The effects of material presence versus absence on skill ...557/fulltext.pdf · Garrigan, & Vangala, 2005). Through the video modeling procedure, complex behavior chains can be acquired

The Effects of Material Presence Verses Absence on Skill Acquisition

During Video Modeling

A Thesis Presented

by

Cara Grieco

The Department of Counseling and Applied Educational Psychology

In partial fulfillment of the requirements

for the degree of

Master of Science

in the field of

Applied Behavioral Analysis

Northeastern University

Boston, MA

August 2011

NORTHEASTERN UNIVERSITY

Bouve College of Health Sciences Graduate School

Thesis Title: The Effects of Material Presence Versus Absence on Skill Acquisition During Video Modeling Author: Cara Grieco Department: Counseling and Applied Educational Psychology Approved for Thesis Requirements of Master of Science Degree ______________________________________________________ __________ Rebecca P. F. MacDonald ______________________________________________________ __________ Chata Dickson ______________________________________________________ __________ Susan Langer

The Effects of Material Presence Versus Absence on Skill Acquisition


by

Cara Grieco

B.A. Vassar College 2008

Submitted in partial fulfillment of the requirements for the degree of Master of Science in Applied Behavior Analysis

in the Bouve College of Health Sciences Graduate School of Northeastern University, August 2011

Acknowledgements

I’d like to thank the New England Center for Children for providing me with the

opportunity to learn a great deal about Applied Behavior Analysis through both work and

study. I also commend The New England Center for Children for the excellent services it

provides to its students, and its dedication to research and the advancement of science. I

extend a special thanks to the faculty of the MABA program for instructing and

encouraging a new generation of behavior analysts.

I am extremely grateful to Becky MacDonald, the chairperson of my thesis

committee, for her guidance, expertise, and support, offered throughout my entire

Master’s program. I also extend gratitude to Chata Dickson and Sue Langer, members of

my thesis committee, for their time and contributions, and to Stephanie DeQuick for her

assistance with data collection.

Table of Contents The Effects of Material Presence Versus Absence on Skill Acquisition

During Video Modeling A. Abstract .................................................................................................... 2 B. Introduction

1. Video Modeling as a Teaching Procedure ................................. 3 2. Variations on the Video Modeling Procedure ............................ 4 3. Attending During Video Modeling ............................................. 7 4. Problem Statement and Experimental Question ......................... 9

C. Method 1. Participants .................................................................................... 10 2. Setting and Materials ..................................................................... 10 3. Independent Variables ................................................................... 12 4. Dependent Variables and Operational Definitions ........................ 12 5. Interobserver Agreement ............................................................... 14

6. Experimental Design ..................................................................... 16 7. Procedures ..................................................................................... 17

D. Results ...................................................................................................... 19 E. Discussion ................................................................................................. 23 F. References ................................................................................................. 28 G. Tables ....................................................................................................... 30 H. Figures ...................................................................................................... 37 I. Appendices .................................................................................................44t

MATERIAL PRESENCE VERSUS ABSENCE 2

Abstract

The purpose of the current study was to determine the effects of material presence and material

absence during video viewing on rate of skill acquisition using video modeling. Three young

boys diagnosed with an autism spectrum disorder participated. A multiple baseline across

participants design and a multi-element within participants design was used to compare

acquisition rates of two pretend play scripts, one presented with the materials visible during

video viewing, and one presented with materials absent during video viewing. An analysis of

attending was conducted using a real-time measurement method to determine what stimuli

participants attended to during video viewing (video, materials, or other stimuli) in both

conditions. For two of the three participants, acquisition rate was faster in the materials absent

condition, and for one of the three participants, acquisition rate was faster in the materials

present condition. For the participants who learned faster in the materials absent condition,

duration of attending to video was higher in the materials absent condition, and duration

attending to other stimuli was similar across conditions. For the participant who learned faster in

the materials present condition, duration of attending to other stimuli was higher in the materials

absent condition, whereas duration of attending to video was similar across conditions. These

findings identify environmental arrangement during video viewing as a crucial component of the

video modeling procedure, as acquisition rates of all three participants were affected when this

aspect was manipulated.


The Effects of Material Presence Versus Absence on Skill Acquisition


Video modeling is a teaching procedure that utilizes a video prompt to model a skill. The

procedure usually consists of two to three presentations of a videotaped sample of a model

engaging in a complex behavior chain. The chain typically consists of a series of scripted

actions and verbalizations. An individual is prompted to watch the video and is then given the

opportunity to perform the modeled actions (Charlop & Milstein, 1989; MacDonald, Clark,

Garrigan, & Vangala, 2005). Through the video modeling procedure, complex behavior chains

can be acquired in relatively few sessions. Furthermore, no outside prompting or reinforcement

is necessary for skill acquisition to occur (Charlop-Christy, Le, & Freeman, 2000; D’Ateno,

Mangiapanello, & Taylor, 2003; MacDonald et al., 2005). These factors, along with ease of

implementation, cost-effectiveness, and high procedural integrity, make video modeling a useful

and important tool (Charlop-Christy et al., 2000). Furthermore, researchers have demonstrated

the utility of video modeling in terms of skill generalization. After exposing participants to a

single video modeling prompt, skills have generalized to untrained settings (Charlop & Milstein,

1989; Patterson & Arco, 2007).

Another factor that makes video modeling an important tool is the broadness of its

application. Through video modeling, a large variety of skills have been taught successfully to a

number of populations, particularly to individuals with autism and other related developmental

disabilities. Among the skills that have been targeted through video modeling are conversational

speech (Charlop & Milstein, 1989), perspective taking (LeBlanc, Coates, Daneshvar, Charlop-

Christy, Morris, & Lancaster; 2003), appropriate social behavior and methods for reducing

problem behavior (Delano, 2007), and daily living skills (Rehfeld, Dahman, Young, Cherry, &


Davis, 2003). Video modeling has also been an effective method for teaching pretend play skills

to children with autism (D’Ateno et al., 2003; MacDonald et al., 2005; MacDonald, Sacramone,

Mansfield, Wiltz, & Ahearn, 2009; Patterson & Arco, 2007). Pretend play is a skill that

naturally emerges in typically developing children, and is thought to contribute to social

development and language acquisition. Children with autism, on the other hand, fail to develop

appropriate play with toys. Toy manipulation by children with autism is characterized by

repetitive, stimulatory behavior (MacDonald et al., 2005). Video modeling has been an effective

tool for teaching complex pretend play sequences to children with autism, decreasing aberrant

behavior during play, and teaching reciprocal pretend play with a typically developing peer

(D’Ateno et al., 2003; MacDonald et al., 2005; MacDonald et al., 2009; Patterson & Arco,

2007).

Given the overwhelming effectiveness of video modeling as a teaching procedure, a large

subset of literature has focused on how to increase its efficacy even further. In their review

article, McCoy and Hermansen (2007) examined the impact of the model on the efficacy of

video modeling. A number of model types are used across video modeling procedures, including

adult models, peer/sibling models, and self as model. Furthermore, the point-of-view differs

across video modeling procedures; some videos are filmed from the point-of-view of the person

performing the task (e.g. only the hands are visible), whereas others are filmed straight on. The

authors’ review revealed no particular benefits of one model type or perspective of filming over

another. Interventions utilizing each model type have produced similar success rates (McCoy &

Hermansen, 2007; Sherer, Pierce, Paredes, Kisacky, Ingersoll, & Schreibman, 2001).

