Learning and Individual Differences 32 (2014) 184–192

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Learning and Individual Differences

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Circadian Preferences, Sleep Quality and Sleep Patterns, Personality,Academic Motivation and Academic Achievement of university students

İsmail Önder a,⁎, Şenol Beşoluk a, Murat İskender b, Ercan Masal c, Eda Demirhan a

a Faculty of Education, Department of Science Education, Sakarya University, Turkeyb Faculty of Education, Department of Psychological Counseling and Guidance, Sakarya University, Turkeyc Faculty of Education, Department of Secondary Science and Mathematics Education, Sakarya University, Turkey

⁎ Corresponding author at: Sakarya Üniversitesi EğiSakarya, Turkey. Tel.: +90 2642957169; fax: +90 264295

E-mail address: ionder@sakarya.edu.tr (İ. Önder).

http://dx.doi.org/10.1016/j.lindif.2014.02.0031041-6080/© 2014 Elsevier Inc. All rights reserved.

a b s t r a c t

a r t i c l e i n f o

Article history:Received 18 July 2013Received in revised form 28 December 2013Accepted 21 February 2014

Keywords:Morningness–Eveningness PreferenceSleepPersonalityMotivationCumulative Grade Point Average

In the current study, the relationships among Circadian Preferences, Sleep Quality and Sleep Patterns, Per-sonality, Academic Motivation and the Academic Achievement of university students are examined. 1343university students (62.8% females and 37.2% males) participated in the study. Data was gathered fromeach participant using a Morningness–Eveningness Questionnaire (MEQ), Pittsburgh Sleep Quality Index(PSQI), Adjective Based Personality Test (ABPT), Academic Motivation Scale (AMS-C) and Descriptive Ques-tionnaire, completed voluntarily. A regression analysis model revealed the following predictors: correctedMidpoint of Sleep, Academic Motivation, Social Jetlag, Conscientiousness, Intrinsic Motivation toward Accom-plishment, Intrinsic Motivation to Experience Stimulation and Neuroticism, explaining 15.1% of the varianceof Cumulative Grade Point Average (CGPA). Meanwhile, CGPA scores of earlier chronotypes were higherthan those of later chronotypes.CorrectedMidpoint of Sleep, global PSQI, Conscientiousness, ExtrinsicMotivation-External Regulation and Intrin-sic Motivation to Experience Stimulation, Social Jetlag, Extraversion, Intrinsic Motivation toward Accomplish-ment and Intrinsic Motivation to Know emerged as significant predictors of MEQ explaining the 26.7% of thevariance. Conscientiousness, CGPA, Openness to Experience, Neuroticism and Social Jetlag were the significantpredictors of AMS-C explaining 14.7% of the variance inAcademicMotivation. Analysis in Sleep Quality presentedthat 13.4% of the variance was explained by chronotype preference, Average Sleep Length (ASL), Neuroticism,corrected Midpoint of Sleep and Extraversion.Moreover, in the female sample both Sleep Quality and AcademicMotivation ofmorning type students werebetter than those of evening types and those of neither type. Meanwhile regression analysis shows that inall Personality traits Academic Motivation and sub-domains of Academic Motivation are significant predic-tors; and in some Personality traits, ASL, circadian typology and Academic Achievement emerged as signif-icant predictors. These results suggested that Circadian Preferences, Sleep Quality and Sleep Patterns,Personality and Academic Motivation were interrelated and had a significant effect on AcademicAchievement.

© 2014 Elsevier Inc. All rights reserved.

1. Introduction

1.1. Chronotype

The concept of morningness–eveningness (M–E) shows inter-individual differences in academic performance (Díaz-Morales &Escribano, 2013; Roeser, Schlarb, & Kübler, 2013), can be derived from

tim Fakültesi, 54300 Hendek,7183.

physiological parameters, e.g., concentration of melatonin or cortisol,core body temperature, sleep–wake cycle (Adan et al., 2012; Randler,2008; Randler & Schaal, 2010; Waterhouse, Fukuda, & Morita, 2012)and is usuallymeasured in a continuous scalewhere individuals depend-ing on their position in the continuum may be morning type (MT), nei-ther type (NT) or evening type (ET) (Natale & Cicogna, 2002). CircadianPreference is partly genetic (Adan et al., 2012) and is also affected byother factors, including age, gender and cultural, social, environmental,technological and biological variables (Adan et al., 2012; Randler, 2008,2011; Randler, Vollmer, Beşoluk, Önder, & Horzum, 2013; Vollmer,Michel, & Randler, 2012). Meanwhile, M–E is related to variables suchas preferred bed/rise times, Midpoint of Sleep, and preferred time for

185İ. Önder et al. / Learning and Individual Differences 32 (2014) 184–192

mental and physical activity (Adan et al., 2012). MT individuals feel andperform best in the morning hours (Valdez, Reilly, &Waterhouse, 2008)while ET individuals perform and feel best later on in the day (Martin &Martin, 2013). However, due to common social demands ET individualshave to keep up with morning activities and duties when theirchronotype is in asynchrony with their preferred time of day (Díaz-Morales & Escribano, 2013). This asynchrony between social and biolog-ical rhythms (Social Jetlag) causes ET individuals to sleep less on work/school days (Tzischinsky & Shochat, 2011; Wittmann, Dinich, Merrow,& Roenneberg, 2006) and may affect their pattern and quality of sleep.Furthermore, MT individuals who have to work or study at later timesof the day may be faced with similar problems. The times at which indi-viduals rise and retire are different onwork/school days and free days be-cause of these social demands. As such Roenneberg, Wirz-Justice, andMerrow (2003) and Roenneberg et al. (2004) suggest determiningchronotype by the use of corrected Midpoint of Sleep in free days(MSFsc).

