Read article and answer 4 questions
- What are the research questions?
- What are the independent and dependent variables?
- Why were these statistical analyses chosen to answer the research questions?
- What are the answers to the questions and how do you know?
A COMPARISON OF VIDEO MODELING, TEXT-BASED
INSTRUCTION, AND NO INSTRUCTION FOR CREATING
MULTIPLE BASELINE GRAPHS IN MICROSOFT EXCEL
BRYAN C. TYNER AND DANIEL M. FIENUP
QUEENS COLLEGE AND THE GRADUATE CENTER, CUNY
Graphing is socially significant for behavior analysts; however, graphing can be difficult to learn.
Video modeling (VM) may be a useful instructional method but lacks evidence for effective
teaching of computer skills. A between-groups design compared the effects of VM, text-based
instruction, and no instruction on graphing performance. Participants who used VM constructed
graphs significantly faster and with fewer errors than those who used text-based instruction or no
instruction. Implications for instruction are discussed.
Key words: video modeling, task analysis, graphing
The ability to analyze graphed data is a socially
significant class of behavior for scientists and
professionals in applied behavior analysis.
Graphs enable visual analysis, interpretation,
and dissemination of behavioral data. Graphs
also facilitate the evaluation of experimental
control, which may enhance treatment evalua-
tion and application (Fahmie & Hanley, 2008).
For these reasons, data organization and graph
design are competencies in the Behavior Analyst
Certification Board (2012) task list; however,
learning to graph can be difficult. Task analyses
(TAs) have been published for a variety of
graphing methods (e.g., Dixon et al., 2009). Task
analyses are typically ordered lists of behavior,
often presented with pictures of relevant stimuli.
Empirical evidence supports the effectiveness of
TAs for graphing instruction. For example,
Dixon et al. (2009) observed that participants
who used an updated TA constructed graphs in
less time and with fewer errors than those who
used a TA for an older version of the software. To
date, no studies have compared text-based TA
instruction to any other instructional format.
The static nature of text may limit outcomes
when one is learning dynamic computer tasks. A
more dynamic instructional approach may be
video modeling (VM): the presentation of target
responses in video format. Video modeling
promotes accurate responding by demonstrating
desired task performance and making relevant
stimuli more salient, and it has been found to be
effective for teaching a variety of target behaviors,
including implementation of behavioral proto-
cols by staff and parents (e.g., Catania, Almeida,
Liu-Constant, & DiGennaro Reed, 2009).
Although VM is prevalent online for a wide
range of computer tasks, its use for complex skill
acquisition with typically developing individuals
is largely underresearched. Because of the
importance of graphing to behavior analysts,
the difficulty of graphing-skill acquisition, and
the lack of research on graphing instruction, the
present study compared the effects of text-based,
video-based, and no instruction on the accuracy
and speed of constructing multiple baseline
graphs.
METHOD
Participants and Setting
Sixty-six undergraduate students participated
and earned extra credit towards their exper-
imental psychology courses in which single-
subject research design and graphing were
competencies. A power analysis, based on data
This research was conducted by the first author in partial
fulfillment of the requirements for a PhD in Psychology
through the Graduate Center, CUNY.
Address correspondence to Daniel M. Fienup, Depart-
ment of Psychology, Queens College, Flushing, New York
11367 (e-mail: daniel.fienup@qc.cuny.edu).
doi: 10.1002/jaba.223
JOURNAL OF APPLIED BEHAVIOR ANALYSIS 2015, 48,
701
–706 NUMBER 3 (FALL)
701
reported in Dixon et al. (2009) revealed that a
sample size of 16 participants per group was
necessary for at least 80% power. In total, 22
participants were randomly assigned to each
group.
Instruction took place in a research lab
containing seven computer work stations, each
equipped with a Windows-based computer that
included a 48.26-cm monitor, keyboard, and
mouse, and Microsoft Excel 2007 spreadsheet
software.
Materials
Previously published TAs (Dixon et al., 2009;
Lo & Konrad, 2007) informed the development
of a TA for constructing multiple baseline graphs
that was then pilot tested with naive and
experienced participants. The final version of
the TA described the steps for making a multiple
baseline graph, including (a) organizing the data
table and inserting the graph, (b) formatting the
data series and chart area, (c) changing axis
values, (d) aligning data points with tic marks, (e)
inserting chart and axis labels and phase-change
lines, (g) stacking and grouping graph panes, and
(h) copying and pasting the graph and all
components as an image for publication sub-
mission purposes.