Despite such interest in variations on the video modeling procedure and their effects on

skill acquisition, there is a lack of comparative studies in the literature. The comparative studies


that do exist, however, allow for a direct comparison between conditions and the effects of

different variables on rate of skill acquisition. Sherer et al. (2001), for example, suggest that

preference for model type (specifically self versus other) might be idiosyncratic. In their study,

three of five participants showed no preference for model type, whereas one of five had a faster

acquisition rate with self as model, and one of five had a faster acquisition rate with other as

model. Palechka and MacDonald (2010) conducted a direct comparison between two video

formats (an instructor created video versus a commercially available video) on skill acquisition.

For two of three participants, acquisition was faster when an instructor created video was used,

and for the other participant, there was no difference in the rate of acquisition between the two

conditions (Palechka & MacDonald, 2010).

Another variable that has been examined through direct comparison is in-vivo versus

video modeling. Whereas the typical video modeling procedure utilizes a videotaped prompt, in-

vivo modeling requires the participant to observe a live model performing the target task

(Charlop-Christy et al., 2000; Gena, Couloura, & Kysmissis, 2005). In a study conducted by

Charlop-Christy et al. (2000), two educational objectives were targeted per participant. One

objective was taught using a video prompt, whereas the other was taught using an in-vivo model.

Across four of the five participants, video modeling resulted in more efficient skill acquisition

and maintenance as compared to in-vivo modeling. A possible explanation of these findings is

that the use of a video prompt eliminates irrelevant stimuli, decreasing the probability of

overselectivity, which is a common problem among learners with autism and other related

developmental disabilities. Furthermore, children are typically motivated by television and

videos, so this learning procedure might be preferred over others (Charlop-Christy et al., 2000).

Although these results have never been replicated, the research conducted by Charlop-Christy et


al. (2000) emphasizes the efficacy of video modeling as a teaching tool, and highlights the

importance of isolating the factors that contribute to its effectiveness.

Factors such as model type, video format, and in-vivo versus videotaped modeling focus

on aspects of the stimulus that is being presented. A new avenue of research is analyzing the

pre-requisite skills necessary for successful video modeling (Weiss & Harris, 2001; Robinson,

2009; Tereshko, MacDonald, & Ahearn, 2010). According to this approach, certain skills in the

learner’s repertoire make him more or less likely to succeed using the video modeling procedure.

Weiss and Harris (2001) identified three necessary pre-requisite skills for successful video

modeling: motor imitation, and the ability to attend to a video, and delayed match-to-sample.

Delayed match-to-sample consists of the presentation of a sample stimulus, which is then

removed for a certain period of time. Following the period of stimulus removal, the comparisons

are presented. Tereshko et al. (2010) demonstrated that children who were unable to perform

delayed match-to-sample tasks were unable to learn an eight-step response chain using the video

modeling procedure. A segmented video modeling teaching procedure was introduced, in which

progressively longer response chains were presented across trials. This procedure was successful

in teaching the eight-step response chain to children who were initially unable to complete it.

Similarly, Robinson (2009) identified delayed object imitation as a possible prerequisite skill for

video modeling. Delayed object imitation consists of a model manipulating an object in vivo.

The object is removed for a specified period of time, and is then presented to the learner, who is

expected to perform the same object manipulation. Participants who were unable to learn

through video modeling also exhibited deficits in delayed object imitation. Following training of

successive discrimination skills (delayed match-to-sample and delayed object imitation), 2 of the

4 participants showed an increase in acquisition through video modeling. Through their studies,


Tereshko et al. (2010) and Robinson (2009) illustrated that by addressing the skill set of a learner

and making appropriate procedural modifications, the video modeling procedure can be an

effective teaching method even for those who were initially unable to learn through video

modeling.

An integral component of any video modeling procedure is the video viewing, as it is the

only source of prompting throughout the whole procedure. If a learner is unable to attend to the

video, then he will not be able to acquire new skills through this method. In their review article,

McCoy and Hermansen (2007) noted that although attending logically seems like an important

pre-requisite skill for successful video modeling, the majority of articles on video modeling do

not include information regarding the attending skills of the participants. The failure to include

such information might limit the interpretation of the findings reported in these studies.

Furthermore, studies that have reported on the attending skills of the participants supply very

little information. For example, Paterson and Arco (2007) simply state that the participants

selected for their study were able to watch television for at least 90 seconds, as per parent report.

Attending skills were assessed indirectly, and furthermore, the authors did not provide an

operational definition of this critical pre-requisite skill. Thus, it is not clear exactly what the

participants’ repertoires consisted of.

This lack of an operational definition of attending extends throughout the video modeling

literature. In 2010, Palechka and MacDonald conducted an analysis of the types of attending that

occur during video modeling. The analysis was conducted retrospectively; the three participants

had already successfully acquired the pretend play skills targeted by the video modeling

procedure. Two types of attending were examined; attending to video and attending to materials.

The researchers observed the video viewing portion of the video modeling session (on


videotape), which took place in a small room containing a chair, a table, and a portable DVD

player, as well as the materials (toys) that were to be manipulated immediately following video

viewing. The researchers used real time duration recording to capture the percentage of time that

the participant attended to the video and to the materials (materials were placed on the floor

adjacent to the participant). Attending to video was scored given any instance in which the

participant’s head and eyes were oriented towards the portable DVD player, and attending to

materials was scored given any instance in which the participants’ head and eyes were oriented

toward the toys. Overall attending was high for all participants across sessions. In regard to the

type of attending that occurred, attending to the video decreased as script mastery increased, and

attending to toys increased as script mastery increased (Palechka & MacDonald, 2010). Thus,

the attending repertoire of all three participants consisted of attention shifting between video and

materials. Given that all three participants acquired the pretend play skills that were targeted, it

is possible that the ability to shift attention between materials and toys is a pre-requisite for

successful video modeling.

Although Palechka and MacDonald (2010) suggest that attending to materials during

video viewing might be an important skill for successful video modeling, the relationship

between material presence and skill acquisition is unclear. On one hand, referencing the

materials during video viewing might increase the likelihood that the stimuli control the response

once the video prompt is removed. This is especially possible given the empirical evidence that

indicate delayed match-to-sample and delayed object imitation as prerequisite skills for

successful video modeling (Robinson, 2009; Tereshko et al., 2010). Attending to materials

during video viewing might account for the transfer of stimulus control from the video to the

materials. However, attending to materials during video viewing might hinder skill acquisition.


In their research, Landry and Bryson (2004) illustrate impaired disengagement of attention in

children with autism. For children with autism, disengaging attention from one stimulus in order

to engage with another stimulus is a difficult task. Therefore, shifting gaze between the video

and the materials might make learning through video modeling more difficult.