1.2. Sleep, chronotype and Academic Achievement

Sleep, as an important human biological process, has effects onhuman behavior, psychology and health (Megdal & Schernhammer,2007). Research indicates that insufficient sleep, poor quality sleep orunusual sleep habits have a negative influence on individuals' physicaland mental health, performance and activity (Preišegolavičiūtė,Leskauskas, & Adomaitienė, 2010; Valdez et al., 2008). Although sleepproblems have such negative effects, insufficient sleep or poor qualitysleep is common among university students (Carney, Edinger, Meyer,Lindman, & Istre, 2006; Suen, Hon, & Tam, 2008). Meanwhile, Gomes,Tavares, and de Azevedo (2011) indicated that self-reported SleepQuality and self-reported frequency of sufficient sleep together withsome other variables were among themain predictors of academic per-formance. On the other hand, Eliasson, Eliasson, King, Gould, andEliasson (2002) reported no correlation between sleep length and aca-demic performance. Chronotype influences the quality of sleep–wakecycle and sleep deprivation thus influence the learning of universitystudents (Onyper, Thacher, Gilbert, & Gradess, 2012). Several studieshave found that ET students have poorer Sleep Quality than MT and/or NT ones (Lima, Varela, Silveira, Parente, & Araujo, 2010; Vardar,Vardar, Molla, Kaynak, & Ersoz, 2008). Meanwhile, Borisenkov,Perminova, and Kosova (2010) indicated that the effect of chronotypewas stronger than that of sleep duration on students' achievement.Students that easily wake up in the morning and are thereforeactive at earlier times of day were found to perform better in schooland exams than ET students (Beşoluk, 2011; Beşoluk, Önder, &Deveci, 2011; Curcio, Ferrara, & De Gennaro, 2006; Önder, Horzum, &Beşoluk, 2012; Preckel, Lipnevich, Schneider, & Roberts, 2011). Similar-ly, MT students were found to have higher grade point averages(GPA) and fewer school-related problems compared to ET students(Vollmer, Schaal, Hummel & Randler, 2011; Wolfson & Carskadon,1998).

1.3. Motivation, chronotype and Academic Achievement

Apart from chronotype and sleep-related variables, Motivationalso affects Academic Achievement and students' performance inschool. Roeser et al. (2013) indicated that learning and achieve-ment Motivation may explain the link between chronotype andAcademic Achievement. Since ET individuals are less alert in theearly hours of the day, they may have difficulty in meeting the de-mands of instructors and therefore have lower motivation to learnand achieve. Moreover, ET individuals have difficulty in waking upearly in the morning and have more sleepiness, so they may go toschool with low motivation. On the other hand, the academic per-formance of MT students might be higher since they are morealert, they have less sleep related problems and better Sleep

Quality (Escribano, Díaz-Morales, Delgado, & Collado, 2012), andthey may have higher motivation to learn and achieve (Roeseret al., 2013).

1.4. Personality, sleep, chronotype and Academic Achievement

Previous research has investigated the association of Big Five Per-sonality traits with sleep–wake variables, chronotype, and academicperformance. Controversial results were reported with respect tothe association between sleep duration and Personality variables.Soehner, Kennedy, and Monk (2007) found no correlation betweensleep duration and Personality variables, but some others havefound a correlation (Gau, 2000; Randler, 2008). With respect to Per-sonality and chronotype, Conscientiousness was reported as the bestpredictor of morningness (Adan et al., 2012). Meanwhile, positive re-lationships were found between Agreeableness and morningness(DeYoung, Hasher, Djikic, Criger, & Peterson, 2007; Randler, 2008),and Neuroticism and eveningness (Randler, 2008; Tonetti, Fabbri, &Natale, 2009). With respect to Personality variables and academicperformance, Conscientiousness was reported as the most stronglyrelated Personality variable with academic performance (Chamorro-Premuzic & Furnham, 2005; Gray & Watson, 2002; O'Connor &Paunonen, 2007) and a positive association was reported betweenOpenness to Experience and academic performance (Chamorro-Premuzic & Furnham, 2005; O'Connor & Paunonen, 2007). The asso-ciation between Conscientiousness and academic performance is ex-plained by Motivation since conscientious students might be moremotivated to perform well academically (Chamorro-Premuzic &Furnham, 2005). Moreover, several studies have shown that IntrinsicMotivation, Extrinsic Motivation and Amotivation are related withPersonality traits (Clark & Schroth, 2010; Komarraju & Karau, 2005;Komarraju, Karau, & Schmeck, 2009).

1.5. Aims of the study

Many factors affect Academic Achievement, and some of those arerelated to individual differences. The ability to predict individual dif-ferences that affect Academic Achievement may have valuable educa-tional applications. We hypothesized that the chronotype/CircadianPreference, Academic Motivation, Personality and sleep variables areassociated with Academic Achievement. However no study wasfound in the literature that investigates the relationships amongthese variables concurrently. Therefore the main purpose of thepresent study is to assess associations among chronotype/CircadianPreferences, Sleep Quality and Sleep Patterns, Personality, AcademicMotivation and Academic Achievement for the first time in a Turkishuniversity population, and to determinewhether chronotype/CircadianPreferences, Sleep Quality and Sleep Patterns, Personality, and Aca-demic Motivation are predictors of Academic Achievement, and ifso how Academic Achievement scores change with respect to thesevariables. Meanwhile, we also hypothesized that Circadian Prefer-ence is associated with Academic Motivation, Personality and sleepvariables. Therefore we have also investigated whether CircadianPreference predicts Academic Motivation, Personality and sleep var-iables and if so, how the scores on these variables change with re-spect to chronotype.

2. Method

In the current study a surveymethodologywas used. Simple randomsampling was used in selecting university students that will participatein the study. Students completed the data-collecting tools anonymouslyand voluntarily.

186 İ. Önder et al. / Learning and Individual Differences 32 (2014) 184–192

2.1. Sample

Data was collected from 1343 university students (62.8% femalesand 37.2% males) enrolled in the departments of science education, so-cial studies education, primary education, Turkish language education,mathematics education, special education, computer education and in-structional technology, and psychological counseling and guidance. Thesample consisted of sophomore, junior, and senior students from eachdepartment and the proportion of each grade level reflects the propor-tion of each grade level in the population. Freshmen students were notincluded in the sample because they can have some adaptation prob-lems which could affect the results. The ages of the students rangedfrom 18 to 34, with a mean of 21.01 years and a standard deviation of1.78 years. The descriptive data regarding the sample were presentedin Appendix 1.

