The Anthropologist

ISSN: 0972-0073 (Print) (Online) Journal homepage: http://www.tandfonline.com/loi/ranp20

Student Engagement, Academic Self-efficacy, and

Academic Motivation as Predictors of Academic
Performance

Ugur Dogan

To cite this article: Ugur Dogan (2015) Student Engagement, Academic Self-efficacy, and
Academic Motivation as Predictors of Academic Performance, The Anthropologist, 20:3, 553-561,
DOI: 10.1080/09720073.2015.11891759

To link to this article: https://doi.org/10.1080/09720073.2015.11891759

Published online: 17 Oct 2017.

Submit your article to this journal

Article views: 1

View related articles

View Crossmark data

Citing articles: 1 View citing articles

Full Terms & Conditions of access and use can be found at

http://www.tandfonline.com/action/journalInformation?journalCode=ranp20
© Kamla-Raj 2015 Anthropologist, 20(3): 553-561 (2015)

Student Engagement, Academic Self-efficacy, and Academic

Motivation as Predictors of Academic Performance
Ugur Dogan

Mugla Sitki Kocman University, Education Faculty,

Department Guidance and Psychological Counselling, Mugla, Turkey
E-mail: ugurdogan@mu.edu.tr
KEYWORDS Academic Performance. Student Engagement. Academic Self-efficacy. Academic Motivation

ABSTRACT The research described in this paper aimed to evaluate the extent to which academic performance is
affected by student engagement (students’ involvement in school activities and commitment to the school’s
mission and rules), academic self-efficacy (the students’ sense of their own capabilities), and academic motivation
(the students’ desire to increase their academic performance). The results of the study, which was conducted with
the participation of 578 middle and high school students, suggest that cognitive engagement, one of the sub-
dimensions of school engagement, predicts academic performance; however, emotional and behavioral engagement
does not predict academic performance. A sense of academic self-efficacy and academic motivation, however, do
predict academic performance. Moreover, the sense of self-capability and related motivations of students, as well
as the sense of the purpose for their learning are significant variables affecting their academic success.

INTRODUCTION the relationship between academic performance

and student engagement was examined, Patrick
A review of the literature revealed that stu- et al. (2007) explained the effects of these vari-
dent engagement has been studied together with ables on academic performance. Teacher sup-
various concepts. Examples of these concepts port, a developed common respect, engagement
include school identity, school socialization style, with a task, and peer support were discovered
bullying, life satisfaction, self-determination, pro- to have positive relationships with motivation
ficiency, staying connected, academic motivation, values, such as students’ success objectives and
self-efficacy, and academic performance. Student self-efficacy perceptions. In this study, a class-
engagement has also been studied in the con- room climate supporting academic motivation
texts of both online learning and traditional class- and student engagement mediators is change-
room environments, and has been supported with able. We can see positive results resulting from
intercultural research. academic motivation and student engagement.
Academic motivation is one concept that has Frey et al. (2009) found that middle and high
been studied with respect to student engage- school students with high levels of student en-
ment. Skinner et al. (2009) consider student en- gagement and academic motivation tend to have
gagement to be an outcome of a motivational much less aggressive beliefs and behave much
process. Additionally, without engagement, no less violently. When teacher and peer support
psychological course is effective in relation to is combined with a school climate that promotes
learning and development. Dörnyei (2000) men- social values, student motivation with respect
tions that students, even those with high levels to having positive social objectives and class-
of self-efficacy, have difficulty in comprehend- room behaviors increases (Wentzel 2003). As a
ing the whole unless they are actively engaged result, academic performance also increases
in the learning. When Lin (2012) explained the (Connell et al. 1994). These results indicate that
relationship between academic motivation and academic motivation and student engagement
student engagement, he considered academic are effective in preventing problems that are like-
motivation to be a perception and a kind of disci- ly to occur.
pline that positively or negatively affects a per- Another term studied in relation to student
son’s behaviors. In addition, academic motiva- engagement which also has various definitions,
tion, together with student engagement, is af- is self-efficacy. One definition describes it as a
fected by a person’s objectives, prior experienc- person’s belief to overcome a situation (Walker
es, cultural background, and the teachers’ and and Greene 2009). Bandura (1977) defines the
peers’ opinions of the person. In a study in which term as the belief in one’s ability to produce de-
554 UGUR DOGAN