Another consideration concerns the importance of the video prompt. If the video is the

most relevant prompt during the video modeling procedure, attending to materials might distract

the learner from the important stimuli and therefore slow acquisition. At this moment, there is

no empirical evidence suggesting the superiority of material presence or material absence on

skill acquisition. Furthermore, video modeling procedures rarely specify whether materials

should be present or absent during video viewing. A study that directly compares these two

environmental arrangements might inform the video modeling procedure and make it even more

effective.

The purpose of the present study was threefold. The first purpose was to replicate the

findings of the video modeling literature, in which video modeling is an effective procedure for

teaching pretend play skills to children with autism (D’Ateno et al., 2003; MacDonald et al.,

2005; MacDonald et al., 2009; Patterson & Arco, 2007). The second purpose of the study was to

extend this literature by conducting a direct comparison between two environmental

arrangements (materials present during video viewing and materials absent during video

viewing), to determine the effects of these arrangements on skill acquisition. The third purpose

of the current study was to conduct an analysis of attending during video viewing (Palechka &

MacDonald, 2010), to determine what stimuli participants attend to when materials are present

and when materials are absent.


Method

Participants

The participants in the current study were Cole, Matthew, and Charles, three young boys

diagnosed with an Autism Spectrum Disorder. Cole (Peabody Picture Vocabulary Test- Fourth

Edition Form A: age equivalent: 5 years 4 months, raw score: 86, 63rd percentile) and Matthew

(Peabody Picture Vocabulary Test- Fourth Edition Form B: age equivalent: 5 years 5 months,

raw score: 90, 34th percentile) were five years old at the beginning of the study, and Charles

(Peabody Picture Vocabulary Test- Fourth Edition Form B: age equivalent: 3 years 10 months,

raw score: 84, 2nd percentile) was six years old. All three participants were students at a

preschool for children with autism, and received intensive one-on-one instruction based on the

principles of Applied Behavior Analysis. They attended school for six hours a day, five days a

week, and had individualized educational programs (IEPs) that outlined their academic

objectives. The IEPs of all participants contained a “play” objective, which aimed to increase

pretend play skills through the use of video modeling. Each of the boys had learned complex

pretend play scripts through video modeling in the past. Thus, video modeling was an effective

teaching procedure for these students. Furthermore, the results of an assessment indicated that

each participant demonstrated a number of skills (e.g. delayed match to sample, delayed

imitation) believed to be prerequisites for successful video modeling. Cole, Matthew, and

Charles communicated vocally through complete sentences.

Setting

All sessions took place in a research room that measured 2.7 by 4.3 meters, and was

separate from the students’ classrooms. The room contained a small chair and table, which was

used for video viewing. Play materials were placed on the floor adjacent to the table. In the


materials present condition, toys were visible during video viewing. The participant could shift

his gaze between the video and the materials by turning his head 90 degrees. In the materials

absent condition, materials were blocked by a 6-foot partition during video viewing. After video

viewing was complete, the partition was removed.

Materials

Materials used in the current study included a table and portable DVD player for video

viewing, two videos, and play materials corresponding to the sequences portrayed in the videos.

The videos used in the current study are those that were created by Palechka and MacDonald

(2010) for their instructor created video (ICV) condition. Both videos were filmed from a third

person perspective, and the sequences were acted out by an adult model. Only the hands of the

model were visible.

The sequences acted out in each video were created to be equivalent in complexity and

length, to control for confounds due to task difficulty. The sequence called “Sonya and the

Super Sundae” ran for 2 minutes and 48 seconds, and contained 27 actions and 32 vocalizations

(Appendix 1). The sequence called “Faster than a Speeding Frog” ran for 2 minutes and 49

seconds, and contained 28 actions and 30 vocalizations (Appendix 2).

Both play sequences included pieces from the Fisher Price “Little People” line. The play

materials for “Faster than a Speeding Frog,” included a Little People town and garage set, 11

Little People figurines, 1 vehicle, 4 props, and 2 floorboards (Appendix 3). The materials for

“Sonya and the Super Sundae,” included a Little People town and barn set, 8 Little People

figurines, 3 vehicles, 10 props, and 3 floorboards (Appendix 4).


Additional materials used in the current study were a 6-foot partition for blocking the

materials during the “materials absent” condition, and a video camera to record all sessions for

scoring purposes.

Independent Variables

The independent variables in the current study were exposure to video, and material

presence versus absence during video viewing. During baseline sessions, each participant was

given access to each play set prior to video exposure. Following baseline, each participant was

exposed to each video, followed by access to the corresponding play set. One video was paired

with material presence during video viewing, while the other was paired with material absence

during video viewing. Each script appeared in each condition twice, and the pairings were

counterbalanced across participants (Table 1).

Dependent Variables

Scripted actions. Scripted actions were scored per occurrence during the play portion of

each session. Scripted actions were defined as play actions that were included in the play

sequence. Scoring guidelines outlined the actions that met this definition (Appendices 5 and 6).

Scripted actions could occur in any order, and did not have to be carried out by the specific

character depicted in the video. For example, the scripted action “Eddie puts springs on feet”

was scored as correct if the participant put the springs on Michael’s feet.

Scripted vocalizations. Scripted vocalizations were scored per occurrence during the

play portion of each session. Scripted vocalizations were defined as vocalizations that were

included in the play sequence. Scoring guidelines outlined the vocalizations that met this

definition (Appendices 5 and 6). Scripted vocalizations did not have to occur in order, and did

not have to be carried out by the appropriate character in order to be scored as correct (for


example, if the participant was holding Sonya Lee while saying one of Michael’s lines, the

vocalization was still counted as correct). Due to the complexity of the script, partial vocals

(defined as at least 50% of the scripted vocalization) were scored as correct. Furthermore,

paraphrases that contained all the important elements of the scripted vocalization were scored as

correct (e.g. “Do you know where Sonya Lee is?” instead of “Where is Sonya Lee?”).

Percent script completion. Percent script completion was calculated by adding the

number of scripted actions and scripted vocalizations emitted by the participant during the play

portion of the session, dividing this number by the total number of scripted actions and

vocalizations, and multiplying it by 100.

Attending to video. The amount of time that the participant attended to the video was

scored for the video-viewing portion of all training sessions. Attending to video was defined as

any instance of the participant’s head oriented and eyes directed toward the portable DVD

screen, lasting for one second or longer (Palechka & MacDonald, 2010). This variable was

measured using a real-time measurement method (Miltenberger, Rapp, & Long, 1999), which

consisted of second-by-second scoring. Percent attending to video was calculated by dividing the

total number of seconds that the participant attended to the video by the total number of seconds

of the video-viewing, and multiplying this number by 100. Appendix 7 contains a photographed

example of a participant attending to video.

Attending to materials. The amount of time that the participant attended to the materials

was scored for the video-viewing portion of all training sessions in the “materials present”

condition. Attending to materials was defined as any instance of the participant’s head oriented

and eyes directed toward the play materials, lasting for one second or longer (Palechka &

MacDonald, 2010). This variable was measured using a real-time measurement method


(Miltenberger et al., 1999), which consisted of second-by-second scoring. Percent attending to

materials was calculated by dividing the total number of seconds that the participant attended to

the materials by the total number of seconds of the video-viewing, and multiplying this number

by 100. Appendix 7 contains a photographed example of a participant attending to materials.

