The Impact of Positive Mood on Learning
Author(s): Tanis Bryan, Sarup Mathur, Karen Sullivan
Source: Learning Disability Quarterly, Vol. 19, No. 3 (Summer, 1996), pp. 153-162
Published by: Council for Learning Disabilities
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THE IMPACTOF POSITIVE
MOOD ON LEARNING
Tanis Bryan, Sarup Mathur, and Karen Sullivan
Abstract. The primary intent of this study was to examine the effects of a brief
positive mood induction on a learning task that stimulates beginning reading acquisition. A secondary intent was to examine the durability of this effect across a period of two weeks. Sixty students, half average-achieving and half with learning disabilities, were randomly assigned to either a positive or a neutral mood induction
condition. In an effort to control for the effects of prior knowledge, all students received instruction in elementary Hindi language on a series of five tasks. After two
weeks, the instruction and tasks were readministered. The results of a MANCOVA
indicated that both groups of students in the positive mood condition performed
better than those in the neutral condition, although not statistically so. However,
gain scores indicated that across a two-week period, students with learning disabilities in the positive condition performed significantly better than students with
learning disabilities in the neutral condition.
BACKGROUND
affect
has been one part of triparHistorically,
tite models of the mind along with cognition
(thinking)and conation (motivation and behavior) (Isen, 1984). This multifaceted perspective
representing the tripartite nature of behavior
dates back at least as far as the third century
B.C., when the Greek physician Erastratosused
psychophysiological observations, such as the
disruption of a regular heart beat in a young
man when his stepmother visited, to isolate the
social cause of the individual's malady "lovesickness"(Mesulam& Perry, 1972).
However, the empirical discipline of psychology operated until recently on the implicit assumption that cognition, conation, and affect
could be adequately studied in separation from
each other. In addition, the behavioristand cognitive models that have dominated psychological
and educational research for the past several
decades share one common characteristic:neither attributesmuch importance to the study of
affective processes and reactions (Forgas, 1991).
In the past 10 years, however, theorists have
proposed a reintegrationof affect into research
on cognition and behavior. For example, in an
influentialpaper, Zajonc (1980) argued that affective reactions are often primaryto, and may
precede, cognitive processing. Zajonc's work
stimulatedgreat interest in research on the interface of affect and cognition in various areas of
cognitive psychology and social psychology.
One of the problems in studyingaffective phenomena has been to arrive at a definition of
what emotion, affect, and related terms mean
(Frijda,1986). In general, the term "emotion"is
used to describe strong feelings that interruptongoing behaviors, result in specific actions, and
involve physiological arousal (Isen, 1984). Emotions are intense, short-lived,and usuallyhave a
TANIS BRYAN, Ph.D., is Professor Emeritus,
University of Illinois at Chicago, and Adjunct
Professor,Arizona State University.
SARUP MATHUR, Ph.D., is Faculty Research
Associate, Arizona State University.
KAREN W SULLIVAN, Ph.D., is Faculty Research Associate, Arizona State University.
Volume 19, Summer 1996
153
definite cause and clear cognitive content (e.g.,
annoyance, anger, or fear). In contrast, "mood"
is used to describe low intensity and relatively
enduring affective states with no immediately
salient antecedent cause and little cognitive content (e.g., feeling good or feeling bad; Forgas,
1991). Affective states "gentlycolor and redirect
ongoing thought and actions, influencing what
will happen next but almost without notice and
certainlywithout ostensibly changing the context
or basic activity"(Isen, 1984, pp. 186-187). It is
clear that the mechanisms that mediate between
affective states and the cognitive processes involved in learning, performance, and behavior
are of criticalimportanceboth in our privateand
our working lives (Forgas, 1991).
Although learning disabilities have been defined primarilyas deficits in informationprocessing, recent research has found that childrenand
adultswith learning disabilitiesexperience significantly more negative and depressed affect than
their nondisabled counterparts. Specifically,
these individuals report more minor somatic
complaints associated with feelings of anxiety
and stress (Margalit& Raviv, 1984); greater test
anxiety (Bryan,Sonnefeld, & Grabowski,1983);
and more depression (Maag& Behrens, 1989).
Rourke and colleagues (cf., Ozols & Rourke,
1985) have argued that there is a subtype of
children with nonverbal learning disabilitieswho
are vulnerableto problems in the affective and
social domains. These children are described as
being at risk for adolescent and adult depression
and suicide (Rourke,Young, & Leenaars, 1989).
