A Moderated Mediation Model of Expectancy-Value Interactions, Engagement, and Foreign Language Performance

Abstract

Based on the Expectancy-Value Theory (EVT), this study examined the interactive relation between expectancy of success and attainment value, and how they predicate students’ Foreign Language (FL) performance via behavioral engagement. Self-report data were collected from 522 Chinese non-English majors aged 18 to 22 years in their sophomore year. Results of structural equation modeling indicated that expectancy of success and attainment value interacted in predicting Chinese sophomores’ FL performance. The expectancy of success had both direct and indirect effects on FL performance when investigating the mediating role of behavioral engagement. Both theoretical and practical implications are discussed.

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DOI: 10.1177/21582440211059176
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Original Research
Introduction
This study examined Chinese sophomores’ Expectancies of
Success (ESs) and Subjective Task Values (STVs), and their
interaction, as the indirect antecedents of FL achievement via
behavioral engagement. From the perspective of expectancy-
value theory (EVT; Eccles, 2009; Eccles(Parsons) et al., 1983;
Guo et al., 2017; Wigfield & Eccles, 2000), ESs and STVs pre-
dict the choice of learning activities and the motivation of
behavioral performance, giving insight into the achievement
motivation of students (Eccles(Parsons) et al. (1983), and thus
predict their academic achievement (e.g., Pintrich & de Groot,
1990). Expectancy and value are also predictors of engagement
(Lam et al., 2012; Nagengast et al., 2011), relate to the motiva-
tional mechanism that decides the quality and level of students’
learning engagement (e.g., Wigfield & Eccles, 2000; Yli-
Piipari & Kokkonen, 2014), and forecast academic achieve-
ment, psychological well-being, and academic emotions
(Meyer et al., 2019; Turner & Schallert, 2001; Wigfield, 1994;
Wigfield & Cambria, 2010). Thus, an appreciation of expec-
tancy and value, as well as their influential mechanism on FL
performance, serves as an opportunity to enhance the under-
standing of the motivation, processes, and results of Chinese
sophomores’ English learning.
The current research aimed to examine how expectancy
and value beliefs affect Chinese sophomores’ English learn-
ing results. With the in-depth development of economic
globalization and mobilization of the international popula-
tion, few would question the importance of English to citi-
zens of the 21st century (Griffiths et al., 2014; Loh, 2019;
Pan & Block, 2011), especially to those citizens from
developing societies (Guilherme, 2007). English is pas-
sionately embraced by students from primary school to uni-
versity because of political, economic, ideological, and
personal development concerns (Bolton & Botha, 2015). In
Mainland China today, among those with a foreign lan-
guage learning experience, 93.8% learned English (Tong,
2006), that is, English is the most important foreign lan-
guage to Chinese language learners. To Chinese university
students, English is the exam-compulsory subject to those
who wish to pursue a graduate degree (Cheng, 2008), and
proficiency in English is regarded as a bonus for those who
seek promotion in governmental, financial, business, edu-
cational, and other government-support institutions (He,
2001). In short, English is of high importance to the aca-
demic, professional promotion, and upward mobility of
1059176SGOXXX10.1177/21582440211059176SAGE OpenWu and Xia
research-article20212021
1Yunnan Normal University, Kunming, China
2The University of Hong Kong, Hong Kong
Corresponding Author:
Yajun Wu, Yunnan Normal University, Kunming City, Yunnan Province
650500, China
Email: wuyajun1225@163.com
A Moderated Mediation Model of
Expectancy-Value Interactions,
Engagement, and Foreign Language
Performance
Yajun Wu1 and Xia Kang2
Abstract
Based on the Expectancy-Value Theory (EVT), this study examined the interactive relation between expectancy of
success and attainment value, and how they predicate students’ Foreign Language (FL) performance via behavioral
engagement. Self-report data were collected from 522 Chinese non-English majors aged 18 to 22 years in their sophomore
year. Results of structural equation modeling indicated that expectancy of success and attainment value interacted in
predicting Chinese sophomores’ FL performance. The expectancy of success had both direct and indirect effects on FL
performance when investigating the mediating role of behavioral engagement. Both theoretical and practical implications
are discussed.