Attending to other stimuli. The amount of time that the participant attended to other

stimuli was scored for the video-viewing portion of all training sessions. Attending to other

stimuli was defined as any instance of the participant’s head oriented and eyes directed toward

anything other than the materials or the DVD screen, including the ceiling, floor, table, wall,

DVD keyboard, camera, and self (e.g. hands, fingers), lasting for one second or longer (Palechka

& MacDonald, 2010). Attending to other stimuli also included any instance of eye closing,

laying face down on the table, and covering both eyes with hands, lasting for one second or

longer. This variable was measured using a real-time measurement method (Miltenberger et al.,

1999), which consisted of second-by-second scoring. Percent attending to other was calculated

by dividing the total number of seconds that the participant attended to other stimuli by the total

number of seconds of the video-viewing, and multiplying this number by 100. Appendix 7

contains a photographed example of a participant attending to other stimuli.

Interobserver Agreement

Tables 2 and 3 summarize interobserver agreement across all dependent variables and

participants. In order to measure interobserver agreement for script completion, a second

independent observer scored 41% of sessions across all participants and conditions. Both the

primary and secondary observers referred to scoring guidelines to increase objectivity

(Appendices 5 and 6). Interobserver agreement was calculated by dividing the number of


agreements by the number of agreements plus disagreements, and multiplying this number by

100.

Interobserver agreement was collected across 50% of baseline sessions for Cole, 33% of

baseline sessions for Matthew, and 38% of baseline sessions for Charles. Interobserver

agreement for Cole was 100% for actions, and 100% for vocalizations. Interobserver agreement

for Matthew was 87% for actions (range 85-88%) and 100% for vocalizations. Interobserver

agreement for Charles was 100% for actions and 100% for vocalizations.

Interobserver agreement was collected across 40% of video viewing sessions for Cole,

44% of video viewing sessions for Matthew, and 38% of video viewing sessions for Charles.

Interobserver agreement for Cole was 90% for actions (range 81-96%) and 91% for vocalizations

(range 83-97%). Interobserver agreement for Matthew was 91% for actions (range 86-96%) and

96% for vocalizations (range 88-100%). Interobserver agreement for Charles was 93% for

actions (range 86-96%) and 87% for vocalizations (range 72-97%).

Interobserver agreement was collected across 33% of no video sessions for Cole, 50% of

no video sessions for Matthew, and 100% of no video sessions for Charles. Interobserver

agreement for Cole was 96% for actions (range 93-100%) and 98% for vocalizations (range 97-

100%). Interobserver agreement for Matthew was 93% for actions (range 89-96%) and 95% for

vocalizations (range 94-97%). Interobserver agreement for Charles was 87% for actions (range

86-89%) and 97% for vocalizations.

In order to measure interobserver agreement for attending to video, attending to

materials, and attending to other stimuli, an independent observer scored 40% of sessions, across

all conditions and participants. Interobserver agreement was calculated by dividing the number


of agreements by the number of agreements plus disagreements, and multiplying this number by

100.

Interobserver agreement was collected for 38% of materials present sessions for Cole,

40% of materials present sessions for Matthew, and 43% of materials present sessions for

Charles. Interobserver agreement for Cole was 92% for attending to video (range 89-95%), 93%

for attending to materials (range 92-95%), and 97% for attending to other stimuli (range

96-100%). Interobserver agreement for Matthew was 96% for attending to video (range 94-

98%), 96% for attending to materials (range 94-98%), and 100% for attending to other stimuli

(range 99-100%). Interobserver agreement for Charles was 88% for attending to video (range 85-

92%), 90% for attending to materials (range 87-93%), and 90% for attending to other stimuli

(range 85-96%).

Interobserver agreement was collected for 43% of materials absent sessions for Cole,

50% of materials absent sessions for Matthew, and 33% of materials absent sessions for Charles.

Interobserver agreement for Cole was 96% for attending to video (range 94-98%) and 96% for

attending to other stimuli (range 94-98%). Interobserver agreement for Matthew was 99% for

attending to video (range 98-100%) and 99% for attending to other stimuli (range 98-100%).

Interobserver agreement for Charles was 88% for attending to video (range 84-90%) and 88% for

attending to other stimuli (range 84-90%).

Experimental Design

A multi-element design within participants and a multiple baseline design across

participants was used in the study. The multiple baseline across participants component

demonstrated the effect of the video modeling procedure on pretend play skills, while the multi-


element within participants component allowed for a direct comparison of acquisition rates

between the materials present and the materials absent conditions.

Procedures

Baseline. During the baseline condition, the experimenter brought the participant to the

research room, where the play materials were set up on the floor. Play materials were set up to

mirror the initial scenes of the video model. The experimenter set a timer for five minutes,

pointed to the toys, and stated, “It’s time to play”. The experimenter did not interact with the

participant, unless she had to redirect his attention to the toys. For example, if the participant

stood up and walked to the door, the experimenter neutrally guided him back to the toys. After

five minutes elapsed, the experimenter said, “Playing with toys is all done,” and walked the

participant back to his classroom. During all baseline, video viewing, and no video sessions, the

experimenter was in the room with a video camera, recording the entire session for scoring

purposes. The experimenter positioned herself as not to interfere with video viewing or toy play.

Video Viewing: Materials Present. Following baseline, all participants were exposed to

video viewing sessions. In the “materials present” condition, the experimenter brought the

participant to the research room, where a portable DVD player was set up on a small table, and

the corresponding play materials were set up on the floor adjacent to the table. The experimenter

guided the participant to sit at the table, and said, “It’s time to watch a video.” The participant

was then exposed to two viewings of the video model, with a two-second pause between

viewings. The participant was positioned such that he could attend to the video screen by

looking straight ahead, and he could attend to the materials by turning his head 45 degrees.

Following the two video viewings, the experimenter set a timer for five minutes, pointed to the

toys, and said, “It’s time to play.” The experimenter did not interact with the participant, unless


it was to redirect his attention to the toys. The discriminative stimulus that signified the

beginning of the play portion (“It’s time to play”) was altered for Charles after 3 training

sessions to, “It’s time to play; do what you saw in the movie.” After the five minutes elapsed,

the experimenter said, “Playing with toys is all done,” and walked the participant back to his

classroom. During the play portion of most video viewing sessions, Cole and Matthew requested

more time after the five minutes elapsed. Following this request, the experimenter allowed the

participant to continue playing until he completed the play sequence.

Video Viewing: Materials Absent. The “materials absent” condition was identical to the

“materials present” condition in all aspects but one. In the “materials absent” condition, play

materials were blocked by a six-foot partition during video viewing. Therefore, materials were

not visible while the participant was watching the video model. The participant was positioned

such that he could attend to the video by looking straight ahead. If the participant turned his

head 45 degrees, he would see the partition. Following video viewing, the experimenter

removed the partition, and continued with procedures identical to those in the “materials present”

condition.