2.2. Instruments

2.2.1. Morningness–Eveningness Questionnaire (MEQ)The MEQ, devised by Horne and Östberg (1976), consists of 19

mixed-format questions regarding habitual rising and bed times,the preferred times for physical and mental activities, and subjec-tive alertness. MEQ yields scores ranging from 16 to 86 wherehigh scores indicate morningness. MEQ was adapted into Turkishby Pündük, Gür, and Ercan (2005) and they have reported thatthe MEQ's reliability is high, with a Cronbach's alpha value of.812. The internal consistency coefficient of the scale in the currentstudy was .761.

2.2.2. Pittsburgh Sleep Quality Index (PSQI)The PSQI is a 19-item self-rating tool designed to measure

Sleep Quality and pattern of sleep over the past month, developed byBuysse, Reynolds, Monk, Berman, and Kupfer (1989). The itemsthat should be rated by the participant's bed partner or roommatewere excluded in this study. The PSQI contains seven components:subjective Sleep Quality, sleep-onset latency, sleep duration, sleepefficiency, sleep disturbances, use of sleepingmedications, and daytimedysfunction. Each component's score can range from 0 to 3 and thesum of those component scores gives a global Sleep Quality scoreranging from 0 to 21. Scores higher than 5 in the global PSQI indicatepoor Sleep Quality (Buysse et al., 1989). The scale was adapted intoTurkish byAğargün, Kara, and Anlar (1996) and they reported the inter-nal consistency coefficient of the scale as .804; in the current study itwas .781.

2.2.3. Adjective Based Personality Test (ABPT)The ABPT was developed by Bacanlı, İlhan, and Aslan (2009),

based on the Five Factor Model of Personality. The instrument con-tains 40 adjective pairs with a 7 point Likert-type scale and fivesubscales; Neuroticism, Extraversion, Openness to Experience,Agreeableness and Conscientiousness. The internal consistency coef-ficients and test–retest reliabilities of the five sub-scales reportedby the original authors range between .73 and .89. Both constructand concurrent validity results were significant. The internal consis-tency coefficients of the five sub-scales in the current study rangedfrom .712 to .874.

2.2.4. Academic Motivation Scale (AMS-C)The AMS-C was developed by Vallerand et al. (1992) and contains

seven sub-scales: Intrinsic Motivation (IM) to Know, IM toward Accom-plishment, IM to Experience Stimulation, Extrinsic Motivation (EM)Identified, EM Introjected, EM External Regulation, and Amotivation.The AMS-C contains 28 items and the scores range from −18 to +18.

The internal consistency coefficients reported by Vallerand et al.(1992) vary from .62 to .86. The AMS-C was adapted into Turkish byDemir (2008) and the internal consistency coefficients of the sevensub-scales ranged from .70 to .80 in her study. The internal consistencycoefficients of seven sub-scales in the current study range between .789and .854.

2.2.5. Descriptive questionnaireA demographic questionnaire was used to gather data on the partic-

ipants' gender, department, grade, age, and retiring and rising times(both on weekdays and on weekends). Corrected Midpoint of Sleep inFree days (MSFsc: as another indicator of chronotype), Average SleepLength (ASL) and Social Jetlag variables were calculated from rise andretire times.

2.2.6. Statistical analysisIn the study the students' Cumulative Grade Point Averages

(CGPAs) were used as an indicator of overall Academic Achievement.Therefore the cumulative grade point averages of students from var-ious majors with mean (M) and standard deviation (SD) of eachmajor and grade level were obtained from the registry, with the stu-dents' permission. The mean and standard deviation scores obtainedfrom the registry were used to compute t-scores in order to stan-dardize CGPA data [t-score = (((Xi − M) ∕ SD) ∗ 10) + 50; Xi:CGPA of ith individual, M: mean CGPA of students with same gradeand department with that of ith individual; and SD: standard devia-tion of CGPA scores obtained from students with same grade and de-partment with that of ith individual]. The t-scores were used as datain all CGPA analyses. Possible associations among Academic Achieve-ment, Circadian Preferences, Sleep Quality and Sleep Patterns, Per-sonality and Academic Motivation variables were tested by Pearsonproduct–moment correlation coefficients. Additionally, a series of si-multaneous regression analyses were conducted to investigate therelationship among Circadian Preferences, Sleep Quality and SleepPatterns, Personality, Academic Motivation and Academic Achieve-ment in a more systematic manner. Stepwise regression detects themodel which explains the highest amount of variance in the datawith the smallest number of predictors. Two-way analysis of covari-ance (ANCOVA) was conducted to evaluate the effect of chronotype(MSFsc) and Sleep Quality [good (PSQI score ≤ 5) and poor (PSQIscore N 5)] on CGPA after adjusting for age and Motivation (AMS-C).Meanwhile, in order to control the effect of gender this analysis wasperformed for males and females separately. MSFsc was calculatedwith the formula described by Roenneberg et al. (2004) [MSFSC =MSF− 0.5 ∗ (SDF − (5 ∗ SDW + 2 ∗ SDF) ∕ 7)]; MSF: Midpoint of Sleep onFree days, SDF: Sleep duration on free days, and SDW: Sleep durationon work days]. Midpoint of Sleep on Weekends was used instead ofMidpoint of Sleep in free days in the formula, because our qualitativestudies in university students showed that they perceive weekends asfree days. For the categorical analysis, MSFSC was divided into twogroups (≤median and Nmedian; earlier and later chronotypes) asindicated in Genzel et al. (2013). ASL was calculated with the formuladescribed by Juda, Vetter, and Roenneberg (2013) [ASL = (5 ∗ SDW +2 ∗ SDF) ∕ 7] and Social Jetlag was calculated with the formulapresented by Roenneberg, Allebrandt, Merrow, and Vetter (2012)[Social Jetlag = MSF − MSW; MSW: mid-sleep on work days]. One-wayANCOVAwas conducted to evaluate the effect of chronotypeprefer-ence (MEQbased;MT, NT, ET) on variables (SleepQuality andAcademicMotivation) controlling the variance of age. Meanwhile, in order tocontrol the effect of gender this analysis was performed for malesand females separately. In this analysis three classes of chronotypepreference were used: ET (MEQ score 16–41), NT (MEQ score 42–58),andMT (MEQ score 59–86). AcademicMotivation scores were calculat-ed with the formula described by Guay, Mageau, and Vallerand (2003)[self-determination index = (2 × (IM to Know + IM to accomplish +

187İ. Önder et al. / Learning and Individual Differences 32 (2014) 184–192

IM to Experience Stimulation) ∕ 3 + Identified Regulation) −((Introjected Regulation + External Regulation) ∕ 2 + 2 ×Amotivation)]. The level of significance was set to .05 corrected

Table 1Regression results.