sired academic results. If a student believes he and Steinberg 1995; Voelkl 1995). Additionally,
can complete a task, he will have stronger en- students with high levels of engagement have
gagement with this task. Conversely, if students higher GPAs and test scores (Goodenow 1993)
have little confidence knowing that they can and are less likely to drop out (Croninger and
complete a task, they consider the task to be Lee 2001), whereas students with low levels of
unnecessary, and consequently do not want to student engagement can have long-term issues,
spend time and energy on it. As a result of this, such as spoiling behaviours in class, absentee-
they do not engage in such task. After Bandura ism, and dropping out (Lee et al. 1997; Steinherg
presented his definition, the relationship be- et al. 1996).
tween self-efficacy and academic success was
noted (Zimmerman and Bandura 1994). Accord- Purpose of the Study
ing to research results, students with high levels
of engagement have more self-efficacy than The research aimed to explore the relations
those with lower levels of engagement; these among student engagement, academic perfor-
students were observed to have spent more time mance, self-efficacy, and academic motivation
on learning (Eccles et al. 1993). Based on these in middle and high school students and to re-
related findings, self-efficacy is effective in reach- veal whether student engagement, self-effica-
ing objectives (Greene et al. 2004) and in increas- cy, and academic motivation predict academic
ing academic success (Turner et al. 2002). Stu- performance.
dents with high levels of self-efficacy demon-
METHODOLOGY
strate positive social behaviors, both directly and
indirectly (Bandura 2006), and prefer deep learn-
This research employed correlational design
ing to superficial learning (Liem et al. 2008). In to see the relations among variables in the
research studies of student engagement and self- present study. In a correlational design, variables
efficacy, these variables were seen to be highly are measured and the data obtained from the
related (Majer 2009; Thijs and Verkuyten 2008). measurement process is analysed to see wheth-
The relationship between student engagement er the variables are related.
and self-efficacy is more significant in high school
students; identity development and increased Research Group
self-determination were shown to be reasons for
this difference. Additionally, self-efficacy is less This research was conducted during the
effective on academic performance in primary and spring semester of the 2013–2014 academic year
middle school students (Multon et al. 1991). with 578 students (354 girls - 62% and 224 boys
Academic success positively affects stu- - 38%),who enrolled in Grades 7 through 11, and
dents in a variety of ways: Productivity and suc- from a variety of middle and high schools in 4
cess, intellectual skills, personal motivation, the cities in Turkey. The students’ age means are
effort on the work, having a prestigious job, and 16.7.
career dynamism are positively related to aca-
demic success (Pascarella and Terenzini 2005). Instrumentation
Ransdell (2001) discussed the variables affect-
ing academic performance. Examples of these Information Request Form
variables were given as verbal and quantitative
skills, self-confidence, test-solving skills, willing- Students were asked to note their school
ness to study, family support, and time spent on name, grade, and gender for the purpose of col-
classroom activities. Tinto (1993) suggests that, lecting demographic information, as well as their
if students exert effort on their academic work, GPA for the purpose of evaluating their academ-
spend time on studying, and take pains to devel- ic performance.
op their skills and behaviors-in other words, if
they engage-they will be successful. According Student Engagement Scale
to the relevant research, one of the most impor-
tant predictors of academic success is student This scale was developed by Dogan (2014)
engagement. Also, student engagement is a pre- and conducted on 400 middle and high school
dictor of school behaviors (Finn 1993; Mounts students. The scale, consisting of 31 items and 3
STUDENT ENGAGEMENT, ACADEMIC SELF-EFFICACY 555