Recently, Duane (1993) reported on eight subjects in mid- to late adulthood with evidence of
right-hemispheredysfunctions. Each subject described a sense of chronic emotional unrest with
periodsof depression;however,only one had previously been treated with psychotropic medication. Six of the eight had elevated depression or
anxiety scores. Further,Peck (1985) reportedthat
50% of children under age 15 who committed
suicide in Los Angeles County over a three-year
period had been diagnosed as learningdisabled.
It is not known whether findings of increased
depression and anxiety among children and
adults with learning disabilitiesare "reflectiveof
chronic frustration,innate biologic risk related to
anomalous CNS development or the genetics of
emotion noted in the family history" (Duane,
1993, p. 7). What is known, however, is that
154
Learning Disability Quarterly
there are important relationshipsbetween affect
and cognitive processes. Thus, the accuracy and
efficiency of thinking processes, perceptions,
and behavior are significantly influenced by affective states, even mild and transientones.
Negative affective states, for example, have
been found to produce low-effort processing of
informationand the use of less complex semantic
processing strategies (Ellis, Thomas, & Rodriguez, 1984) and lower cognitive processing effort (Leight& Ellis, 1981).
In contrast, positive affective states have been
found to increase memory on various tasks
(Potts, Morse, Felleman, & Masters, 1986); mastery of a discriminationtask (Masters,Barden, &
Ford, 1979); altruism(Isen& Levine, 1972); and
child compliance (Lay, Waters, & Park, 1989).
Positive affect has also been shown to facilitate
complex cognitive functions that require flexibility, integration,and utilizationof cognitive material (e.g., word association and memory, creativity, and problem-solving).In general, in studies of
children, positive affect has shown a facilitating
impact on memory, learning and behavior,
whereas negative affect has a depressingimpact.
The physiological relationshipsbetween negative and positive affect and cognitive processes
are largely unknown. However, Schwartz (1993)
reported that electroencephalographresearch by
Ekmanhas linkedspecific patterns of brainactivity with smiling and positive affect. This pattern
of brain activity could be self-inducedby having
subjects show a "sincere" smile, defined as a
smile that involves contractions of eye and
mouth muscles at the same time. It may be possible for an individualto choose when to generate some of the physiologicalchanges that occur
duringemotion by making the appropriatefacial
expression (Schwartz,1993).
A varietyof methods have been used to induce
positive and negative moods: having subjects
read self-statements (Velten, 1968); distributing
cookies (Isen& Levine, 1972); inducinghypnotic
states (Bower & Mayer, 1985); spraying a room
with an air freshener (Baron, 1990); planting a
dime in a phone booth (Isen & Levine, 1972);
and giving a small amount of change (Isen,Horn,
& Rosenhan, 1973).
Most of the studies involving children have
used a self-generatedvisualizationmethod to induce moods. Childrenwere asked to close their
eyes and think of something that makes them
happy or sad for periods ranging from 30 seconds to 2 minutes. Other studies used cartoons,
movies, reading stories, or manipulatedwinning
and losing scores on a game to induce moods.
A number of studies have employed the selfgenerated visualization technique with students
with learning disabilitiesand students at risk for
referral to special education. The performance
of children in self-generated positive moods was
contrasted with that of students in a neutral
mood generated by having students close their
eyes and count to themselves from 1 to 50.
Bryan and Bryan (1991a) employed students
identifiedby teachers as being at risk for referral
because of reading or math problems. The task
involved learning five survivalvocabularywords.
Childrenin the positive mood condition learned
more words than children in the neutral condition. Two studies (Bryan & Bryan, 1991a,
1991b) examined the impact of mood induction
on the performance of addition and subtraction
problems. In one study, subjectswere childrenat
risk for referral;in the other study, subjectswere
third- through eleventh-grade students with severe learning disabilities attending a private
school for students with learning disabilities.The
results of both studies showed that students in
the positive mood computed more problems
accurately than students in the neutral mood
condition.
Yasutakeand Bryan (1995) used a short-term
memory (digit span) task with first- and secondgrade students with severe learning disabilities.
The results showed that students performed better in the positive than in the neutral condition.
Similarly, using a listening comprehension task
with students classified as high or low readers,
Bryan, Yasutake, and Binstock (in preparation)
found that good readers benefited much more
than poor readers from the positive mood induction. Across these studies, self-generated positive moods have resulted in positive consequences.
Not yet tested, however, is whether positive
consequences would be found for tasks that require new learning, such as learning to read.
