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The influence of chronotype and intelligence on academic achievement in primary school is mediated by conscientiousness, midpoint of sleep and motivation


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Individuals differ in their timing of sleep (bed times, rise times) and in their preference for morning or evening hours. Previous work focused on the relationship between academic achievement and these variables in secondary school students. The main aim of the study is to investigate the relationship between chronotype and academic achievement in 10-year-old children (n = 1125) attending 4th grade of primary school. They filled a cognitive test (Culture Fair Intelligence Test, CFT 20-R) and questions about rise times and bed times, academic achievement, conscientiousness and motivation. We used the "scales for the assessment of learning and performance motivation" (SELLMO; Skalen zur Erfassung der Lern- und Leistungsmotivation for motivation), the short version of the Five-Factor Personality Inventory Children (FFPI-C) to measure conscientiousness, and the Composite Scale of Morningness (CSM) to assess morningness-eveningness. Mean CSM score was 37.84 ± 6.66, midpoint of sleep was 1:36 ± 00:25 and average sleep duration (time in bed) was 10:15 ± 0:48. Morningness orientation was positively related to intelligence, conscientiousness and learning objectives. Eveningness orientation was related to avoidance performance objectives and work avoidance. Early midpoint of sleep, conscientiousness and intelligence were associated with better grades. The multivariate model showed that intelligence was the strongest predictor of good grades. Conscientiousness, motivation, younger age and an earlier midpoint of sleep were positively related to good grades. This is the first study in primary school pupils, and it shows that the relationship between evening orientation and academic achievement is already prevalent at this age even when controlling for important predictors of achievement.
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Chronobiology International, Early Online: 1–9, (2014)
Informa Healthcare USA, Inc.
ISSN: 0742-0528 print / 1525-6073 online
DOI: 10.3109/07420528.2014.980508
The influence of chronotype and intelligence on academic
achievement in primary school is mediated by conscientiousness,
midpoint of sleep and motivation
Talat Arbabi
, Christian Vollmer
, Tobias Do
, and Christoph Randler
Institute of Science, Technology & Geography, University of Education, Heidelberg, Germany and
Institute of Psychology,
University of Education, Heidelberg, Germany
Individuals differ in their timing of sleep (bed times, rise times) and in their preference for morning or evening
hours. Previous work focused on the relationship between academic achievement and these variables in
secondary school students. The main aim of the study is to investigate the relationship between chronotype
and academic achievement in 10-year-old children (n ¼ 1125) attending 4th grade of primary school. They filled a
cognitive test (Culture Fair Intelligence Test, CFT 20-R) and questions about rise times and bed times, academic
achievement, conscientiousness and motivation. We used the ‘‘scales for the assessment of learning and performance
motivation’’ (SELLMO; Skalen zur Erfassung der Lern- und Leistungsmotivation for motivation), the short version of
the Five-Factor Personality Inventory Children (FFPI-C) to measure conscientiousness, and the Composite Scale
of Morningness (CSM) to assess morningness–eveningness. Mean CSM score was 37.84 ± 6.66, midpoint of sleep
was 1:36 ± 00:25 and average sleep duration (time in bed) was 10:15 ± 0:48. Morningness orientation was positively
related to intelligence, conscientiousness and learning objectives. Eveningness orientation was related to avoidance
performance objectives and work avoidance. Early midpoint of sleep, conscientiousness and intelligence
were associated with better grades. The multivariate model showed that intelligence was the strongest predictor
of good grades. Conscientiousness, motivation, younger age and an earlier midpoint of sleep were positively related
to good grades. This is the first study in primary school pupils, and it shows that the relationship between evening
orientation and academic achievement is already prevalent at this age even when controlling for important predictors
of achievement.
Academic achievement, children, chronotype, conscientiousness, intelligence, morningness–eveningness,
school performance
One striking fact in school and University students
is that late chronotype (or evening preference) is
linked with poor school or academic performance
az-Morales & Escribano, 2013; Preckel et al., 2013;
Randler & Frech, 2006; Vollmer et al., 2013), but all of
these studies have been carried out in secondary schools
or in University settings. The present study is the
first to investigate this relationship in primary school
pupils. In addition, the study aims at declaring the incre-
mental validity of chronotype on grade that goes beyond
the well-established predictors of school achievement as
intelligence, conscientiousness, achievement motiv-
ation, age and sex.
Predictors of academic achievement
Chronotype is an individual difference reflecting the
time of day at which individuals are ‘‘at their best’’
(Adan et al., 2012). Some people (morning types, or
sometimes called ‘‘larks’’) prefer morning hours for
intellectual and physical activities. They have no prob-
lems with early rising and soon achieve their maximum
of mental and physical activity and become tired early in
the evening. In contrast, evening types, or ‘‘owls’’ feel
and perform best at late afternoon or in the evening.
They tend to have late sleep schedules, irregular waking
time, bedtime, and sleep time, and are more often
dissatisfied with their sleep (Wittmann et al., 2006).
Evening types have difficulties to get out of bed in
Correspondence: Christoph Randler, Institute of Science, Geography and Technology, University of Education, Im Neuenheimer
Feld 561-2, 69120 Heidelberg, Germany. E-mail:
Submitted September 2, 2014, Returned for revision October 19, 2014, Accepted October 22, 2014
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the morning, and they need a longer time to have their
senses cleared. However, owls are able to work until
late in the evening and they often achieve their phys-
ical and mental acrophase during late afternoon and
evening hours.
In addition, other variables of the sleep–wake
rhythm have been used in previous work, e.g. sleep
duration (time spent sleeping) and social jetlag, that is,
a misalignment between one owns’ internal clock
(or internal rhythm) and the social rhythm/schedule.
The latter is measured in the absolute difference in
midpoint of sleep between weekdays or days with
obligation and free days, based on the idea that sleep
on free days follows the internal clock (Wittmann et al.,
2006). In school pupils, these variables are moderately
correlated with morningness–eveningness scores.
At the primary school level (up to the age of 10 years),
most children are morning oriented, i.e. active in the
morning, even at the weekend (Randler & Truc, 2014).
Adolescents shift from morningness to eveningness
around the age of puberty (12–14 years) which has
been reported in many studies (Carskadon et al., 1993;
az-Morales & Sorroche, 2008; Laberge et al., 2001;
Randler, 2008). This change is associated with pubertal
development (Carskadon et al., 1993). Young people
turn back towards morningness at the end of adoles-
cence, which occurs around the age of 19.5 in women
and at 21 years in men (Roenneberg et al., 2004; Tonetti
et al., 2008). Some studies have reported differences
among gender. On average, boys and men are later
chronotypes than girls and women (Adan et al., 2012).
The relationship between chronotype and academic
performance in adults and adolescents has been
examined in some studies showing that eveningness
and academic achievement are strongly and inversely
related, whereas morningness and performance are
positively related. These patterns hold for both second-
ary school children (Be¸soluk, 2011; Giannotti & Cortesi,
2002; Randler & Frech, 2009; Vollmer et al., 2013) and
University students (Be¸soluk et al., 2011; Randler &
Frech, 2006) but have not yet been investigated in
primary school pupils. Further, no study yet covered all
the confounding variables as predictors of academic
performance in addition to chronotype. We hypothesize
that chronotype is a predictor of school achievement
in primary school pupils with morningness being
positively related to better achievement.