No Video. No video sessions were run once the participant met mastery criteria for both

scripts. Mastery criteria were met once the participant completed 80% of the script for two

consecutive training sessions. No video sessions were identical to baseline sessions. During the

play portion of most no video sessions, Cole and Matthew requested more time after the timer

went off. Following this request, the experimenter allowed the participant to continue playing

until he completed the play sequence.


Results

Total percentage script completion for each participant is depicted in Figure 1. Cole met

mastery criteria for script completion in 8 sessions in the materials present condition, and in 5

sessions in the materials absent condition. Matthew met mastery criteria for script completion in

5 sessions in the materials present condition, and in 4 sessions in the materials absent condition.

Charles met mastery criteria for script completion in 6 sessions in the materials present

condition, and did not meet mastery criteria for script completion in the materials absent

condition. Due to time constraints, training ceased following 9 sessions in the materials absent

condition. However, one no video session was conducted prior to the end of the study, in which

Charles performed 78% of the play sequence (20 scripted actions and 25 scripted vocalizations).

It is likely that Charles would have met mastery criteria had training continued. Table 8

summarizes the number of sessions needed to meet mastery criteria for each participant in each

condition.

Number of completed scripted actions and vocalizations for Cole are depicted in Figure

2. During baseline, number of completed scripted actions was low across both play sets. Once

video viewing began, number of scripted actions immediately increased in both conditions. In

the materials present condition, number of scripted actions increased to 22 (out of 27) in the first

no video session, and in the materials absent condition, number of scripted actions increased to

25 (out of 28) in the first no video session. As time elapsed, Cole’s performance in the no video

sessions (which spanned a period of months) regressed. However, rates remained higher than

baseline, with number of scripted actions at 19 in the materials present condition, and 22 in the

materials absent condition.


Cole did not complete any scripted vocalizations during baseline in either play set. Once

video viewing began, number of scripted vocalizations immediately increased in both conditions.

In the materials present condition, number of scripted vocalizations increased to 31 (out of 32) in

the first no video session, and in the materials absent condition, number of scripted vocalizations

increased to 27 (out of 30) in the first no video session. As time elapsed (the no video condition

spanned a period of months), Cole’s performance in the no video sessions regressed. However,

rates remained higher than baseline, with number of scripted vocalizations at 16 in the materials

present condition, and 21 in the materials absent condition. For Cole, there was a bigger

discrepancy between conditions in the acquisition of scripted actions as compared to scripted

vocalizations.

Number of completed scripted actions and vocalizations for Matthew are depicted in

Figure 3. During baseline, number of completed scripted actions was low across both play sets.

Once video viewing began, number of scripted actions immediately increased in both conditions.

In the materials present condition, number of scripted actions increased to 24 (out of 28) in video

viewing sessions 37 and 39, and in the materials absent condition, number of scripted actions

increased to 26 (out of 27) in video viewing session 41. In the first no video session, Matthew

performed 22 scripted actions in the materials present condition, and 25 scripted actions in the

materials absent condition. As time elapsed (the no video condition spanned a period of months),

Matthew’s performance in the no video sessions regressed for the sequence associated with the

materials absent condition. However, rates remained higher than baseline, with number of

scripted actions at 22.

Matthew did not complete any scripted vocalizations during baseline in either play set.

Once video viewing began, number of scripted vocalizations immediately increased in both


conditions. In the materials present condition, number of scripted vocalizations increased to 28

(out of 30) in video viewing session 42, and in the materials absent condition, number of scripted

vocalizations increased to 29 (out of 32) in video viewing session 41. In the no video sessions,

Matthew emitted 26 scripted vocalizations in the materials present condition, and 28 scripted

vocalizations in the materials absent condition. As time elapsed (the no video condition spanned

a period of months), Matthew’s performance in the no video sessions regressed for sequence

associated with materials absent condition. However, rates remained higher than baseline, with

number of scripted vocalizations at 21. For Matthew, there was a similar differentiation between

conditions in the acquisition of scripted actions as compared to scripted vocalizations.

Number of completed scripted actions and vocalizations for Charles are depicted in

Figure 4. During baseline, number of completed scripted actions was low across both play sets,

and remained low in both conditions during video viewing sessions 49 through 51. The

discriminative stimulus signifying the beginning of the play portion was changed in video

viewing session 52, and number of scripted actions immediately increased in both conditions. In

the materials present condition, number of scripted actions increased to 25 (out of 27) in the no

video session, and in the materials absent condition, number of scripted actions stabilized,

ranging from 18-21 (out of 28).

Charles did not complete any scripted vocalizations during baseline in either play set, and

number of scripted vocalizations remained low in both conditions during video viewing sessions

49 through 51. Once the discriminative stimulus was changed, number of scripted vocalizations

immediately increased in both conditions. In the materials present condition, number of scripted

vocalizations increased to 29 (out of 32) in the no video session, and in the materials absent

condition, number of scripted vocalizations increased to 25 (out of 30) in the no video session.


For Charles, there was a slightly larger differentiation between conditions in the acquisition of

scripted vocalizations as compared to scripted actions.

Attending data for Cole are depicted in Figure 5 and Table 9. In the materials present

condition, Cole attended to the video for an average of 71% (range 54-86%) of the duration of

the training video. He attended to the materials for an average of 21% (range 12-35%) of the

duration of the training video. Lastly, Cole attended to other stimuli for an average of 9% (range

2-20%) of the duration of the training video. In the materials absent condition, Cole attended to

the video for an average of 90% (range 82-97%) of the duration of the training video. He

attended to other stimuli for an average of 10% (range 3-18%) of the duration of the training

video. Although attending to video was higher in the materials absent condition, attending to

other stimuli was similar between the two conditions.

Attending data for Matthew are depicted in Figure 6 and Table 10. In the materials

present condition, Matthew attended to the video for an average of 89% (range 82-96%) of the

duration of the training video. He attended to the materials for an average of 10% (range 4-16%)

of the duration of the training video. Lastly, he attended to other stimuli for an average of 1%

(range 0-2%) of the duration of the training video. In the materials absent condition, Matthew

attended to the video for an average of 99% (range 98-99%) of the duration of the training video.

He attended to other stimuli for an average of 1% (range 1-2%) of the duration of the training

video. Attending data for Matthew showed a similar trend to attending data for Cole. Attending

to video was higher in the materials absent condition, and attending to other stimuli was similar

between the two conditions.

Attending data for Charles are depicted in Figure 7 and Table 11. In the materials present

condition, Charles attended to the video for an average of 72% (range 60-89%) of the duration of


the training video. He attended to the materials for an average of 17% (range 3-26%) of the

duration of the training video. Lastly, Charles attended to other stimuli for an average of 11%

(range 5-20%) of the duration of the training video. In the materials absent condition, Charles

attended to the video for an average of 76% (range 64-88%) of the duration of the training video.

He attended to other stimuli for an average of 24% (range 12-36%) of the duration of the training

video. Attending data for Charles followed a different trend than the attending data for the other

two participants. Attending to video was slightly higher in the materials absent condition;

however, the difference was not as great as the differences observed in the other participants’

data. Furthermore, attending to other stimuli was higher in the materials absent condition.

