Observational Learning in Children with Down Syndrome and Developmental Delays: The Effect of Presentation Speed in Videotaped Modelling
Gerald Biederman, Stephen Stepaniuk, Valerie Davey, Kim Raven and Darlene Ahn
Children with severe developmental delays (three with Down syndrome and three with autism as the primary diagnosis) observed a videotaped model performing two basic dressing skills without prompting, verbal or otherwise, or explanation by an instructor. In a within-subjects design, dressing skills that were presented at a relatively slow presentation speed through videotaped modelling were eventually performed better than those presented at a relatively fast speed. These data in combination with evidence from this laboratory that passive modelling of basic skills is more effective than interactive modelling (e.g., Biederman, Fairhall, Raven, Davey, 1998; Biederman, Davey, Ryder, Franchi, 1994; Biederman, Ryder, Davey, Gibson, l991) suggest that standard instructional techniques warrant reexamination both from the basis of instructional effectiveness and the efficient use of the allotment of teacher time.
Biederman GB, Stepaniuk S, Davey VA, Raven K, Ahn D. Observational Learning in Children with Down Syndrome and Developmental Delays: The Effect of Presentation Speed in Videotaped Modelling. Down Syndrome Research and Practice. 1999;6(1);12-18.
doi:10.3104/reports.93
Current instructional strategies for children with severe developmental delays often
include interactive modelling techniques with instructors delivering physical and
verbal guidance and social responses such as "Good job!" or "Good
girl!" intended as rewards for appropriate student behaviour. This is known
as response-contingent prompting (Morgan
& Salzberg, 1992;
Skinner, Adamson, Woodward, Jackson, Atchison, & Mims, 1993). In
interactive modelling, the instructor literally leads the student by the hand so
that the student sees himself or herself as modelling the behaviour (Robertson & Biederman,
1989). Other modelling techniques use passive modelling strategies (Ezell & Goldstein, 1991;
Shelton, Gast, Wolery & Winterling, 1991;
Wolery, Ault, Gast, Doyle & Griffen, 1991). Social learning theory
proposes that learning can occur through simple passive observation of behaviour
(Bandura, 1971). Recent
evidence suggests that passive observational learning may be more effective than
interactive modelling as an instructional technique (Biederman,
Davey, Ryder & Franchi, 1994;
Biederman, Ryder, Davey & Gibson, 1991). In the 1994 study which
used a within-subjects design, children were instructed in life skills under two
conditions. We have discussed the efficacy of within-subjects designs elsewhere
(Robertson
& Biederman, 1989). Briefly, in this technique, two skills are taught
to each child under contrasting instructional arrangements. In the 1994 study, one
skill was actively modelled while the other was passively modelled. For the active
modelling task, half the children received social prompts intended as rewards, while
the remaining children received no verbal or gestural prompting by the instructor.
This study confirmed the 1991 finding that passively modelled tasks were learned
significantly better than actively modelled tasks and also supported the hypothesis
that verbal prompting in active modelling was not helpful for children with severe
delays. More recent evidence (Biederman,
Fairhall, Raven, & Davey, 1998) using the same design as in the 1994
study but with rigorous criteria for the delivery of verbal reinforcement again
showed that this sort of intervention produced learning no better than that in a
passive modelling intervention in a group with Down syndrome and developmental delays.
It has been proposed that attention difficulties or delays in processing inhibit
the formation of associations between behaviour and social responses in active modelling
(Biederman,
et al., 1994). That is, a child may be attending to one aspect of his or
her behaviour and the instructor may be attending to and commenting on another.
When a social reward is delivered under these circumstances, confusion may arise.
It seems useful therefore to consider techniques that focus on passive learning
strategies.
One such passive learning strategy uses observational learning through videotaped
presentation (Hepting
& Goldstein, 1996). In a 63-study meta-analysis of the relevant literature
from 1978, the use of videotaped instruction in classrooms was found to be effective
(McNeil &
Nelson, 1991). Success has also been reported in modifying the social skills
of adolescents with developmental delays (Kelly,
Wildman & Berler, 1980).
