Mentor: Marty DeWindt

Capstone Facilitator: Bryan Skelton

IPAD APPS FOR SELF-MONITORING

ii

Abstract

People with autism spectrum disorder (ASD) often have difficulty becoming independent due to

challenges in executive functioning. Impairments in executive functioning affect social and

learning behaviors, information processing, and the ability to generalize learned skills between

settings. One effective method of promoting independence is self-monitoring. This study

explored the use of iPad applications (apps) for self-monitoring of independently identified target

behaviors. Participant teams, consisting of one school age child with ASD and his or her parent,

received specific instruction in implementing the steps of a self-monitoring program. Using the

iPad app, behavior events were recorded for three weeks. Based on the findings, the researcher

concluded that iPad apps are an effective tool for self-monitoring as part of a self-management

program.


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Table of Contents

Chapter 1: Topic and Problem ............................................................................................1

Topic ....................................................................................................................................1

Rationale ..................................................................................................................1

Topic importance .....................................................................................................2

Problem Statement ...............................................................................................................3

Problem background ................................................................................................3

Possible causes .........................................................................................................4

Significance of the problem .....................................................................................5

Research Questions ..............................................................................................................5

Chapter 2: Review of the Literature....................................................................................6

Overview of the Literature ...................................................................................................6

Self-Management .................................................................................................................6

Self-monitoring is a pivotal behavior ......................................................................6

Self-monitoring increases independence .................................................................7

Habits ...................................................................................................................................7

Repetition and the habit loop ...................................................................................8

Habit formation and automaticity ............................................................................8

Self-management for automaticity ...........................................................................9

Touch technology for intervention.......................................................................................9

Prior Research ....................................................................................................................10

Best Practices Research .....................................................................................................11

Summary ............................................................................................................................12


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Chapter 3: Methodology ....................................................................................................13

Overview of the Research Methodology ...........................................................................13

Research Questions ............................................................................................................13

Hypotheses .........................................................................................................................13

Research Design.................................................................................................................13

Participants .........................................................................................................................14

Participant one .......................................................................................................15

Participant two .......................................................................................................15

Participant three .....................................................................................................15

Permissions ............................................................................................................15

Evaluation Methods and Tools ..........................................................................................16

Quantitative data ....................................................................................................16

Qualitative data ......................................................................................................17

Validity and reliability ...........................................................................................17

Baseline data chart .................................................................................................18

The iPad apps .........................................................................................................18

Attitude survey .......................................................................................................19

Field notes ..............................................................................................................19

Data integrity .........................................................................................................19

Method Adoption ...............................................................................................................20

Instructional plan ...................................................................................................20

Justification ............................................................................................................22

Differences .............................................................................................................23


v

Summary ............................................................................................................................24

Chapter 4: Findings ............................................................................................................25

Results Overview ...............................................................................................................25

Data Driven Findings Summary ........................................................................................25

Data Analysis .....................................................................................................................26

Quantitative data ....................................................................................................26

Qualitative data ......................................................................................................28

Perceived potential for behavior change ................................................................28

Perceived usefulness of iPad technology ...............................................................30

Discussion questions ..............................................................................................32

Answers to the Research Questions ...................................................................................34

Findings Summary .............................................................................................................34

Chapter 5: Discussion and Conclusions .............................................................................36

Overview ............................................................................................................................36

Problem Solutions ..............................................................................................................36

Strengths ............................................................................................................................38

Weaknesses ........................................................................................................................38

Problems and Factors .........................................................................................................39

Implications........................................................................................................................40

Limitations .........................................................................................................................41

Recommendations ..............................................................................................................41

Improvement ..........................................................................................................41

Further investigation ..............................................................................................42


vi

Implementation ..................................................................................................................43

Master’s Degree Experience ..............................................................................................44

References ..........................................................................................................................46

Appendix A: Instructional Unit .........................................................................................51

Appendix B: Session One PowerPoint Slides ....................................................................63

Appendix C: Session Two PowerPoint Slides ...................................................................73

Appendix D: Session Three PowerPoint Slides ...............................................................106

Appendix E: Session Four PowerPoint Slides .................................................................117

Appendix F: Goal-Setting Worksheet One ......................................................................123

Appendix G: Goal-Setting Worksheet Two .....................................................................124

Appendix H: Fading Reference Sheet..............................................................................125

Appendix I: Baseline Data Chart .....................................................................................126

Appendix J: Pre-intervention Survey ...............................................................................127

Appendix K: Post-intervention Survey ............................................................................128

Appendix L: Group Discussion Questions ......................................................................129

Appendix M: Informed Consent Form ............................................................................130

IPAD APPS FOR SELF-MONITORING 1

Chapter 1

Topic and Problem

Topic

The focus of the research involves the use of iPad applications (or apps) by persons with

autism spectrum disorder (ASD) for self-monitoring of independently identified target behaviors.

The overall goal of instruction is for people with ASD to gain independence through self-

monitoring using iPad technology. Given specific instruction in the use of an iPad app for data

tracking, the participants will independently track the frequency, duration, or intensity of a self-

selected target behavior (a functional life skill or related behavior that the participant hopes to

increase or eliminate). This researcher believes that with increased self-awareness and

repetition of the target behavior, each participant will meet his or her goal.

Rationale. This topic was chosen in response to the author’s personal experience with

her own daughter, who is high functioning on the autism spectrum. The child, age 12, struggles

with many self-care tasks that typically developing peers have mastered. Last summer, the child

indicated that she would like to work on a personal care goal at home. The author designed a

data chart and taught the child to self-report behavior events. The child’s target behavior

improved immediately, and that improvement continued over time until it reached a plateau.

Notably, the child maintained her achieved success for several weeks after the self-monitoring

routine was faded. The author reflected that the child’s success was potentially due to a number

of key factors, including: the child’s intrinsic motivation to change, increased awareness of the

behavior, weekly reinforcement, and the visual representation of progress over time.


The insight led this author to consult several prior studies that endorse self-monitoring as

a positive behavior intervention for people with learning and behavior challenges. Much of the

existing research supports self-monitoring as a method to increase independence for people with

ASD. Throughout the graduate studies program, this author has focused heavily on researching

the use of iOS devices, including the iPad, to support students with ASD. With one-to-one iPad

initiatives growing in popularity among local special education programs, the author wondered

how iPad apps could be used for self-monitoring. A search of Apple’s App Store (https://

www.itunes.apple.com/us, December 4, 2013) revealed that while many apps exist for

monitoring behaviors using a token system as part of a therapeutic or school program, there are

no apps designed specifically for self-monitoring of self-selected behaviors for students with

ASD. This initial evaluation suggested a need for research in the area of the use of iPad apps for

self-management.

Topic importance. According to Lee Wilkenson, Ph.D. (2012), “Self-management is an

evidence-based strategy for fostering independence and self-control in high-functioning students

with ASD” (Conclusion, para. 1). Self-management is comprised of setting goals, monitoring

behavior, and evaluating progress. Self-monitoring is an important component of self-

management, in which the individual observes his or her own behavior and independently

records behavior events on a data collection form. Self-monitoring can help build novel skills or

desirable behaviors while reducing or eliminating undesirable behaviors. When an individual

learns to self-observe and self-record a behavior event or non-event, this increases independence

because the individual is the agent of the intervention (Hume, Loftin, & Lantz, 2009).

An iPad is a viable means for collecting behavior data across a variety of settings, from

home to school. The portability of the iPad allows individuals to collect data frequently and at


the point of need. Repetition is vital to the formation of new behaviors; those performed with

frequency become encoded in the brain and are harder to break (Dean, 2013). This encoding is a

step toward automaticity, or the ability to do something without consciously thinking about it.

Automaticity allows the individual to focus attention on the more complex aspects of a task (i.e.,

generalization) and subsequently perform that task independently with few or no prompts (Gray,

2004).

Problem Statement

The problem is that people with ASD typically have difficulty becoming independent.

One of the keys to independence is self-monitoring. There are many tools available for self-

monitoring. Current apps for self-monitoring using the iPad are very accessible and can be

reasonably adapted for use in a self-monitoring program. The solution to the problem is helping

people with autism become more independent through self-monitoring using apps on the iPad.

Problem background. ASD is a prevalent developmental disability affecting 1 in 50

children in the United States (U.S. Department of Health and Human Services, 2013). While

characteristics of ASD are different for every affected individual, diagnostic criteria according to

the DSM-IV-TR describes deficits in three core areas: communication, social functioning, and

behavior (American Psychiatric Association, 2000). For individuals with ASD, impairments in

executive functioning impede the ability to become independent. Executive functioning is

defined as “a set of processes that have to do with managing oneself and one’s resources in order

to achieve a goal” (Cooper-Kahn & Dietzel, 2008, p. 10). Challenges in executive function

affect independence in the areas of task initiation, planning, information processing, motivation,

and generalization (Hume et al., 2009). Executive functioning affects more than just academic

skills. Related tasks may include basic life skills such as grooming, making a list, holding a


conversation, or using money to buy food. Because executive functioning is so crucial to

independence, and because ASD is not limited to the classroom, it is important to find effective

strategies that promote independence across a variety of settings.

Possible causes. There are several possible reasons why there is limited research

regarding the use of iPad apps as a self-monitoring strategy. First is the variability of the

diagnosis itself. ASD represents a spectrum of functionality. ASD varies in severity, and no two

individuals are affected in exactly the same way. Those considered high functioning on the

spectrum, including some people with Asperger Syndrome, may not be educationally recognized

as having ASD. For others, ASD might remain undiagnosed until adulthood, when the

individual begins to have challenges with maintaining independence in his or her workplace,

school, or personal life.

Family members and teachers of people on the ASD may not have the expertise to

understand how the executive functioning deficits associated with ASD affect functional life

skills and independence. Many people with ASD require caregiver support and prompting in

order to communicate effectively, demonstrate a skill, or disengage from disruptive behaviors.

For the caregiver, it may be easier to continue to do what is working than it is to fade support and

implement a new strategy or routine.

Parents and practitioners who understand the benefits of self-monitoring do not always

have the time or resources to develop a self-monitoring program using the iPad. In order for a

self-monitoring program to be effective, the student must have access to the self-reporting tool.