Individual differences in cognitive ability are a good
single predictor of academic performance (Deary et al.,
2007; Mayes et al., 2009). The relationship between
measures of intelligence and measures of school
achievement is usually around 0.30–0.50 (Gustafsson &
Undheim, 1996; Rindermann & Neubauer, 2004; Spinath
et al., 2006).
In their meta-analysis, Preckel et al. (2011) investi-
gated the relationship between cognitive ability and
chronotype and reported a mean effect size of 0.08
between eveningness and cognitive ability and of 0.04
between morningness and cognitive ability, suggesting
that evening types are more intelligent. In detail,
some studies showed that evening types were more
intelligent (mental speed, working memory; Roberts &
Kyllonen, 1999), or that eveningness scored higher on
verbal abilities (Killgore & Killgore, 2007). Morning-
oriented students scored lower on inductive reasoning
than evening-oriented students (Dı
az-Morales &
Escribano, 2013). In total, Preckel et al. (2011) reported
seven positive and four negative correlations between
eveningness and cognitive ability. However, the effect
size is rather low and the fail-safe number, the number
of non-significant, potentially unpublished or missing,
studies that are needed to draw the result (effect size)
to zero was n ¼ 7, suggesting that further studies are
needed to assess this relationship.
There was a weak difference between the sexes in
intelligence but a larger variance in males (Deary, 2003;
Hedges & Nowell, 1995). Girls generally perform better
at school than boys (e.g. Burusic et al., 2012; Demie,
2001; Duckworth et al., 2006; Gibb et al., 2008; Leeson
et al., 2008; Steinmayr & Spinath, 2008), especially in
languages while boys perform better in mathematics
(e.g. Jacobs et al., 2002; Spinath et al., 2008).
It is still unclear what interplay between the vari-
ables chronotype, intelligence and school achievement
occurs at primary school age. We hypothesize a correl-
ation between chronotype and intelligence with even-
ingness being positively related to intelligence and
assume intelligence to be a strong predictor of academic
achievement in primary school.
Conscientiousness predicts academic outcomes
among school students (Bratko et al., 2006; Heaven
et al., 2002; Spinath et al., 2010; Steinmayr & Spinath,
2008; Wolfe & Johnson, 1995), undergraduates
(Busato et al., 1998; Diseth, 2003; Furnham et al., 2002;
Lounsbury et al., 2002) and postgraduates (Rothstein
et al., 1994). Conscientiousness was confirmed as the
strongest Big Five predictor of academic performance,
faring better in some samples than intelligence (cor-
rected r ¼ 0.22, meta-analysis by Poropat, 2009).
Moreover, in a young age group (between 3 and 12
years of age), boys were rated less conscientious than
girls based on parents’ statements (De Fruyt et al., 1998).
Concerning chronotype, numerous studies reported
that morning people are more conscientious (review:
Adan et al., 2012). We proclaim a mediation hypothesis:
It can be presumed that conscientiousness is the
mediating variable between chronotype and school
Studying the construct of intrinsic motivation in young
children is important, because academic intrinsic
2 T. Arbabi et al.
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motivation in the early elementary years will impact on
initial and future school achievement (Gottfried, 1990).
Furthermore, differences between boys and girls con-
cerning motivational variables like beliefs or interests
can be found (Meece et al., 2006), with a clear
interplay between interests and grades in primary
school (von Maurice et al., 2014).
The predictive validity of achievement motivation
for academic performance has been demonstrated in
several studies (Hejazi et al., 2009; Steinmayr & Spinath,
2009). It has been shown that, above and beyond
intelligence, motivation explains variance in academic
achievement (Gose et al., 1980; Schicke & Fagan, 1994;
Spinath et al., 2006). Concerning chronotype, there are
few studies that show a relationship between motivation
and chronotype. Roeser et al. (2013) showed that the
relationship between chronotype and academic
achievement is mediated by learning motivation. Their
study moved the field forward, but they included less
predictors of achievement than our present one. We
expect a positive correlation between motivation and
grades (Steinmayr & Spinath, 2009) and a mediation of
the relationship between chronotype and achievement
by motivation (Roeser et al., 2013).
The current study
The main aim of the current study was to investigate
the relationship between chronotype and academic
achievement during the 4th grade of primary school.
To our knowledge, there are no studies that investigated
the relationship between chronotype and academic
performance of primary school children, and thus, this
is a neglected age group. As the change towards
eveningness occurs mainly at the ages of 12–14 years,
we hypothesize that the correlation between chronotype
and achievement might be lower compared to older
age groups. First, because the number of evening types
in primary school pupils is lower compared to second-
ary school pupils, but there are already evening
types present in primary school. The morningness–
eveningness scores are normally distributed, so the
scores are generally shifted to morningness in primary
school. Second, the internal sleep–wake cycle of primary
school pupils better fits the social and school schedules,
suggesting a smaller misalignment between their own
internal clock and the social clock, and therefore, a
weaker correlation between achievement and chrono-
type. This could also be viewed as a better person–
environment-fit. In addition, we simultaneously mod-
eled the interplay of many of the above-mentioned
variables that have also been found to influence school
Participants and data collection
The sample consisted of 1125 students, 536 girls and 584
boys (five sex unspecified), aged 10.22 years (SD ¼ 0.47,
n ¼ 1117) from 48 primary schools (4th grade). On
average schools start at 8:00 in the morning. The
study took place between 15.04.2013 and 02.07.2013
and from 8:00 to 12:15 in southwest Germany (Rhine-
Neckar-Region). Mean testing time was 9:57 ± 1:03,
which is situated right in the middle of the school day.
The cognitive test and the self-administered question-
naire were completed by the students during normal
classroom settings in the presence of a researcher and
their teacher. The cognitive test was carried out in all
classes by the same researcher. Participation was
voluntary and anonymous with written consent of
parents and school administration. The present study
complied with the tenets of the Declaration of Helsinki
and the international ethical standards of chronobiolo-
gical research (Portaluppi et al., 2010).
Chronotype and sleep variables
The Composite Scale of Morningness (CSM; Smith et al.,
1989) consists of 13 questions in a Likert-type format
regarding the time individuals get up and go to bed,
preferred times for physical and mental activity, and
subjective alertness. Five of the elements of the scale
refer to different times of day. The score is obtained by
adding the items and ranges from 13 (extreme evening-
ness) to 55 (extreme morningness). The CSM score is
unaffected by the time of the day one fills in the
questionnaire. Cronbach’s alpha was 0.78.