Should empirical evidence show in the final analysis that videotaped modelling is
no more effective than live modelling, videotaped modelling would arguably be preferable
to live modelling because videotaped presentations are a less labour-intensive instructional
tool. Videotaped modelling conveys realistic behaviour with complex stimulus and
response routines (Houlihan,
Miltenberger, Trench, Larson, Larson & Vincent, 1995). The effectiveness
of instructional videos in teaching basic life skills to children with developmental
delays is consistent with results from classroom instruction with children without
developmental delays (McNeil
& Nelson, 1991). The participants in this study were able to abstract
the necessary skills from the videotaped model and apply them to task performance.
Children with developmental delays were taught to name food items using a progressive
time delay procedure with an additional stimulus embedded within the discrimination
(Doyle,
Schuster & Meyer, 1996). Finally, videotaped modelling presentation
has a clear advantage for experimentation in that it standardizes instruction which
is a useful control technique (Morgan
& Salzberg, 1992).
Despite the generally positive results from instructional strategies with video
presentations, modelling factors that may optimize the effectiveness of such instruction
have not been systematically addressed (Morgan
& Salzberg, 1992). Basic parameters that are candidates for such examination
are presentation speed, number of repetitions of the modelled behaviour, and duration
of videotaped presentation segments. In fact, few experiments have attempted to
isolate the effects of presentation speed in live modelling conditions. In one study,
varying the rate of verbal passage readings to a faster or slower speed than students'
usual reading rate produced no improvements in reading (Shapiro & McCurdy, 1989;
Skinner et al., 1993). Other studies claim improved accuracy of reading
is directly related to an increased presentation speed (Freeman & McLaughlin, 1984;
Smith, 1979). In live modelling,
experimental control of presentation speed has been limited to audio recordings
with little success.
The present experiment was intended to explore timing parameters in videotaped modelling
of basic skills to children with developmental delays. We used a between-subjects
design to determine whether the number of presentations or duration of the video
presentation are significant factors in such instruction. For half the participants,
the number of repetitions (video loops) of each task presentation was held constant,
while the presentation speed of the video modelling was varied. For the remaining
participants, the overall presentation time was held constant while the number of
repetitions of the modelled skill was varied. Each participant was also exposed
to two videotaped modelling presentations at different rates of speed in a within-subjects
design. This two-task procedure has been used to assess the efficacy of live modelling
variables (e.g.,
Biederman et al., 1991;
Biederman et al., 1994).
Method
Participants
Eight children (7 males, 1 female; 6-10 years of age) from schools in Toronto, Canada
participated. The children were from special education classes and were assessed
by the Metropolitan Toronto Separate School Board as demonstrating pervasive developmental
delay (PDD). Permission was obtained from the Separate School Board for the conduct
of this experiment. Written consent for participation was obtained from the parents
or guardians of each of the children. Participant parameters are given in
Table 1. Inclusion in this study required that each child's skills repertoire
not include any of the skills modelled in the videotapes.
Table 1. Participant age, sex, diagnosis, tasks, and speed
of presentation
|
|
Participant |
Age |
Sex |
Diagnosis |
Task (1:2) |
Speed (1:2) |
Equal Number
of Presentations
Group: |
1 |
8 |
M |
DS/PDD |
L:S |
s:n |
|
2 |
10 |
M |
AU/PDD |
B:L |
n:f |
|
3 |
9 |
M |
DS/PDD |
B:S |
f:n |
|
4 |
8 |
M |
AU/PDD |
B:L |
n:s |
Equal Duration
of Presentations
Group: |
5 |
8 |
F |
PDD |
B:S |
s:n |
|
6 |
7 |
M |
DS/PDD |
S:B |
f:s |
|
7 |
6 |
M |
PDD |
B:S |
f:s |
|
8 |
6 |
M |
AU/PDD |
L:T |
s:n |
AU-autism, PDD-pervasive developmental delay, DS-Down syndrome,
L-lacing,S-snapping, B-buttoning, T-bow tying,
s-slow speed (15 frames/sec.), n-normal speed (30 frames/sec), f-fast speed (45
frames/sec). |
Materials
The apparatus consisted of dressing frames manufactured by Galt Toys (including
snapping, buttoning, and lacing). Videotapes showing the frames and an adult female
model's hands performing the tasks were edited for three different presentation
speeds: slow (15 frames/second), normal (30 frames/second), and fast (45 frames/second).
Videotapes were presented via 20-in colour monitors.