While there are one-to-one iPad programs in some schools, the technology often cannot be

removed from the classroom. Students may not have their own iPad at home, or they are

required to share the iPad with a family member. Finally, parents of children with ASD may


prioritize other therapies or activities above the cost and effort of implementing a self-monitoring

program using the iPad.

Significance of the problem. Multiple studies have indicated technology as a viable tool

for teaching functional and academic skills in educational settings (Neely, Rispoli, Camargo,

Davis, & Boles, 2013). The iPad is a portable technology device that is readily available,

relatively low-cost (as compared with other assistive technologies), and holds no stigma due to

its widespread popularity as a school, work and entertainment device. The iPad offers easy and

inexpensive access to thousands of apps, of which more than 500 are specifically designed to

assist individuals with ASD (https://itunes.apple.com, December 2013). As a whole, these apps

offer individuals with ASD a variety of supports for independence.

Significant research exists regarding the effect of self-monitoring for students with ASD.

Recent studies have examined the use of iPad technology as an academic intervention for

students with ASD. Very few studies examine the use of iPad technology for self-monitoring of

functional behaviors. This researcher believes this study to be unique in three respects:

1. The study takes place in a nonacademic setting outside of school hours.

2. The participant self-selects the target behavior.

3. The participant’s parent is taught to implement and fade the self-monitoring program.

Research Question

The question is: What effect will using iPad apps for self-monitoring have on target

behaviors for high functioning individuals with Autism Spectrum Disorders? The

related hypothesis is: When an individual who is high functioning on the autism spectrum uses

an iPad app to self-monitor a self-selected target behavior for two weeks, the target behavior will

improve.


Chapter 2

Review of the Literature

Overview of the Literature

The purpose of this study is to examine the effectiveness of using an iPad app to self-

monitor self-selected target behaviors for school-age individuals who are considered high

functioning on the autism spectrum. A review of the extant research revealed three areas of

interest that contribute to understanding the problem and solution. These are: self-management,

habit formation, and the use of touch technology (i.e., iPads) to support individuals with ASD.

Self-Management

In its National Standards report, the National Autism Center (2009) recognizes self-

management as an established and effective intervention or treatment for ASD. Self-

management procedures have been widely researched and subsequently recommended as a part

of a comprehensive intervention program (Ganz, 2008; Wilkenson, 2012). Prior research reveals

that self-management strategies are effective for students of all ages, and appropriate for a

diversity of academic and behavioral challenges, ability levels, and cognitive functioning (Loftin,

Gibb, & Skiba, 2005; Ganz, 2008; Mitchum, Young, & Benyo, 2001). In her review of the

research on the use of self-monitoring, Ganz (2008) observes that through self-assessment, self-

recording and self-reinforcement (the three integral parts of self-management), students are

better able and more motivated to change target behaviors.

Self-monitoring is a pivotal behavior. A primary aspect of self-management, self-

monitoring is comprised of self-observation and self-recording. Self-monitoring is a positive

behavioral intervention and a pivotal behavior (Ganz, 2008). Pivotal behaviors are those that

have the potential to lead to improvements in other areas. The notion of self-monitoring as a


pivotal behavior is supported in the research of Hume et al. (2009); Koegel, Koegel, & Carter

(1999); Mammolenti, Vollmer, & Smith (2002); and Ganz (2008). Wilkenson (2010) supports

these findings in Chapter 5 of his book, A Best Practice Guide to Assessment and Intervention

for Autism and Asperger Syndrome in Schools. For individuals with ASD, self-monitoring has

proven pivotal in improving social functioning, daily living skills, and on-task behavior (Hume

et al., 2009; Ganz, 2008). Self-monitoring is also tied to decreases in undesirable behaviors such

as echolalia, self-stimulation, and stereotypic actions (Ganz, 2008; Loftin et al., 2005; Hume et

al., 2009; Mammolenti et al., 2002; Koegel, Koegel, Harrower, & Carter, 1999). In his adapted

report on self-management as an evidence-based intervention, Wilkenson (2012) adds that self-

monitoring is a pivotal skill that promotes generalization between settings.

Self-monitoring increases independence. Self-monitoring promotes independent

functioning and self-regulation for persons with disabilities (Loftin et al., 2005; Hume et al.,

2009; Ganz, 2008), and is particularly effective for students who are high functioning on the

autism spectrum (Wilkenson, 2012). Multiple studies confirm that self-monitoring is a viable

way to shift control of a target behavior from the caregiver to the individual with ASD (Koegel

& Koegel, 1990; Dunlap, Dunlap, Koegel, & Koegel, 1991; Koegel, Koegel, Harrower, &

Carter, 1999; Koegel, Koegel, & Brookman, 2003). Ganz (2008), Loftin et al. (2005) and

Wilkenson (2012) add that when individuals are able to self-manage independently, they rely

less on prompts from others.

Habits

An initial Web search for the cognitive process behind self-monitoring reveals references

to the science of habit formation. Understanding how habits are formed can help us make better

sense of how the self-monitoring process works to change behavior.


Repetition and the habit loop. Self-monitoring plays a part in making and breaking

habits, as part of the habit loop (Duhigg, 2012). The habit loop describes the formula through

which our brain forms habits: cue, routine, and reward (Dean, 2013; Duhigg, 2012; Yoke, 2013).

In their research and writings about the habit loop, Duhigg (2012) and Dean (2013) heavily

reference the work of Ann Graybiel, Institute Professor of Neuroscience at Massachusetts

Institute of Technology (MIT). Through groundbreaking research on the neurobiological

processes that influence habit formation, Graybiel and her team confirmed that habits are formed

through repetition of behavior (Hutchison, 2008). Graybiel (2008) discovered that when the

brain repeatedly associates a cue with a reward, it encodes the action as an indelible habit in the

basal ganglia. The basal ganglia are the only place in the brain that deals with both cognitive and

physical actions. Disorders of the basal ganglia are commonly tied to motor disorders such as

Parkinson’s and Huntington’s disease (Sukel, 2007). Graybiel and her contemporaries propose

that the basal ganglia are also implicated in disorders of mood and thought, such as Tourette’s

syndrome, obsessive-compulsive disorder, attention deficit disorder, and autism spectrum

disorders (Sukel, 2007; Hutchison, 2008).

Habit formation and automaticity. Researchers agree that automaticity is key to

success when attempting to develop a new behavior or transform an undesirable behavior (Lally,

Van Jaarsveld, Potts, & Wardle, 2009; Gray, 2004; Graybiel, 2008; Wood & Neal, 2007; Dean,

2013). In a 1999 interview, Graybiel expressed that “no two brains have an identical response to

an identical stimulus. While it may take one person one week to develop a habit, good or bad, it

may take another person considerably more time” (MIT news, 1999, Responding to the Call

section, para. 2). Ten years later, Lally et al. (2009) published a study examining the amount of

time it takes people to reach automaticity. Lally et al. (2009) confirmed that the amount of time


to form a habitual behavior varies widely between individuals, and depends on the complexity of

the behavior.

Self-management for automaticity. Self-management interventions help to develop

automaticity through intentional repetition of the target behavior. The majority of the research

consulted recommends a five step self-monitoring program (Ganz, 2008; Hume et al., 2009;

Loftin et al., 2005; Koegel & Koegel, 1990). The National Professional Development Center on

Autism Spectrum Disorders identifies four steps for implementing a self-management system for

individuals with ASD (Busick & Neitzel, 2009). These four basic concepts are: identify a target

behavior, teach the learner how to self-observe and self-record, assist the learner to become an

independent self-recorder, and fade the self-monitoring system (Busick & Neitzel, 2009).

One of reasons self-monitoring works is because it helps the individual develop an

awareness of a target behavior. Awareness of the behavior is important for habit change, as

many habits are unconscious (Yoke, 2013). In a study by Legge, DeBar, & Alber-Morgan

(2010), researchers found that students with ASD showed immediate and sustained

improvements upon initiation of a self-management intervention. Multiple research studies

revealed that self-recording does not have to be accurate in order to be effective (Webber,

Schuermann, McCall, & Coleman, 1993; Legge et al., 2010; Mammolenti et al, 2002). However,

Lally et al. (2009) found that even with a self-management intervention, some individuals

require continued external prompts until the desired behavior becomes automatic. This

reinforces the words of Graybiel (1999), who reminds us that every individual is a unique

learner.


Touch technology for intervention

Legge et al. (2010) recommends that for individuals with ASD, teachers supply materials

that reinforce accurate self-monitoring. Apple’s iPad offers a variety of apps that can provide

additional cues and prompts to help students stay on track. Professor Rhonda McEwen (2010)

was the first academic researcher to examine the use of iPads to support students with ASD in

the classroom. Though the final report is not yet available, preliminary results of the study

indicate a positive correlation between the students’ use of the iPad and increased engagement

and time-on-task (McEwen, 2010). The results of McEwen’s study were echoed by Neely et al.

(2013) in their research regarding the iPad as an instructional method for students with

challenging behaviors related to ASD. The researchers found that with the introduction of the

iPad, for both participants, challenging behaviors decreased significantly and on-task behaviors

increased (Neely et al., 2013).

A recent action research study by Erin Rigo (2013) explores the viability of the iPad as a

video modeling device for self-monitoring for students with ASD. The intervention produced a

positive change in on-task behavior for all four participants (Rigo, 2013). Results were

consistent with prior research studies on the combination of self-monitoring and video modeling

(Rigo, 2013).

Prior Research

Past research has investigated self-management strategies and interventions for

individuals with ASD. The vast majority of the studies were single subject designs, with

consistent results. A well-researched and proven intervention, self-management is among the

National Autism Center’s eleven established treatments for ASD (National Autism Center,

2009). Likewise, there are multiple studies regarding habit formation. Over thirty years,


Graybiel and her team have performed groundbreaking research regarding the neurobiological

processes that influence habit formation. Graybiel’s research, while significant, involves a team

of researchers studying the cognitive processes of mice, rats, and monkeys. Research by Lally et

al. (2009) builds on Graybiel’s findings, but uses human subjects who track their own data using

a self-report habit index.

Limited research exists regarding the use of touch technology, such as the iPad, for self-

monitoring. This researcher was able to locate only one study that used the iPad as a tool for

self-monitoring. The study uses the iPad for self-monitoring combined with video modeling in a

classroom setting. Previous research has recognized technology as a potential tool for teaching

academic skills and functional behaviors to students with ASD. Based on the prior research

results, Neely et al. (2013) recommends future research identifying the effectiveness of the iPad

as an intervention in the home setting. As well, Hume et al. (2009) calls for the continued

development of strategies to promote independence for people with ASD.