A tutorial was developed using PowerPoint
presentation software, Windows Media Player,
and Camtasia Studio 7 to present the TA to all
groups in one of three formats: (a) text-based
instruction, (b) video-based instruction, or (c)
no-instruction control. The tutorial first dis-
played a button with the word “Begin” that
recorded the start time of instruction and then
presented the first step of TA. Buttons permitted
navigation backward or forward one slide and to
a table of contents. After the last instructional
slide, a slide presented a button with the words
“I’m done” that recorded the end time of
instruction.
Text-based tutorial. The text-based tutorial
included 41 slides that contained two to 15
sentences each. Twelve slides included screenshot
images of the software menus and the graph in
progress, as described in the tutorial.
Video tutorial. The video tutorial was iden-
tical to the text-based tutorial except the steps of
the TA were narrated in 30-s to 3-min video
segments during a screen-capture video record-
ing of the first author performing each step. The
video zoomed in and out to focus on relevant
stimuli on the screen. Controls were available for
participants to play, pause, fast forward, rewind,
and adjust the volume.
No-instruction control tutorial. The no-in-
struction control tutorial presented the same
slides as the text version, describing conventio
ns
for each graph element; however, text that
described how to accomplish formatting changes
was omitted.
Demographics and social validity questionnaire.
After completing the tutorial, participants
completed a questionnaire regarding their
previous course, computer, and graphing expe-
rience and their acceptability of the goals,
procedures, and outcomes of the tutorial. Social
validity was assessed using a 5-point Likert-type
scale (1 ¼ strongly disagree to 5 ¼ strongly agree).
Dependent Variables
The dependent variables were graphing
accuracy and duration to graph completion.
Graphing accuracy was defined as the number of
graph elements scored correct using a 50-
question checklist of graph components linked
to the steps of the TA. The checklist was tested by
scoring pilot participants’ graphs and was revised
until interobserver agreement on novel graphs
reached at least 90%. Duration to graph
completion was defined as the number of minutes
that passed from the start to end times.
Procedure
A between-groups design compared text,
video, and no-instruction control conditions.
Experimenters used block randomization to
assign participants to groups. Before a partic-
ipant arrived at the laboratory, the researcher
702 BRYAN C. TYNER and DANIEL M. FIENUP
prepared the tutorial so that the “Begin” button
was displayed. The researcher arranged com-
puter desktops with the tutorial on the left side of
the screen and a new spreadsheet open on the
right.
After seating participants at a computer
station, the researcher provided basic instruc-
tions to begin and end the tutorial. No feedback
or instructions for graphing were provided other
than those presented in the tutorial. When
participants completed the graph and clicked the
“I’m done” button, the researcher gave them a
paper copy of the demographics and social
validity questionnaire to complete before leav-
ing. To ensure treatment integrity, researchers
followed procedures according to a script and
checked off each step as it was completed. Self-
reported treatment integrity was 100%.
Interobserver Agreement
A masters-level research assistant independ-
ently coded 33% of all graphs. Items on the
checklist scored by both observers as correct or
incorrect were rated as agreements. Interobserver
agreement was calculated for each graph by
dividing the number of checklist items scored in
agreement by the total number of checklist items
and converting the result to a percentage. Mean
agreement was 94% (SD ¼ 5.11%; range, 82%
to 100%) for all graphs. Only one participant’s
graph scored 82% agreement; all others were
88% or higher.
RESULTS AND DISCUSSION
A one-way ANOVA and chi-square (x2)
statistic indicated no significant differences
between groups in preexisting skills and experi-
ence (courses completed, computer skills, fre-
quency of Excel use, and number of graphs
previously made). Separate one-way ANOVAs
(with post-hoc Tukey’s HSD pairwise compar-
isons) were conducted to evaluate overall differ-
ences between groups in graphing accuracy and
duration.
Figure 1 (top) displays the average number of
graph elements formatted correctly by instruc-
tion group and individual performances. An
overall significant difference was found for
graphing accuracy, F(2, 63) ¼ 15.03, p < .001.
On average, participants who used VM for-
matted significantly more graph elements cor-
rectly compared to those who used text-based
instruction, p ¼ .007, and no instruction,
p < .001. On average, participants who used
text-based instruction formatted more graph
elements correctly compared to no instruction;
however this difference was not significant,
p > .05. Figure 1 (bottom) displays minutes to
graph completion. There was an overall signifi-
cant difference for the duration to complete the
graph, F(2, 63) ¼ 12.41, p < .001. On average,
participants who used VM constructed the graph
in significantly fewer minutes than participants
who used text (p < .026) and no instruction
(p < .001). There was no significant difference in
time between text-based and no instruction
(p > .05).