Keywords
attainment value, expectancy of success, FL performance, behavioral engagement, expectancy-value theory

2 SAGE Open
Chinese college students. Besides, both expectancy and
value in the horizon of EVT are domain-specific (Eccles
et al., 1993; Trautwein et al., 2012), however, recent studies
(Guo et al., 2016, 2017; Guo, Marsh et al., 2015; Putwain
et al., 2019; Trautwein et al., 2012) mainly focused on
Science, Technology, Engineering, and Mathematics
(STEM) areas, very few studies have addressed the impact
of expectancy and value beliefs on academic performance
of English as a Foreign Language (EFL; Loh, 2019) though
English education is momentous to college students in the
Chinese context. To address this limitation, this study delib-
erated on the impact of students’ expectancy and subjective
value on English performance.
According to the classic EVT (Atkinson, 1957), both
expectancy and value are emphasized to jointly affect the
learning outcome (Trautwein et al., 2012). More precisely,
only a high level of expectancy and subjective task value
beliefs simultaneously will help to accomplish a task and
gain a high academic achievement. That is, the educational
outcomes are impacted by both expectancy and value beliefs
in a multiplicative way. However, due to the lack of means to
detect the multiplicative relations between expectancy and
value beliefs (e.g., Guo, Marsh et al., 2015; Nagengast et al.,
2011), their latent synergistic effects on academic achieve-
ment have not been extensively examined in the previous
empirical studies (e.g., Guo et al., 2016; Putwain et al.,
2019). Extending previous work, structural equation model-
ing techniques (Bollen, 1989), specifically, the Latent
Moderated Structural equations approach (LMS; Klein &
Moosbrugger, 2000) was adopted to examine the interaction
effects of expectancy and value beliefs on foreign-language
performance.
The sociocultural context was regarded as one of the
proximal socializers for the production of ESs and STVs
(Eccles & Wigfield, 2020), however, the Mainland Chinese
students who are deeply influenced by Confucian culture
have gained surprisingly little attention. Compared with
Western students, students influenced by Confucian culture
are described as generally facing academic stress, having a
passive learning style, and hardly engaging in deep critical
thinking (Tan & Yates, 2011; Tran, 2013). Several studies
(Eccles & Wigfield, 2020; Kumar et al., 2018; Tonks et al.,
2018; Wigfield & Wagner, 2005) indicated that both the
meaning of a construct in expectancy-value model (e.g.,
ESs) and the meaning of those relations that specified in this
model could vary greatly from culture to culture. Kumar
et al. (2018) argued that the research on motivation mainly
took European American students as participants and stu-
dents from other cultures remain to be investigated. However,
with a few exceptions (e.g., Guo, Marsh et al., 2015; Jiang
et al., 2018;) that touched upon the mathematics-related
expectations and values of middle school students in South
Korea and Hong Kong, many of these empirical studies pre-
dominantly focused on primary and secondary school stu-
dents in Western countries (e.g., Guo et al., 2016; Putwain
et al., 2019; Safavian, 2019; Trautwein et al., 2012).
Therefore, there is a great need for research that focuses on
students from Mainland China to examine the validity and
robustness of EVT in a non-Western cultural context.
Expectancy-Value Theory
As a prominent theory of motivation in education, EVT pro-
poses that expectancy of success and subjective value are the
two chief influencing factors of academic outcomes (Putwain
et al., 2019). That is, the modern EVT emphasizes that stu-
dents’ motivational beliefs exert significant influences on
their achievement-related behaviors, educational aspiration,
academic choice, engagement, and achievement (Eccles,
2009; Guo et al., 2017; Putwain et al., 2019; Trautwein et al.,
2012), and expectancy of success and value are presumed to
be the driving forces behind the wide-ranging educational
outcomes. According to Eccles(Parsons) et al. (1983), the
expectancy of success refers to the subject’s task-related
belief in the possibility of achieving success in that task.
However, as highlighted by Eccles and Wigfield (2002), the
expectancy of success is inseparable from one’s ability
beliefs and the subjective capability evaluation (e.g., aca-
demic self-concept) was applied to serve as the operational
definition of the expectancy element (Arens et al., 2019; Guo
et al., 2017; Guo, Marsh et al., 2015; Putwain et al., 2019).