Best Practices

According to the National Research Council (Lord & McGee, 2001), it is recommended

best practice to be actively working toward increasing independence for children with autism.

Educational objectives that can be addressed through this study include:

the development of independent behaviors and the replacement of problem behaviors

with socially appropriate behaviors (Lord & McGee, p. 218),

promoting the individual’s ability to “attend to the environment and respond to an

appropriate motivational system” (p. 218), and

the use of fine and gross motor skills for functional activities (p. 218), via the iPad’s

touch interface.


Summary

After a careful review of the research, this author has identified a present need to examine

the use of iPad apps for self-monitoring of target behaviors for individuals with ASD. Self-

monitoring is a proven, effective intervention for people with ASD because it has the potential to

improve target behaviors and reduce the occurrence of undesirable behaviors. Self-monitoring

encourages the development of automaticity through the repetition of positive behaviors. The

science of habit formation underscores the importance of repetition as a way to achieve

automaticity. Studies have shown the usefulness of self-monitoring tools such as data sheets,

video modeling, and picture prompts. However, there are very few extant studies regarding the

use of iOS devices for self-management.

Apple’s iPad technology offers an intuitive, accessible platform for self-monitoring

interventions. The large touch screen layout, multitude of education apps, portability, and

positive social connotation makes the iPad a desirable assistive device for people with ASD.

Moreover, the use of an iPad in the classroom has been shown to have a positive impact on

student motivation (Harmon, 2011), engagement and on-task behavior (McEwen, 2010; Neely et

al., 2013; Rigo, 2013) of students with and without special needs.

By integrating iPad technology into a self-monitoring program, persons with ASD will

have increased opportunities to self-record data across environments, thus promoting

generalization and automaticity through greater repetition. The resources reviewed will help

shape a research study that examines the effectiveness of iPad apps as a self-monitoring strategy

for people with ASD.


Chapter 3

Research Methodology

Overview of the Research Methodology

This researcher used action research to evaluate the effectiveness of using iPad apps for

self-monitoring independently identified target behaviors of people with ASD. Students and

their parents participated in four, two-hour instructional sessions, during which they received

focused training in the use of iPad apps for self-monitoring. The researcher used both

quantitative and qualitative data to answer the research question.

Research Question

The focus of the research involved the use of iPad apps by persons with ASD for self-

monitoring of independently identified target behaviors. The research question was: What effect

will using iPad apps for self-monitoring have on target behaviors for high functioning

individuals with autism spectrum disorders?

Hypotheses

The research hypothesis was: When an individual who is high functioning on the autism

spectrum uses an iPad app to self-monitor a self-selected target behavior for two weeks, the

target behavior will improve.

The related null hypothesis was: When an individual who is high functioning on the

autism spectrum uses an iPad app to self-monitor a self-selected target behavior for two weeks,

the target behavior will neither improve nor regress.

Research Design

For this action research study, both quantitative and qualitative data collection methods

were employed. A single subject A-B design was used to gather data regarding the effectiveness


of using an iPad app for self-monitoring of target behaviors. The independent variable was the

use of an iPad app for data tracking as part of a self-monitoring program. The dependent

variable was, for each participant, his or her self-selected target behavior. In an effort to explore

unquantifiable improvements, such as changes in student motivation, qualitative data augmented

the quantitative data. Likert-type attitude surveys (Appendix J, Appendix K) provided evidence

of each participant’s perceived ability and motivation to achieve a self-selected goal using the

iPad app. Additional qualitative data were garnered through group discussions that occurred

during instruction.

Participants

The learner group consisted of three parent-child teams (“participant teams”), each of

which consisted of one primary caregiver (“parent”) and his or her school-aged child with ASD

(“student”). Participant teams were recruited through an advertisement on a local parent support

group, and through a direct email campaign to clients of a local autism services provider. The

inclusion criteria for the families in this study were: (a) the student must be school-age or older;

(b) the student must have a diagnosis of PDD-NOS, Asperger Syndrome, or be considered high-

functioning on the autism spectrum; (c) the student must be cognitively able to choose and work

toward a functional behavior goal; and (d) the participant team must have full-time access to an

iPad. Canvassing resulted in inquiries from six families who met inclusion criteria and were

invited to participate in the study. Of those, three participant teams entered the study. All

participant teams who entered the study also completed the study.

The participant teams were of similar demographic background. All families were

Caucasian and lived in middle class suburban neighborhoods. All participating parents were

married and worked outside of the home. There were two female students and one male.


Participant one. “Student one” was an eight-year-old male who attended public school

in an inclusion setting. Either his mother or father, each of whom attended two sessions,

accompanied him at each session. The participant’s self-selected goal was to increase attention

during school-assigned at home reading activities. “Paying attention” was defined as: remaining

seated, following along in the book, reading the book aloud as required, and asking on-topic

questions when appropriate.

Participant two. “Student two” was a 16-year-old female who attended a parochial high

school in an inclusion setting after having attended a private therapeutic school for several years.

Her mother accompanied her for all four sessions. The participant’s self-selected goal was to

wait for a three-second pause in conversation before adding a verbal comment.

Participant three. “Student three” was a 12-year-old girl who was in her first year of

homeschooling after attending a private therapeutic school for several years. Her father

accompanied her for all four sessions. The participant’s self-selected goal was to increase active

play time with her assistance dog, which would promote bonding. “Active play time” was

defined as: the child and the dog mutually participating in an interactive recreational activity.

Permissions. The researcher was granted a capstone exception from Western Governors

University (WGU) to perform the study at LifeSkills-TouchPoint Autism Services, a local

support provider for families of people with developmental disabilities. The researcher is neither

employed by nor otherwise affiliated with LifeSkills-TouchPoint. Approval to conduct research

was obtained from the organization prior to the start of the study.

Families that confirmed their participation in the study received the Informed Consent

Form (Appendix M), as approved by WGU’s instructional review board and LifeSkills-

Touchpoint. Signed copies of the informed consent forms were submitted to the researcher prior


to instruction on the first day of the study. Because the student participants were under the age

of consent, their parents’ permissions were required. The researcher scanned the informed

consent documents into an electronic file and kept a paper copy on site during every session.

Evaluation Methods and Tools

Data collection was ongoing throughout a month-long series of mini-lectures. The group

met every Saturday for instruction. Between instructional sessions, parents and participants

collected data at home. Pre-intervention and post-intervention attitude surveys were

administered during the instructional sessions. Notes taken during group discussions provided

further qualitative data. Quantitative and qualitative data were considered together to form an

integrated analysis.

Quantitative data. Quantitative data primarily consisted of the participants’ self-

reported data. “Self-reported data” describes the performance data that participants reported

using an iPad app for self-monitoring. Data indicated simply whether the participant

successfully completed the self-selected task/goal for each attempt. For example, if the goal is to

sit with the family for a meal, the participant indicated for each family meal that yes, he or she

sat with the family for the entirely of the meal, or no, the participant did not sit with the family

for the entirety of the meal. Because each participant’s target behavior was unique, the

researcher approved the goal for appropriateness.

Baseline data were collected prior to the introduction of the iPad app. A paper behavior

chart (Appendix I) was provided to each parent at the first Saturday session for this purpose.

During the first session, the instructor guided the participant teams to select a functional behavior

goal. Instruction was given on how to use the baseline charts to track target behaviors. The

baseline charts were collected at the beginning of the second session.


Several iPad apps for self-monitoring were introduced in the course of instruction, along

with explicit instruction in how to use each app for self-monitoring of target behaviors.

Participant teams reviewed the apps and each student selected the one that they felt would work

for his or her goal and personal preferences. Two participants chose to use the 123TokenMe app

(2013), and one participant used the iRewardChart app (2009). Target behaviors were tracked

using the iPad apps for a total of three weeks. Data, in the form of screen captures or in-app

emails, were collected by the researcher weekly, and then transferred to a spreadsheet for

analysis.

Qualitative data. Attitude surveys, administered once before and once after the

intervention, provided qualitative data. The surveys consisted of ten Likert-type items divided

into two, five-item sets. The first set of items reflected each student’s attitude about his or her

readiness and motivation to achieve his or her self-selected goal. The second set of items

addressed the students’ attitudes about using an iPad for self-monitoring. For each item, the pre-

instruction and post-instruction responses were analyzed using a paired t-test and the statistical

means charted for visual inspection. Additional qualitative data were collected through group

discussions that occurred during the instruction.

Validity and reliability. Data were collected through a single subject A-B research

method. The nature of the study was to test the effects of a self-monitoring intervention

outside of the clinical setting. This meant that the researcher did not directly monitor or

observe data collection. To address and improve the reliability of the data, the researcher

extensively trained participant teams, including parents of participants, to observe and record

target behaviors using the approved data collection tools (baseline charts and iPad apps). To

increase the external validity of the data, the study looked at data provided by three individual


participants (self-observers), each tracking a different target behavior on one of two different

iPad apps, across multiple settings.

Baseline data chart. The validity of the baseline instrument was addressed through

two measures: the use of a uniform data chart, and the creation and use of a clearly stated

target behavior. The researcher designed a uniform baseline chart, which parents used to track

target behaviors for one week prior to the intervention. At the top of the baseline chart, the

participant team clearly stated their chosen target behavior. The researcher approved each

participant’s goal for appropriateness to the study, according to research-based guidelines for

goal selection. The reliability of the instrument was increased through specific training for

parents in how to take baseline data. Baseline data were collected over a period of one week,

with three data sessions per day.

The iPad apps. Because data sessions occurred outside of the instructional setting, the

validity and reliability of the implemented iPad apps was important. First, the use and function

of the iPad app was parallel to the use of the paper baseline chart for tracking behavioral data.

Reliability was further demonstrated as each participant used the same app for data collection

repeatedly. One advantage of using a digital app for data collection is that it functions in

exactly the same way, every time. Throughout the study, the app was accessible by the

participant across settings, regardless of the availability of an internet connection. The

selected apps recorded the time and date of every data entry, which bolstered the reliability of

the data. However, reliability of the apps as self-monitoring instruments was threatened

because, within each app, it was also possible to falsely report behavior. The iPad apps

showed criterion validity and face validity. The researcher first narrowed down a list of

available data tracking apps by testing the ability of each app to track each student’s target


behavior. Then, the participant teams were instructed to select an approved app based on their

personal preferences. The data collected using the iPad apps corresponded to the data from the

attitude survey.