Additionally, we asked for habitual rise time and
bed time on weekdays and on the weekend (Giannotti &
Cortesi, 2002; Russo et al., 2007). These variables are
considered as a proxy of sleep length because they focus
on total time in bed (including sleep onset latency and
bed time after awakening). From these, we calculated a
single phase-reference point, the corrected mid-sleep
point (MSFsc; Roenneberg et al., 2004). The self-report
MSFsc has been used in adults, adolescents and
children as young as 10 years of age (Roenneberg
et al., 2003). Social jetlag was calculated using the
method from Wittmann et al. (2006).
We used the Culture Fair Intelligence Test (CFT 20-R)
as a measure of cognitive ability. The CFT 20-R is a
German adaptation of the Culture Fair Intelligence
Test (Weib, 2008). The paper-and-pencil test assesses
fluid intelligence with four types of figural tasks: Series
(15 items), Classifications (15 items), Matrices (15 items)
and Topological Reasoning (11 items). Tasks were
presented in a multiple-choice format. Each subtest is
timed and the items increase in difficulty.
The purpose of a culture-fair intelligence test is
to minimize any social or cultural advantages, or
disadvantages, that a person may have due to their
upbringing. The CFT seems unaffected by time of day,
so a synchrony effect is not expected. To our knowledge,
this has not been tested. In our study population, testing
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time correlated weakly positively with CFT scores
(r ¼ 0.095, p50.001). We consider this effect negligible
(below 1% of variance explained), and there was no
synchrony effect because time of testing did not correl-
ate with CSM scores (r ¼ 0.010) nor with midpoint of
sleep (r ¼ 0.017). Cronbach’s alpha of the total CFT (56
items) was 0.74.
The short version of the Five-Factor Personality
Inventory-Children (FFPI-C; McGhee et al., 2007) was
used for the measurement of conscientiousness.
The scale consists of 15 bipolar pairs of sentences on a
5-point Likert-scale. Cronbach’s alpha in the present
study was 0.73.
Achievement motivation was measured by SELLMO,
the ‘‘Skalen zur Erfassung der Lern- und
Leistungsmotivation’’ (scales for the assessment of
learning and performance motivation; Spinath et al.,
2002). It contains of 4 scales and 31 items and is suitable
for use in primary school (Swoboda, 2010). The response
scale was a 5-point Likert scale ranging from ‘‘not true
at all’’ (1) to ‘‘exactly true’’ (5). Cronbach’s alpha
was 0.68 for ‘‘learning objectives’’, 0.75 for ‘‘approach
performance objectives’’, 0.81 for ‘‘avoidance perform-
ance objectives’’ and 0.80 for ‘‘work avoidance’’. The
‘‘learning objectives’’ scale describes the goal of wanting
to expand one’s own abilities. The ‘‘approach perform-
ance objectives’’ scale describes the goal of wanting to
demonstrate one’s skills in front of others, a property
associated with somewhat short-term learning success,
but without ensuring adequate long-term learning
success. The ‘‘avoidance performance objectives’’
scale describes the tendency to try to hide low skills
or inability/ignorance due to previous negative experi-
ences; a property associated with poor short and long-
term benefits. The ‘‘work avoidance’’ behavior is not
learning or performance motivated, i.e. the motivation
to invest as little effort as possible. This attitude has a
particularly negative effect on interest and intrinsic
Academic achievement
School performance was measured by self-reported
grades. Students reported their half year grades
(February 2013) in Mathematics, German, English and
Nature & Culture (a combined elementary school sub-
ject including fine arts, music, biology and culture) on a
21-point scale from 1.0 ¼ fail, 1.25, 1.5, [...] 5.5, 5.75 to
6.0 ¼ outstanding and thus, higher scores in grades
indicate higher achievement. Thus, self-reported
grades do not reflect grades from a single test but
represent accumulations of attainments of a whole
school term. Further, school grades are real measure-
ments that have an influence on career decisions.
Research suggests that self-reported school grades can
be assumed to be valid, since they do not seem to be
subject to systematic bias (Dickha
user & Plenter, 2005).
Statistical analyses
SPSS 21 and AMOS 21 (both IBM, Somers, NY) were
used for statistical calculation. t-Tests and Pearson’s
correlations were used to analyze the bivariate relation-
ships between all variables under study. Structural
equation modeling (SEM) was used to explore associ-
ations between variables in context. Gender differences
were included in a group analysis to investigate gender
as a moderator variable. Specification search in AMOS
21 was used with associations between variables with
50.20 specified as optional for best model fit. Missing
values were substituted with estimates in the multivari-
ate analyses.
Descriptive statistics for the sleep–wake and chronotype
variables are depicted in Table 1.
Bivariate analyses
Boys and girls did not differ in chronotype and intelli-
gence (Table 2). There were significant differences
between the sexes in academic performance but the
direction was subject-specific: girls did better in
Languages and Nature & Culture, but boys had better
scores in Mathematics. Overall, there were no gender
differences in grades. There were significant gender
differences in midpoint of sleep with girls sleeping later
and in social jetlag with girls sharing more social jetlag.
Girls scored higher on conscientiousness and learning
objectives than boys. Boys scored higher on avoidance
performance objectives. There were no gender differ-
ences in work avoidance (Table 2).
There was no significant correlation of chronotype
as measured by the CSM and age, but midpoint of
sleep was significantly related to age with a later
midpoint at an older age (Table 3). Evening-oriented
individuals shared higher social jetlag. Morningness
orientation was positively related with higher intelli-
gence, higher scores in conscientiousness and learning
objectives. Eveningness orientation was related to higher
avoidance performance objectives and higher work
avoidance. Age correlated negatively with intelligence.
TABLE 1. Descriptive sleep–wake variables of the sample.
Mean SD
Chronotype (CSM) 37:84 6:66
Midpoint of sleep before school days 01:36 0:25
Midpoint of sleep at the weekend 03:23 0:59
Midpoint of sleep (MSFsc) 02:58 0:57
Sleep duration before school days (time in bed) 10:10 0:47
Sleep duration on weekends (time in bed) 10:27 1:32
Average sleep duration (time in bed) 10:15 0:48
Social jetlag 1:46 0:54
4 T. Arbabi et al.
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Students with later midpoint of sleep scored lower
in intelligence. Higher intelligence scores were posi-
tively related to higher conscientiousness. Age was not
significantly correlated with conscientiousness.
Conscientiousness was positively related to better
grades. Older students reported higher approach per-
formance objectives, higher avoidance performance
objectives, and higher work avoidance. There were no
age differences in learning objectives.
Age had significant influence on grades. Grades
decreased with increasing age and younger children
were earlier chronotypes than older children as mea-
sured by the midpoint of sleep. Both conscientious-
ness and intelligence were associated with good grades.
Good grades, in turn, correlated with the four aspects
of motivation. Furthermore, better grades were related
to an early midpoint of sleep, lower social jetlag and
younger age.
Multivariate analyses
Goodness of fit statistics of the SEM revealed that
the overall model (M1) and the unconstrained gen-
der group analysis (M2) fitted best (Table 4). The
specification search of the SEM removed two facets of
motivation, resulting in a single factor of motivation
labeled ‘‘negative motivation’’ (avoidance performance
objectives and work avoidance).