The studies conducted to date in this area have
used fairlysimple tasks, such as learning five vocabulary words (Bryan & Bryan, 1991a); a
short-term memory task (Yasutake & Bryan,
1995); and the WISC-R Coding subtest (Yasutake & Bryan, in press). These tasks do not cap-
ture the processing involved in beginning reading acquisition,however.
Because these studies have had positive effects, we believe it is important to test whether
self-generatedpositive moods facilitateacademic
learning; for instance, learning to read. If so, induced positive affect could be employed as a
classroom strategy. However, the transferability
of this strategy to academic tasks has to be
demonstratedbefore its adoption can be recommended.
One purpose of the study reported here was
to examine the impact of self-induced positive
versus neutralaffect on a learning task that stimulated beginning reading acquisition. Second,
since the durabilityof positive mood effects has
not been examined, we examined the impact of
positive moods on a posttest of learning conducted two weeks after the initial instructional
session.
METHOD
Design
The study was a 2 (group: LD-learning disabled placement, regular education placement)
by 2 (condition: positive, neutral mood) unbalanced factorialdesign (Overall& Spiegel, 1969).
Setting
The setting was three middle schools in a suburb of Phoenix, Arizona. The school population
includedchildrenfrom parents of low to high socioeconomic status.
Subjects
The total sample population was 66 students.
Subjects included 28 students (14 males and 14
females) in 7th grade who had been classifiedby
the school districtas having learning disabilities.
The males' mean age was 13.07, SD .73; the
females' mean age was 12.92, SD .47.
In this school districtstudents are classifiedas
having learning disabilitiesif they are of average
intelligenceand have academic achievement that
is at least one grade below grade level in several
areas. Further,the discrepancy between intelligence and achievement must not be due primarily to environmental, cultural, behavioral, or
speech-language factors, though these may be
secondary contributingfactors. The mean Iowa
Test of Basic Skills (ITBS) Reading score for
males was 63.57, SD 11.06. For females the
mean ITBS Reading score was 58.71, SD
13.27. The mean ITBS Language score was
Volume 19, Summer 1996
155
53.2, SD 12.81 for males; for females, the
mean was 55.14, SD 14.20.
The group withoutlearningdisabilitiesincluded
38 7th-grade students, 22 males, 16 females.
The mean age of the males was 12.71, SD. 56;
the mean age for the girls was 12.56, SD .51.
Only students who were not experiencing learning difficulties or were not at risk for learning
problems as indicated by teacher observations
were includedin the nondisabledgroup.
The mean ITBS Reading score for males was
76.68, SD 16.09; for females, the mean was
83.81, SD 13.92. The mean ITBS Language
score for males was 74.86, SD 14.36; for females, the mean was 80.00, SD 15.72. Table 1
represents the subjects' age and ITBS Reading
and Language scores by conditions and placements.
Task
A major concern in conducting a study of
learning is to ensure that prior knowledge does
not make the experimental task easier for some
subjectsthan others. To control for students' entry-levelskillsand knowledge, therefore, we constructed a series of tasks in which students
learned to sight read a set of Hindi nouns and
verbs.
Task 1. Students were shown a series of five
cards. Each card showed a pictureof a noun and
its Hindi transcription (e.g., girl-larki,
boy-larka). As the experimenterpresented each
card to the subject,she said the noun and the student repeated it. Students were told the English
translationof each noun (e.g., "InEnglishKhargosh means rabbit. This is how khargosh is written in Hindi").This process was repeatedtwice.