Attitude survey. The attitude survey provided data to augment the quantitative data.

The survey consisted of ten Likert-type items, divided into two distinct areas of concern. The

Likert-type attitude scale is widely regarded by researchers as a reliable and valid instrument

for the measurement of attitude. The survey demonstrated test-retest reliability, as it was

administered before and after the intervention. The validity of the instrument was

demonstrated through face validity. Test items were designed by the researcher to reveal

information about the participants’ readiness for behavior change and their perceived

usefulness of the iPad for behavior intervention.

Field notes. The reliability of the field notes was maintained in that the researcher

recorded all notes and observations personally. Participant contributions to the discussion

during instruction were transcribed verbatim. The validity of the field notes and personal

reflections was not of concern.

Data integrity. The integrity of the data was maintained to the best of the researcher’s

ability. Although the goals and apps differed among the students, the self-monitoring program

and related instruction was consistent. The small group size allowed the researcher to work

one-on-one with each participant team to apply the instruction within the context of their

chosen goal and app. The researcher approved each participant’s goal for appropriateness to

the study, according to research-based guidelines for goal selection. The iPad apps also met

with specific criteria, including the ability for participants to capture or send recorded data to

the researcher.


Confidentiality of participants was preserved throughout this study. Participants were

assigned team numbers (one, two, and three) on the first day of instruction. All lesson

materials, attitude surveys, and field notes referred to the participant by his or her team

number. Because the participants used personal iPads for data collection, some of the

participants set up the apps using the initials of their first and last names. Data sets from the

iPad apps were sent from the participant’s personal email account to the researcher’s personal

email account. Personally-identifying features were removed, the data were transferred to a

spreadsheet, and the original files were destroyed after the study. All the data have been

presented as averages and cumulative responses.

Method Adoption

Subjects for this study were identified through convenience sampling. Though the

research site provided space for up to twelve individuals, only three participant teams (a total

of six people) elected to participate in the study. Eight hours of instruction took place over

four weeks. The participant group met every Saturday for two hours of instruction.

Instruction included PowerPoint presentations, interactive lesson activities, and group

discussions.

Instructional plan. The first Saturday, instruction focused on selecting a target

behavior and conducting a baseline. After a PowerPoint presentation on goal setting, the

participant teams used guided worksheets to select a target behavior and state their behavior

goal clearly. The researcher met with participant teams one-on-one to discuss, refine, and

approve the individuals’ goals for use in the study. After a break, the researcher taught parents

to collect baseline data. Parents practiced taking baseline data with each other, rather than

with their children, to preserve the authenticity of the baseline. During the week between the


first and second Saturday sessions, the parents collected baseline data daily, during three ten-

minute sessions.

The iPad apps for data collection were introduced on the second Saturday. Upon

entering the room, participant teams were asked to complete a pre-intervention attitude survey.

Parents assisted student participants with reading the survey, as appropriate. When the survey

had been collected, the instructor began a PowerPoint presentation on data collection.

Participant teams learned about the purpose of data collection and types of data collection

tools. After a break, the iPad apps were introduced. Although six apps were discussed,

explicit instruction focused on two iPad apps in particular: 123TokenMe and Healthy Habit

Tracker. The researcher selected the apps specifically for their potential alignment with the

participants’ goals. After instruction, participant teams were encouraged to explore the

different apps and choose one for their self-monitoring program. The researcher circled the

room to monitor app exploration, and met with each participant team to discuss the benefits

and drawbacks of each app, as the app pertained to each participant’s behavior goal. Each

participant set up his or her chosen app during the instructional session. The researcher

worked with the parents to demonstrate how the app would be used for collecting behavior

data specific to the participant’s goal. Participants also learned how to use the app to send data

reports electronically to the researcher. During the week between the second and third

Saturday sessions, the parents used the iPad app exclusively to collect data daily, during three

ten-minute sessions. Data summaries continued to be submitted to the researcher.

The third Saturday session was focused on self-management and fading. A PowerPoint

presentation discussed self-management programs, the definition of self-monitoring, and

benefits of self-monitoring programs. After the break, participant teams learned the


importance of fading parent involvement as part of a self-management intervention. Parents

received explicit instruction regarding the steps of fading their involvement in tracking data

using the iPad app, including a fading schedule. During the week between the third and fourth

Saturday sessions, the parents transferred the data tracking responsibility to the student

participant. By the fourth Saturday session, students independently used the iPad app to collect

data, during three ten-minute sessions. Parents maintained responsibility for submitting

weekly data summaries to the researcher.

The theme of the final Saturday session was achieving lasting success. Instruction

included a PowerPoint presentation that discussed when and how to fade the self-monitoring

program. After the presentation, the post-intervention attitude survey was administered to the

participants. Again, parents were permitted to help their children read the test items. Finally,

the researcher led the participant teams in a group discussion. Five questions were introduced

to stimulate the discussion. After the final instructional session, participants continued to take

data independently using the iPad app during daily ten-minute sessions. Data were submitted

to the researcher via email on the following Saturday.

Justification. The instructional sequence was guided by research-based steps for

designing a self-management plan for people with ASD, as recommended by Wilkenson

(2012), Loftin et al. (2005, p. 12), and the National Professional Development Center on

Autism Spectrum Disorders (Busick & Neitzel, 2009). Because children with ASD are not

predictably similar in all areas of functionality, the researcher had to prepare lessons that

would accommodate a variety of learning styles, sensory sensitivities, and learning challenges.

Thus, it was important to keep lesson activities brief enough to keep the student participants

engaged, while making sure the parents received the information necessary to implement a


self-monitoring program effectively. Lesson materials and iPad apps were thoughtfully

selected to accommodate individualized learning strategies and supports.

Differences. The methodological approach was implemented as planned, with only a

few differences. Discrepancies occurred in the number of data sessions and the amount of time

it took for parents to fade support.

The original plan assumed that each participant would complete three data sessions

daily throughout the length of the study. In reality, the participants were inconsistent with

their data sessions. This might have affected the outcome of the study. Although repetition

contributes to automaticity, multiple research studies indicate that self-recording improves

target behaviors, regardless of accuracy (Webber, Schuermann, McCall, & Coleman, 1993;

Legge et al., 2010; Mammolenti et al, 2002).

The original research plan called for two full weeks of independent data tracking. It

took two of the participants less than two days to achieve independence in self-monitoring

using the iPad app. One participant continued to receive parent support through the end of the

fading week. That same participant self-monitored independently in the final week of data

collection.

Finally, on the last day of the study, the researcher had hoped to garner responses to

discussion questions from both parents and students. Parents answered every question and

contributed actively to the discussion. Despite efforts by their parents and the researcher, the

student participants refused to answer questions or participate in the discussion.


Summary

The research examined the use of iPad apps for self-monitoring of target behaviors for

student with ASD. Common characteristics of ASD include atypical social and learning

behaviors. One effective method of increasing positive behaviors is self-monitoring. Self-

monitoring is typically implemented in classrooms or therapeutic settings. This study

incorporated the active use of existing iPad apps for self-monitoring of functional target

behaviors between settings. Because data collection took place outside of the clinical setting,

parents of the participants were taught to implement the steps of the self-monitoring program.

Data were collected using the iPad app for a total of three weeks. Data reports from the apps

were electronically transferred to the researcher weekly.

Due to the abbreviated length of the study and the characteristics of the participant group,

it was necessary to reflect on areas of improvement that cannot be quantified, such as changes in

the participants’ self-perceived likelihood of achieving a behavioral goal. Group discussions

during the instructional sessions provided further qualitative data. Together, quantitative and

qualitative data were considered to form an integrated analysis.


Chapter 4

Findings

Results Overview

The purpose of this research project was to learn the effectiveness of iPad apps for self-

monitoring of target behaviors for students with ASD. In this report, results are organized

according to quantitative and qualitative findings. Findings from the intervention and attitude

survey are presented visually in the form of line graphs. Together, the qualitative and

quantitative data offer evidence in support of the hypothesis.

Data Driven Findings Summary

Through systematic instruction, three participant teams were taught to use an iPad app as

part of a self-monitoring intervention. Behavior events were recorded for every week of the

study, including the baseline, and calculated as a mean. For all participants, there was a

significant upward trend from the baseline through week two of the intervention. Improvement

continued for two of the participants and regressed for one of the participants. Possible reasons

for the regression are presented in future sections of this report.

The Likert-type items on the attitude surveys were categorized into two areas of interest:

participant readiness for change, and perceived usefulness of iPad technology. Results of the

pre-intervention/post-intervention attitude surveys were analyzed statistically using a paired t-

test. For each item, the group mean of the pre-intervention response was compared to the group

mean of the post-intervention response. Although the number of participants was too small to

make the results of the survey valid for consideration as quantitative data, a simple comparison

of pretest-posttest scores reinforced the behavior data. Therefore, the results of the survey were

admitted as qualitative data.


Data Analysis

Quantitative data. For each participant, behavior data were recorded during daily data

sessions for each week of the study, including the baseline. For this particular study, each

participant was considered a single subject with unique behavior goals. Because the number of

data sessions was not consistent across subjects, the data were calculated by averaging the

number of times the target behavior occurred per session over the course of each week. Each

participant’s weekly average was expressed as a percentage.

In week one of the intervention, the parents were using the iPad app to monitor

behaviors. All participants experienced a significant increase in the expression of target

behaviors. For participant one, tracked behavior expressions improved 24 percentage points

from the baseline. The behavior events of participant three increased by 55 percentage points.

Participant two experienced a dramatic increase from a baseline of zero to her week one average

of 58%.

For all participants, the upswing continued through the second week of the intervention,

as parents faded involvement with monitoring and participants began self-recording

independently. Participant one was most improved in the second week of the intervention, with

an increase of 43 percentage points from the week one average. Participant two improved an

additional 17 percentage points from week one, while participant three progressed just eight

points.

The participants were self-monitoring independently by week three of the intervention.

Participants two and three continued to show a modest increase in behavior events (eight

percentage points and four percentage points, respectively). Participant one experienced a 33%

regression from his week two average, but maintained an improvement from his week one score.