sub-dimensions (cognitive, emotional, and be- and in the analysis, academic self-efficacy ex-
havioral engagement), accounted for 46.74 per- pectancy subscale data were evaluated. As a re-
cent total variance. In the reliability study, inter- sult of the analysis in SPSS 19, Scale’s Cronbach
nal consistency coefficients were.91 for the alpha value was calculated .91.
whole scale, .88 for cognitive engagement, .88
for emotional engagement, and .86 for behavior- Data Analysis
al engagement. Additionally, the test-retest reli-
ability study resulted in a correlation of .77 be- The analysis used the Pearson product-mo-
tween two studies. Another process was to use ment correlation coefficient (r) to calculate the
an upper 27 percent -lower 27 percent method, relationship between the variables, and used
which demonstrated that the results differed for multiple regression analysis to identify whether
each of the items. In student engagement scale student engagement sub-dimensions predict
as a 5-point Likert Scale, 5 means definitely agree, academic performance variance. Simple regres-
while 1 mean definitely disagree. As a result of sion analysis was used to identify whether aca-
the analysis in SPSS 19, Scale’s Cronbach Alpha demic self-efficacy and academic motivation pre-
value was calculated .86. dict academic performance.
Before analyzing the data, a test was con-
Academic Motivation Scale ducted to determine whether multiple regression
analysis would be applicable. Durbin-Watson (D-
This was developed by Bozanoglu (2004) and W) statistics were used to test the autocorrela-
conducted on 757 high school students. The tions between variables, and the result was D-W
scale consists of 20 items and accounts for 42.2 = 1.57. As this value shows a change between
percent total variance. It features 3 factors: “self- 1.5 and 2.5, it can be assumed that there are no
discovery,” “using the knowledge,” and “dis- autocorrelations between the variables (Field
2005). On the other hand, to identify outliers,
covery.” Internal consistency changes between data 3 values which are lower and higher than
.72 and .88 in both factors and total. In an upper the average standard deviation were omitted from
27 percent -lower 27percent comparison analy- the data set. No outliers were found in the data
sis, all the items differed, and the test-retest reli- set. For the analysis, SPSS 19 software was used.
ability study resulted in a reliability score of .87.
As a result of the analysis in SPSS 19, Scale’s RESULTS
Cronbach Alpha value was calculated .92.
In this part of the research, findings included
Expectancy of Self-efficacy for a relationship between the students’ academic
Adolescents Scale performance and student engagement sub-di-
mensions (cognitive, emotional, and behavior-
This scale was developed by Muris (2001) al), academic self-efficacy, and academic motiva-
and was translated and adapted into Turkish by tion, as well as how these variables predict aca-
Çelikkaleli et al. (2006). The scale is a 5-point Lik- demic performance.
ert Scale consisting of 23 items and 3 factors. Descriptive findings and correlation coeffi-
These factors are “Academic Self-Efficacy Ex- cients which are related to students’ academic
pectancy”, “Social Self-Efficacy Expectancy,” performance, cognitive, emotional, behavioral
and “Emotional Self-Efficacy Expectancy.” The engagement, academic self-efficacy, and academ-
correlation between the academic self-efficacy ic motivation are shown in Table 1.
expectancy subscale, the social self-efficacy ex- An evaluation of Table 1 reveals that the ac-
pectancy, and emotional self-efficacy expectan- ademic performances of the students have a pos-
cy was found to be .39 and .34, respectively; the itive relationship with cognitive (r = .36) and
correlation between social self-efficacy expect- emotional engagement (r = .19), with academic
ancy and emotional self-efficacy expectancy self-efficacy (r = .50), and with academic motiva-
was.42. Academic self-efficacy expectancy and tion (r = .11). One can also see that academic
the whole scale correlation were calculated as performance has a meaningful relationship with
.74. In the reliability study of the scale, the inter- behavioral engagement (r = .13) (p < .01). These
nal consistency coefficient was .64, and the test- findings indicate that academic performance,
retest correlation was .77. In this research, all the cognitive and emotional student engagement,
students in the sample group completed the “Ex- academic self-efficacy, and academic motivation
pectancy of Self-efficacy for Adolescents Scale,” are positively changing variables, whereas the
556 UGUR DOGAN

Table 1: Descriptive findings and correlation coefficients of academic performance, subdimensions of

student engagement (cognitive, emotional, and behavioral), academic self-efficacy, and academic
motivation

Variables Mean Ss 1 2 3 4 5 6

1-Academic performance 72.88 12.65 1

2-Cognitive engagement 45.47 8.93 .36 * 1
3-Emotional engagement 38.46 7.96 .19 * .43 * 1
4-Behavioral engagement 20.85 4.71 .13 * .33 * -.29 * 1
5-Academic self-efficacy 28.49 4.92 .50 * .59 * .39 * -.25 * 1
6-Academic motivation 66.59 8.66 .11 * .48 * .35 * -.21 * .40 * 1
*
p < .01, n = 578
behavioral dimensions of student engagement = 29.575, p < .01]. However, emotional engage-
and academic performance are negatively chang- ment (t = .962, p > .05) and behavioral engage-
ing variables. ment (t = .003, p > .05) did not have any meaning-
Findings related to student engagement as a ful explanations for the prediction of academic
predictor of academic performance are shown in performance (t = 1.554, p > .05).
Table 2. Findings related to the prediction of academ-
As seen in Table 2, a multiple regression anal- ic performance with academic self-efficacy are
ysis of how students’ cognitive, emotional, and shown in Table 3.
behavioural engagement predict the academic As seen in Table 3, students’ academic self-
performance variance shows that only the cog- efficacy beliefs were seen as a meaningful pre-
nitive engagement variable is a meaningful pre- dictor for the academic performance variance.
dictor. Cognitive engagement, as a sub-dimen- Outcomes show that academic self-efficacy ex-
sion of student engagement, explains the .134 plains the .254 percent academic performance
percent academic performance variance [F(3-574) variance [F(1-576) = 195.717, p < .05].