Variable Predictor

CGPA MSFscAMS-CSocial JetlagConscientiousnessIntrinsic motivation toward acIntrinsic motivation to experieNeuroticism

MEQ MSFscGlobal PSQIConscientiousnessExtrinsic motivation external rIntrinsic motivation to experieSocial JetlagExtroversionIntrinsic motivation toward acIntrinsic motivation to know

Academic Motivation AMS-C ConscientiousnessCGPAOpenness to ExperienceNeuroticismSocial Jetlag

Intrinsic Motivation Openness to ExperienceCGPAConscientiousnessAgreeablenessMSFscNeuroticism

Extrinsic Motivation ConscientiousnessMSFscCGPAOpenness to ExperienceMEQAgreeableness

Amotivation ConscientiousnessCGPAAgreeablenessNeuroticism

Sleep Quality (Global PSQI) MEQASLNeuroticismMSFscExtroversion

Big Five Personality Traits Extroversion Intrinsic motivation to knowAMS-C

Agreeableness AMS-CMEQASLIntrinsic motivation toward acExtrinsic motivation identified

Conscientiousness AMS-CMEQIntrinsic motivation toward acCGPAIntrinsic motivation to experieExtrinsic motivation introjecteASLGlobal PSQI

Neuroticism Global PSQIASLAMS-CCGPAIntrinsic motivation toward acIntrinsic motivation to know

Openness to Experience AMS-CIntrinsic motivation to know

MEQ: Morningness–Eveningness Questionnaire; AMS-C: Self-determination Index; Global PSQCorrected mid-sleep time on free days; ASL: Average Sleep Length.

according to the Bonferroni procedure for multiple testing (to hold thealpha level at ≤ .05). The software package PASW Statistics 18.0 wasused for all statistical analyses.

Beta R2 Change in R2 Significance

−.194 .064 .064 F(7, 1106) = 28.197, p b .001.166 .109 .044

−.115 .122 .014.100 .135 .013

complishment .161 .142 .007nce stimulation −.110 .148 .006

.059 .151 .003−.403 .191 .191 F(9, 1104) = 44.582, p b .001−.153 .213 .022

.166 .229 .016egulation −.136 .242 .013nce stimulation .122 .253 .011

.067 .258 .004−.070 .261 .003

complishment −.103 .264 .003.084 .267 .003.149 .080 .080 F(5, 1108) = 38.246, p b .001.197 .108 .028.185 .134 .026

−.089 .143 .008.067 .147 .004.259 .074 .074 F(6, 1107) = 26.123, p b .001.156 .096 .022.155 .104 .008

−.144 .115 .011.076 .120 .005

−.061 .124 .004.211 .052 .052 F(6, 1107) = 20.504, p b .001.132 .072 .020.123 .086 .014.120 .092 .006

−.074 .096 .005−.077 .100 .004−.116 .042 .042 F(4, 1109) = 23.079, p b .001−.135 .057 .016−.119 .069 .013

.073 .074 .005−.176 .044 .044 F(5, 1108) = 34.417, p b .001−.241 .088 .043

.182 .119 .031

.119 .130 .011−.069 .134 .005

.126 .041 .041 F(2, 1111) = 27.981, p b .001

.114 .048 .007

.201 .052 .052 F(5, 1108) = 19.077, p b .001

.098 .062 .011−.080 .068 .006

complishment −.120 .073 .005.116 .079 .006.204 .080 .080 F(8, 1105) = 25.333, p b .001.143 .105 .025

complishment .144 .123 .018.115 .137 .013

nce stimulation −.141 .144 .008d .101 .148 .004

−.074 .152 .004−.060 .155 .003

.195 .033 .033 F(6, 1107) = 11.901, p b .001

.073 .040 .007−.091 .046 .006

.070 .052 .006complishment .121 .056 .004

−.105 .061 .005.168 .077 .077 F(2, 1111) = 55.808, p b .001.162 .091 .014

I: Global Pittsburgh Sleep Quality Index; CGPA: Cumulative Grade Point Average; MSFsc:

188 İ. Önder et al. / Learning and Individual Differences 32 (2014) 184–192

3. Results

3.1. Preliminary analysis

The distributions of the variables [CGPA, Circadian Preferences(MEQ), Sleep Quality (PSQI), Sleep Patterns (ASL, MSFSC and So-cial Jetlag), Personality and Academic Motivation (AMS-C andsub-domains)] were examined for normality via skewness andkurtosis (N±1). The variables were normally distributed exceptthe Amotivation variable (skewness = 1.56 and kurtosis =1.97). Past research indicated that the Amotivation sub-domainoften displays a skewed distribution and this non-normal distri-bution does not pose any problem (Gillet, Vallerand, & Rosnet,2009).

3.2. Descriptive results

The data collecting tools were completed by 1343 universitystudents; however there were missing values in each variable andthese missing values were excluded from the analysis. Therefore,full datasets for each variable were used. Group size, mean andstandard deviation of MEQ, Academic Motivation, Personalityvariables, Sleep variables, Sleep Quality and CGPA for total sample,gender, chronotype, Sleep Quality and age are presented inAppendix 1.