Thus, in the current study, academic self-concept that refers
to students’ self-assessment of academic competence was
used to measure the expectancy of success.
The value component of modern EVT contains multiple
facets rather than a single-dimensional factor (Arens et al.,
2019). For example, based on the previous studies
(Eccles(Parsons) et al., 1983; Wigfield & Eccles, 1992),
Wigfield and Eccles (2000) identified four dimensions of
values, those are, intrinsic value (interest and enjoyment),
attainment value (subjective importance), utility/instrumen-
tal value (usefulness for future goals), and cost (opportunity
or emotional expenditure (Wigfield & Eccles, 2000). All of
these four value facets are positively correlated with the
expectancy of success and exert interactive influences on
achievement motivation (Eccles & Wigfield, 2002;
Nagengast et al., 2011; Putwain et al., 2019), however, the
correlations between value facets and expectancy of success
are different. Relatively higher relations were found between
academic self-concept and intrinsic value (Arens et al., 2011;
Eccles(Parsons) et al., 1983; Fredricks & Eccles, 2002).
Additionally, an empirical study showed that the correlation
between academic self-concept and attainment value is simi-
lar to the relationship between academic self-concept and
intrinsic value and the effect size of relations between these
two value facets and academic self-concept is higher than the
association between the left two value facets and academic
self-concept (Trautwein et al., 2012). For that reason, intrin-
sic value that depicts the liking and enjoyment a student
gains from performing a task and attainment value that

Wu and Xia 3
encompasses students’ subjective importance of achieving
success were the focuses of the current investigation.
Expectancy and Value Beliefs as Antecedents of
Academic Achievement
In the field of EVT, the expectancy of success and value are
theorized to affect achievement-related outcomes in direct/
indirect or additive/multiplicative ways. As far as different
participants (e.g., elementary school students, secondary
school students, undergraduate students) are concerned, the
relationship between expectancy of success and task value is
not consistent (Wigfield, 1994; see review by Wigfield &
Cambria, 2010). In elementary and junior high school, stu-
dents’ expectancy and value beliefs are relatively independent
because they may pursue some activities they are interested in
without considering whether they are capable of doing them
well. Moreover, the lack of appropriate statistical methods
makes previous studies unable to test the latent interactions
between expectancy and value (Guo, Marsh et al., 2015;
Nagengast et al., 2011; Putwain et al., 2019). Consequently,
expectancy and value beliefs were taken as two distinct direct
factors in predicting students’ academic achievement (Eccles
et al., 1993; Pintrich & de Groot, 1990). Taking secondary
school students as samples, several studies have suggested that
the relations between expectancy, value, and academic
achievement are indirect, which are mediated through vari-
ables such as academic effort (Nagengast et al., 2011;
Trautwein et al., 2006; Wu & Fan, 2017), academic engage-
ment (Nagengast et al., 2011; Putwain et al., 2019), emotional
consequences (Frenzel et al., 2007; Pekrun, 2009), achieve-
ment goals (Plante et al., 2013), and self-control (Galla et al.,
2018). Among the various mediating variables between expec-
tancy, value, and academic achievement, Putwain et al. (2019)
argued that behavioral engagement is the dominant one. Thus,
this study mainly focuses on behavioral engagement.
Except for the few studies on primary school students that
show expectancy and value beliefs can predict students’ aca-
demic performance separately (e.g., Pintrich & de Groot,
1990), the joint prediction of expectancy and value on aca-
demic performance reflect the cornerstone of EVT
(Nagengast et al., 2011). This means that the relationship
between the two elements of EVT is in a dynamic develop-
ment process with the aging of the participants (Wigfield &
Cambria, 2010) and the accumulated effect of them will not
stabilize till late adolescence (Fredricks & Eccles, 2002).
Thus, the interactive effect between expectancy and value
beliefs need to be considered if the participants are not pri-
mary school students (e.g., Guo, Marsh et al., 2015; Guo,
Parker et al., 2015; Meyer et al., 2019; Nagengast et al.,
2011; Trautwein et al., 2012). The present study takes col-
lege students as the participants, so when discussing expec-
tancy and value beliefs’ effect on EFL learners’ academic
performance, we should take the multiplicative effect of
expectancy and value into consideration.