Discussion

In this study, three young boys diagnosed with an autism spectrum disorder learned two

complex pretend play sequences through video modeling, thus replicating the findings that video

modeling is an effective procedure for teaching pretend play to this population (D’Ateno et al.,

2003; MacDonald et al., 2005; MacDonald et al., 2009; Patterson & Arco, 2007). For two of the

three participants (Cole and Matthew), acquisition rate was faster when materials were absent

during video viewing compared to when they were present. For one of the three participants

(Charles), acquisition rate was faster when materials were present during video viewing. For this

participant, mastery criteria in the materials absent condition were never reached.

The findings regarding attending reported by Palechka and MacDonald (2010) were also

replicated, as all three participants shifted their gaze between the video and the materials when

they were present. These findings were extended through a more in-depth analysis, which

included attending to other stimuli. In the current study, all three participants spent the majority

of the video viewing portion of the session attending to the video, regardless of whether


materials were present or absent. For all three participants, attending to video was higher in the

materials absent condition as compared to the materials present condition. However, the

differences observed between attending to video in the two conditions were much larger for two

participants (Cole and Matthew) than they were for the third participant (Charles). Furthermore,

all three participants spent a portion of time attending to the materials when they were present

during video viewing. Across both conditions, all participants also spent time attending to other

stimuli (e.g. the ceiling, the wall, their hands) during video viewing. For Cole and Matthew, who

learned faster in the materials absent condition, attending to other stimuli was similar across

conditions, whereas for Charles, who learned faster in the materials present condition, attending

to other stimuli was higher in the materials absent condition.

The results of the current study have important implications. For all three participants,

acquisition rate was faster in one condition compared to the other. Therefore, environmental

arrangement is a crucial component of the video modeling procedure. Up to this point, very few

video modeling procedures have specified whether materials should be present or absent during

video viewing. According to the data provided in the current study, failure to take this factor

into account might actually slow a learner’s progress. Furthermore, this study is the first to

provide a direct comparison between acquisition rate when materials are present and acquisition

rate when materials are absent. Therefore, any video modeling procedures which have specified

environmental arrangement during video viewing have done so without the aid of empirical data.

The data provided in the current study also elucidate the idiosyncrasies among learners.

Among the three participants, two different trends emerged. For two of the three participants,

material presence hindered acquisition, whereas for one participant, material presence fostered

acquisition. The behavioral processes that underlie this outcome are uncertain. However, the


analysis of attending might lend some clues. For the two participants who learned faster in the

materials absent condition, environmental arrangement did not affect duration of attending to

other stimuli; it only affected duration of attending to video. Duration of attending to video was

higher in the materials absent condition as compared to the materials present condition. It is

possible that for these two participants, material presence distracted attention away from the

video, which is the only source of prompting in the video modeling procedure. This might have

led to a slower rate of acquisition in the material present condition. Furthermore, material

presence might have evoked gaze shifting, which is difficult for children with autism (Landry &

Bryson, 2004). For these participants, engaging in gaze shifting when materials were present

might have impaired learning.

For the participant who learned faster in the materials present condition, environmental

arrangement did not have as large an effect on attending to video as compared to the other two

participants. It did, however, affect duration of attending to other stimuli. It is possible that for

this participant, material presence served as a discriminative stimulus for attending to relevant

stimuli. Material presence might have redirected the participant’s attention from other stimuli

back to relevant stimuli, leading to a faster rate of acquisition.

There are many limitations to the current study. A major limitation is that for Cole and

Matthew, the play portion of the training and probe sessions were longer than the time allotted in

baseline. This factor decreases experimental control, as duration of play was not held consistent

across sessions. However, it must be noted that Cole and Matthew did not ask for extra time

during baseline sessions; these requests only occurred after training began. The scripts used in

the current study required complex figure manipulation, such as placing characters in vehicles,

attaching small pieces to one another, and balancing pieces on top of one another. Due to


deficits in fine motor skills, Cole and Matthew required a lot of time to complete such actions.

Therefore, acquisition of the play sequence is most likely the factor that evoked the mand for

more time. Another factor that decreases experimental control of the current study is the change

in the discriminative stimulus that was presented to Charles prior to the play portion of the

session. However, additional instructions were required for Charles in order to evoke skill

acquisition.

Another limitation of the current study is that the room set-up during video viewing was

slightly different across conditions. For true experimental control, the only difference should

have been material presence or absence. However, since a partition was used to block materials

in the materials absent condition, partition presence versus absence was another difference

between conditions. From a logistical standpoint, it was necessary to use a partition due to the

size of the play materials, as well as the amount of time required to set them up. However, future

research should try to keep the room set-up more consistent across conditions. For example,

rather than using a partition in the materials absent condition, the experimenter can set up the

play materials on a dolly in the hallway, and then wheel them into the room following video

viewing.

The results of the current study suggest a number of exciting avenues for future research.

Firstly, other researchers should try to replicate the study using different materials and play

sequences, to determine if the same trends emerge among participants. If similar trends do

emerge across studies, future research might examine a way to determine which environmental

arrangement is most beneficial for a specific learner. It might also be helpful to examine what in

the learner’s history accounts for the emergence of different trends in attending. This might

make it possible to pre-teach attending skills to make video modeling more effective for a


learner. Furthermore, future research should examine whether adding additional discriminative

stimuli to the environment (e.g. materials, pictures) fosters the acquisition rate of children who

are likely to attend to other stimuli during video modeling.

The data collected in the current study elucidate the importance of environmental

arrangement during the video viewing portion of the video modeling procedure. Thus, it is

important to continue this line of research, and broaden the knowledge base with additional

empirically-based information.


References

Charlop, M. H. & Milstein, J. P. (1989). Teaching autistic children conversational speech using

video modeling. Journal of Applied Behavior Analysis, 22, 275-285.

Charlop-Christy, M.H., Le, L. & Freeman, K.A. (2000). A comparison of video modeling and in vivo

modeling for teaching children with autism. Journal of Autism and Developmental Disorders,

30, 537-552.

D’Ateno, P., Mangiapanello, K., & Taylor, B. (2003). Using video modeling to teach complex play

sequences to preschoolers with autism. Journal of Positive Behavior Interventions, 5, 5-11.

Delano, M. E. (2007). Video modeling intervention for individuals with autism. Remedial and Special

Education, 28, 33-42.

Gena, A., Couloura, S., & Kymissis, E. (2005). Modifying the affective behavior of preschoolers with

Autism using in-vivo or video modeling and reinforcement contingencies. Journal of Autism and

Developmental Disorders, 35, 545-556.

Landry, R., & Bryson, S. E. (2004). Impaired disengagement of attention in young children with

autism. Journal of Child Psychology and Psychiatry, 45, 1115-1122.

LeBlanc, L.A., Coates, A.M., Daneshvar, S., Charlop-Christy, M.H., Morris, C., & Lancaster, B.M.,

(2003). Using video modeling and reinforcement to teach perspective-taking skills to children

with autism. Journal of Applied Behavior Analysis, 36, 253-257.

MacDonald, R., Clark, M., Garrigan, E., & Vangala, M. (2005). Using video modeling to teach

pretend play to children with autism. Behavioral Interventions, 20, 225-238.