UI
Table 1
Subjects' Age and ITBS Reading
Placements
Boys N
Age
Reading
ITBS
Language
ITBS
LD Neutral
6
Language
ITBS
156
by Conditions
Non-LD Neutral
10
and
Non-LD Positive
12
mean
13.16
mean
13.00
mean
12.60
mean
12.81
0.98
12.00
14.00
68.00
6.29
60.00
75.00
55.00
13.90
43.00
81.99
SD
min
max
mean
SD
min
max
mean
SD
min
max
0.53
12.00
14.00
60.25
13.87
40.00
82.00
51.87
12.73
37.00
73.00
SD
min
max
mean
SD
min
max
mean
SD
min
max
0.51
12.00
13.00
68.90
14.24
50.00
97.00
71.20
15.98
42.00
96.00
SD
min
max
mean
SD
min
max
mean
SD
min
max
0.60
12.00
14.00
83.16
15.08
66.00
110.00
77.91
12.74
63.00
100.00
12.87
0.37
12.00
13.00
51.28
14.20
40.00
80.00
54.71
18.93
32.00
89.00
mean
SD
13.00
0.57
12.00
14.00
66.14
7.15
53.00
73.00
55.57
8.84
47.00
72.00
mean
SD
12.75
0.46
12.00
13.00
76.75
14.57
53.00
93.00
77.87
20.41
42.00
102.00
mean
SD
7
mean
SD
min
max
Reading
ITBS
LD Positive
8
Scores
SD
min
max
mean
SD
min
max
mean
SD
min
max
Girls N
Age
and Language
mean
SD
min
max
mean
SD
min
max
Learning Disability Quarterly
7
min
max
mean
SD
min
max
mean
SD
min
max
8
min
max
mean
SD
min
max
mean
SD
min
max
8
12.37
0.51
min
12.00
max
13.00
mean 90.87
SD
9.43
min
76.00
max 106.00
mean 82.12
SD
10.13
min
60.00
max 93.00
On the second trial, the student was asked to
translatethe Hindiwords into English.Then, with
the five cards face up on the table, the experimenter said each word in Hindi and the student
pointed to the correspondingcard. Studentswere
scored for the number of nouns identified correctly(0 to 5).
On this and subsequent tasks, students were
given a 10 second wait time to respond. If the
student did not respond within 10 seconds, the
experimenter moved to the next word or task.
Students received no feedback during the tasks.
At the end of each task, however, the student
was told, "Youdid reallywell. A lot of kids find it
hard."
Task 2. On this task a set of five verbs were
taught using the same procedures as in Task 1.
Students were scored for the number of verbs
correctlyidentified(0 to 5).
Task 3. The five noun and the five verb cards
were displayed on the table with the nouns in a
row above the verbs. The experimentermodeled
the task by saying a two-word, noun-verb sentence, pointingto the noun from the top row and
the verb from the bottom row. The experimenter
then uttered 10 two-wordsentences and the student pointed to the noun-verbcards represented
in each sentence. Students'scores were based on
the number of correctly identified nouns and
verbsused in the 10 sentences (0 to 20).
Task 4. The cards were now removed. The
experimenter uttered 10 two-word, noun-verb
sentences, which the student translatedinto English. Scores were the number of correctlytranslated words (0 to 20).
Task 5. The 10 cards were shuffled and
spread out on the table. The experimenter
pointed to each card and the student read the
Hindi word for each. Scores were the number of
words correctlytranslated(0 to 10).
Procedures
Subjects with and without learning disabilities
were randomlyassigned to one of the two mood
induction conditions (positive, neutral).Students
were individuallybrought to a vacant classroom
in the school. To avoid experimenter bias, the
three graduate assistants who served as the experimenters were "blind"to the subjects' mood
assignment.
One of the co-investigatorsserved as the mood
inductor for all students. In the positive mood
condition, studentswere asked to close their eyes
and think of a happy moment in their lives for 45
seconds. In the neutral mood condition, subjects
were asked to close their eyes and count silently
from 1 to 50 for 45 seconds. The mood inductor
then left the room, and one of the graduateassistants entered and taughtthe tasks.
To check on the mood induction,the co-investigator returnedat the end of the session to ask
students in the positive mood condition, "What
did you think." Students were asked to share
their thoughts only if they wished to, and their
responses were recorded. Students in the neutral
mood condition were asked how high they had
counted.
Follow-up test. Two weeks later, students
were individually retested using the same five
tasks and like experimental conditions. At this
time, there was no mood induction.
RESULTS
The study was a factorialdesign that included
two placements (students with learning disabilities and nonlearning disabled students) by two
affect conditions (positive and neutral) across
two administrationsof a series of five learning
tasks designed to measure students' abilityto recall Hindi language nouns and verbs.
The data set consisted of the dependent measures: results of five learning tasks and totals
from the initial testing, results of the follow-up
retesting two weeks later, and totals - gain
scores (the difference between the totals of the
initial testing and the follow-up testing) - and
specific demographicdata.
Initial examination of the data indicated that
students with learning disabilitiesin the positive
condition outperformed their LD peers in the
neutral condition on three of the five subtests
during the first testing, on four of the five subtests in the follow-up testing, and on the total
scores of both initial and follow-up tests. Nonlearning disabled students in the positive condition outperformed their NLD peers in the neutral condition on all five subtests on initial
testing, but failed to outperform them on all but
one of the follow-uptests.