3.3. Academic Achievement-related results

Pearson product–moment correlations (presented in Appendix 2)among Circadian Preference, Sleep Quality, Sleep Pattern, Personality,Academic Motivation and Academic Achievement variables showedthat CGPA mainly correlates positively with AMS-C, IM, EM, MEQ,Agreeableness and Conscientiousness, and negatively with MSFSC,Social Jetlag and Amotivation. A stepwise regression analysis modelclarified the nature of relations, and revealed MSFSC (β = − .194),AMS-C (β = .166), Social Jetlag (β = − .115), Conscientiousness(β = .100), IM toward Accomplishment (β = .161), IM to Experi-ence Stimulation (β = − .110) and Neuroticism (β = .059) asthe predictors explaining 15.1% (R2) of the variance of CGPA (seeTable 1). The effect size of the analysis was [f2 = R2 / (1 − R2)]0.178 indicating a medium effect size. MSFSC was the main predic-tor of CGPA and the Sleep Quality of the sample was mainly poor,therefore in order to investigate the effect of both variables onCGPA, two-way ANCOVA was performed. ANCOVA with chronotype(earlier/later) and Sleep Quality (poor/good) as fixed factors, andage and Academic Motivation as covariates presented a significantmain effect of chronotype on Academic Achievement (CGPA) inboth female [F(1, 636) = 8.896, p = .003, η2 = .014] and male[F(1, 310) = 12.511, p b .001, η2 = .039] samples. The main effectof Sleep Quality andthe interaction's simple effect were not statisti-cally significant (p N .05) in both samples. Bonferroni-correctedmultiple comparison tests indicated that the CGPA scores of earlierchronotypes (female sample: adj. M = 53.86, SE = 0.49, 95% CI =52.90–54.83; male sample: adj. M = 49.09, SE = 0.85, 95% CI =47.41–50.76) were better than later chronotypes (female sample:adj. M = 51.49, SE = 0.62, 95% CI = 50.27–52.71; male sample:adj. M = 45.16, SE = 0.70, 95% CI = 43.79–46.54) in both samples.

3.4. Circadian Preference (MEQ)-related results

On the whole, MEQ correlates positively with AMS-C, Agreeable-ness and Conscientiousness, and negatively with global PSQI, andASL (correlations already presented in the previous analysis werenot indicated). To clarify the nature of relations, regression analysiswas conducted and it was found that 26.7% of the variance wasexplained by MSFSC (β = − .403), global PSQI (β = − .153),

Conscientiousness (β = .166), EM External Regulation (β =− .136), IM to Experience Stimulation (β = .122), Social Jetlag (β =.067), Extraversion (β = − .070), IM toward Accomplishment (β =− .103) and IM to Know (β = .084). The effect size of the analysiswas 0.364 (f2) indicating a large effect size.

3.5. Sleep-related results

Global PSQI mainly correlates positively with Neuroticism, MSFSCand Social Jetlag, and negatively with ASL. Regression analysis conduct-ed to investigate the extent to which Circadian Preference, Sleep Pat-terns, Big Five traits, CGPA and Academic Motivation explained thevariance in Sleep Quality presented that 13.4% of the variance was ex-plained by MEQ (β = − .176), ASL (β = − .241), Neuroticism (β =.182), MSFSC (β = − .119) and Extraversion (β = − .069). The ef-fect size of the analysis was 0.155 (f2) indicating a medium effectsize. Since MEQ was the main predictor of Sleep Quality one-wayANCOVA was run to investigate whether Sleep Quality differsamong Circadian Preferences. ANCOVA with chronotype preference(MT, NT and ET) as a fixed factor, and age as a covariate showed asignificant effect of chronotype preference on Sleep Quality (globalPSQI) in the female sample [F(2, 742) = 16.783, p b .001, η2 =.043] but no effect of chronotype preference on Sleep Quality wasfound in the male sample (p N .05). Bonferroni-corrected multiplecomparison tests conducted in the female sample indicated thatthe sleep qualities of MT students (adj. M = 6.39, SE = 0.22, 95%CI = 5.96–6.83) were better than both NT (adj. M = 7.14, SE =0.13, 95% CI = 6.89–7.39) and ET (adj. M = 8.47, SE = 0.28, 95%CI = 7.92–9.02) students. Similarly, the sleep qualities of NT stu-dents were better than ET students.

3.6. Academic Motivation-related results

On the whole, AMS-C correlates positively with the Big Five Person-ality traits (except Neuroticism). Moreover, regression analysis re-vealed that 14.7% of the variance in Academic Motivation (AMS-Ctotal) was explained by Conscientiousness (β = .149), CGPA (β =.197), Openness to Experience (β = .185), Neuroticism (β = − .089),and Social Jetlag (β = .067), and the effect size was medium (f2 =0.172). For IM, 12.4% of the variance was explained by Openness to Ex-perience (β = .259), CGPA (β = .156), Conscientiousness (β = .155),Agreeableness (β = − .144), MSFSC (β = .076) and Neuroticism (β =− .061), and the effect size was medium (f2 = 0.142). For EM, 10.0%of the variance was explained by Conscientiousness (β = .211), MSFSC(β = .132), CGPA (β = .123), Openness to Experience (β = .120),MEQ (β = − .074) and Agreeableness (β = − .077). The effect sizewas small (f2 = 0.111). For Amotivation, 7.4% of the variance wasexplained by Conscientiousness (β = − .116), CGPA (β = − .135),Agreeableness (β = − .119) and Neuroticism (β = .073). The effectsize was small (f2 = 0.079). Since sub-domains of Academic Motiva-tion was predicted by MEQ or MSFSC, one-way ANCOVA was run toinvestigate whether Academic Motivation differs among CircadianPreferences. ANCOVA with chronotype preference (MT, NT and ET)as a fixed factor, and age as a covariate showed a significant effectof chronotype preference on AMS-C in the female sample [F(2,708) = 9.645, p b .001, η2 = .027] but no effect of chronotype pref-erence on Academic Motivation was found in male sample (p N .05).The Bonferroni-corrected multiple comparison tests conducted in thefemale sample indicated that the Academic Motivations of MT stu-dents (adj. M = 7.80, SE = 0.30, 95% CI = 7.20–8.40) were betterthan both NT (adj. M = 6.32, SE = 0.18, 95% CI = 5.97–6.67) andET (adj. M = 6.16, SE = 0.38, 95% CI = 5.41–6.91) students. Howev-er, Academic Motivations of NT students and ET students did not dif-fer (p N .05).