Joint and Mediated Effects of Expectancy, Value,
and Engagement on EFL Academic Achievement
In EFL educational settings, expectancy and value beliefs
were demonstrated to be positively correlated with students’
academic achievement. For example, Mori and Gobel (2006)
and Gu (Michelle) (2009) argued that expectancy and value
beliefs are significant predictors of college students’ foreign
language learning effect. Plante et al. (2013) also found a
positive relationship between EVT facets and French-
speaking adolescent students’ grades in language arts through
path analysis. Loh (2019) reviewed the antecedents of stu-
dents’ expectancy-value theory of motivation as well as its
predictive effect on students’ achievement-related outcomes
(e.g., academic performance, persistence, choices) while
learning a second language. What needs to be emphasized is
that cultural variation plays a role in shaping students’ L2
motivation (Huang et al., 2015), that is, students’ motivation
in learning a foreign language may differ as to their cultural
context and social identities change. The findings were not
carried out in Confucian cultural context, nevertheless, have
provided a theoretical possibility for exploring how EVT
predicts Chinese students’ academic achievement in EFL.
Engagement characterizes the actual energy that a learner
has expended to achieve a certain result, which is an effec-
tive mean for achievement motivation to be implemented.
The motivation in the model of the expectancy-value theory
was viewed as both a quantitative and qualitative phenome-
non (e.g., Fryer, 2019; Loh, 2019) that can potentially pro-
mote L1 and L2/FL learning. That is, the motivation construct
does not directly achieve a certain academic outcome, but
rather it integrates an individual’s internal processes and the
external world she or he experiences, and develops dynami-
cally in the interaction of individual and social factors (Gu
(Michelle) (2009). The contextual model for student engage-
ment that was proposed by Lam et al. (2012) was recognized
by most educational researchers (Oga-Baldwin, 2019), and
according to which, engagement plays a central mediating
role between motivational beliefs and academic perfor-
mance. Further, as argued by Ericsson and Pool (2016),
engagement is an essential element of practice and through
which, motivation as the pre-decisional force of student out-
comes was embodied and produced practical results. In line
with Dörnyei’s (2000) process-oriented model of student
motivation, the mediating effect of engagement between
motivation and performance has been confirmed in empirical
studies (González et al., 2015; Salanova et al., 2010). More
generally, motivation in the model of EVT integrates instruc-
tional contexts and social relatedness contests (Lam et al.,
2012), and considers engagement as the core mediator in
achieving certain academic outcomes (Oga-Baldwin, 2019;
Putwain et al., 2019).
Behavioral engagement refers to students’ laborious
dedication in learning activities and extracurricular activi-
ties provided by schools (Lam et al., 2012), which is

4 SAGE Open
positively correlated with academic outcomes (Kuh et al.,
2008; Ladd & Dinella, 2009). In the existing literature, the
meta construct of engagement applies three interrelated
dimensions to conceptualize the rich connotation of
engagement construct (e.g., Fredricks et al., 2004; Lam
et al., 2012), those are behavioral, emotional, and cogni-
tive dimensions. These three subdimensions act simulta-
neously and are interrelated with each other in the learning
process, although their effect sizes on academic perfor-
mance are not the same. For example, Ladd and Dinella
(2009) found that behavioral engagement is a greater pre-
dictor in predicting students’ long-term achievement tra-
jectories than emotional engagement. Li, Lerner, et al.
(2010) confirmed that both emotional engagement and
behavioral engagement play a mediating role between
developmental assets and academic competence, but the
predictive effect size on academic competence is different
as emotional engagement solely exerts an indirect influ-
ence on academic competence through behavioral engage-
ment. Lei et al. (2018) compared the effect sizes of
behavioral engagement, cognitive engagement, and emo-
tional engagement on academic achievement, and found
that behavioral engagement has the highest predictive
effect, followed by cognitive engagement and emotional
engagement. In sum, behavioral engagement was consid-
ered the most significant predictor in predicting the subse-
quent academic achievement (Fredricks et al., 2004; Ladd
& Dinella, 2009; Lei et al., 2018; Li, Chen, et al., 2010).