Total-score performance for NLD students in
the positive condition was greater than that of
NLD students in the neutral condition. Further,
NLD students outperformed students in LD
placements on all tasks, both in the initialand follow-up testing sessions. Table 2 presents the
Volume 19, Summer 1996
157
UII
Table 2
Means and Standard Deviations of Scores on Five Hindi Language
Total Scores for Initial and Follow-Up Tests
Task
Task 1 Mean
SD
Task 2 Mean
SD
Task 3 Mean
SD
Task 4 Mean
SD
Task 5 Mean
SD
TOTALMean
SD
GAINS Mean
SD
LD-N
2.93
1.03
1.46
1.30
8.26
4.46
6.66
5.55
1.86
1.06
21.20
12.13
Initial Test
LD-P
NLD-N
2.67
3.76
1.53
1.71
1.66
2.07
1.12
1.50
10.26
11.84
4.53
3.76
8.20
10.92
3.82
4.09
2.93
1.46
1.68
1.89
24.06
30.76
10.32
11.17
means and standarddeviations of LD and NLD
students in positive and neutralconditionson initial and follow-uptesting, as well as gain scores.
Data analysis was conducted at three levels.
The first level of analysis examined the data set
with respect to potential effects of the categorical variables of age, gender, experimenter,
school, and reading and language ability as reflected by ITBS scores. Table 1 presents the
means and standard deviations for Age and
ITBS Reading and Language scores. Had the results yielded significantp values for any of these
variables, they would have been included in a
MANCOVAas covariates, hence controlling for
the effects of these categorical variables. However, since none of these factors was found to
be significant,they were not used as covariates.
As random sample selection was not possible,
the total test score was used as a covariate in an
effort to control for possible sample bias. Separate Multivariate Analyses of Covariance
(MANCOVAs)were then used to test the effects
of condition and placement on the dependent
measures of the initialand follow-uptests.
The results of the MANCOVA of the initial
testing revealed no significant main effects for
158
Learning Disability Quarterly
NLD-P
3.85
0.94
2.64
1.83
13.21
3.19
12.35
2.62
3.92
1.68
35.92
6.34
LD-N
3.64
1.33
2.57
1.33
11.07
4.32
8.42
5.24
3.14
2.47
28.64
12.25
6.92
6.30
Tasks and
Follow-Up
LD-P
NLD-N
4.20
4.76
1.08
0.59
2.06
3.92
1.11
1.25
12.20
16.69
4.52
3.32
11.93
16.61
5.00
4.68
4.13
7.23
1.90
2.16
34.67
49.23
12.12
10.78
10.60
18.46
11.83
6.73
NLD-P
4.57
0.76
3.50
1.09
16.87
2.21
16.21
2.42
6.37
1.98
47.50
5.41
11.57
6.48
placement or condition and no interaction between condition and placement. Even though
initial review of the data indicated that students
in the positive condition as well as students in
regulareducation placement achieved higher total scores, these differences were not found to
be statisticallydifferent.
MANCOVAresults of the follow-up tests indicated a highly significant main effect for placement, Wilks'Lambda= 0.729, F(5,47) = 3.502,
p < .0009. UnivariateF tests for the five individual tasks are presented in Table 3. As shown,
students in regular education settings outperformed students in LD placements on four out of
the five tasks. No main effect was noted for condition. However, a significantinteractionwas indicated between placement and condition, Wilks'
Lambda= 0.788, F(5,47) = 2.526, p < .042.
UnivariateF tests for the five individualtasks
are presented in Table 4. Three out of the five
tasks showed significantor marginallysignificant
interactionsbetween placement and condition.
The third level of analysis involved examining
the gain score, or difference between the total
scores on the initialand follow-up tests. Table 2
presents the means and standard deviations of
the gain scores by placement and condition. A
one-way Analysis of Covariance (ANCOVA)was
performed. The initialtest total of five tasks was
used as a covariateto attempt to control for bias
as in the previouslyreported MANCOVA.Table
5 is a source table for the results of this
ANCOVA. A significant main effect was found
for placement as well as a significantinteraction
between placement and condition.
In order to ascertain the nature of this interaction, a Tukey's HSD post-hoc test of significance was conducted. Results indicatedthat students in LD placements in the positive condition
significantly outperformed students with LD in
the neutralcondition, p < .000.
Verification of moods found that all but two
studentsin the positive condition reportedhaving
happy thoughts. Specifically,they reportedthinking about passing school, music, dance, going
out with friends, "my cat Oliver,"and so forth.