By the end of the research study, the occurrence of target behaviors had improved

significantly from the baseline. Participant one ended the study with an increase of 34

percentage points, even after the regression from week one to week two. Participant two’s target

behaviors improved 83 percentage points from her baseline of zero. Behavior averages for

participant three showed a gain of 67 percentage points. Figure 1 presents the average

achievement of behavior goals per data session, beginning with the baseline, for each participant.

Figure 1. Achievement of behavior goals per data session. This line graph presents the

weekly average of target behavior occurrences per data session, expressed as a percentage,

during the baseline and intervention.

Baseline Week 1 Week 2 Week 3

Participant one 0.33 0.57 1 0.67

Participant two 0 0.58 0.75 0.83

Participant three 0.22 0.77 0.85 0.89

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Wee

kly

Aver

age

Achievement of Behavior Goals Per Data Session


Qualitative data. An attitude survey with ten Likert-type items was administered before

and after the intervention. Each student participant completed a pre-intervention and post-

intervention survey, totaling three paired sets. Individual responses were given a score of two

(strongly agree) to negative two (strongly disagree), and the group mean calculated for each

item. Pretest and posttest differences became obvious when displayed as line graphs. Responses

from the group interview conducted on the last day of instruction are presented as a table.

Perceived potential for behavior change. Five of the ten items assessed the

participants’ self-perceived readiness and potential to improve the chosen target behavior.

Pre-intervention survey items. For the pre-intervention measure, the five statements (S)

were:

1. The goal is important to me.

2. Meeting this goal means changing my behavior.

3. I am ready to change my behavior.

4. I will be rewarded for meeting my goal.

5. I will be successful in meeting my goal.

Post-intervention survey items. For the post-intervention measure, the five

corresponding statements were:

1. The goal is important to me.

2. I successfully changed my behavior to meet my goal.

3. I willingly changed my behavior to meet my goal.

4. I feel rewarded for making progress toward my goal.

5. I was/will be successful in meeting my goal.


For statements one, three, four, and five, mean scores improved from pre-

intervention to post-intervention. Statement five, which indicated the respondent’s

confidence in his or her ability to be successful in meeting the behavior goal, showed the

greatest increase. The mean post-intervention score for statement five was 1.0, compared

to a pre-intervention score of 0.33. Statement two was the only statement to regress from

pre-intervention to post-intervention, dropping from a group mean of 1.33 pre-instruction

to 1.0 post-instruction. Figure 2 presents the results of attitude survey for perceived

potential for behavior change.

Figure 2. Perceived potential for behavior change. This line graph presents the pre-

intervention to post-intervention difference in the participants' self-perceived potential to achieve

behavior change through participation in the intervention. Individual survey items are expressed

as S1, S2, S3, S4, and S5.

Pre-intervention Post-intervention

S1 1.33 1.66

S2 1.33 1

S3 0.66 1

S4 1 1.33

S5 0.33 1

0

0.3

0.6

0.9

1.2

1.5

1.8

2.1

Gro

up M

ean

Perceived Potential for Behavior Change


Perceived usefulness of iPad technology. The second half of the attitude survey

assessed the participants’ attitudes about iPad technology and its usefulness as a tool for behavior

intervention.

Pre-intervention survey items. For the pre-intervention measure, the five statements

were:

1. I am comfortable using an iPad by myself.

2. I enjoy using an iPad for entertainment.

3. I enjoy using an iPad for schoolwork.

4. Using an iPad app can help me change my behavior.

5. Using an iPad app will help me meet my goal.

Post-intervention survey items. For the post-intervention measure, the five

corresponding statements were:

1. I am comfortable using an iPad by myself.

2. I enjoy using an iPad for entertainment.

3. I enjoy using an iPad for schoolwork.

4. Using an iPad app can help me change my behavior.

5. Using an iPad app helped me make progress toward my goal.

Statements one, two and three established the students’ existing use of the iPad.

Statements one and two received the highest possible mean score; all participants strongly agreed

that they were comfortable using an iPad independently and that they enjoyed using the iPad for

entertainment. There was no pre-post intervention difference in the responses to items one and

two. Students agreed less strongly with statement three: enjoyment of using an iPad for


schoolwork. The mean scores for statement three, four and five increased from pre-intervention

to post-intervention. Statement four showed the greatest improvement, indicating the

respondent’s confidence in the use of an iPad app to help change his or her behavior. The mean

pre-intervention score for statement four was 0.33, which rose to a post-intervention score of

1.33. Figure 3 presents the results of attitude survey for perceived usefulness of iPad technology

for intervention.

Figure 3. Perceived usefulness of iPad technology for intervention. This line graph

presents the pre-intervention to post-intervention difference in the participants' perceived

usefulness of iPad technology as a tool for the self-monitoring intervention.

Pre-intervention Post-intervention

S1 2 2

S2 2 2

S3 1 1.33

S4 0.33 1.33

S5 0.66 1

0

0.3

0.6

0.9

1.2

1.5

1.8

2.1

Gro

up M

ean

Perceived Usefulness of iPad Technology for Intervention


Discussion questions. On the last day of instruction, the researcher presented five

questions (Appendix L) to stimulate a reflective discussion about the participants’ experience

using iPad technology for self-monitoring of target behaviors. Data from the group discussion

was garnered solely from parent responses. All parents replied to every question. Some parents

gave multiple responses for some questions.

Responses to the group discussion questions represent the opinions and speculations of

the parents involved in the research study. Therefore, this researcher considers that any data

garnered from the group discussion are inconclusive for the purpose of this study. A summary of

the questions and responses follows.

Question one. Participants were asked how using an app for self-monitoring helped each

student achieve his or her behavior goal. Two parents suggested that self-monitoring increased

their child’s awareness of the behavior. Two parents stated that the student enjoyed using the

app, which increased task initiation. All three parents agreed that the students found the in-app

token system rewarding, which increased time on task.

Question two. The researcher prompted participants to describe the most challenging part

of using the iPad app for self-monitoring. Two parents said that awarding tokens distracted from

the students’ on-task behaviors. One parent reported that the in-app timer created a definite end

point for the participant, at which point the student ceased engaging in the target behavior. The

parent believed that, without the interruption, the student might have continued performing the

behavior. Another parent observed that during the first and second week of the intervention, the

student sometimes closed the self-monitoring app before the data session was over in order to

access an entertainment app or game.


Question three. Through the course of instruction, the researcher learned that all of the

participants had tried other self-management strategies prior to the study. Question three asked

participants to compare the use of the iPad app for self-monitoring to other self-monitoring tools

with which they had experience. All of the parents stated that they liked that the iPad app they

used in the study created a weekly data summary that could be emailed to therapists or teachers.

All parents liked that the apps were simple to individualize based on student preference for color,

token and sound effects. Two parents expressed that their children felt rewarded by the in-app

tokens and award shows, which eliminated the necessity of tangible or edible rewards. Two

parents appreciated that, unlike other self-reporting tools, the iPad is portable and the apps can be

accessed across settings.

Question four. This question asked participants whether they would be likely to use an

iPad app for self-monitoring again with a different goal. Two parents replied that yes, they

would use the app again for a different goal. The same two parents elaborated that they would

continue to use the app for the current goal, until the target behavior is stable. One parent stated

that although his student would not continue using the app to track this particular target behavior,

the student did benefit from the use of the app and the parent would likely employ the iPad app

(or one like it) to track a different behavior.

Question five. Participants were invited to share any pertinent information not addressed

by the prior questions. Parents unanimously stated that a visual chart showing progress over

time would be motivating for the student. The apps used by the parents did not feature a graph

or chart option to show progress. Two of the parents reported an improvement in the target

behavior outside of data sessions.


Answers to the Research Questions

The research question was: What effect will using iPad apps for self-monitoring have on

target behaviors for high functioning individuals with autism spectrum disorder? The findings

support the research hypothesis that when an individual who is high functioning on the autism

spectrum uses an iPad app to self-monitor a self-selected target behavior for two weeks, the

target behavior will improve. This was demonstrated through an examination of the average

achievement of target behaviors from the baseline through week three of the implemented

intervention. Overall, every participant’s target behavior showed significant improvement over

two weeks of independent self-monitoring. Even for the participant who regressed, the end

result was that the target behavior had increased from the baseline by 34 percentage points. The

qualitative data supported the quantitative data. Results of the pre-intervention/post-intervention

attitude surveys showed an improvement in the participants’ perceived usefulness of the iPad app

as a behavior intervention. As well, parents were generally supportive of the iPad app as part of

a self-monitoring program.

Findings Summary

Based on analysis of the data, the iPad app is an effective tool for self-monitoring of

target behaviors for students with ASD. The quantitative findings showed immediate,

measurable improvement from the baseline to the first week of the intervention. Improvement

continued overall, resulting in significant improvements in the participants’ target behaviors

from the baseline to the end of the study. The quantitative findings supported a study by Legge

et al. (2010), who found that the initiation of a self-management intervention for students with

ASD resulted in the immediate and sustained improvement of target behaviors. A qualitative

examination of the pre-/post-intervention attitude surveys showed an upswing in participant


attitude and confidence in the use of an iPad app to effect behavior change as part of the self-

monitoring program. Together, the quantitative and qualitative findings provide clear evidence

supporting the use of an iPad app for self-monitoring of target behaviors as part of a self-

management program.


Chapter 5

Discussion and Conclusion

Overview

The instructional unit (Appendix A) was designed to provide instruction in the use of

iPad technology as part of a self-monitoring program to improve independently identified target

behaviors for people with ASD. The overall goal of instruction was for people with ASD to gain

independence through self-monitoring using iPad technology. Three school-age students with

ASD participated in the study. One parent accompanied each participant. Participant teams

attended two-hour instructional sessions for four consecutive Saturdays. The instructor provided

eight hours of instruction in self-monitoring, incorporating the use of an iPad app as a tool to

self-record behavior. Given instruction from the teacher-researcher, parents recorded baseline

data and oversaw the implementation of the self-monitoring program in the home setting

between Saturday sessions. Students self-monitored their chosen target behaviors for the last

two weeks of the study.

Problem Solutions

The problem is that people with ASD typically have difficulty becoming independent.