MacDonald, R.P.F., Sacramone, S.R., Mansfield, R., Wiltz, K., & Ahearn, W.H. (2009). Using video

modeling to teach reciprocal pretend play to children with autism. Journal of Applied Behavior

Analysis, 42, 43-55.


McCoy, K., & Hermansen, E. (2007). Video modeling for individuals with autism: A review of model

types and effects. Education and Treatment of Children, 30, 183-213.

Miltenberger, R.G., Rapp, J. T., & Long, E. S. (1999). A low-tech method for conducting real-time

recording. Journal of Applied Behavior Analysis, 32, 119-120.

Palechka, G., & MacDonald, R. (2010). A comparison of the acquisition of play skills using

instructor-created video models and commercially available videos. Education and Treatment of

Children, 33, 457-474.

Patterson, C.R., & Arco, L. (2007). Using video modeling for generalizing toy play in children with

autism. Behavior Modification, 31, 660-681.

Rehfeld, R. A., Dahman, D., Young, A., Cherry, H. & Davis, P. (2003). Teaching a simple, meal

preparation skill to adults with severe and mental retardation using video modeling. Behavioral

Intervention, 18, 209-218.

Robinson, Meghan, "Examining Prerequisite Skills for Learning Through Video Modeling" (2009).

Applied Behavioral Analysis Master's Theses. Paper 11. http://hdl.handle.net/2047/d20000009

Sherer, M., Pierce, K.L., Paredes, S., Kisacky, K. L., Ingersoll, B., & Schreibman, L. (2001).

Enhancing conversation skills in children with autism via video technology. Which is better,

“self” or “other” as a model? Behavior Modification, 25, 140-158.

Tereshko, L., MacDonald, R., & Ahearn, W. H. (2010). Strategies for teaching children with autism to

imitate response chains using video modeling. Research in Autism Spectrum Disorders, 4(3),

479-489.

Weiss, M.J., & Harris, S.L. (2001). Reaching out, joining in: Teaching social skills to young children

with autism. Bethesda, MD: Woodbine House, Inc.


Table 1

Environmental Arrangements and Play Sequences for Each Participant

Participant Materials Present Materials Absent

Cole Faster than a Speeding Frog Sonya Lee and the Super Sundae

Matthew Sonya Lee and the Super Sundae Faster than a Speeding Frog

Charles Faster than a Speeding Frog Sonya Lee and the Super Sundae


Table 2

Summary of Interobserver Agreement (Average and Range) for Script Completion for All

Participants

Participant Dependent Variable Baseline Training Mastery Probes

Cole

Scripted Actions

100%

90%

(range 81-96%)

96%

(range 93-100%)

Scripted Vocalizations 100% 91% (range 83-97%)

98% (range 97-100%)

Matthew

Scripted Actions

87%

(range 85-88%)

91%

(range 86-96%)

93%

(range 89-96%)


95% (range 94-97%)

Charles

Scripted Actions 100% 93% (range 86-96%)

87% (range 86-89%)


97%


Table 3

Summary of Interobserver Agreement (Average and Range) for Attending for All Participants

Participant Dependent Variable Materials Present Materials Absent

Cole

Attending to Video 92% (range 89-95%)

96% (range 94-98%)

Attending to Materials 93% (range 92-95%)

N/A

Attending to Other 97% (range 96-100%)

96% (range 94-98%)

Matthew


99% (range 98-100%)

Attending to Materials 96%

(range 94-98%)

N/A


99% (range 98-100%)

Charles


88% (range 84-90%)


N/A


88% (range 84-90%)


Table 4

Number of Sessions Required to Meet Mastery Criteria for Each Participant in Each Condition

Participant Materials Present Materials Absent

Cole 8 5

Matthew 5 4

Charles 6 9*

*Not mastered


Table 5

Summary Data (Average and Range Across Sessions) for Cole for Attending During Video

Viewing

Materials Present Materials Absent


90% (range 82-97%)


(range 12-25%)

N/A


10% (range 3-18%)


Table 6

Summary Data (Average and Range Across Sessions) for Matthew for Attending During Video

Viewing



99% (range 98-99%)


(range 4-16%) N/A


1% (range 1-2%)


Table 7

Summary Data (Average and Range Across Sessions) for Charles for Attending During Video

Viewing



77% (range 64-88%)


N/A


24% (range 12-36%)


Sessions

Perc

entS

cript

Com

pletio

n

Sd changed

Figure 1. Data for percent script completion across all three participants. Open diamonds

represent the script trained in the materials present condition, and closed squares represent the

script trained in the materials absent condition.


-202468

10121416182022242628

1 2 3 5 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 45 46 64 70

Scrip

ted A

ctio

ns

Sessions

-202468

101214161820222426283032

1 2 3 5 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 45 46 64 70

Scrip

ted V

ocali

zatio

ns

Sessions

Materials PresentMaterials Absent

Baseline Video Viewing No Video


Cole

Figure 2. Number of completed scripted actions and scripted vocalizations for Cole. Open

diamonds represent the script trained in the materials present condition, and closed squares

represent the script trained in the materials absent condition.


-202468

10121416182022242628

4 6 7 8 30 32 34 35 36 37 38 39 40 41 42 43 44 53 69

Scrip

ted A

ctio

ns

Sessions

-202468

101214161820222426283032

4 6 7 8 30 32 34 35 36 37 38 39 40 41 42 43 44 53 69

Scrip

ted V

ocali

zatio

ns

Sessions




Matthew

Figure 3. Number of completed scripted actions and scripted vocalizations for Matthew. Open




-202468

10121416182022242628

9 10 11 12 31 33 47 48 49 50 51 52 54 55 56 57 58 59 60 61 62 63 65 66 67 68

Scrip

ted A

ctio

ns

Sessions

-202468

101214161820222426283032

9 10 11 12 31 33 47 48 49 50 51 52 54 55 56 57 58 59 60 61 62 63 65 66 67 68

Scrip

ted V

ocali

zatio

ns

Sessions


Charles Baseline Video Viewing No Video


Sd changed

Sd changed

Figure 4. Number of completed scripted actions and scripted vocalizations for Charles. Open




0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

14 15 18 19 22 24 26 27

Perc

ent D

urati

on

SessionsAttending to Video Attending to Materials Attending to Other

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

13 16 17 20 21 22 25

Perc

ent D

urati

on

SessionsAttending to Video Attending to Other

Cole

Materials Present

Materials Absent

Figure 5. Percent duration of attending to video, attending to materials, and attending to other

stimuli for Cole across both conditions.


0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

34 36 37 39 42

Perc

ent D

urati

on

Sessions

Attending to Video Attending to Materials Attending to Other

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

35 38 40 41

Perc

ent D

urati

on

Sessions

Attending to Video Attending to Other

Matthew

Materials Present

Materials Absent


stimuli for Matthew across both conditions.


0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

49 51 55 57 58 60 62

Perc

ent D

urati

on

Sessions

Attending to Video Attending to Materials Attending to Other

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

50 52 54 56 59 61 63 65 66

Perc

ent D

urati

on

Sessions

Attending to Video Attending to Other

Charles

Materials Present

Materials Absent


stimuli for Charles across both conditions.