Higher intelligence was the strongest predictor of
good grades. Moreover, conscientiousness, motivation,
younger age and an earlier midpoint of sleep were
positively related to good grades. Although earlier
CSM score was associated with good grades in bivari-
ate analysis, CSM scores did not directly contribute
to differences in grades in the SEM. However, chron-
otype contributed to grades mediated by midpoint of
sleep and conscientiousness. Whereas intelligence con-
tributed on a direct path to grades, intelligence also
contributed indirectly by motivation, conscientiousness
and midpoint of sleep (Figure 1).
The strength of the study is that it controls for many
co-variates and predictors of academic achievement
to unveil the effects of chronotype on academic
achievement. Nevertheless, an effect of chronotype on
achievement remained significant. Considering all these
variables, higher intelligence contributed the most to
good grades. This goes in line with most studies and is a
well-known fact. The negative association between
age and intelligence can be explained by the German
school system where gifted children are sent to school
earlier (sometimes around the age of 5 years, whereas
less skilled pupils start schooling around the age of
7 years), or they skip a grade and thus are younger in our
population, the 4th grade of primary school. Older and
less conscientious children with lower motivation and a
later sleep rhythm perform worse at school.
In line with previous work (Dı
az-Morales & Sorroche,
2008), we found that earlier chronotype was associated
with earlier midpoint of sleep and less social jetlag,
showing that individual circadian preferences are mani-
fest, and, thus late chronotype can be detrimental to
early school schedules already in pre-adolescent chil-
dren. The mean CSM score was 37.84, and thus much
more shifted towards morningness compared, e.g. to
adolescents (e.g. about 30–32 at age of 15–17 years;
Randler, 2011). Similarly, midpoint of sleep was
very early at 1:36 compared to an average of 4:28 in
about 14-year-old adolescents (Vollmer et al., 2012).
This indicates that primary school pupils in grade 4 are
more morning oriented compared to adolescents.
Generally, the influence of chronotype on academic
achievement is lower compared to studies based on
TABLE 2. Means, standard deviations of study variables and gender differences (t-test).
Girls Boys t-Test Total
Mean SD n Mean SD nt p Mean SD n
Chronotype (CSM) 37.99 6.64 536 37.65 6.65 581 0.862 0.389 37.81 6.65 1117
Midpoint of sleep (MSFsc) 3:02 am 53 min 526 2:54 am 60 min 566 2.510 0.012 2:58 am 57 min 1092
Social jetlag 1 h 51 min 52 min 526 1 h 41 min 56 min 566 3.094 0.002 1 h 46 min 55 min 1092
Intelligence (CFT total) 0.55 0.10 536 0.55 0.11 584 1.048 0.295 0.55 0.10 1120
Conscientiousness 3.79 0.51 534 3.68 0.50 582 3.766 50.001 3.73 0.51 1116
Motivation: Learning objectives 4.24 0.55 536 4.17 0.59 580 2.065 0.039 4.20 0.57 1116
Motivation: Approach performance
3.37 0.79 535 3.45 0.79 580 1.744 0.081 3.42 0.79 1115
Motivation: Avoidance
performance objectives
2.73 0.95 535 2.86 0.90 580 2.438 0.015 2.80 0.92 1115
Motivation: Work avoidance 2.62 0.89 535 2.70 0.95 580 1.425 0.154 2.66 0.92 1115
Average grades 4.98 0.50 499 4.92 0.54 531 1.937 0.053 4.95 0.52 1030
Grades, Mathematics 4.75 0.79 510 4.90 0.74 541 3.242 0.001 4.83 0.77 1051
Grades, German 4.87 0.64 504 4.72 0.78 534 3.332 0.001 4.79 0.72 1038
Grades, Science & Culture 5.10 0.54 488 4.94 0.61 522 4.310 50.001 5.02 0.58 1010
Grades, English 5.24 0.56 505 5.12 0.66 537 3.063 0.002 5.18 0.61 1042
CSM, Composite Scale of Morningness; CFT, Cultural Fair Test. Significant differences are depicted in bold.
Please note that a conservative approach would focus on significant variables only (p50.01).
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secondary school pupils and University students in
Germany. For example, Vollmer et al. (2013) reported a
correlation coefficient between achievement and morn-
ingness–eveningness of 0.227 and Randler & Frech
(2009) of 0.182 in secondary school pupils, while
Randler & Frech (2006) reported a coefficient of 0.230
in University students. This might have several reasons:
one might lie in the nature of our study where we
have controlled for many other important predictors
of school achievement thus decreasing the effect size
of the bivariate relationship. Another reason might lie in
the developmental aspects: young people have their
strong transition to eveningness around the age of 12–14
years, thus their delayed sleep pattern is less obvious in
primary school. The sleep–wake schedule of primary
pupils does not differ so much between weekdays and
weekends, so their internal biological rhythm better fits
the school schedules. However, this was one of the
reasons why we carried out the study: we wanted to test
whether the association between chronotype and
achievement is already prevalent in this neglected age
group with a smaller difference in misalignment.
Nevertheless, there are evening-type pupils already in
primary school although their proportion is lower
compared to adolescent samples.
Another possibility might lie in the school start times.
School start times in primary school might be a bit later
(albeit only up to half an hour), but taken together with
the fact that pupils at this age are more morning
oriented and may go to school a bit later, these factors
may be responsible for the lower correlation between
morningness–eveningness and achievement in primary
In contrast to previous studies (Killgore et al., 2007;
Roberts & Kyllonen, 1999), morning orientation was
positively related with higher intelligence in bivariate
analyses. This could be based on the samples, because
we assessed school children in primary school (thus a
different age) and further, a more representative sample,
since Roberts & Kyllonen (1999) were based on army
people and Killgore & Killgore (2007) relied on a small
sample size. However, the results are not contradictory
because Preckel et al. (2011) reported four studies with a
positive correlation between cognitive ability and
morningness, and their main effect size is low so that
the result should be treated with caution. Unfortunately,
exactly these four studies with a positive relation-
ship between morningness and intelligence are unpub-
lished (for details, see Preckel et al., 2011), so we here
conclude that the relationship between cognitive ability
or intelligence on the one hand and chronotype on the
other is far from being resolved. The few studies focus
on different populations (pupils, students and army
people) and use different measures of cognitive ability.
Morning orientation was related to proactive behav-
ior such as a higher conscientiousness and higher
learning objectives, which is important for school
performance, while late midpoint of sleep was related
TABLE 3. Correlations of study variables. Please note that a conservative approach would focus on highly significant variables only (p 50.001, ***).