One student said he could not think of anything,
and one said he didn't know what his thoughts
were. With the exception of these students, it appears that the inductionmethod used was effective in inducingpositive thoughts by students.
DISCUSSION
The most interesting and importantfinding of
this study is the impact of positive mood on the
performance of the students with learning dis-
abilities on the follow-up test conducted two
weeks after the original learning experience.
Thus, examination of group means on the initial
and follow-up tests revealed that LD students in
the positive conditions performed better than
their LD peers in the neutral condition. The differences on the initial testing were not statistically different, but on the posttest students with
learning disabilities significantly outperformed
their LD peers in the neutralcondition. Hence, it
appears that the positive mood induction, carried out two weeks prior to the posttest, may
have increased the differences between the students with learning disabilities.
This interaction effect may be considered a
sleeper effect, in which the results of instruction
are not immediatelydemonstratedbut appear at
some later time. A sleeper effect was also found
by Bay, Stavers, Bryan, and Hale (1992), who
compared immediate learning and generalization
of science learning among students with learning
disabilitiesand average-achievingstudents under
two instructionalstrategies. No group differences
were found on the immediate test, but the students with learning disabilitiesperformed significantly better on the posttest of generalization
under one of the teaching strategies. In this
study, as in Bay et al. (1992), the effects of the
teaching strategies would not have been found if
posttest resultshad not been examined.
Table 3
Follow-Up Test - Univariate F Tests of Placement
Univariate F Tests
Variable
Task1
Error
Task2
Error
Task3
Error
Task4
Error
Task5
Error
SS
1.403
43.646
12.754
67.674
78.019
420.286
118.838
622.169
35.759
151.281
DF
1
51
1
51
1
51
1
51
1
51
Effect for Five Tasks
MS
1.403
0.856
12.754
1.327
78.019
8.241
118.838
12.199
35.759
2.966
F
1.640
P
0.206
9.611
0.003**
9.467
0.003**
9.741
0.003**
12.055
0.001**
**p< .01.
Volume 19, Summer 1996
159
I
Table 4
Follow-Up Test - Univariate F Tests of Placement
Five Tasks
Univariate F Tests
Variable
Task1
Error
Task2
Error
Task3
Error
Task4
Error
Task5
Error
SS
2.568
43.646
0.209
67.674
9.186
420.286
76.550
622.169
17.210
151.281
DF
1
51
1
51
1
51
1
51
1
51
by Condition Interaction for
MS
2.568
0.856
0.209
1.327
9.186
8.241
76.550
12.199
17.210
2.966
F
3.001
P
0.089
0.157
0.693
1.115
0.296
6.275
0.015*
5.802
0.020*
*p < .05.
L
Table 5
Source Table: Analysis of Covariance for Gain Scores
Analysis of Variance
Source
Condition
Placement
Condition
*Placement
Pretotal
Error
I
SS
4.092
925.722
DF
1
1
MS
4.092
925.722
F
0.071
16.044
P
0.791
0.000**
331.612
2847.658
2942.698
1
1
51
331.612
2847.658
57.700
5.747
49.353
0.020*
0.000
*p < .05. **p< .01.
II
How do we explain this "sleeper"effect? Isen
(1987) suggested that it is easier to recall and
utilize material in memory under the influence
of a positive mood state; that is, that positive
affect results in a more efficient utilization of
cognitive material than neutral or negative
moods. Because of evidence showing that positive affect facilitates complex cognitive functions requiringflexibility,integration, and utilization of cognitive material such as memory,
categorization, creative problem-solving, deci160
Learning Disability Quarterly
sion-making and learning, it is reasonable to assume that it also affects underlyingcognitive organization (Isen, 1987). Positive affect may influence cognitive organization such that
cognitive materialis more integratedand related
than might occur without the influence of positive affect. Although clearly hypothetical, we
suggest that somehow, perhaps through rehearsal, positive moods induced students with
learning disabilities to organize the material in
memory for better recall.
Earlierstudies have reported main effects for
induced positive moods on the learning and performance of students with learning disabilities
(e.g., Bryan & Bryan, 1991a, 1991b; Yasutake
& Bryan, in press). Two exceptions have been
reported. For example, Yasutake and Bryan (in
press) found that students in the neutral mood
condition did better than students in the positive
mood condition on the Woodcock-Johnson
(1978) math computation subtest. Bryan, Yasutake, and Binstock (in preparation) found that
good readers outperformed poor readers on a
listening comprehension task.