Design
In this experiment, modelling speed effects were assessed using a within-subjects
design in which each subject was instructed in two different skills under different
presentation speeds. That is, one task was modelled at one speed, and the other
was modelled at another speed. Two of three possible speeds were used (15, 30, or
45 frames per second) for each participant. Passive observation was used as the
instructional context. That is subjects watched the videotape without prompting,
verbal or otherwise, or explanation by an instructor. Counterbalancing of the order
of speed-specific skills was arranged.
Procedure
Children were instructed in two of four possible skills, buttoning, snapping, lacing,
and bow tying, through videotaped modelling. The two skills that were shown to each
child were selected through teacher and parent consultation. But none of the children
could perform any of the videotaped skills at the beginning of the experiment as
noted above. The skills were presented by videotape. For four participants (participants
1-4), the number of repetitions for each of the two skills was held constant while
the total presentation time varied. The total presentation time per skill was 7.5
min for the slow speed, 5.0 min for the normal speed, and 2.5 min for the fast speed,
for each training session (total of six sessions). For the remaining four participants
(participants 5-8), the total display time for each skill was held constant at 5.0
min. per session (total of six sessions) while the number of repetitions varied.
The actual number of total repetitions per training session for slow, normal, and
fast speeds, were respectively: 5, 10, and 12.5 for snapping, 3.75, 7.5, and 11.25
for buttoning, 3, 6, and 9 for lacing, and 2.7, 5.3, and 8 for bow tying.
Table
1 gives the videotape presentation speeds for the two skills for each participant.
Each child was removed from his or her classroom and, in a quiet room, seated in
a chair facing a video monitor and simply asked to watch. During the instructional
sessions no experimenter prompting occurred. The training sessions lasted 20-30
min each day for six daily sessions, counterbalancing for task order. Testing occurred
on the first day following the final training session and consisted of the child's
first physical contact with the appropriate dressing frame. Participants were asked
to perform each of the two skills without further instruction, demonstration, or
prompting. Performance was videotaped for later evaluation.
Performance Evaluation
Participant performance was rated by multiple judges viewing videotaped segments
of participant behaviour in a method described by Biederman et al., (1991). The
videotaped performances by the participants were edited to 30-sec segments for each
skill. The editor was unaware of modelling condition or group assignment. Subject
number and task identification letters (A or B) were superimposed in black letters
over a white background for 10 sec prior to each 30-sec segment.
The raters were undergraduate psychology students (N=31) at the University of Toronto
at Scarborough. Written instructions with rating examples were provided and any
questions were answered. Raters were untrained and blind to hypotheses and variables
in the study. Video presentations were randomized for participant and task order.
The advantages of the use of untrained raters has been described elsewhere (Biederman
et al., 1994). Briefly, the judges were instructed to view these behaviours
from the perspective of "a person in the street," on the assumption that
if significant relative differences in the quality of performance in the two tasks
occurred, these differences should be apparent to anyone and not as a subtle (and
perhaps minor) difference detectable only to a specialist. Raters were otherwise
untrained and unaware of the purpose of the study. The use of untrained judges and
their effective equivalence to trained judges has been described by Wallander, Conger,
and Ward (1983). It is interesting to speculate that untrained raters are likely
to be, in effect, more conservative than trained raters. The latter might see important
small differences in behaviour and rate the performances as more different than
would untrained raters who are likely to notice only large differences. Possible
issues are (1) whether there is any bias introduced into the raters' judgements
about the relative merits of the two tasks they judge for each child, and (2) whether
the raters are competent to detect differential performance between tasks: Counterbalancing
of the order of type of task first seen by the raters, randomizing the order in
which videotapes of the children are seen, and lack of knowledge by the raters of
the prior training history of each of the skills make it extremely unlikely that
any systematic bias was introduced into the ratings. We have evidence that the raters
are competent to judge differential performance through control data in Biederman
et al. (1991), where untrained skills not in the repertoire of control subjects
were compared with skills already in their repertoire. Untrained judges are easily
able to discriminate between these performances which is appropriately reflected
in the difference scores of their ratings (Biederman
et al., 1991, Fig. 1, p.178). The statistical safety inherent in large numbers
of raters is perhaps obvious, but the uniformity of the raters' judgments must be
assessed to confirm the validity of this approach in determining instructional efficacy
(cf. Aiken, 1985; Roff,
1981; Seiz, 1982). The
uniformity of raters' judgments in both Biederman et al. (1991) and Biederman et
al. (1994) meet strict tests of reliability (cf.
Weiner, 1971;
Shrout and Fleiss, 1979).