Table 2:Multiple regression analysis results on how student engagement subdimensions (cognitive,
behavioral, and emotional) predict academic performance

Variables R ÄR2 B SHB â t

Stable - - 48.031 4.542 - 10.575 *

Cognitive engagement .366 .134 .490 .063 .346 7.819 *
Emotional engagement - - .067 .069 .042 .962
Behavioral engagement - - .000 .112 .000 .003

F(3-574) = 29.575, *p < .05

Table 3: Simple regression analysis results related to prediction of academic performance using
academic self-efficacy

Variables R ÄR2 B SHB â t

Stable - - 35.995 2.675 - 13.454 *

Academic self-efficacy .114 .254 1.295 .093 .504 13.990 *

F(1-576) = 195.717, *p < .001

Table 4: Simple regression analysis results related to prediction of academic performance using
academic motivation

Variables R ÄR2 B SHB â t

Stable - - 61.792 4.063 - 15.209 *

Academic motivation .366 .013 .166 .061 .114 2.752*

F(1-576) = 7.573, *p < .05

STUDENT ENGAGEMENT, ACADEMIC SELF-EFFICACY 557

Findings related to the prediction of academ- either high school or middle school students. For
ic performance using academic motivation be- example, the study by Wang and Holcombe (2010)
liefs are shown in Table 4. included only middle school students, whereas
As seen in Table 3, a simple regression anal- Hepinger’s study included only high school stu-
ysis of how students’ academic motivation be- dents. Nevertheless, most of these studies con-
liefs predict academic performance variances ducted abroad included a wide range of work
shows that academic motivation is meaningful groups. For example, Rotermund’s (2011) study
for academic performance variables. Academic was conducted with more than 16,000 high
motivation was seen to explain the 0.13 percent school students, and Stafford (2011) conducted
academic performance variance [F(1-576) = 7.573, his study with 1,549 9th- and 10th-grade students;
p < .05]. in contrast, 578 participants participated in the
current research. The researcher anticipates that,
DISCUSSION if this study had been conducted with more par-
ticipants (similar to those mentioned), it may have
In this research, the relationship between led to much different findings.
academic performance, student engagement Our literature also revealed some differences
(cognitive, emotional, and behavioural), academ- between the behavioral engagement observed
ic motivation, and self-efficacy was analysed in in our study and the behavioral engagement re-
middle and high school students; a study to de- flected in studies described in the literature. Be-
termine whether student engagement (cognitive, havioral engagement, often referred to as partic-
emotional, and behavioral), academic motivation, ipation in school activities, was considered in
and self-efficacy predicts academic performance the scale developed for this study as “regular
variances in adolescents followed the analysis. attendance, being loyal to school rules, and not
The first findings of the research indicated getting into trouble in school.” In terms of this
that academic performance can be determined definition, an evaluation of the findings of this
by cognitive engagement, and the sub-dimen- study suggests that regular attendance and obe-
dience to school rules, only, does not bring about
sion of student engagement, but cannot be de- success. In the scale developed for this research,
termined by the emotional and behavioural sub- emotional engagement items are coherent to the
dimensions. In the correlation analysis addition- literature. It is interesting to note, however, that
ally made after these findings, cognitive engage- the literature points to a positive relationship
ment and academic performance were related at between emotional engagement and academic
a medium level, while behavioral, emotional en- performance or success, but the present research
gagement and academic performance were seen findings contradict that finding. According to
to have low and meaningful levels. Findings are research findings, having positive feelings to-
partially consistent with research results (Hep- wards teachers, management, and school is not
inger 2004; Rotermund 2011; Stafford 2011; Tin- enough to be successful. A general evaluation
to 1993). In a structural equation modeling de- about student engagement demonstrates that
signed by Rotermunda, cognitive and behavior- regular attendance, obeying rules, and having
al engagement predicted success directly, and positive feelings towards teachers, management,
emotional engagement predicted success indi- and school, alone, is not enough to be success-
rectly. The studies by Wang and Holcombe (2010) ful or to have a satisfactory academic perfor-
and Wang et al. (2015) demonstrated that suc- mance. An exploratory factor analysis revealed
cess is predicted by all sub-dimensions of stu- that, with respect to cognitive engagement, the
dent engagement: cognitive, emotional, and be- items with the highest factor-loading values are
havioural while Wang et al. (2015) found oppo- “I spend a lot of time on my studies and home-
site results to the result of this study which sug- work,” “I give all my attention to the lesson in
gests that emotional engagement predicted aca- the class,” “I do my homework (work about the
demic success directly. One likely reason for the school) on time,” and “I work as hard as I can for
discrepancy between the present research find- my lessons.” It is not surprising that the con-
ings and the literature includes the fact that the tents of these values result in success. Doing of
present study encompassed a wider target pop- homework and giving attention to the lessons
ulation, including both middle and high school are seen as the most critical criteria for success.
students. A review of the literature demonstrates Other findings from the research suggest that
that some previous studies were conducted with self-efficacy predicts academic performance and
558 UGUR DOGAN