We believe that the math computationsubtest,
the listening comprehension, and the Hindi
reading tasks used in the present study were
more difficultfor students than the tasks in the
other affect studies. On the Hindi tasks, there
were neither floor nor ceiling effects. This suggests that research is needed to establish such
parameters as which tasks, materials, and even
instructionalmethods are affected by and interact with induced mood states.
To the best of our knowledge, this study represents the first attempt to examine the durability of induced positive moods on learning. Isen,
Clark, and Schwartz (1976) studied the duration
of mood states in field studies of altruism.Positive moods were induced by presenting adults
with a free sample of stationery, or no sample
for the neutral mood. At designated time intervals, from 3 minutes up to 20 minutes, participants were called on the telephone and asked to
contact someone else by phone. The results indicated that induced positive moods did not last
past 20 minutes. Also, a negative linear trend
suggested that as the time intervalincreased, the
effect on altruismdecreased.
The results of the present study, on the other
hand, suggest that induced moods may have a
far more robust influence on children's learning
than they did on adults'altruism.For example, it
is remarkablethat 45 seconds of positive thinking had a significant impact on children'slearning across a two-week time span. Whether these
differences are reliable, and which factor(s) account for the differences, calls for furtherstudy.
Thus, the results of this study suggest that there
is a need for furtherresearch on the relationship
between affect and task difficulty.
Inductionof positive affect in the cognitive domain appears to be a promising area of research
and interventionwith students with learning disabilities. However, the effects of positive mood
are complex. For example, there may be significant interactions between mood, frequency of
inductions, age, child factors, and cognitive
tasks. Because studies have found students with
learning disabilitiesto experience greater depression and anxiety than nonlearning disabled students (Maag & Behrens, 1989), an additional
question relates to whether prior moods, such as
general depressive states, influence efforts to induce positive moods.
It has been suggested that positive and negative affect have differenteffects on cognitive processing (Forgas, 1991). It is not clear whether
they are two separate or relativelyindependent
systems. Many aspects of these areas need to be
studied, but it is clear that futureresearch on the
interrelationships between affect and cognitive
processing is likely to have implications for understandingthe nature of learning disabilities,as
well as contemporarymodes of assessing the effects of intervention.
REFERENCES
inducedposiBaron,R.A. (1990). Environmentally
tive affect: Its impact on self-efficacy,task performance,negotiation,and conflict.Journalof Applied
Social Psychology, 20, 368-384.
Bay, M., Stavers,J., Bryan,T., & Hale,G. (1992).
for the mildlyhandicapped:
Direct
Scienceinstruction
versusdiscoveryteaching.Journalof Reinstruction
search on Science Teaching, 46, 78-90.
Bower, G.H., & Mayer,J.D. (1985). Failureto
replicatemood-dependentretrieval.Bulletin of the
Psychonomic Society, 23, 39-42.
F. (1981).
Bryan,J.H., Sonnefeld,J., & Grabowski,
Children'sand parents'views aboutingratiationtactics. Learning Disability Quarterly, 4, 170-179.
Bryan,T., & Bryan,J. (1991a).Positivemoodand
math performance. Journal of Learning Disabilities,
24, 490-494.
Bryan,T., & Bryan,J. (1991b). Positive mood
and vocabulary learning. Unpublished manuscript,
of Illinoisat Chicago.
University
Bryan,T., Yasutake,D., & Binstock,E. (inprepara-
tion). The effect of induced positive mood on high
and low readers' comprehension. Unpublished
of Illinoisat Chicago.
manuscript,
University
Duane, D.D. (1993). Later-life affective, cognitive
and neurological manifestations of developmental
right-hemisphere syndromes. Paper presented at the
AnnualMeetingof the International
Academyfor Researchin LearningDisabilities,
Boston.
Ellis, H.C., Thomas, R.L., & Rodrigues, I.A.
(1984). Emotionalmoodstatesand memory:ElaboraVolume 19, Summer 1996
161
tive encoding, semantic processing, and cognitive effort. Journal of Experimental Psychology: Learning, Memory, and Cognition, 10, 470-482.
Forgas, J.P. (1991). Affect and social judgments:An
introductoryreview. In J.P. Forgas (Ed.),Emotion and
social judgments (pp. 3-30). New York:Pergamon.
Frijda, N.H. (1986). The emotions. Cambridge:
CambridgeUniversityPress.