1 Average grades 1.000 ***0.135 0.042 ***0.217 ***0.198 ***0.266 ***0.370 ***0.225 ***0.114 ***0.283 ***0.281 ***0.360
2 Chronotype (CSM) 1.000 *0.063 ***0.327 ***0.306 0.010 *0.061 ***0.149 0.037 **0.096 ***0.125 ***0.355
3 Average sleep length 1.000 0.045 **0.083 ***0.140 0.036 0.030 0.034 0.057 0.040 0.027
4 Midpoint of Sleep (MSFsc) 1.000 ***0.833 ***0.139 *0.140 *0.062 **0.098 ***0.117 ***0.106 0.056
5 Social jetlag 1.000 ***0.129 *0.152 *0.072 **0.098 ***0.121 ***0.121 0.054
6 Age (in months) 1.000 0.122 **0.029 **0.091 ***0.106 ***0.142 0.042
7 Intelligence (CFT total) 1.000 **0.103 *0.073 ***0.136 ***0.148 ***0.131
8 Motivation: Learning objectives 1.000 ***0.262 0.003 ***0.156 ***0.332
9 Motivation: Approach performance objectives 1.000 ***0.610 ***0.420 ***0.127
10 Motivation: Avoidance performance objectives 1.000 ***0.635 ***0.113
11 Motivation: Work avoidance 1.000 ***0.179
12 Conscientiousness 1.000
Pearson’s correlation coefficients, *Significance50.05. **Significance50.01. ***Significance50.001.
6 T. Arbabi et al.
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to higher avoidance performance objectives and higher
work avoidance. This suggests that the ‘‘morning per-
sonality’’ indeed is already prevalent in young children
at the primary level, and, that these factors are respon-
sible for academic achievement in primary school.
Further studies might assess trajectories of personality
and chronotype in combination with progress of the
schooling in a prospective study.
We found a correlation between age and chronotype
only in the midpoint of sleep measure but not with the
CSM scores. Further, we found differences in sleep
timing and social jetlag between boys and girls. Both
aspects taken together suggest that it might be a
possible effect of developmental age, thus further
studies might consider developmental age and compare
it with chronological age. Second, girls being more
evening oriented may be a result of the fact that girls are
on average more advanced in their development.
In addition, we found an unexpected time of testing
effect on CFT scores (cognitive ability). This result does
Chronotype (CSM)
= .500
Midpoint of sleep (MSFsc)
= .146 (.154/.144)
= .143 (.131/.151)
= .101
= .030
Avoidance performance objecves
Work avoidance
Nature & Culture
CFT Series
CFT Classificaons
CFT Matrices
CFT Condions
β = –.191 (–.135/–.231)
β = –.353 (–.364/–.339)
β = .293 (.232/.350)
β = –.172 (–.188/–.159)
β = .115 (.100/.140)
β = –.161 (–.121/–.188)
= .107 (n.s./.102)
β = .351 (.339/.360)
β = –.149 (–.122/–.166)
β = .140 (.128/.146)
= .083 (.098/n.s.)
β = –.145 (–.153/–.147)
= –.108 (n.s./–.135)
β = .428 (.446/.424)
= –.189
= .766
β = .828 (.799/.903)
β = .615 (.621/.625)
β = .457 (.443/.464)
β = .328 (.260/.380)
β = .641 (.559/.688)
β = .694 (.752/.635)
β = .686 (.713/.717)
β = .620
β = .715 (.690/.730)
β = .097 (.088/.093)
FIGURE 1. Influence chronotype and intelligence on grades with conscientiousness, midpoint of sleep and motivation as mediators
and gender as moderator variable, structural equation model. Note: Significant regression coefficients () from the overall model
were included: overall model (M1), in brackets: moderator variable (girls/boys; unconstrained model M2). Age in months; chronotype
(CSM, Composite Scale of Morningness) from 13 ¼ extreme evening type to 55 ¼ extreme morning type; midpoint of sleep (MSFsc) in clock
times; intelligence: Cultural Fair Test (CFT) with higher values indicating higher intelligence, conscientiousness (FFPI-C) with higher values
indicating higher conscientiousness; negative motivation (2 facets from SELLMO) with lower values indicating higher motivation; grades
from 1 ¼ fail to 6 ¼ outstanding.
TABLE 4. Goodness of fit statistics of the structural equation model.
Overall model
M1 125.388 1.929 0.029 0.979
Multiple group (boys/girls) comparison
M2: Unconstrained 204.471 1.573 0.023 0.974
M3: Invariance of measurement weights 227.350 1.636 0.024 0.970
M4: Invariance of measurement intercepts 299.839 1.986 0.030 0.949
M5: Invariance of structural weights 336.117 2.037 0.030 0.941
M6: Invariance of structural intercepts 340.664 2.040 0.030 0.940
M7: Invariance of structural residuals 355.776 2.068 0.031 0.937
M8: Invariance of measurement residuals 411.484 2.236 0.033 0.922
¼ Chi-square; df ¼ degrees of freedom; RMSEA ¼ root mean square error of approximation; CFI ¼ comparative
fit index. Parameters are constrained to be equal for both groups (boys/girls). M1 and M2 do not differ
significantly. Other models (M3–M8) fitted significantly worse than M1 and M2.
Chronotype, intelligence and academic achievement in primary school 7
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not affect the study because of its small size (below 1%
of variance explained) and should be therefore unim-
portant for survey studies but might become important
for individual diagnostics.
We did not assess all variables that were related to
school achievement, e.g. the need for cognition was
not assessed although it might have an influence on
grades because there was no instrument applicable for
primary school the instrument by Preckel et al. (2013)
for 5th and 6th graders was published after the study
was carried out and should be taken into account in
future work.
Concerning the grades, intelligence, conscientiousness
and motivation were important predictors. The results
further show that these important predictors have to
be taken into account when assessing the relationship
between chronotype and academic achievement.
Nevertheless, chronotype was an important predictor
of school achievement even when controlling for many
confounding variables. In addition, the relationship
between academic achievement and chronotype was
weaker in primary school students, probably because
they are not yet in their transition to evening types,
which occurs around the age of 12–14 years (Adan et al.,
2012). The internal sleep–wake cycle of the primary
school pupils, therefore, better fits the social and school
schedules, suggesting a smaller misalignment between
their own internal clock and the social clock, and
therefore, a weaker correlation between achievement
and chronotype. One implication of the study could be
to reduce the misalignment of adolescents (and hence
improve their person–environment-fit), which are pre-
dominantly evening types, and to start school later in
adolescents to better fit the internal clocks of the
evening types. An implication for primary school
pupils would be to carefully check school start times
and time for travelling to school (which is different
among the many schools) to avoid early getting up
times. Further, as the CFT was weakly related to testing
time, we suggest to write examinations in primary
school pupils later during the day, e.g. at 10:00 o’clock,
and not in the first lesson.
We are grateful to all pupils, parents, teachers and
principals for supporting our study.
The authors report no conflicts of interest. The authors
alone are responsible for the content and writing of this
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... People with a morning chronotype (M-types, also called "larks") exhibit an earlier sleep-wake schedule and a phase advance (i.e., earlier peaks) in behavioral and physiological functions, contrary to evening-types (E-types, also called "owls"). Intermediate types (I-types) do not have a clear preference for earlier or later times of the day and fall between these two extremes (Biss and Hasher 2012;Dagys et al. 2012;Díaz-Morales and Escribano 2014;Antúnez et al. 2015;Arbabi et al. 2015;Díaz-Morales et al. 2015). Chronotype has been typically measured with self-report questionnaires (Levandovski et al. 2013;Au and Reece 2017;Randler et al. 2017;Cox and Olatunji 2019) and considered an indirect measure of circadian rhythm (Levandovski et al. 2013). ...