that there is a moderate relationship between self- and thereby fulfill the cognitive activities re-
efficacy and academic performance. In review- quired to help them become successful.
ing the literature, the researcher found several
studies suggesting that self-efficacy predicts ac- RECOMMENDATIONS
ademic performance and that the two have a cor-
relational relationship (Adeyemo 2007; Baker The following recommendations can be made
2015; Brown et al. 1989; Carroll et al. 2009; Chem- to the researchers;
ers et al. 2001; Clay-Spotser 2015; Feldman and ΠMany researches with big samples need to
Kubota 2015; Galla et al. 2014; Gore 2006; Hamp- be conducted in order to make a very clear
ton and Mason 2003; Lent et al. 1986; McIlroy et distinction between these variables.
al. 2015; Mone et al. 1995; Motlagh et al. 2011; ΠTeachers should provide positive oral inspi-
Pajares and Johnson 1996; Wang and Neither 2015; rations to support students’ academic self-
Wood and Locke 1987; Yazici et al. 2011; Yusuf efficacy.
2011; Zimmerman et al. 1992). A review of the liter- ΠTeachers should show positive attitudes
ature confirms that the findings of the research which helps to motivate students in learning
can be regarded as expected. Students’ strong contexts.
beliefs in their academic capacities result in aca- ΠThe results showed that while affective en-
demic performance. Additionally, self-efficacy is gagement and behavioral engagement did
the strongest predictor when compared with oth- not make a contribution to prediction of aca-
demic performance, cognitive engagement-
er academic performance variance predicting
made a contribution to prediction of academic
variables.
performance. In this regard, it needs to be
Finally, the research findings suggest that
given more attention to activities relevant to
academic motivation meaningfully predicts aca- cognitive engagement in learning settings.
demic performance and these two have a posi- ΠThe results also showed that academic self-
tive and meaningful relationship. The results of efficacy and academic motivation jointly
the studies described in the literature are in agree- made positive contributions to the predic-
ment with this suggestion (Amrai et al. 2011; tion of academic performance. Because of
Bakhtiarvand et al. 2011; Guay et al. 2010; Lee et this, students are required to gather experi-
al. 2012; Önder et al. 2014; Soufi et al. 2014; Worm- ences related to increasing academic moti-
ington et al. 2012). Based on the definition of vation and academic self-efficacy in schools.
academic motivation by Tucker et al. (2002) as
“the element determining student’s investments LIMITATIONS OF THE RESEARCH AND
and engagement”, it is reasonable to assume that DIRECTIONS FOR FUTURE RESEARCH
academic motivation predicts academic perfor-
mance. An understanding of students’ academic There were some limitations in the present
motivation levels is considered to be a crucial research. Subsequent researches can be planned
factor in achieving success. to analyze variables predicting academic success
which has to beconducted on either high or mid-
CONCLUSION dle school, but not jointly. Again, as in the exam-
ples in literature, planning and applications of
An evaluation of the research findings from research with higher numbers of participants can
a holistic perspective made us to conclude that be beneficial if the results are compared with oth-
self-efficacy is the strongest predictor of aca- er researches conducted abroad. To better un-
demic performance, or academic success, of mid- derstand the concepts and also reveal the rela-
dle and high school students. The present re- tionships which exist among other variables,
search also suggested that academic motivation school engagement, concepts related to academ-
and cognitive engagement, a subdimension of ic motivation, self-efficacy and academic perfor-
student engagement, predicts academic perfor- mance can be evaluated with associative stud-
mance. It also made us to know that the two are ies. Based on these limitations, the research was
related. Students who believe in their self-effica- conducted in Mugla, Istanbul, Manisa and Bolu.
cy and who are able and willing to act academi- It would be beneficial to plan a research that in-
cally will be able to motivate themselves to learn cludes other territories and cities in order to in-
STUDENT ENGAGEMENT, ACADEMIC SELF-EFFICACY 559