Isen, A.M. (1984). Toward understandingthe role
of affect in cognition. In R.S. Wyer, Jr., & T.K. Srull
(Eds.), Handbook of motivation and cognition
(Vol. 3, pp. 179-236). Hillsdale, NJ: Lawrence Erlbaum.
Isen, A.M. (1987). The influence of positive and
negative affect on cognitive organization. In N.L.
Stein, E. Leventhal,& T. Trabasso(Eds.),Psychological and biological approaches to emotion (pp. 7594). Hillsdale,NJ: LawrenceErlbaum.
Isen, A.M., Clark, M., & Schwartz, M.F. (1976).
Duration of the effect of good mood on helping:
"Footprintson the sands of time." Journal of Personality and Social Psychology, 34, 385-393.
Isen, A.M., Horn, N., & Rosenhan, D.L. (1973).
Effects of success and failureon children'sgenerosity.
Journal of Personality and Social Psychology, 27,
239-247.
Isen, A.M., & Levine, P.F. (1972). Effect of feeling
good on helping: Cookies and kindness. Journal of
Personality and Social Psychology, 21, 384-388.
Lay, K., Waters, E., & Park, K.A. (1989). Maternal
responsiveness and child compliance: The role of
mood as a mediator.Child Development, 60, 14051411.
Leight, K.A., & Ellis,H.C. (1981). Emotionalmood
states, strategies, and state-dependency in memory.
Journal of Verbal Learning and Verbal Behavior,
20, 251-266.
Maag, J.W., & Behrens, J.T. (1989). Depression
and cognitive self-statementsof learning disabled and
seriously emotionally disturbedadolescents. Journal
of Special Education, 23, 17-27.
Margalit,M., & Raviv, A. (1984). LDs' expression
of anxiety in terms of minor somatic complaints.
Journal of Learning Disabilities, 17, 226-228.
Masters, J.C., Barden, C., & Ford, M.E. (1979).
Affective states, expressive behavior, and learning in
children.Journal of Personality and Social Psychology, 37, 380-390.
I
0-rT111j71=
M-J
MNOVEMBER
"LITERACY:
Mesulam, M., & Perry, J. (1972). The diagnosis of
lovesickness: Experimentalpsychophysiology without
the polygraph.Psychophysiology, 9, 546-551.
Overall,J., & Spiegel, D. (1969). Concerning least
squares analysis of experimental data. Psychological
Bulletin, 72, 311-322.
Ozols, E.J., & Rourke, B.P. (1985). Dimensions of
social sensitivityin two types of learning disabledchildren. In B.P. Rourke (Ed.), Neuropsychology of
learning disabilities: Essentials of subtype analysis
(pp. 281-301). New York:Guilford.
Peck, M. (1985). Crisis interventiontreatment with
chronically and acutely suicidal adolescents. In M.
Peck, N.L. Farberow, & R.E. Litman (Eds.), Youth
suicide (pp. 112-122). New York:Springer.
Potts, R., Morse, M., Felleman, E., & Master,J.C.
(1986). Children'semotions and memory for affective
narrativecontent.Motivationand Emotion, 10, 39-57.
Rourke, R., Morse, M., Felleman, E., & Master,
J.C. (1986). Children'semotions and memory for affective narrative content. Journal of Learning Disabilities, 22, 169-175.
Schwartz, J. (1993). Sincere smile delivers good
vibes. Arizona Republic, December 5.
Velten, E. (1968). A laboratorytask for inductionof
mood states. Behavior Research and Therapy, 6,
473-482.
Wechsler, D. (1974). Manual for the Wechsler Intelligence Scale for Children-Revised. New York:
PsychologicalCorporation.
Woodcock, R. (1978). Woodcock-Johnson PsychoEducational Battery. Boston: TeachingResources.
Yasutake,D., & Bryan, T. (1995). The influence of
induced positive affect on middle school childrenwith
and without learning disabilities.Learning Disabilities
Research and Practice, 10, 38-45.
Yasutake,D., & Bryan, T. (in press). The influence
of affect on achievement and behavior of students
with learning disabilities. Journal of Learning Disabilities.
Zajonc, R.B. (1980). Feeling and thinking: Preferences need no inferences. American Psychologist,
35, 151-175.
Requests for reprintsshould be addressedto: Dr. Tanis
Bryan, Special EducationProgram, College of Education, Arizona State University, Box 872011, Tempe,
AZ 85287-2011.
_
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