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Thank you all for the replies! You have given me much to (re)think
about:). I have a few follow-up questions if I may...
1. It was mentioned that a floor or ceiling effect could affect the
interpretation of the results. I do believe that there could have been a
"floor/basement" effects during the pretest. I understand how this can
have an effect on the results, but why only for the interaction and not the
main effects?
2. I have plotted my results a number of different ways and have run
simple effects to see where differences and relationships occur as
suggested. (I wish I could show you the graphs), but let me give you the
means for
test x model (p = .003 N = 82):
Pretest Posttest Gain
Model 16.85 21.13 4.28
No Model 17.05 19.16 2.11
and test x modeling x self-evaluation (p = .023)
Pretest
Posttest Gain
Model/Eval 16.35
21.48 5.13
Model/No Eval 17.41 20.87
3.46
No Model/Eval 15.59 17.78
2.19
No Model/No Eval 16.96 20.17 3.21
These results are for overall performance. I also examined other areas of
performance such as melodic accuracy and tone with similar results for all
areas. I interpreted this to mean that listening to a model may be
effective during "self-evaluation", but not necessarily during "no
self-evaluation". So...the effects of modeling may be more clearly
understood when you combine it with evaluation. Also, there were no
significant effects for Self-Evaluation. Are the following conclusions
correct?
1. The combination of listening to a model and self-evaluation is the most
effective method for improving performance.
2. When performing self-evaluation, listening to a model is more effective
for improving performance than not listening to a model.
3. Listening to a model may not be more effective than not listening to a
model when not performing self-evaluation.
Finally, my last question(#3) ...Could you recommend a good resource that
focusses on interpreting the results of multivariate tests.
Again, thank you all!
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Thank you all for the replies! You have given me much to (re)think
about:). I have a few follow-up questions if I may...
<p>1. It was mentioned that a floor or ceiling effect could affect
the interpretation of the results. I do believe that there could
have been a "floor/basement" effects during the pretest. I understand
how this can have an effect on the results, but why only for the interaction
and not the main effects?
<p>2. I have plotted my results a number of different ways and have
run simple effects to see where differences and relationships occur as
suggested. (I wish I could show you the graphs), but let me give
you the means for
<p>test x model (<i>p </i>= .003 <i>N = 82)</i>:
<p>
Pretest
Posttest
Gain
<p>Model
16.85
21.13
4.28
<br>No Model
17.05
19.16 2.11
<p>and test x modeling x self-evaluation (<i>p </i>= .023)
<p>
Pretest
Posttest
Gain
<br>Model/Eval
16.35
21.48 5.13
<br>Model/No
Eval
17.41
20.87 3.46
<br>No
Model/Eval
15.59
17.78 2.19
<br>No Model/No
Eval
16.96
20.17 3.21
<p>These results are for overall performance. I also examined other
areas of performance such as melodic accuracy and tone with similar results
for all areas. I interpreted this to mean that listening to a model
may be effective during "self-evaluation", but not necessarily during "no
self-evaluation". So...the effects of modeling may be more clearly
understood when you combine it with evaluation. Also, there were
no significant effects for Self-Evaluation. Are the following conclusions
correct?
<p>1. The combination of listening to a model and self-evaluation
is the most effective method for improving performance.
<br>2. When performing self-evaluation, listening to a model is more
effective for improving performance than not listening to a model.
<br>3. Listening to a model may not be more effective than not listening
to a model when not performing self-evaluation.
<p>Finally, my last question(#3) ...Could you recommend a good resource
that focusses on <i>interpreting</i> the results of multivariate tests.
<p>Again, thank you all!
<br>
<br> </html>
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