Table 1 displays social validity data. Questions
1 through 7 were compared using separate one-
way ANOVAs (and Tukey’s HSD), and Question
8 was compared using a x2 test. No differences
were observed between groups on goal-related
questions (Questions 1 and 2). Significant
differences were found for all questions regarding
instructional methods and outcomes, and pair-
wise tests revealed significant differences between
VM and control and between text and no
instruction, but not between VM and text. In
other words, participants in all groups agreed
that graphing skills are important; however,
across all procedure and outcome statements,
participants who completed VM and text
instruction agreed that the procedures were
acceptable and that their performance had
improved. No-instruction participants generally
disagreed with these statements.
The present study extends previous research
that has demonstrated the effectiveness of TA
graphing instruction (Dixon et al., 2009; Lo &
GRAPHING INSTRUCTION 703
Konrad, 2007). The present study found that
participants who received the TA in video format
constructed more accurate graphs in fewer
minutes than participants who received the
same TA as text with images. Performance
differences between VM and text were statisti-
cally significant and differences observed be-
tween text and no instruction were not
significant, demonstrating the relative utility of
VM over text-based instruction for graphing-
skill acquisition. Furthermore, both graphing
accuracy and duration were less variable for
participants who received VM compared to those
who used text and no instruction (Figure 1),
because the scores are distributed much more
closely around the mean for VM than for text
and no instruction. Therefore, VM may produce
more predictable behavior change compared to
Figure 1. The number of correct checklist items (top) and the number of minutes to graph completion (bottom). Black
bars represent group means. Data points represent individual participants’scores. Darker data points represent overlapping
scores.
704 BRYAN C. TYNER and DANIEL M. FIENUP
the other two methods. Generalizations of these
findings to the overall effectiveness of VM may
be premature, however, because this study
compared only these two instructional methods.
This study benefits applied behavior analysis
by providing a novel comparison between two
empirically supported interventions for teaching
typically developing learners a complex skill.
These results may also be useful for guiding
decisions about graphing instruction. Partici-
pants who used VM demonstrated more socially
valid graphing performance. The observed
differences could determine whether a figure is
publishable, interpreted with ease, or understood
correctly. Practitioners who are capable of
quickly graphing a client’s behavior may be
more likely to do so and will be better able to
identify behavior–environment and functional
relations in their client’s behavior (Fahmie &
Hanley, 2008), which may improve treatment
outcomes.
Additional research is needed to clarify the
generality of the reported outcomes. First,
participants’ preexisting graphing skills were
not directly measured. Some students reported
having little to no computer skills or graphing
experience, and pilot data suggested that
completing both pretest and instruction graphs
may be too time intensive. Second, practice
effects threaten internal validity; given enough
time, participants may have learned either
correct or incorrect methods for performing
each step, potentially limiting the degree to
which differences between instructional methods
were detected. Demographic data indicated that
random assignment balanced preexisting com-
puter skills and experience between groups;
however, future research might more directly
measure preexisting skills. A third limitation is
one inherent to any comparison of multiple
treatments: The ideal presentation of each
tutorial is unknown. Future research should
make parametric analyses of both text-based and
video instructions to improve the effectiveness of
both methods.
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GRAPHING INSTRUCTION 705
The present study is one step in the
continuing evaluation of instructional effec-
tiveness for teaching complex tasks to typically
developing adults. The data presented here
may specifically inform decisions regarding
graphing instruction for instructors and stu-
dents of applied behavior analysis. Although
response effort for VM development may
seem high, after it has been completed it is a
permanent product that can be widely dis-
seminated and reused. The long-term invest-
ment may be smaller than apparent and should
be considered when deciding whether perform-
ance differences reported in the present study
justify the increased response effort. Further-
more, free versions of video software are
available that are increasingly simple to use
and often come preinstalled on new computers.
Future research may also publish tutorials for
such software to minimize the response effort
to educators.
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train staff to implement discrete-trial instruction.
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Creating single-subject design graphs in Microsoft Excel
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Received September 10, 2014
Final acceptance May 5, 2015
Action Editor, Mark Dixon
706 BRYAN C. TYNER and DANIEL M. FIENUP
http://www.bacb.com/index.php?page&x003D;100165
http://www.bacb.com/index.php?page&x003D;100165