189İ. Önder et al. / Learning and Individual Differences 32 (2014) 184–192

3.7. Personality related results

Agreeableness and Conscientiousness were found to correlate nega-tively withMSFSC and ASL. Regression analysis conducted to investigatehowmuch of the variance in the Big Five traits was explained by Circa-dian Preference, Sleep Quality/Patterns, CGPA and AcademicMotivationrevealed that: 4.8% of the variance in Extraversion was explained by IMto Know (β = .126) and AMS-C (β = .114), and the effect size wassmall (f2 = 0.050). For Agreeableness, 7.9% of the variance was ex-plained by AMS-C (β = .201), MEQ (β = .098), ASL (β = − .080), IMtoward Accomplishment (β = − .120) and EM Identified (β = .116).The effect size of the analysiswas small (f2= 0.086). For Conscientious-ness, 15.5% of the variance was explained by AMS-C (β = .204), MEQ(β = .143), IM toward Accomplishment (β= .144), CGPA (β= .115),IM to Experience Stimulation (β=− .141), EM Introjected (β= .101),ASL (β = − .074) and global PSQI (β = − .060), and effect size wasmedium (f2 = 0.183). For Neuroticism, 6.1% of the variance was ex-plained by global PSQI (β = .195), ASL (β = .073), AMS-C (β =− .091), CGPA (β = .070), IM toward Accomplishment (β = .121)and IM to Know (β = − .105). The effect size of the analysis wassmall (f2 = 0.065). And for Openness to Experience, 9.1% of the vari-ance was explained by AMS-C (β = .168) and IM to Know (β =.162), and effect size was small (f2 = 0.100).

4. Discussion and conclusion

In the current study, CGPA was found to relate with CircadianPreference (Morningness–Eveningness), Academic Motivation, Per-sonality traits (Agreeableness, Conscientiousness) and Sleep Patterns(MSFsc and Social Jetlag). Similar results were reported in previousresearches (Beşoluk et al., 2011; Borisenkov et al., 2010; Gomeset al., 2011; Komarraju et al., 2009; Vollmer, Pötsch, & Randler,2013; Wolfson & Carskadon, 2003). The regression analysis clarifiedthe nature of the relationship between CGPA and other variables(chronotype/Circadian Preference, Sleep Quality and Sleep Patterns,Big Five Personality traits and Academic Motivation). MSFsc, AMS-C,Social Jetlag and Conscientiousness were the main predictors of Aca-demic Achievement. Meanwhile, IM toward Accomplishment, IM toExperience Stimulation and Neuroticism also contributed to the vari-ance explained. Students who are more morning-oriented, have a de-sire to accomplish, are more conscientious and neurotic and are likelyto have higher CGPA scores. Since MSFsc is the best marker for sleep-based assessments of chronotype (Juda et al., 2013), a negative rela-tion of MSFsc and Social Jetlag with CGPA indicates that studentswith morning chronotype and with less sleep debt have higherCGPA scores. O'Connor and Paunonen (2007) have indicated thatsince conscientious students are more motivated, self-disciplinedand diligent, they may perform better academically than less consci-entious students. Meanwhile, conscientious students are more moti-vated to perform well academically, so the relationship betweenConscientiousness and Academic Achievement should be interpretedwith consideration for motivation (Chamorro-Premuzic & Furnham,2005; O'Connor & Paunonen, 2007). In the current study the highestcorrelation between Personality traits and Academic Achievementwas observed between Conscientiousness and Academic Achieve-ment. This supports the notion that conscientious students are moremotivated and more morning-oriented than less conscientious stu-dents and therefore have higher CGPA scores. However, the weak re-lationship between Neuroticism and CGPA is interesting and a similarresult was reported in the literature (Komarraju & Karau, 2005;Komarraju et al., 2009; Spinath, Freudenthaler, & Neubauer, 2010).This relationship may indicate that students with high academicambition may also experience some degree of anxiety about beingsuccessful (Komarraju et al., 2009).

In the regression analysis regarding CGPA, chronotype(MSFsc) appeared as a predictor like many studies in the literature

(Borisenkov et al., 2010; Randler & Frech, 2006). Unlike many studieswhich indicate that Sleep Quality is related to Academic Achieve-ment (Curcio et al., 2006; Gilbert & Weaver, 2010; Wolfson &Carskadon, 2003) in this study Sleep Quality did not correlate withAcademic Achievement. However, the Sleep Quality of the samplein general was poor (66.23%) and the sample was gender biased,which may have affected the results, since the achievement of femalestudents is generally high. Thus we have investigated whether bothSleep Quality and chronotype have an effect on CGPA, both in the fe-male and male samples, and have found a significant effect ofchronotype but no effect of Sleep Quality on CGPA in both samples.The CGPA scores of earlier chronotypes were higher than those oflater chronotypes. A significant portion of courses in the universityare taught before noon, and therefore earlier chronotypes are at anadvantage, since they are more active both cognitively and psycho-logically earlier in the day, which may help them to attain highergrades.

MEQ was correlated to global PSQI, AMS-C, Agreeableness, Consci-entiousness, CGPA, MSFsc and ASL. Similar results were reported inliterature regarding MEQ (DeYoung et al., 2007; Randler, 2008;Roenneberg et al., 2004; Roeser et al., 2013; Tonetti et al., 2009;Vardar et al., 2008). MSFsc, global PSQI, Conscientiousness, EM Exter-nal Regulation and IM to Experience Stimulation, Social Jetlag, Extra-version, IM toward Accomplishment and IM to Know emerged assignificant predictors of MEQ. MSFsc is a good predictor of MEQ asaforementioned. Moreover, students who sleep well, are more consci-entious, less externally regulated and engage in activity for fun andexcitement, and are more likely to have morning circadian typology.Our Sleep Quality analysis in the female sample supports this finding,where the Sleep Quality of MT students was better than both NT andET students, meanwhile the Sleep Quality of ET students was theworst. Similar results were reported by Lima et al. (2010). Besides,MT students were more conscientious, and of the Big Five Personalitytraits, Conscientiousness best discriminates the three circadian typol-ogies. A similar result was reported by Tonetti et al. (2009). Further,our findings show that MT students engage in activity not becauseof external demands or possible rewards but for the experience ofsensory stimulation.

This study found that Academic Motivation of female MT studentswas higher than both NT and ET students. Female students are gen-erally more achievement-oriented and display some anxiety with re-gard to their academic success, and as a result may have poor SleepQuality. Meanwhile they are more morning-oriented, which confersan advantage in the teaching and learning process, since most teach-ing is scheduled during the morning. As such, they may have higherCGPA scores.