... Therefore, the main aim of the present study was to investigate potential chronotype and time-of-day interactive effects on momentary emotional states (i.e., momentary mood, PA, NA, 1 and state-anxiety) of M-and E-type primary school children, in a naturalistic school setting, while controlling for the effect of sleep-related variables, psychological symptoms (i.e., confounding variables). Despite the scarce research on this age group (Arbabi et al. 2015), our general hypothesis was that differences on children's momentary emotional states, comparing the first to the last hour of the school day, would be determined by both chronotype and time-of-day, representing a generalized synchrony effect (i.e., better emotional states at optimal times-of-day): M-types and E-types children would exhibit better momentary emotional states at an optimal time-of-day (i.e. morning for M-types, afternoon for E-types) and worst momentary emotional states at suboptimal time-of-day (i.e. ...
... Note 1. Despite the apparent lack of NA circadian rhythmicity in adults and adolescents (e.g., Randler and Weber 2015), NA was included in this study due to insufficient research on the potential daily variation of NA in children (e.g., Arbabi et al. 2015) and the results obtained in more recent studies (e.g., Emens et al. 2020). ...
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Synchrony effects regarding mood diurnal fluctuations (i.e., better mood at optimal and worse mood at suboptimal times-of-day, corresponding to the interaction between chronotype* time-of-day) have been studied in adolescents and adults. However, evidence in children is lacking. We investigated the interactive effect of chronotype and time-of-day on primary school children’s momentary emotional states, in a naturalistic setting. From an initial pool of 298 3rd/4th graders (7–11 years-old), 134 Morning (M)-type and Evening (E)-type children were selected using the parental-report Children ChronoType Questionnaire (CCTQ). Potential covariates were assessed based on parental questionnaires. Students completed emotional states’ measures on the first (9 a.m.) and last lessons (4 p.m.) of the school day, in a counterbalanced order. Given the intercorrelations between emotional measures, a composite score of momentary emotional states was determined. There was a small-to-moderate significant interactive effect of chronotype*time-of-day in the overall momentary emotional states score. M/E-types showed better overall momentary emotional states when tested at their optimal time-of-day. Chronotype or time-of-day main effects were non-significant, and the overall momentary emotional states score did not correlate with sleep or psychopathological symptoms. In the present study, children overall momentary emotional states in a naturalistic setting varied depending on chronotype combined with time-of-day.
... Academic achievement, usually measured with the grade point average (GPA), is a very stable and heritable characteristic that remains constant over time [1]; however, it has been associated with a variety of sociodemographic, psychological and intellectual factors including positive associations with non-verbal intelligence, academic motivation, academic self-efficacy, emotional intelligence, task-oriented coping strategies, physical activity, sleep-related factors, conscientiousness and female sex, and negative associations with stressful life events, alcohol use, depression, stress, delinquent activity and avoidance coping [2][3][4][5][6][7][8][9]. In addition, intelligence has shown negative correlations with psychosocial adversities and low income, and positive correlations with maternal education [10]; as well as with specific personality traits [11]. ...
... As non-verbal intelligence, preparatory GPA and the admission exam test were also more correlated with GPA in women than in men. In general, these results coincide with other studies performed in children that showed that non-verbal intelligence has been the strongest associated variable to GPA [5,6]; however, no differences by sex were reported. ...
... Different to the expected, sleep satisfaction and sleep quality did not show a correlation or tendency with GPA; however, we observed that a previous report [6] did not show an association between sleep efficiency and GPA in children (r = 0.05), and another report only showed associations between GPA and morningness chronotype (r = 0.14) and an earlier midpoint of sleep (r = −0.22), but not with the average sleep length (r = 0.04) in children [5]. This suggests that sleep satisfaction or sleep quality are not associated with GPA in these populations (children and university), however, other variables associated to sleep, as previously mentioned, could be associated. ...
Full-text available
Academic achievement, measured with the grade point average (GPA), is a stable characteristic that has been associated with many sociodemographic and psychological variables; however, the relation of these variables with GPA has not been totally elucidated. The objective of this study was to perform an association of health, psychological and personal variables with GPA and non-verbal intelligence in low-academic performance population according to sex. We invited health sciences university students who had failed the same subject twice to complete a set of sociodemographic and psychological variables and a non-verbal intelligence test. The GPA, admission exam test and preparatory GPA were obtained. We included 124 students, and found that GPA was associated with non-verbal intelligence in women but not in men; in whom, having a job and having a romantic partner, were more correlated. In women, positive relations with others, emotion perception and weekly physical activity hours were marginally correlated with GPA; while in men, emotion regulation and self-motivation had a tendency of correlation with GPA. In addition, we found that non-verbal intelligence was associated somatization and the number of diseases in women. Academic achievement is regulated by different variables in each sex; therefore, intervention programs addressed by sex are needed to increase it.
... A somewhat different picture emerges from studies conducted in school settings, which have indicated that morning chronotypes, compared with evening ones, not only obtain higher scores in fluid intelligence but also get higher academic grades (Arbabi et al. 2015), which can be considered a proxy for crystallized intelligence (Zhang and Ziegler 2022). Associations of higher academic performance with morningness have appeared consistently across various studies, but they can be offset by delaying school day starts that cancel the academic supremacy of morning chronotypes (Goldin et al. 2020). ...
Full-text available
Research suggests the existence of an association between chronotype and intellectual performance , but the nature of this link remains unclear. Studies conducted in a laboratory setting point to the synchrony effect (better performance at a person's preferred time of day) for fluid intelligence, but not for crystallized intelligence, whereas studies that have analyzed students' grades suggest that the effect exists for both. In the present study, we aimed to verify the synchrony effect by applying direct measures of crystallized intelligence, fluid intelligence, and subjective sleepiness-alertness in a sample of high school students during their morning or afternoon class. The results revealed a synchrony effect for crystallized, but not for fluid intelligence. During morning class, students with a morning chronotype performed better than evening chronotypes on a test of crystallized intelligence, whereas during afternoon class there was no difference between chronotypes. The association resulted from decreased performance during morning class in evening chronotypes that improved during afternoon class and constant performance in morning chronotypes. These effects were independent of sleepiness-alertness levels. The results suggest that individual differences between chronotypes may be important for tasks performed during morning classes, but not during afternoon ones, and that performance across school days may depend on time of day in evening chronotypes.
... This line of results focusing on age and chronotype can be explained in a first perspective that relates to the pioneering North American research on the prevalence of chronotypes, which considers age as a determining and modifying factor. The chronotype varies according to age but in a decreasing direction according to Fischer et al. [47]. ...