Self-monitoring is an evidence-based strategy that promotes independence in students who are

considered high functioning on the autism spectrum. For individuals with ASD, characteristic

impairments in executive functioning affect the ability to generalize learned skills between

settings. As a mobile technology with a variety of apps for data tracking, the iPad holds promise

as a tool for self-monitoring across settings. The solution to the problem is helping people with

autism become more independent through self-monitoring using apps on the iPad. This study

explored the effectiveness of iPad apps as a tool for self-monitoring behaviors in the home


setting. The instruction sustained the research by explicitly teaching participants and their

parents to implement a self-monitoring program at home.

Results suggest that the instruction was effective in teaching parents and participants to

implement the self-monitoring program at home. Participants and parents moved through the

steps of the self-monitoring program and provided weekly data summaries to the researcher via

email. Upon analysis, the researcher noted that changes in the participants’ data from week to

week followed a predictable curve were consistent with the findings of other studies of self-

monitoring interventions for students with autism (Legge et al., 2010; Mammolenti et al., 2002;

Ganz, 2008; Loftin et al., 2005; Hume et al., 2009; Dunlap et al., 1991). As in the prior studies

reviewed by this researcher, the introduction of the intervention corresponded with a surge in

positive behavior for all participants. Also similar to the results of prior studies, improvement

continued at a lesser rate as parents faded involvement and students began self-monitoring

independently. Although one participant did regress slightly from week two to week three of the

study, this researcher believes that other variables, such as the Thanksgiving holiday, may

affected the student’s performance in that week. Ultimately, the data from all three participants

demonstrated the effectiveness of the self-monitoring program. The fact that the data followed

an established pattern for self-monitoring interventions suggests that the iPad technology was an

effective and appropriate self-monitoring tool. The results of the study are in agreement with the

research hypothesis, which states that when students who are high functioning on the autism

spectrum use an iPad app for self-monitoring of self-selected behaviors for two weeks, the target

behaviors will improve.


Strengths

A major strength of this action research project is the within-subject design. This

approach provides empirical evidence that a behavior change occurred as a response to the

intervention. Significance is established through replication of the results across subjects. Due

to the specialized nature of the study, the participant group was small. Single-subject designs are

used extensively in clinical settings for examining the effectiveness of interventions for one to

three subjects.

Data from single-subject designs are typically presented in line graphs as a continuum,

which allows the researcher to detect individual differences in the subjects’ response to the

intervention. In respect to this study, the researcher observed that the line graphs, which

represent data points over time, appear visually similar to the line graphs from similar studies.

This observation increased the researcher’s confidence in the effectiveness of the intervention.

Another strength of the project is the instruction. The instruction incorporated the basic

steps of existing evidence-based self-management programs for people with ASD (Ganz, 2008;

Hume et al., 2009; Loftin et al., 2005; Koegel & Koegel, 1990; Busick & Neitzel, 2009). These

steps are: identify a target behavior, teach the learner how to self-observe and self-record, assist

the learner to become an independent self-recorder, and fade the self-monitoring system (Busick

& Neitzel, 2009).

Parent participation is a unique aspect of the intervention. Prior studies suggest the

effectiveness of parents as capable intervention providers (Nefdt, Koegel, Singer, & Gerber,

2010). It was necessary to train parents to implement the self-monitoring program because the

bulk of the data collection occurred outside of the clinical environment and away from the

researcher. Given explicit training in the steps of the self-monitoring program and the use of the


iPad app, the parents provided support to the students throughout the intervention and supplied a

level of interobserver reliability to the students’ self-monitoring efforts.

Weaknesses

Although the single-subject design is considered a strength of the project, it is also a

weakness. The A-B design in particular is criticized as a less-than-ideal method to isolate the

cause of change. Results of A-B designs cannot usually be generalized from single subjects to

groups of individuals because it is possible that changes in behavior are not related to the

intervention.

Another weakness of this study is the baseline. In single-subject research, the baseline

must be reliable. The reliability of the baseline data for this study can be argued. The baseline

data were taken by the parents in the absence of the researcher. Although the parents were

specifically trained by the researcher to be objective observers of the target behavior, the

researcher must consider the possibility that the parents did not conduct the baseline

authentically. In hindsight, this researcher recommends that at least two impartial observers

conduct the baseline.

Problems and Factors

Perhaps the greatest obstacle encountered was finding a cooperating research site and

participants for the study. Because this researcher was not employed at the time of the study,

significant time was spent seeking a research site to host the study and, once obtained,

independently canvassing for participants.

The research study was conducted within the constraints given by the cooperating site,

which limited the length and dates of the study. Hence, the last week of data collection

coincided with the Thanksgiving holiday. This added a new variable to the data period. It is


known that young children with ASD are typically sensitive to changes in routine, such as

holidays and time off school. It is plausible, then, that the change in routine as a result of the

Thanksgiving holiday caused a regression in behavior of the youngest participant in the study,

whose behavior goal was to increase time-on-task for school-assigned reading homework. In an

ideal study, the intervention period would not include a major holiday.

The ages of participants ranged from age eight to age sixteen. While people with autism

are functional at differing levels across a variety of characteristics, older students often have the

benefit of maturity and years of intervention. The two older participants had a history of

receiving academic and behavioral interventions at a private therapeutic school for students with

ASD. The youngest participant had a more recent diagnosis; his family was just beginning to

research therapeutic interventions. As a result, the youngest participant required a greater level

of parent support than did the two older participants. This may have affected the data and

outcomes.

Implications

Given the results of the study, it can be inferred that an iPad app is an effective tool for

self-recording of target behaviors as part of a self-management program for students with ASD.

This research project incorporates unique approaches to behavior intervention for students with

ASD. The results provide evidence supporting the capacity of parents, given training, to act as

interventionists. The findings support the notion that committing to change as part of a group,

such as the participant teams, improves the odds of success (Yoke, 2013). Furthermore, the

research study demonstrated that, through self-monitoring, functional behaviors can be improved

outside of the classroom or therapeutic setting.


Limitations

The research project was limited by the length of the study, the size and characteristics of

the participant group, and the nature of the intervention. The researcher was required, for a

number of reasons, to conclude the study after four Saturdays and four weeks of data collection.

As a result, the researcher was forced to form conclusions based on limited data. Without a

maintenance phase, the researcher cannot determine whether the iPad intervention effects lasting

success. The criteria required for participation in the study narrowed the field of potential

subjects. Of those who qualified and were interested in the study, only three families were

willing to participate in the study. With a participant group of three, one cannot assume that the

results of the study will generalize to a larger population. The study would need to be conducted

on a larger scale to produce significant data. The results of the study were limited by the choice

of iPad apps for intervention. Of the iPad apps presented, only two were used by the participants

to take data. In order to test the effectiveness of iPad apps for self-monitoring, a greater variety

of apps must be tested.

Recommendations

Improvement. If the researcher were to redesign the action research study, she would

begin by changing the research method and the research hypothesis. To test whether the use of

an iPad app for self-monitoring is an effective behavior intervention, one must determine the

effectiveness of the self-monitoring program without the use of iPad technology. The current

research design cannot confirm that the reported improvement in participants’ target behaviors is

attributable to the introduction of the iPad app as a self-monitoring tool. It is possible that the

participants’ behaviors would have improved with any self-monitoring intervention. The


researcher would also redesign qualitative measures, such as the attitude surveys and discussion

questions, to better correspond with the new hypothesis.

A larger number of participants are necessary to provide substantial proof of the research

hypothesis. However, due to the unique social and learning challenges of people with ASD,

participant groups need to be small. For participants with ASD, more than six or eight people in

a room can be overwhelming and impede instruction. People with ASD often have difficulty

with new routines and transitions, which can discourage participants from attending Saturday

morning classes. In order to accommodate the needs of the demographic and increase the

likelihood of participation, this researcher suggests that the same instruction be offered on

multiple days, at different times of the day, with no more than four participant teams attending

each session.

Further investigation. A review of the literature suggested potential areas of study for

researchers who are interested in the connection between ASD, habit formation, and self-

monitoring. It is well documented that many individuals with ASD have a propensity for

pattern recognition (Eveleth, 2011). It is known that repetition is vital to encoding behaviors

because the brain learns by recognizing patterns. Graybiel (2008) found that the basal ganglia

encode behaviors in the brain. Following this train of thought, future research could be

conducted to explore the relationship between enhanced pattern recognition in people with

ASD, and encoding within the basal ganglia. For example, one such research question might

be, “Do people with ASD encode repeated behaviors more readily than neurotypical

individuals?”

As mentioned previously, although the current study supports the existing hypothesis,

more research is needed regarding the effectiveness of iPad technology as part of a self-


monitoring intervention. Research is needed to determine the long-term effects of self-

monitoring using the iPad. Future research efforts might explore the pivotal behaviors that

result from the use of iPad technology for self-monitoring. Other research might include a

comparison between self-monitoring interventions with and without the use of iPad

technology, an exploration of the most effective use of iPad technology as part of a self-

management intervention, or the development of a self-directed learning program to provide

training in self-monitoring using the iPad for parents and adults with ASD.

In the process of research and instruction, it became evident that the currently available

iPad apps for data tracking are not ideal for self-monitoring. The researcher found that the

existing apps fell short in ways that affected the validity, reliability, or integrity of the data.

This research project could encourage the research and development of iPad apps that meet the

needs of a self-monitoring program. On a larger scale, the research might instigate the

development of a dedicated iPad app that is part of a related self-management program.

Implementation

This research study provides evidence for the implementation of iPad apps for self-

monitoring across settings. Potentially, teachers and parents of children with ASD can work

cooperatively to teach students to use iPad technology as part of a self-management program that

moves from school to home. Self-monitoring is regarded as an effective intervention for

academic behaviors within a therapeutic setting (Wilkenson, 2012). The results of the study

indicate that by incorporating the use of iPad apps into a self-monitoring program, students may

be able to improve functional academic behaviors, such as homework completion, outside of the

classroom.


The results of the study may prompt board members and administrators to consider bring

your own technology/device (BYOT/D) policies for their schools. Since Apple’s introduction of

the iPad in 2010, its use in the classroom has been a hot topic for educators and district policy-

makers. The advantages of mobile technology in the classroom are well documented. However,

the costs associated with implementing a school wide one-to-one iPad program can be

prohibitive. BYOT/D programs allow teachers and students to benefit from the use of iPad

technology at a reduced expenditure to the district. Network security is another concern

regarding the use of personal technology devices in schools. Teachers of students with ASD

who wish to advocate for the use of personal iPads as part of a self-monitoring program can

highlight the fact that the apps used in this study do not require a network connection.