crease academic performance, both scientifical- Dogan U 2014. Validity and reliability of student en-
ly and for application purposes. gagement scale. Bartin University Journal of Faculty
of Education, 3: 309-403. doi: 10.14686/BUE-
FAD.201428190
REFERENCES Dörnyei Z 2000. Motivation in action: Towards a pro-
cess oriented conceptualization of student motiva-
Adeyemo DA 2007. Moderating influence of emotion- tion. British Journal of Educational Psychology, 70:
al intelligence on the link between academic self-effi- 519-538.
cacy and achievement of university students. Psy- Eccles JS, Midgley C, Wigfield A, Buchanan CM, Re-
chology Developing Societies, 19: 199-213. doi: uman D, Flanagan C, Mac Iver D 1993. Development
10.1177/097133360701900204 during adolescence: The impact of stage-environment
Amrai K, Motlagh SE, Zalani HA, Parhon H 2011. The fit on young adolescents’ experiences in schools and
relationship between academic motivation and aca- in families. American Psychologist, 48: 90-101. doi:
demic achievement students. Procedia - Social and 10.1037/0003-066X.48.2.90
Behavioral Sciences, 15: 399-402. doi: 10.1016/ Feldman BD, Kubota M 2015. Hope, self-efficacy, op-
j.sbspro.2011.03.111 timism, and academic achievement: Distinguishing
Baker MMH 2015. The Relationship of Technology Use constructs and levels of specificity in predicting col-
with Academic Self-efficacy and Academic Achieve- lege grade-point average. Learning and Individual
ment in Urban Middle School Students. PhD Thesis, Difference, 37: 210-216. doi: 10.1016/j.lindif. 2014.
Unpublished. United States: Johnson and Wales Uni- 11.022
versity. Field A 2005. Discovering Statistics Using IBM SPSS
Bakhtiarvand F, Ahmadian S, Delrooz K, Farahani HA Statistics. 2nd Edition. California: Sage Publications.
2011. The moderating effect of achievement moti- Finn JD 1993. School Engagement and Students at
vation on relationship of learning approaches and Risk. Washington DC: National Center for Education
academic achievement. Procedia - Social and Be- Statistics.
havioral Sciences, 28: 486-488. doi: 10.1016/
Frey A, Ruchkin V, Martin A, Schwab-Stone M 2009.
j.sbspro.2011.11.093
Bandura A 1977. Self-efficacy: Toward a unifying theo- Adolescents in transition: School and family charac-
ry of behavioral change. Psychological Review, 84: teristics in the development of violent behaviors en-
191-215. tering high school. Child Psychiatry and Human De-
Bandura A 2006. Guide for Constructing Self-efficacy velopment, 40: 1-13.
Scales; Self-efficacy Beliefs of Adolescents. 5th Edi- Galla BM, Wood JJ, Tsukayama E, Kim H, Chiu AW,
tion. Greenwich, CT: Information Age Publishing. Langer DA 2014. A longitudinal multilevel model anal-
Bozanoglu I 2004. Academic motivation scale: Devel- ysis of the within-person and between-person effect
opment, reliability, validity. Ankara University, Jour- of effortful engagement and academic self-efficacy
nal of Faculty of Educational Sciences, 37: 83-98. on academic performance. Journal of School Psy-
Brown SD, Lent RW, Larkin KC 1989. Self-efficacy as chology, 52: 295-308. doi: 10.1016/j.jsp.2014.04.001
a moderator of scholastic aptitude-academic perfor- Goodenow C 1993. Classroom belonging among early
mance relationships. Journal of Vocational Behav- adolescent students’ relationships to motivation and
ior, 35: 64-75. doi: 10.1016/0001-8791(89)90048- achievement. The Journal of Early Adolescence, 13:
1. 21-43.
Carroll A, Houghton S, Wood R, Unsworth K, Hattie J, Gore PA 2006. Academic self-efficacy as a predictor of
Gordon L, Bower J 2009. Self-efficacy and academic college outcomes: Two incremental validity studies.
achievement in Australian high school students: The Journal of Career Assessment, 14: 92-115. doi: 10.
mediating effects of academic aspirations and delin- 1177/1069072705281367
quency. Journal of Adolescence, 32: 797-817. doi: Guay F, Ratelle CF, Roy A, Litalien D 2010. Academic
10.1016/j.adolescence.2008.10.009. self-concept, autonomous academic motivation, and
Çelikkaleli Ö, Gündogdu M, Kiran-Esen B 2006. Ques- academic achievement: Mediating and additive effects.
tionnaire for measuring self-efficacy in youths: Va- Learning and Individual Differences, 20: 644-653.
lidity and reliability study. Eurasian Journal of Edu- doi: 10.1016/j.lindif.2010.08.001
cational Research, 25: 62-72. Hampton NZ, Mason E 2003. Learning disabilities,
Chemers MM, Hu L,Garcia BF 2001. Academic self- gender, sources of efficacy, self-efficacy beliefs, and
efficacy and first year college student performance academic achievement in high school students. Jour-
and adjustment. Journal of Educational Psychology, nal of School Psychology, 41: 101-112. doi: 10.1016/
93: 55-64. doi: 10.1037/0022-0663.93.1.55
Clay-Spotser H 2015. Self-efficacy, Locus of Control, S0022-4405(03)00028-1
and Parental Involvement on Students’ Academic Hepinger PL 2004. Block Scheduled and Traditionally
Achievement. PhD Thesis, Unpublished, United States: Scheduled Pennsylvania High Schools: A Compari-
Walden University. son of Student Academic Achievement and Engage-
Connell JP, Spencer MB, Aber JL 1994. Educational ment. PhD Thesis, Unpublished. United States: Indi-
risk and resilience in African American youth: Con- ana University of Pennsylvania.
text, self, action, and outcomes in school. Child De- Lee NC, Krabbendam L, Dekker S, Boschloo A, de Groot
velopment, 65: 493-506. RHM, Jolles J 2012. Academic motivation mediates
Croninger R, Lee V 2001. Social capital and dropping the influence of temporal discounting on academic
out of high school: Benefits to at-risk students of achievement during adolescence. Trends in Neuro-
teachers’ support and guidance. The Teachers College science and Education, 1: 43-48. doi: 10.1016/
Record, 103: 548-581. j.tine.2012.07.001
560 UGUR DOGAN