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The aim of this study is to examine the relationship between chronotype, classroom behaviour and school performance in 140 healthy school-age children attending various levels of education during the 1st cycle during 2021 in Portugal. In this cross-sectional and quantitative study, the Chronotype Questionnaire for Children (to assess the chronotype) and the Conners Scale—a reduced version was presented to the teachers (to assess behaviours such as excessive movement, inattention and oppositional behaviours)—were used. The methodology of this study followed a comparative method since the independent variables were not controlled, and therefore, it was still possible to compare the differences between the morning and evening groups. Statistical methods were used such as multivariate analyses, inter-item correlations and reliability tests, and descriptive tests were used for the percentile analysis. The sample was divided into three groups based on the identification of the chronotype—morning, intermediate and evening types—to further study the relationship between these chronotypes, their academic performance and classroom behaviour were studied. A multivariate analysis of variance revealed that there was a higher rate of oppositional behaviour in the morning type and no differences in the school performance during the two semesters (covering all of the school periods) regarding the chronotype effect, even with the analysis of regression parameters and covariates. On the other hand, the morning-type children showed a greater amount of motor agitation and impulsivity after controlling for the gender covariate. Age had an effect on the chronotype, after controlling for the covariate parental education. This study highlights the need for further research on the chronotype of the morning children in order to regulate their behaviour. The data that were obtained raise questions that have not been yet considered in the literature in the area of education and infant development.
... This optimization is related to the adequacy between the time of the day and the accomplishment of tasks by subjects with different diurnal predispositions. However, studies on the effect of synchrony (chronotype x task -time of day) have been mostly conducted in samples of adolescents (Hahn et al., 2012), and research on chronobiology, with further interest for Psychology, Education and Teaching fields, has recently seen the need for focus on samples of primary school children (Arbabi et al., 2015). ...
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Schools start early in the morning all over the world, contrasting with adolescents’ late chronotype. These early school timings have negative consequences on academic performance (i.e. grades), which are worse for students with later chronotypes. This academic disadvantage has been associated with the misalignment between school schedule and adolescents’ internal timing, but it is unclear how this affects students’ academic success beyond their grades. To address this gap in knowledge, we studied how school timing and chronotype affect grade retention in a unique sample of students randomly assigned to one of three different school timings (starting at 07:45, 12.40 or 17:20). Even when controlling for academic performance, we found that later chronotypes exhibit higher odds of grade retention only in the morning, but not in later school timings. Altogether, ensuring a better alignment between school timing and students’ biological rhythms might enhance future opportunities of adolescents.
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Learning styles, cerebral dominance and chronotypes are among the factors that have been determined to be effective on individuals' learning. It is stated in the literature that these three variables are interrelated or affect each other. Therefore, the aim of the study is to determine the extent to which students' cerebral dominance predicts their learning styles and whether chronotypes have an effect on this level of prediction as a moderating variable. In the research, the "Morningness-Eveningness Stability Scale improved" (MESSI), the "Kolb Learning Style Inventory" (KLSI) and the "Hermann Brain Dominance Instrument" (HBDI) were used as data collection tools. The selection of upper-secondary schools included in the sample was made in a district of Antalya province with the convenience sampling method. The sample of 593 students who agreed to respond to the scale was formed from 9th, 10th, 11 th , and 12th grade students studying at these upper-secondary schools in the 2021-2022 academic year. According to the analysis results of the structural equation model (SEM) obtained in the study, it was concluded that there were significant positive correlations between learning styles and the sub-dimensions of cerebral dominance; however, chronotypes did not significantly mediate the determined correlations. The findings of this study may provide implications for determining learning styles, which have proven effects on student performance in the teaching-learning process, and, by establishing relationships between individuals' brain structures and chronotypes, the characteristics that direct learning preferences.
Objectives Chronotype impacts our state at a given time of day, however, chronotype is also heritable, trait-like, and varies systematically as a function of age and sex. However, only a handful of studies support a relationship between chronotype and trait-like cognitive abilities (i.e., intelligence), and the evidence is sparse and inconsistent between studies. Typically, studies have: (1) focused on limited subjective measures of chronotype, (2) focused on young adults only, and (3) have not considered sex differences. Here, using a combination of cognitive aptitude and ability testing, subjective chronotype, and objective actigraphy, we aimed to explore the relationship between trait-like cognitive abilities and chronotype. Design Participants (N = 61; 44 females; age = 35.30 ± 18.04 years) completed the Horne-Ostberg Morningness-Eveningness Questionnaire (MEQ) to determine subjective chronotype and wore an activity monitor for 10 days to objectively assess bedtime, rise-time, total sleep time, inter-daily stability, intra-daily variability, and relative amplitude. Cognitive ability (e.g., Verbal, Reasoning and Short-Term Memory) testing took place at the completion of the study. Results Higher MEQ scores (i.e., more morning) were associated with higher inter-daily stability scores. Superior verbal abilities were associated with later bedtimes, younger age, but paradoxically, higher (i.e., more morning) MEQ scores. Superior STM abilities were associated with younger age only. The relationships between chronotype and trait-like cognitive abilities were similar for both men and women and did not differ between younger and older adults. Conclusions The present study demonstrates that chronotype, measured by the MEQ, is highly related to inter-daily stability (i.e., the strength of circadian synchronization). Furthermore, although evening types have superior verbal abilities overall, higher (i.e., more morning) MEQ scores were related to superior verbal abilities after controlling for “evening type” behaviours.
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Background: There is growing evidence for the role of circadian factors in adolescents' sleep and academic adjustment, with greater evening preference being linked to poorer academic functioning. However, studies have yet to evaluate this association prospectively in adolescence, nor have studies examined daytime sleepiness as a putative mechanism linking evening preference to poor academic functioning. The current study used a multi-informant design to test the prospective association of evening circadian preference, daytime sleepiness, and academic functioning (e.g., global academic impairment and grades) across 2 years in adolescence. As evening circadian preference, sleepiness, and academic problems are elevated in adolescents with ADHD, we used a sample enriched for adolescents with ADHD and explored whether ADHD moderated effects. Method: Participants were 302 adolescents (Mage = 13.17 years; 44.7% female; 81.8% White; 52% with ADHD). In the fall of eighth grade, adolescents reported on their circadian preference, and in the fall of ninth grade, adolescents and parents completed ratings of daytime sleepiness. In the middle of 10th grade, parents and teachers reported on adolescents' academic impairment and at the end of 10th grade, adolescents' grade point average (GPA) was obtained from school records. Results: Above and beyond covariates (e.g., adolescent sex, ADHD status, medication, sleep duration) and baseline academic impairment, greater self-reported evening preference in 8th grade predicted increased parent ratings of academic impairment in 10th grade indirectly via adolescent and parent ratings of daytime sleepiness in 9th grade. Furthermore, evening preference in 8th grade predicted greater teacher ratings of academic impairment and lower average GPA in 10th grade via parent ratings of daytime sleepiness in 9th grade, controlling for covariates and baseline GPA. ADHD status did not moderate indirect effects. Conclusion: Findings underscore daytime sleepiness as a possible intervening mechanism linking evening preference to poor academic functioning across adolescence. Intervention studies are needed to evaluate whether targeting circadian preference and sleepiness improves academic functioning in adolescents.