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Appendix A

Instructional Unit

Session 1: Establishing a Goal & Conducting a Baseline

Lesson Overview: Participant teams will set a behavior goal and learn to conduct a baseline.

Resources or Materials Needed:

Goal-setting worksheets one and two (Appendix F & G)

Index cards

Session one PPT presentation (Appendix B)

Projector

PPT outlines (1 per participant team)

Paper baseline charts (4-6 per parent) (Appendix I)

Lesson Objectives:

1. Given specific instruction in goal-setting, the participant team will clearly state a target

behavior for the purpose of a self-monitoring intervention.

2. Given specific instruction in collecting baseline data, the parent will collect one week of

baseline data for the frequency of the defined target behavior performed by the student in ten-

minute data sessions.

Time to Complete: Two hours

Step 1: Greeting and Introduction

a) Introduce yourself and reiterate the expectations of the participants. Verify that each

participant has signed and submitted an Informed Consent Form.


b) Inform participants that the intent of this program is to teach parents and students to use an

iPad app to help improve or reduce the occurrence of a specific behavior.

c) Ice-breaker activity: Ask participants to introduce themselves by stating their name and

what prompted them to participate in the workshop. (Students may prefer to state a

hobby, favorite book or area of interest.)

d) Assign team numbers. Explain that in order to maintain anonymity of materials used in

the study, each team will use participant team numbers instead of names on all materials.

Step 2: Pre-Instructional Activities

a) Tell the participants and caregivers that before we can learn how to achieve a goal, we

must determine the goal. During first part of this session, each the participant team will

set an individual goal, or target behavior, that the student we hopes to improve upon over

the next 4 weeks. During the second part of the session, learners will learn to conduct a

baseline.

b) Hand out Goal-Setting Worksheet one (one per team). Read each item of the worksheet

aloud and provide clarification as necessary. Allow parents and participants 15 to 20

minutes to complete the worksheet. Collect the worksheet.

Step 3: Content Presentation: Goal-Setting

a) Lecture and PowerPoint presentation. Each participant team will have an outline of the

PowerPoint slides with room for notes. The presentation will discuss the value of goal-

setting, the qualities of a “good” goal, defining the target behavior, and observable vs. not

observable behaviors.

Step 4: Group Practice


a) The learners will watch animated gifs and discuss what the subject is doing. Through this

exercise, the learners will practice distinguishing between observable and non-observable

behavior.

b) The learners will categorize common verbs into one of three categories: Not Observable,

Directly Observable, or Needs Clarification.

Directly observable: draw, press a lever, point to, walk, underline, write, lift,

say, chew, blink, kick, bark, hold

Not observable: conclude, feel, want, think, concentrate, appreciate, wonder,

analyze, solve, learn, understand, know, like, dislike

Requires clarification: play, give, finish, see, demonstrate, find, subtract, make,

read, perform, complete, identify, borrow, change

BREAK (5 minutes) - During the break, the instructor will review the participant teams’

completed Goal Setting Worksheets from the first part of the session. The instructor should

use this information to check for understanding and guide participants as they write target

behaviors in the second half of the session.

Step 5: Independent Practice

a) Hand back Goal-Setting Worksheet 1. Tell participant teams that they will use Goal-

Setting Worksheet 1, along with the information presented in the lecture, to refine and

select the participant’s target goal.

b) Hand out Goal-Setting Worksheet two (one per team). Read each item of the worksheet

aloud and provide clarification as necessary. Allow parents and participants 15 to 20

minutes to complete the worksheet.


c) As each participant team selects a behavior goal, review it with them for appropriateness

to the study. Discuss what the behavior will and will not look like.

d) When the participant teams are able to define the target behavior with enough clarity that

an actor could perform the target behavior accurately, direct the participant to write the

target behavior on an index card for personal reference. The instructor will make a

separate record of the target behavior.

Step 6: Content Presentation: Conducting a Baseline


PowerPoint slides with room for notes. The presentation will discuss the definition and

purpose of baseline data, data collection tools, the importance of objectivity, and types of

data.

Step 7: Learner practice and participation

a) Hand out paper data charts (several per team). Demonstrate how to use the paper data

chart to take baseline data. Suggest fictional scenarios to demonstrate collection of

various types of data while maintaining participant privacy.

b) Through role play, learners will rehearse baseline data collection. Ask a volunteer to

perform simple act, such as touching his or her own nose. For the purpose of the practice

baseline, this will be the target behavior. Ask the volunteer to randomly perform the

behavior in over the course of a timed, two-minute conversation. Record each time the

participant performs the behavior. Ask learners to take turns role-playing with a peer

using fictional behaviors (i.e., pat your own head, pick up a plastic duck, say the word


“orange”, etc.). Students should pair with other students; parents pair with other parents.

This way, no one is rehearsing their own target behavior.

c) While the learners are role-playing, go around to each parent and discuss what his or her

individual baseline data collection plan will look like.

Step 8: Assignment and Closing

a) Tell the parents/caregivers that this week they will be taking the baseline of their

participant’s target behavior. Instruct the student participants to continue on with “life as

usual”. Ask them to make no changes to their routine for the coming week. Remind

caregivers to be objective observers. Make sure the parents/caregivers have enough

paper data charts for the week!

b) Invite the group to ask any questions. Remind them of the time and location of the next

class. Remind the participants that next week they will need to bring their iPads and the

baseline data.

Session 2: Using iPad Apps for Data Collection

Lesson Overview: Participants will select iPad apps for data tracking and learn how to use the

apps to record behavior events.


Attitude surveys (Appendix J)

iPads with Wi-Fi connection enabled

Access to a wireless internet connection for all participants

Session two PPT presentation (Appendix C)



Lesson Objective: Given specific instruction in the use of two or more iPad apps for self-

monitoring, the learner will select an appropriate app for self-recording the behavior events

during the study.


Step 1: Welcome and Attitude Survey

a) Greet parents quietly. Hand an attitude survey to each student as he or she enters the

room. Allow students 5-10 minutes to complete the survey. Parents may help with

reading, as necessary.

b) Collect the attitude surveys from the students and the baseline data sheets from the

parents.

c) Welcome the learners back. Engage in a brief discussion of the parents’ experiences and

reflections regarding taking the baseline data.


a) Tell participants that during this session, we will explore some different iPad apps for data

tracking, and learn how to track behavior events using the apps.

b) Check to make sure every team has brought an iPad, and that each iPad can connect to the

wireless internet connection.

c) Engage the learners in a brief discussion about data tracking. Is anyone familiar with

tracking behavior data? Allow participants to elaborate on their experiences.

Step 3: Content Presentation: Data Collection



PowerPoint slides with room for notes. The presentation will discuss the definition of

data, a discussion of different types of data (frequency, duration, intensity, and latency),

various types of data tracking tools, and the characteristics of good observers.

BREAK (5 minutes)

Step 4: Content Presentation: Introduction to iPad Apps

a) Lecture and PowerPoint presentation. The instructor will present six different iPad apps

that can be used for self-monitoring. Pros and cons of each app will be discussed.

Step 5: Content Presentation: Using an iPad App to Track Behaviors

a) Lecture and PowerPoint presentation. Introduce: “Most apps for data collection are

similar in the way they function. For our purposes, I will demonstrate two that I think

work well for the purposes of this group: 123 Token Me (a free app) and Healthy Habit

Tracker ($1.99).”

b) The instructor will model the use of both apps, including set-up, a demonstration of data

collection , and the electronic transfer of weekly data summaries to the researcher.

Step 6: Learner participation

a) Together, parents and students will explore the data collection apps. Invite the parents to

explore other apps available in the app store.

b) Discuss the criteria the researcher used to select the apps for the PowerPoint presentation.

This will promote understanding and provide guidance for participants who choose to

explore other available apps.

c) Encourage participants to choose apps that are visually appealing and easy to navigate.


d) As learners begin to choose apps, talk with each team individually about their choice.

Make sure the app is appropriate for the behavior goal.

e) During the instructional session, the parent and participant must set up their chosen app

and demonstrate to the instructor that they know how to use the app for the purpose of

tracking behavior data specific to the student’s goal.


a) Tell the parents that this week they will be responsible for taking data using the app.

Students will learn to self-monitor in Session 3. Remind participant teams to do three

data sessions every day.

b) Invite the group to ask any questions. Remind parents to save all data and send data

summaries to the researcher.

Session 3: Becoming an Independent Data Tracker

Lesson Overview: Parents will learn how to fade participation from the self-monitoring

intervention. Students will learn how to self-monitor independently.


Session three PPT presentation (Appendix D)


Projector

Fading reference sheet (Appendix H)

Lesson Objective: Given specific instruction in fading, the parent will use the steps of fading to

transfer the responsibility of data collection to the student within 12 data sessions.



Step 1: Greeting

a) Welcome participant teams back. Invite questions, comments, and concerns about data

collection using the chosen iPad apps.

b) Make sure that all parents have submitted a data summary for the week.


a) Tell participants that during this session, parents will learn how to transfer the

responsibility of data collection to the student through a process called “fading”.

b) Engage the learners in a brief discussion about what they suppose fading might be. Allow

participants to elaborate on their thoughts and experiences.

Step 3: Content Presentation: Self-monitoring

Lecture and PowerPoint presentation. Each participant team will have an outline of the

PowerPoint slides with room for notes. The presentation will incorporate an introduction

to self-management, the relevance of self-management programs for people with ASD,

and a discussion about how iPad technology can support self-monitoring efforts.

BREAK (5 minutes)

Step 4: Content Presentation: Fading

a) Lecture and PowerPoint presentation. The instructor will introduce fading. Topics will

include a definition of fading, how fading is used in Applied Behavior Analysis (with

which the participants are already familiar), and a discussion of how fading is employed

as part of a self-monitoring intervention. The presentation describes the systematic

procedure for fading parent involvement from the self-monitoring intervention.