Rating Instructions
Raters were instructed to follow rating instructions read aloud by an investigator
and printed on sheets distributed to the raters:
On the video monitor directly in front of you, you will see children performing
two tasks each (labelled TASK A and TASK B, respectively). On the rating sheet given
to you, indicate your judgement of the relative performance quality of the two tasks
that you will see. Place a mark at the place which represents your opinion of the
relative quality of the performance of the two tasks. Please wait until you have
seen both tasks performed before you form an opinion.
CHILD 1: TASK A TASK B
_______ _______ _______ _______ ___X___
This rating would mean TASK B was much better than A;
CHILD 2: TASK A TASK B
_______ ___X___ _______ _______ _______
This rating would mean TASK A was somewhat better than B;
CHILD 3: TASK A TASK B
_______ _______ ___X___ _______ _______
This rating would mean that TASK A and B were performed equally well.
Results and Discussion
Interrater reliability was calculated using analysis of variance (ANOVA) according
to a method described by Weiner (1971) and
Shrout and Fleiss (1979). The interrater
reliability was consistent with previous studies from this laboratory (R=0.97, p<0.05)
(Aiken, 1985; Biederman,
et al., 1991 &1994;
Seiz, 1982). The value
of the effective reliability of judges (R) shows that judges as a group were very
reliable in assessing relative task differences. Figure 1 shows the mean of the
judges' ratings giving their assessments of the relative performance quality for
the two skills for each participant. One purpose of this study was to contrast videotaped
modelling under conditions which permitted the total number of presentations to
vary with conditions which permitted the total exposure time to vary. However, it
became necessary to exclude participants 7 and 8 from statistical evaluation when,
during the course of training, the experimenter learned that they were incapable
of the level of manipulation required for inclusion in this study. The relative
performance ratings for participants 7 and 8 are consistent with their failure to
manipulate either of their tasks on test and may be considered as control ratings
(see Figure 1). When the mean ratings of participants 1-4 (number of presentations
equalized) are compared with the ratings of the remaining two participants (duration
of presentation equalized), the participants in the former group show higher ratings
for their slower-presented skill, t(4)=1.21, but the comparison fails to reach the
value required for statistical significance at the conventional alpha level of .05
[t(4)=2.78, two-tailed]. However, the direction of the finding suggests that these
factors should be considered for future research.

Figure 1. The mean of the judges' ratings for each child. A rating
greater than 0.0 indicates better performance on the faster modelled
task and a rating less than 0.0 indicates better performance on the
slower modelled task, on a 5-point scale. Vertical lines depict standard
errors of the means.
Combining data from the remaining six participants, a paired samples t-test for
differences between relatively slower and faster presentation speeds showed that
performance of skills modelled under slower speeds were rated significantly better
than those modelled under faster speeds, t(5)=2.64, p< 0.05.
In addition to the finding that relatively slower speeds of videotaped presentation
of skills modelling to children with Down syndrome and developmental delays significantly
improved the eventual performance of such tasks, the results of this experiment
are also consistent with the use of observational learning without verbal prompting
intended as reinforcement as in
Biederman, et al. (1994). These data suggest that
better learning may result by permitting children with severe delays sufficient
time to process observational information. It further reinforces the view that standard
classroom instruction and individual instruction using interactive modelling strategies
may be less efficient than simple observational arrangements for children with severe
delays. Our evidence suggests that video presentation of modelled skills at an appropriate
speed has potential as a powerful instructional medium which could have interesting
implications for teachers and clinicians in group contexts. Information that different
speeds of video presentation may be differentially effective for children with and
without developmental delays presents clear challenges for instruction in inclusive,
mixed-ability setting.
Acknowledgement
Supported by a grant to GBB from the Social Science and Humanities Research Council
of Canada. The authors are grateful to the students, teachers, and parents of the
Metropolitan Toronto Separate School Board who participated in this study and to
Mr. Trevor Wilson of the Board for his advice and assistance in facilitating this
research. The authors thank the anonymous reviewers for respectively pointing out
an omission concerning the pre-instructional performance levels of the children
and for suggesting some additional implications of this research.
Correspondence
G.B. Biederman, Division of Life Sciences, University of Toronto at Scarborough,
Scarborough, Ontario, Canada, M1C 1A4. (Tel: 416 287 7433, Fax: 416 287 7642, E-mail:
bieder@scar.utoronto.ca)
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