Appendix 1

Script for “Faster than a Speeding Frog”


Appendix 2

Script for “Sonya Lee and the Super Sundae”


Appendix 3

Materials for “Faster than a Speeding Frog” Play Sequence


Appendix 4

Materials for “Sonya and the Super Sundae” Play Sequence


Appendix 5 Scoring Guidelines for “Faster than a Speeding Frog”

Faster Than a Speeding Frog: Action Guidelines General Scoring rules

If a character walks they must contact the ground, they cannot fly Actions are scored + if they are with the wrong character Vehicles must contact the ground, they cannot fly over or be lifted Actions still count if a character/piece is placed somewhere and then falls off Actions can occur out of order from the original script

Crosses street Feet contact the ground, can float or step

Jumps on Eddie’s head Freddie the frog jumps up, and feet contact the top of Eddie’s head

Leapfrogs over Freddie Eddie jumps (can be lifted) over Freddie and lands on the other side

Leapfrogs over Eddie Freddie jumps (can be lifted) over Eddie and lands on the other side

Jumps on spring Eddie’s feet contact the springs, and he bounces upward

Falls down Comes back to ground, contacts the ground either on his back, side or standing

Picks up spring Eddie picks up any of the springs. Child can hang spring on Eddie’s hand or can hold it up in front of him.

Puts springs on feet Child attaches springs to Eddie’s feet, either by holding them on his feet, or by placing the marble in the figurine. Springs do not have to stay attached for whole duration. Mark as + if child attaches springs, even momentarily.

Jumping with springs on feet Jumps at least once with the springs attached to his feet (springs are either held on, or attached by marble)

Does a flip Flips at least once, with or without springs on feet

Lands in cloud upside down Sits on top of cloud, head first Sits in cloud right side up Sits on top of cloud, feet first

Reaches for springs and knocks them down

Springs are on top of the cloud, and then fall out of the cloud. Eddie may or may not touch them. Springs can be brought to the top of the cloud with Eddie, or may be placed on top of cloud separately.

Drives in toward cloud Fire truck moves toward cloud, can float or make contact with ground.

Gets out of truck At least one fireman gets out of his seat

Raises ladder

Child extends ladder to cloud. Ladder may not extend all the way or child may extend truck

Climbs up ladder Fireman moves to the top of the ladder and sits in the yellow seat. Can either float or step up to yellow seat.

Reach toward firefighter Child moves Eddie toward firefighter, tips him toward firefighter, or moves Eddie to the edge of the cloud toward fire truck

Pull down ladder Ladder is put back to its original position

Backs away Fire truck moves away from cloud Jumps, gains attention Frog jumps, or makes some other attention getting response

Takes yo-yo Yo-yo (string or whole thing) goes to frog. Child can lay string on frog, or hold it up in front of the figurine.

Winds up and jumps Jumps next to cloud, but does not land in cloud

Jumps and lands in cloud Sits on top of cloud, body can be in any orientation Ties yo-yo string to cloud Child lays a piece of yo-yo string on cloud

Jumps down holding yo-yo Eddie jumps down to ground with yo-yo and/or Freddie Stands in the middle of his friends Eddie is placed in the middle of his friends

Faster Than a Speeding Frog: Vocal Guidelines General Scoring rules:

Scored as + if it is complete and matches the script. Scored as + if it is a partial vocal (at least 50%) or a paraphrase of a vocal (example: script says “Help us eat the

world biggest ice cream sundae” and student says “Let’s eat the world’s largest ice cream cone”) Student does not have to be holding/manipulating character for + Scored as + if it is with the wrong character Vocals are only counted once, but do not count against student if they repeat them Scored as + if they occur out of order from the original script


Appendix 6

Scoring Guidelines for “Sonya and the Super Sundae”

Sonya Lee and the Super Sundae: Action Guidelines General Scoring rules

If a character walks they must contact the ground, they cannot fly Actions are scored + if they are with the wrong character Vehicles must contact the ground, they cannot fly over or be lifted Actions still count if a character/piece is placed somewhere and then falls off Actions can occur out of order from the original script

Sits in truck Sonya is placed in the driver’s seat of the dump truck

Drive to sand box The truck pulls up to the park and the sandbox from off set Turns around to dump sand Truck turns around so the back side is facing the sandbox

Dumps sand Back of truck tips up and sand pile either falls or is placed on the sandbox Turns to face forward Truck turns around so that the front of the truck is facing the sandbox

Drives away Truck leaves the park scene. Can exit on either side. Walks away Sonya leaves the park scene. Can exit on either side.

Enters on tractor Farmer Jed is in tractor, and tractor is moved toward the sand box Gang sits in tractor At least one of the gang is placed in a tractor seat

Tractor drives toward snow mound Child orients the tractor toward the snow mound, and moves it toward snow Cow jumps in snow Cow bounces or glides at least once along the mound of cotton balls

Cow does a flip in the snow Cow flips at least once in the mound of cotton balls Gang stands in the snow At least one of the gang stands in or next to the mound of cotton balls Farmer stands in the snow Farmer Jed stands in or next to the mound of cotton balls Gang walks over to milk At least one of the gang moves toward the milk, can glide or step Farmer walks over to milk Farmer Jed moves toward the milk, can glide or step

Drive toward snow Sonya and truck enter (can fly in but must be placed on the set, oriented toward snow pile)

Backs up and pushes Backs up and drives forward at least once

Breaks through snow Student can part snow with hands and have the truck drive through or they can use the truck to part the snow

Gang sits in truck and fire truck At least 1 character sits in the truck, rest of the gang can sit in truck or fire truck Put ice cream in truck Ice cream cones are placed in truck or fire truck

Truck - Drive to the middle of town Truck moves to the middle of the town set (can fly in but must be placed on the set)

Fire truck - Drive to the middle of town Fire truck moves to the middle of the town set (can fly in but must be placed on the set)

Put chocolate topping on ice cream Chocolate topping is placed on top of one of the ice creams. Put whipped cream on ice cream White topping is placed on top of one of the ice creams.

Flies in on helicopter Child must lift the helicopter off the ground. Character does not have to be present.

Spin propellers Child must spin the propellers at least once, either when helicopter is on the ground, or when it is in the air.

Drops cherry on ice cream Cherry can be dropped or placed. Must hit the ice cream topping. Does not have to stay placed.

Sonya Lee and the Super Sundae: Vocal Guidelines General Scoring rules:

Scored as + if it is complete and matches the script. Scored as + if it is a partial vocal (at least 50%) or a paraphrase of a vocal (example: script says “Help us eat the

world biggest ice cream sundae” and student says “Let’s eat the world’s largest ice cream cone”) Student does not have to be holding/manipulating character for + Scored as + if it is with the wrong character Vocals are only counted once, but do not count against student if they repeat them Scored as + if they occur out of order from the original script


Appendix 7

Photographs of participant attending to video, attending to materials, and attending to other

stimuli

Attending to video

Attending to materials

Attending to other stimuli

Documents

The effects of material presence versus absence on skill ...557/fulltext.pdf · Garrigan, & Vangala, 2005). Through the video modeling procedure, complex behavior chains can be acquired