Step 5: Learner participation

a) Hand out the Fading Reference Sheet to every parent. The sheet is just a reference for the

steps discussed in the PowerPoint presentation.

b) Ask for a parent volunteer for role play. The parent will play the part of the student, and

the instructor will play the part of the parent. Ask the parent to assume a fictitious target

behavior for the purpose of the activity. Demonstrate the steps of the fading process as

outlined on the fading reference sheet.

c) Have parents role play with each other until they are comfortable with the steps of fading.


a) Tell the parents that by the middle of this week, students should be self-monitoring

independently. Remind participant teams to do three data sessions every day.

b) Invite the group to ask any questions. Remind parents to save all data and send data

summaries to the researcher.

Session 4: Achieving Lasting Success

Lesson Overview: Participants will learn when and how to fade the self-monitoring program.

The session ends with a group discussion reflecting on the participants’ experiences and

impressions of the intervention.


Post-intervention attitude survey (Appendix K)

Session 4 PPT presentation (Appendix E)


Projector


Lesson Objective: Given specific instruction in the use of iPad technology for self-monitoring,

the student will demonstrate the development of independent behaviors by self-monitoring

during ten-minute data sessions daily for a period of two weeks.


Step 1: Greeting

a) Welcome participant teams back. Invite questions, comments, and concerns about data

collection using the chosen iPad apps.

b) Make sure that all parents have submitted a data summary for the week.


a) Prompt participants to recall a time when they have worked to develop a healthy habit or

break an undesirable one. Permit the group to briefly share and discuss.

b) Suggest that sometimes people return to undesirable habits and behaviors. Discuss

plausible situations like stopping an exercise program in midwinter, breaking a diet during

the holiday season, etc.

c) Say, “Today we will discuss what success looks like. In other words, how do you know

that you have achieved a goal? We will also talk about how to fade the self-monitoring

plan. Finally, I will ask you to share your feedback about data tracking using the iPad.”

Step 3: Content Presentation: Defining “Success”

Lecture and PowerPoint presentation. Each participant team will have an outline of the

PowerPoint slides with room for notes. The presentation will include the definitions of

success and automaticity, what constitutes a successful behavior intervention, and a

discussion of habit formation. Finally, the instructor will present the systematic process of


fading the self-monitoring program.

BREAK (5 minutes)

Step 4: Post-intervention Attitude Survey

As he or she enters the room after the break, hand an attitude survey to each student.

Allow students 5-10 minutes to complete the survey. Parents may help with reading, as

necessary. Collect the attitude surveys from the students upon completion.

Step 5: Group discussion

a) Introduce a discussion of the participants’ reflections regarding the workshop, the self-

monitoring process, the use of iPad technology, their own perceived successes and

challenges, etc.

b) A list of discussion questions is included at the end of the PowerPoint presentation for

Session 4. Use these questions to inspire discussion. Encourage students to participate.

c) Allow the natural flow of discussion to develop into conversations, observations, and

inquiries. Record answers to the posted discussion questions verbatim.


a) By now, the participants should be conducting data sessions independently. This week,

participants should continue taking data regarding the target behavior.

b) Ask the participants to email a final data report on Saturday, November 30.

c) Thank the participants for taking the time to come to participate in the workshop. Remind

the participants that they may ask for a copy of their data and the final report at any time.

d) Be sure each participant has the instructor’s email and contact phone number.


Appendix B

PowerPoint Presentation: Session1











Appendix C

PowerPoint Presentation: Session 2


































Appendix D













Appendix E








Appendix F

Goal-Setting Worksheet #1

Generate a list of three or 4 behaviors or characteristics for each of the following:

1. Typical behaviors and characteristics of the participant:

2. Atypical behaviors and characteristics of the participant:

3. Specific behaviors that bother you the most:

4. Behaviors you would like to decrease:

5. Behaviors you would like to increase:


Appendix G

Goal-Setting Worksheet #2

Before beginning your assessment, you will need to answer the following questions:

1. State your target behavior specifically, including setting, timing, frequency, duration,

intensity, etc.:

2. How many times will you collect data?

3. When will you observe the behavior?

4. How long will each observation period be?

5. How will you ensure that the data is objective and accurate?


Appendix H

Fading reference sheet


Appendix I

Baseline Data Chart


Appendix J

Pre-intervention Attitude Survey


Appendix K

Post-intervention Attitude Survey


Appendix L

Group Discussion Questions

1. In what way has using an app for self-monitoring been helpful to you in meeting your goal?

2. What was the most challenging part of using the app for self-monitoring?

3. How is using an iPad app for self-monitoring better or worse than other self-monitoring tools

you have tried?

4. Are you likely to use an iPad app for self-monitoring again with a different goal? Why or

why not?

5. Is there anything we have not yet discussed, that you feel is important for me to know about

the effectively of using an iPad app for self-monitoring?


Appendix M

Research Study Informed Consent Form

Western Governors University Teachers College

M.Ed., Learning and Technology

“What Effect Will Using iPad Apps for Self-Monitoring Have on Target Behaviors for People

with Autism Spectrum Disorders?”

Sarah K. Conway

Introduction

The following information is being presented to help you and your child decide whether or not

your child wishes to be a part of a research study. Please read this information carefully. If you

have any questions or if you do not understand the information, you are encouraged to contact

the researcher, Sarah Conway.

You are being asked to allow your child to take part in a research study called: “What Effect

Will Using iPad Apps for Self-Monitoring Have on Target Behaviors for People with Autism

Spectrum Disorders?” The focus of the research involves the use of iPad apps by persons with

autism spectrum disorders for self-monitoring of independently identified target behaviors. The

overall goal of instruction is for people with autism spectrum disorders to gain independence

through self-monitoring using iPad technology.

The person who is in charge of this research study is Sarah K. Conway. Ms. Conway is a student

researcher in the Teachers College of Western Governors University. Ms. Conway is pursuing

her Master’s degree in Learning and Technology, building on her teacher certifications in Special

Education and Elementary Education. Her expertise includes Applied Behavior Analysis and

working with people with autism spectrum disorders.


The research will be conducted at LifeSkills-TouchPoint Autism Services. Approval to conduct

the study was obtained from the organization prior to this announcement.

By signing this consent form, parents allow their child’s research data to be reported, in the

aggregate (individual participant names will not be used), in the WGU student researcher’s

written capstone project.


Description of the project

The purpose of the research is to find out whether the use of iPad apps for self-

monitoring will help people with autism spectrum disorders achieve personal goals. The

researcher believes that with increased self-awareness of the target behavior (a functional

life skill or related behavior that the participant hopes to increase or eliminate), each

participant will meet his or her goal.

The research project will be conducted over the period of three consecutive weeks,

including four Saturdays, beginning November 2, 2013. The project will include two-

hour instructional workshops on each Saturday and independent data collection during

the weeks in between. Instruction will take place at LifeSkills-TouchPoint Autism

Services Main Office at 10176 Corporate Square Drive, Suite 150, St. Louis, MO 63132.

Given specific instruction in the use of an iPad app for data tracking, the participants will

independently track the frequency, duration, or intensity of a self-selected target behavior

(a functional life skill or related behavior that the participant hopes to increase or

eliminate). Data collection will be ongoing during a month-long series of mini-lectures.

The group will meet every Saturday for instruction. For the first week, the

parents/caregivers will supervise the participants’ self-monitoring efforts. The second

week, the parents/caregivers will fade involvement with the self-monitoring. The third

week, participants will independently self-monitor.

All members of the participant group will have a medical diagnosis of autism spectrum

disorder. Participants will be school-age or older, and must be cognitively able to self-

select and work toward a functional behavior goal. Additionally, participants must be

able to use an iPad independently for tracking data. Parents or caregivers of the

participants will attend the workshops to help provide baseline data and assist participants

in the process of learning and using the new data tracking technology.

All participants, including parents/caregivers, agree to participate fully in all aspects of

the research study.

Participants and their parents/caregivers (if appropriate) will be required to attend four

two-hour workshops (dates to be determined) and track data using their own personal

iPads. Participants will be required to provide the researcher weekly screen captures of

behavioral data from the self-monitoring app for the purposes of data analysis.

Additionally, each participant will be required to take part in surveys or questionnaires

regarding the participant’s attitude about his or her own ability and motivation to achieve

the selected goal.

LifeSkills-TouchPoint Autism Services has reviewed and approved the researcher’s

request to conduct this project.


Potential benefits

The potential benefits to the participants of this study include:

increased independence through self-monitoring using learned iPad apps

the elimination or improvement of self-selected target behaviors of focus during the study

It is unknown whether this study will improve or eliminate behaviors for persons with autism

spectrum disorders, or help them gain independence. That is why the study is being conducted.

By volunteering, you are helping researchers learn more about the use of iPad apps for behavior

intervention. The final report may be used in the future to help other researchers, behaviorists,

and people with autism spectrum disorders.

Potential risks

There are no known risks to those who take part in this study.

Confidentiality

Any information that is obtained in connection with this study and that can be identified with

the participant, parents or caregivers will remain confidential. Raw data will only be seen by the

researcher, and individual participant names will not be used in reported findings. All data will

be reported in the aggregate. Raw data will be destroyed at the end of the study to ensure

confidentiality.

Voluntary participation and withdrawal

Participants can choose whether or not to be included in this study. If you volunteer to

participate in this study, you may withdraw at any time without consequences of any kind or loss

of benefits to which you are otherwise entitled. You may also refuse to answer any questions

you do not want to answer. Participants may request that individual results be excluded from the

final report.

Parental permission and the consent of the organization, LifeSkills-TouchPoint Autism Services,

must be obtained before the researcher may gather data for the purposes of this Capstone Project.


Questions, Rights and Complaints

LifeSkills-TouchPoint Autism Services has reviewed and approved the researcher’s request to

conduct this project. If you have any questions or concerns about your rights in this study,

please contact the researcher, Sarah Conway, by phone at (314) 306-5353 or by email at

[email protected].

Participants and their legal guardians have a right to view the results of the study.

Consent statement

I understand that by signing this document, the administrator grants permission for participant

data collection and reporting as necessary for this study.

I understand that by signing this document I am agreeing to let my child take part in this research

study and authorize that data pertaining to my child will be collected in this study and disclosed

within the parameters outlined above.

____________________________ ________________________________

Organization Administrator Signature Parental Signature

____________________________ ________________________________

Title of Administrator Typed/printed Name

____________________________ ________________________________

Typed/printed Name Date

Examining the Effect of Using iPad Apps for Self-Monitoring of Target Behaviors for People with Autism Spectrum Disorder

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