Lee VE, Smith JB, Croninger RG 1997. How high school of High School Dropout. PhD Thesis, Unpublished.
organization influences the equitable distribution of United States: University of California.
learning in mathematics and science. Sociology of Skinner EA, Kindermann TA, Furrer CJ 2009. A moti-
Education, 70: 128-150. vational perspective on engagement and disaffection
Lent RW, Brown SD, Larkin, KC 1986. Self-efficacy in conceptualization and assessment of children’s be-
the prediction of academic performance and perceived havioral and emotional participation in academic
career options. Journal of Counseling Psychology, activities in the classroom. Educational and Psycho-
33: 265-269. logical Measurement, 69: 493-525.
Liem AD, Lau S, Nie Y 2008. The role of self-efficacy, Soufi S, Damirchi ES, Sedghi N, Sabayan B 2014. De-
task value, and achievement goals in predicting learn- velopment of structural model for prediction of aca-
ing strategies, task disengagement, peer relationship, demic achievement by global self-esteem, academic
and achievement outcome. Contemporary Education-
self-concept, self-regulated learning strategies and au-
al Psychology, 33: 486-512.
Lin T 2012. Student Engagement and Motivation in tonomous academic motivation. Procedia - Social
the Foreign Language Classroom. PhD Thesis Un- and Behavioral Sciences, 114: 26-35. doi: 10.1016/
published. United States: Washington State Universi- j.sbspro.2013.12.651
ty. Stafford RE 2011. Evaluation of the Student Engage-
Majer JM 2009. Self-efficacy and academic success ment Instrument: Measurement Invariance across
among ethnically diverse first generation communi- Economic Status and Association with Academic
ty college students. Journal of Diversity in Higher Achievement. Master Thesis, Unpublished. United
Education, 2: 243-250. States: Southeastern Louisiana University, Ann Ar-
McIlroy D, Poole K, Ursavas ÖF, Moriarty A 2015. bor.
Distal and proximal associates of academic perfor- Steinherg LD, Brown BB, Dornhusch SM 1996. Be-
mance at secondary level: A mediation model of per- yond Classroom: Why School Reform Has Failed and
sonality and self-efficacy. Learning and Individual What Parents Need to Do. New York: Simon and
Differences, 38: 1-9. doi: 10.1016/j.lindif.2015.01.004 Schuster.
Mone MA, Baker DD, Jeffries F 1995. Predictive va- Thijs J, Verkuyten M 2008. Peer victimization and ac-
lidity and time dependency of self-efficacy, self-es- ademic achievement in a multiethnic sample: The
teem, personal goals, and academic performance. Ed- role of perceived academic self-efficacy. Journal of
ucational and Psychological Measurement, 55: 716- Educational Psychology, 100: 754-764.
727. doi: 10.1177/0013164495055005002 Tinto V 1993. Leaving College: Rethinking the Causes
Motlagh SE, Amrai K, Yazdani MJ, Abderahim, HA, and Cures of Student Attrition. 2nd Edition. Chicago:
Souri H 2011. The relationship between self-efficacy The University of Chicago Press.
and academic achievement in high school students.
Tucker CM, Zayco RA, Herman KC, Reinke WM,
Procedia - Social and Behavioral Sciences, 15: 765-
768. doi: 10.1016/j.sbspro.2011.03.180 Trujillo M, Carraway K, Wallack C, Ivery PD 2002.
Mounts NS, Steinberg L 1995. An ecological analysis of Teacher and child variables as predictors of academic
peer influence on adolescent grade point average and engagement among low income African American chil-
drug use. Developmental Psychology, 31: 915-922. dren. Psychology in the Schools, 39: 477-488. doi:
Multon KD, Brown SD, Lent RW 1991. Relation of 10.1002/pits.10038
self-efficacy beliefs to academic outcomes: A meta- Turner JC, Midgley C, Meyer DK, Gheen M, Anderman
analytic investigation. Journal of Counseling Psy- EM, Kang Y, Patrick H 2002. The classroom envi-