Regression analysis showed that Conscientiousness, CGPA, Open-ness to Experience, Neuroticism and Social Jetlag were the sig-nificant predictors of AMS-C. Regarding the three domains ofMotivation (Intrinsic, Extrinsic and Amotivation); Personality traits,CGPA and MSFsc emerged as predictors. Our results indicated thatPersonality traits, Academic Achievement and circadian typologyare related with a wide variety of Academic Motivations. Opennessand Conscientiousness were positively related with Motivation,while Neuroticism was negatively related. Students who are intel-lectually curious, disciplined, organized and less neurotic are likelyto have higher Academic Motivation. Our findings are to some ex-tent similar to Komarraju and Karau (2005) and Komarraju et al.(2009).

Personality traits in general correlate with Academic Motivationor with its sub-domains. Extraversion, Agreeableness, Conscientious-ness and Openness to Experience were found to correlate positivelywhile Neuroticism correlated negatively with the Academic Motiva-tion. Meanwhile regression analysis presented that in all Personalitytraits; Academic Motivation/sub-domains of Academic Motivationand in some Personality traits; ASL, circadian typology and Academic

vestatistics

(M±

SD)

Motivation

(AMS-C)

Person

ality

Slee

pPa

tterns

Globa

lPSQ

ICG

PA(t

scores)

Extrov

ersion

Agree

ablene

ssCo

nscien

tiou

sness

Neu

roticism

Ope

nnessto

Expe

rien

ceMSFsc

ASL

Social

Jetla

g

±8.8

5.7±

4.2

46.0

±9.6

49.7

±8.6

37.6

±7.2

23.7

±7.2

42.5

±7.6

06:04±

01:38

08:02±

01:17

01:00±

01:06

6.9±

2.8

50.0

±9.9

±8.8

6.6±

3.7

46.5

±9.2

50.5

±7.9

38.0

±6.9

24.4

±7.4

42.9

±7.2

05:47±

01:23

08:02±

01:11

00:54±

01:02

7.1±

2.8

52.5

±9.1

±8.9

4.1±

4.6

45.3

±10

.048

.5±

9.6

37.0

±7.5

22.4

±6.9

41.9

±8.1

06:33±

01:52

08:02±

01:26

01:08±

01:12

6.7±

2.9

45.7

±9.8

±3.6

6.6±

4.4

47.0

±10

.151

.2±

8.5

39.5

±6.4

23.1

±7.7

43.5

±7.6

05:10±

01:29

07:51±

01:09

00:48±

00:56

6.3±

2.6

51.8

±9.7

±4.5

5.5±

4.1

45.6

±9.2

49.9

±8.4

37.5

±7.0

24.0

±7.1

42.3

±7.2

06:01±

01:28

08:06±

01:11

01:01±

01:04

6.9±

2.8

49.9

±9.7

±3.9

5.0±

4.4

46.4

±9.4

48.3

±8.9

35.7

±7.9

24.3

±7.7

42.2

±7.9

07:14±

01:42

08:22±

01:38

01:01±

01:25

8.0±

3.2

49.4

±10

.1

±7.9

5.9±

4.3

46.1

±9.7

50.1

±8.6

38.5

±6.8

23.8

±7.4

42.5

±7.5

04:48±

00:45

07:49±

01:12

00:42±

01:02

6.6±

2.8

52.1

±9.2

±8.5

5.6±

4.1

46.2

±9.4

49.4

±8.6

36.9

±7.2

23.5

±7.1

42.6

±7.5

07:18±

01:16

08:14±

01:20

01:17±

01:06

7.2±

2.8

48.1

±10

.1

±8.4

6.0±

4.1

47.5

±9.1

50.4

±8.

638

.7±

6.7

22.2

±6.9

43.2

±7.3

05:48±

01:29

08:19±

01:04

00:48±

00:59

4.0±

0.9

50.5

±9.8

±8.8

5.7±

4.3

45.5

±9.7

49.5

±8.6

37.2

±7.3

24.5

±7.47

42.4

±7.6

06:13±

01:40

07:53±

01:21

01:05±

01:08

8.4±

2.3

49.8

±10

.0

±9.0

6.8±

3.6

45.7

±9.9

49.4

±8.2

38.0

±7.2

24.0

±7.4

42.3

±7.7

06:16±

01:37

07:58±

01:15

01:18±

01:00

7.3±

2.7

49.7

±10

.3±

8.3

6.2±

3.7

45.5

±9.2

49.4

±8.7

37.6

±7.1

24.1

±6.9

42.1

±7.3

05:54±

01:28

07:57±

01:09

00:59±

01:10

7.3±

2.8

49.2

±10

.1±

8.9

5.8±

4.3

47.3

±8.9

50.4

±8.4

38.3

±6.2

24.0

±7.3

42.8

±7.3

06:00±

01:29

08:09±

01:16

00:54±

01:01

6.8±

2.9

50.8

±9.6

±8.4

4.9±

4.5

46.5

±9.4

50.7

±7.9

37.6

±7.1

23.8

±7.8

43.4

±6.8

06:02±

01:39

08:12±

01:17

00:49±

01:04

6.6±

2.7

51.8

±9.0

±9.6

4.4±

4.7

44.8

±10

.049

.4±

9.7

36.8

±8.2

22.8

±7.2

42.0

±8.2

05:57±

01:54

08:02±

01:23

00:52±

01:12

6.5±

3.0

49.8

±9.8

ation;

MEQ

:Morning

ness–Ev

eningn

essQue

stionn

aire;A

MS-C:

Self-de

term

inationinde

x;MSFsc:C

orrected

mid-sleep

timeon

free

days;A

SL:A

verage

Slee

pLeng

th;G

loba

lPSQ

I:Globa

lPittsbu

rghSlee

pQua

lityInde

x;intAve

rage

;M-typ

e:Morning

type

;N-typ

e:Neither

type

;E-typ

e:Ev

eningtype

.

190 İ. Önder et al. / Learning and Individual Differences 32 (2014) 184–192

Achievement emerged as significant predictors. Several studies pre-sented that Academic Motivation, circadian typology and AcademicAchievement are related to Personality traits (Clark & Schroth,2010; Komarraju et al., 2009; Roeser et al., 2013).