Objective: The purpose of this study was to assess the prevalence of child behavior, academic and sleep concerns, and parent stress and depression symptoms during COVID-19; to test associations of parent-child well-being with child school format; and to examine effect moderation by child race/ethnicity and material hardship. Methods: A total of 305 English-speaking parents of elementary school-age children completed online surveys regarding demographics, child school format, behavior, learning-related experiences, sleep, and parent stress and depression symptoms. Multivariable linear and logistic regression analyses examined associations of school format with child and parent outcomes. Results: Children were aged 5.00 to 10.99 years, with 27.8% underrepresented minority race/ethnicity. Per parental report, 27.7% attended school in-person, 12.8% hybrid, and 59.5% remote. In multivariable models, compared with children receiving in-person instruction, children receiving remote instruction exhibited more hyperactivity (β 0.94 [95% confidence interval, 0.18-1.70]), peer problems (β 0.71 [0.17-1.25]), and total behavioral difficulties (β 2.82 [1.11-4.53]); were less likely to show academic motivation (odds ratio [OR] 0.47 [0.26-0.85]) and social engagement (OR 0.13 [0.06-0.25]); were more likely to show schoolwork defiance (OR 2.91 [1.56-5.40]); and had a later sleep midpoint (β 0.37 [0.18-0.56]) and higher odds of cosleeping (OR 1.89 [1.06-3.37]). Associations of remote learning with behavior difficulties were stronger for children without material hardships. Conclusion: Children receiving remote and hybrid instruction were reported to have more difficulties compared with children receiving in-person instruction. Children with material hardships showed more behavior challenges overall but less associated with school format. Therefore, planning for a return to in-person learning should also include consideration of family supports.
There is a growing concern in relation to the problem of insufficient sleep, particularly in the United States. In the early 1990s a Congressionally mandated commission noted that insufficient sleep is a major contributor to catastrophic events, such as Chernobyl and the Exxon Valdez, as well as personal tragedies, such as automobile accidents. Adolescents appear to be among the most sleep-deprived populations in our society, though they are rarely included in sleep assessments. This book explores the genesis and development of sleep patterns in adolenscents. It examines biological and cultural factors that influence sleep patterns, presents risks associated with lack of sleep, and reveals the effects of environmental factors such as work and school schedules on sleep. Originally published in 2002, Adolescent Sleep Patterns will appeal to psychologists and sociologists of adolescence who have not yet considered the important role of sleep in the lives of our youth.
The present study examined the extent to which motivation contributes to the prediction of school achievement among elementary school children beyond general mental ability (g). The sample consisted of N = 1678 nine-year-old UK elementary school children who took part in the Twins Early Development Study (TEDS). Teachers provided achievement assessments according to the UK National Curriculum criteria for Mathematics, English, and Science, and pupils reported their ability self-perceptions and intrinsic values for these subjects. For all three domains, g proved to be the strongest, and, in the case of Science, the only predictor of school achievement. However, in Mathematics and English, children's ability self-perceptions as well as intrinsic values each contributed incrementally to the prediction of achievement beyond g, with ability self-perceptions being a better predictor than intrinsic values. Finally, commonality analyses revealed a substantial portion of common variance in school achievement explained both by g and motivation. In the light of these results it is argued that the study of motivation offers valuable clues for the understanding and improvement of school achievement.
The feasibility of using self-concept measures along with intelligence measures to improve the prediction of achievement was explored. Two self-concept tests, an intelligence test, and an achievement test battery were administered to 47 male and 49 female sixth graders. Achievement was found to be related to academic success self-concept, but not to physical maturity, peer relations, or school adaptiveness self-concepts. Achievement in the content areas of reading, language, and mathematics was most directly related to self-concept measures that were specifically reflective of academic success in these content areas. In each of these areas, the combination of intelligence and the related academic success self-concept measure accounted for more achievement variance than did intelligence alone. This last finding was interpreted as evidence suggesting that content area specific self-concept measures might facilitate the prediction of academic success, and researchers wishing to control for self-concept in studies of academic achievement should use measures of self-concept that are specifically reflective of academic success in the content area being investigated.
A cross-validation study is reported in which both personality variables and cognitive ability variables were evaluated as predictors of two separate performance criteria in a sample of 450 Master of Business Administration students. Whereas verbal and quantitative aptitudes of the students were found to be strong predictors of performance at written work, they were weak predictors of an in-class performance criterion. The opposite was true when specific personality trait variables were used as predictors. The personality characteristics of the students predicted classroom performance better than they predicted written performance. The Big Five factors of personality (Extraversion, Agreeableness, Conscientiousness, Neuroticism, and Openness to Experience) did not predict either criterion consistently. In conclusion, personality variables are related to academic success when characteristic modes of behavior play a role in academic performance.
Two studies, 1 longitudinal and 1 cross-sectional, demonstrate that for young elementary school children, academic intrinsic motivation is a reliable, valid, and significant construct. It was positively related to achievement, IQ, and perception of competence, and inversely related to anxiety. Academic intrinsic motivation at age 9 was significantly predicted by motivation measured 1 and 2 years earlier, above and beyond the contribution of IQ and achievement. Children with higher academic intrinsic motivation at ages 7 and 8 were more likely to show higher motivation at age 9. Whereas young children could reliably distinguish between subject areas of academic intrinsic motivation, only math motivation showed consistently specific relations to other math criteria. Findings are discussed with regard to developmental theories of intrinsic motivation and the significance of academic intrinsic motivation for children's education.
Within the school context substantial correlations between interests and grades are well documented, but the causal ordering still remains unclear. The paper examines how the relation between interests and grades over several measurement waves in elementary school age can be characterized, whether gender differences in the pattern of effects can be shown, and whether the effects are school-subject-specific. The present analysis follows N = 1.199 students in the 3rd Grade over a year and a half. It can be shown that grading determines the level of future interests but not vice versa. Thereby, the pattern of results concerning interests and grades is similar for boys and girls. The effects of grades on subsequent interests are mostly school-subject-specific.
Many adolescents experience a discrepancy between their biological time, which is shifted toward eveningness, and early school starting times. Due to this social jetlag, eveningness is negatively correlated with school performance. On the basis of the here presented data, we derived a model for the association of chronotype and school performance, the Chronotype-Academic Performance Model (CAM), including daytime sleepiness and achievement motivation as mediating factors. The sample comprised N = 273 adolescents aged 14–16 years. Circadian preference, daytime sleepiness, learning and achievement motivation, and information about participants’ last school certificate were assessed online. Chronotype was not directly related to academic performance, but was mediated by daytime sleepiness and learning motivation. Morning-orientation was negatively associated with daytime sleepiness and positively with learning motivation, which, in turn, affected performance. In evening-types, we found the strongest association between sleepiness and refusal to work. The CAM suggests that chronotype may not directly influence academic performance, but be mediated by daytime sleepiness and learning motivation. Evening types seem to be at high risk to suffer from daytime sleepiness and to display dysfunctional attitudes toward work. Measures of reducing sleepiness and modifying attitudes toward academic achievement might attenuate the disadvantages of evening-types due to social jetlag.