chology, 38: 30-38. ronment and students’ reports of avoidance strate-
Muris P 2001. A brief questionnaire for measuring self- gies in mathematics: A multimethod study. Journal of
efficacy in youths. Psychopathology and Behavioral Educational Psychology, 94: 88-106. doi: 10.1037/
Assessment, 23: 145-149. 0022-0663.94.1.88
Onder I, Besoluk S, Iskender M, Masal E, Demirhan E Voelkl KE 1995. School warmth, student participation,
2014. Circadian preferences sleep quality and sleep and achievement. The Journal of Experimental Edu-
patterns, personality, academic motivation and aca- cation, 63: 127-138.
demic achievement of university students. Learning Walker CO, Greene BA 2009. The relations between
and Individual Differences, 32: 184-192. doi: student motivational beliefs and cognitive engage-
10.1016/j.lindif.2014.02.003 ment in high school. Journal of Educational Research,
Pajares F, Johnson, MJ 1996. Self-efficacy beliefs and 102: 463-472.
the writing performance of entering high school stu- Wang CW, Neihart M 2015. Academic self-concept and
dents. Psychology in the Schools, 33: 163-175. academic self-efficacy: Self-beliefs enable academic
Pascarella ET, Terenzini PT 2005. How College Af-
fects Students: A Third Decade of Research. San Fran- achievement of twice-exceptional students. Roeper
cisco: Jossey-Bass. Review, 37: 63-73. doi: 10.1080/02783193. 2015.
Patrick H, Ryan AM, Kaplan A 2007. Early adoles- 1008660
cents’ perceptions of the classroom social environ- Wang M, Holcombe R 2010. Adolescents’ perceptions
ment, motivational beliefs, and engagement. Journal of school environment, engagement, and academic
of Educational Psychology, 99: 83-98. achievement in middle school. American Education-
Ransdell S 2001. Predicting college success: The impor- al Research Journal, 47: 633-662. doi: 10.3102/
tance of ability and non-cognitive variables. Interna- 0002831209361209
tional Journal of Educational Research, 35: 357-364. Wang M, Chow A, Hofkens T, Salmela-Aro K 2015.
Rotermund SL 2011. The Role of Psychological Pre- The trajectories of student emotional engagement
cursors and Student Engagement in a Process Model and school burnout with academic and psychological
STUDENT ENGAGEMENT, ACADEMIC SELF-EFFICACY 561
development: Findings from Finnish adolescent. achievement among high school students. Procedia -
Learning and Instruction, 36: 57-65. doi: 10.106/ Social and Behavioral Sciences, 15: 2319-2323. doi:
j.learninstruc.2014.11.004 10.1016/j.sbspro.2011.04.100
Wentzel KR 2003. Motivating students to behave in Yusuf M 2011. The impact of self-efficacy, achieve-
socially competent ways. Theory into Practice, 42: ment motivation, and self-regulated learning strate-
319-326. gies on students’ academic achievement. Procedia -
Wood RE, Locke EA 1987. The relation of self-effica- Social and Behavioral Sciences, 15: 2623-2626. doi:
cy and grade goals to academic performance. Educa- 10.1016/j.sbspro.2011.04.158
tional and Psychological Measurement, 47: 1013- Zimmerman BJ, Bandura A 1994. Impact of self-regu-
1024.
Wormington SV, Corpus JH, Anderson KG 2012. A per- latory influences on writing course attainment. Amer-
son-centered investigation of academic motivation ican Educational Research Journal, 31: 845-862.
and its correlates in high school. Learning and Indi- Zimmerman BJ, Bandura A, Martinez-Pons M 1992.
vidual Differences, 22: 429-438. doi: 10.1016/ Self-motivation for academic attainment: The role
j.lindif.2012.03.004 of self-efficacy beliefs and personal goal setting. Amer-
Yazici H, Seyis S, Altun F 2011. Emotional intelligence ican Educational Research Journal, 29: 663-676.
and self-efficacy beliefs as predictors of academic doi: 10.3102/00028312029003663