In the current study, IM to Know was a positive predictor ofExtraversion and Openness to Experience while a negative pre-dictor of Neuroticism. This result shows that students who aresocial, active, ambitious, literate, open-minded and emotionallystable can be expected to have an intrinsic motivation to learnnew things for pleasure. A similar result was reported by Clarkand Schroth (2010), where they indicated that Extraverted andOpen students tend to be Intrinsically Motivated to Know, andNeurotic students attend university out of a sense of obligation.Meanwhile, in the current study IM toward Accomplishmentwas a positive predictor of Conscientiousness and Neuroticism,but a negative predictor of Agreeableness. Those students whoare self-disciplined, responsible and less flexible have an intrinsicmotivation to surpass themselves, but they experience stress andanxiety in that process.

Further, IM to Experience Stimulation was a negative predictorof Conscientiousness, which implies that self-disciplined and re-sponsible students have an Intrinsic Motivation to experiencepleasant sensations. Besides, students who are emotionally unsta-ble sleep more but their Sleep Quality is poor since ASL and globalPSQI were positive predictors of Neuroticism. Emotionally unstablestudents are also likely to have more sleep problems (Gau, 2000),and therefore they spend more time in bed. However, ASL was anegative predictor of Conscientiousness and Agreeableness. Con-scientious students spend more time studying, and Agreeable stu-dents are more optimistic, calm, emotionally stable, and freefrom persistent negative feelings (Henle & Gross, 2013) so theysleep well but for less time.

In conclusion, this study extends our understanding of the effectof Personality traits, Academic Motivation, circadian typology, SleepQuality and Sleep Patterns in explaining Academic Achievementand the relationship among these variables. In the current researchthe variables investigated explained just 15.1% of the variation inAcademic Achievement. Although this may be seen as a small varia-tion, the current findings show that Personality, sleep variables,chronotype and Motivation affect Academic Achievement. All the var-iables investigated in this research were interrelated to some extent,and the effects of some of them vary with respect to gender. Howev-er, there are other important features that differ individually (e.g. in-telligence, learning style, learning autonomy, learning approach,thinking style, creativity, problem solving skills etc.) and also affectAcademic Achievement and educational outcomes. Therefore, theseindividual differences and their interactions could be investigatedbroadly, deeply and longitudinally by applying both qualitativeand quantitative research methods to clarify the construction ofinteractions.

There are some limitations in the study and results regarding theselimitations should be interpreted with caution. The correlation coeffi-cients obtained are generally low. Meanwhile, most of the participantsin the study reported poor Sleep Quality. This may in turn affect relatedresults. Moreover, the sample is gender biased although it representsthe population, and female students are more morning-oriented in thesample age range, so the proportion of MT students is higher than ETstudents.

App

endix1.

Descripti

NMEQ

Total

1251

50.9

Gen

der

Female

813

51.2

Male

432

50.2

Chrono

type

(MEQ

)M-typ

e26

362

.6N-typ

e80

250

.4E-type

186

36.4

Chrono

type

(MSFsc)

Earlier

631

54.0

Later

620

47.7

SleepQua

lity

Goo

d39

452

.9Po

or77

349

.8

Age

19−

219

50.7

2026

750

.621

294

51.0

2225

550

.923

+17

651

.3

M:M

ean;

SD:S

tand

ardDev

iCG

PA:C

umulativeGrade

Po

Acknowledgments

We are grateful to the students of Sakarya University Facultyof Education who participated in this study. This study was supportedby the Research Fund of Sakarya University (Project Number: 2012-06-01-001).

App

endix2.

Correlations

Acade

micMotivation

Person

ality

Slee

pPa

tterns

MEQ

Globa

lPSQ

IIntrinsic

Extrinsic

Amotivation

AMS-C

Extrov

ersion

Agree

ablene

ssCo

nscien

tious

ness

Neu

roticism

Ope

nnessto

Expe

rien

ceCG

PA(t

scores)

MSFsc

ASL

Social

Jetlag

MEQ

Globa

lPSQ

I−

.211

a

Acade

micmotivation

Intrinsic

nsns

Extrinsic

−.081

ans

.687

a

Amotivation

−.082

a.067

b−

.158

a−

.186

a

AMS-C

.114

a−

.055

b.686

a.477

a−

.791

a

Person

ality

Extrov

ersion

ns−

.059

b.192

a.125

a−

.113

a.198

a

Agree

ablene

ss.128

ans

.096

a.090

a−

.202

a.227

a.398

a

Cons

cien

tiou

sness

.190

a−

.095

a.239

a.228

a−

.206

a.283

a.471

a.505

a

Neu

roticism

−.071

b.183

ans

ns.088

a−

.091

ans

−.148

ans

Ope

nnessto

Expe

rien

ce.065

bns

.272

a.191

a−

.151

a.277

a.725

a.545

a.514

ans

CGPA

(tscores)

.106

ans

.166

a.124

a−

.166

a.221

a.064

b.101

a.200

ans

.062

b

Slee

pPa

tterns

MSFsc

−.437

a.144

ans

.113

a.058

bns

ns−

.060

b−

.125

ans

ns−

.253

a

ASL

−.134

a−

.178

ans

.058

bns

−.065

b−

.072

a−

.103

a−

.085

ns−

.061

bns

.217

a

Social

Jetlag

−.088

a.129

ans

nsns

nsns

nsns

nsns

−.184

a.331

a−

.145

a

ns:N

otstatistically

sign

ificant.M

EQ:M

orning

ness–Ev

eningn

essQue

stionn

aire;A

MS-C:

Self-de

term

inationinde

x;Globa

lPSQ

I:Globa

lPittsbu

rghSlee

pQua

lityInde

x;CG

PA:C

umulativeGrade

PointA

verage

;MSFsc:C

orrected

mid-sleep

timeon

free

days;A

SL:A

verage

Slee

pLeng

th.

a Correlation

issign

ificant

atthe0.01

leve

l.bCo

rrelationissign

ificant

atthe0.05

leve

l.

191İ. Önder et al. / Learning and Individual Differences 32 (2014) 184–192

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