Aims and Hypotheses
This study aimed to examine the main assumption of EVT
about the multiplicative effects of ESs and STVs on students’
academic achievement through the medium of behavioral
engagement (see Figure 1). The links among these construc-
tions were tested in the context of FL learning of students
from Confucian culture. By doing so, this study would
improve on earlier research by revealing the multiplicative
and mediational mechanism among the variables of ESs,
STVs, behavioral engagement, and academic achievement.
Further, this study would expand the validity range of EVT
by considering sophomores’ FL learning in the Confucian
cultural context. Although all the constructs (i.e., ESs, STVs,
behavioral engagement, and academic achievement) are
domain-specific (Putwain et al., 2019) and students’ apprais-
als of their ESs and STVs are culturally determined (Eccles
& Wigfield, 2020), only two studies that drew on EVT were
conducted in Confucian cultural context (Guo, Marsh et al.,
2015; Jiang et al., 2018). Furthermore, these two studies
focused on eighth graders, and the interactions between ESs
and STVs in older students have not been examined. Finally,
the previous studies on EVT mainly focused on STEM sub-
jects (e.g., Guo et al., 2017; Guo, Marsh et al., 2015; Jiang
et al., 2018; Putwain et al., 2019) and few studies have exam-
ined EVT by focusing on English subject even in Western
cultural context (Loh, 2019), and fewer studies have exam-
ined EVT by focusing on English subject in the Confucian
cultural context.
Based on EVT as outlined already, Figure 1 pictures the
hypothesized model specifying the proposed correlations
among ESs, STVs, engagement, and FL performance.
Concisely speaking, our research hypotheses were as
follows:
Hypothesis 1. Expectancy and attainment value will posi-
tively predict behavioral engagement in a multiplicative
manner. Precisely, the higher the attainment value, the
stronger the predictive effect of expectancy on behavioral
engagement.
Hypothesis 2. Expectancy and attainment value interac-
tion will indirectly and positively predict FL academic
performance via behavioral engagement.
Figure 1. The theoretical model of expectancy, attainment value, and foreign language achievement.

Wu and Xia 5
Methods
Participants
A total of N = 522 sophomores (female n = 409, male n = 113)
from a normal university in Southwest China (mean
age = 19.4 years, SD = 0.72) were recruited. All participants
were non-English majors in their final year of learning EFL,
and they have four college English classes per week, two
classes each in listening and speaking, and comprehensive
exercises. The ratio of boys to girls in normal universities in
China is unbalanced, with the ratio of boys to girls reaching
1 to 4 (Wang, 2015). And the gender distribution of the sam-
ple is consistent with the gender distribution of normal uni-
versity students in China. The participants came from 10
classes, of which five classes are for science majors such as
mathematics and engineering, and the other five classes are
for liberal arts majors such as business administration and
literature. As far as socioeconomic status is concerned, most
of the students in this normal university are from the middle
class.
Measures
Expectancy of success. Students’ expectancy of success was
assessed by the four-item version of Liem et al.’s (2015) Eng-
lish Self-concept Scale to measure their expectation of achiev-
ing a good score in learning English (e.g., “I have always done
well in English”). Participants responded using a seven-point
scale (1 = strongly disagree to 7 = strongly agreed; α = .90).
The English Self-concept Scale has good psychometric prop-
erties in the respects of internal consistency and constructs
validity. These items were partially taken from the Academic
Self-description Questionnaire Ⅱ (Marsh, 2007) and it has
been utilized in quite a few studies to investigate tie-up with
academic achievement (Guo, Parker et al., 2015; Marsh &
Martin, 2011; Televantou et al., 2021).
Values. The perceived value of the English course was mea-
sured with the 12-item version of the Michigan Study of Ado-
lescent Life Transitions (MASLT) scale (Eccles et al., 2005).
This scale consists of three subscales (four items for each
subscale), which were applied to assess students’ intrinsic
value, attainment value, and utility value. Items were adapted
to be relevant to English lessons and examinations (e.g., “I
like the subject matter of English course” for intrinsic value;
“The amount of effort it takes to do well in English courses
worthwhile to me” for attainment value; “I think English is
useful” for utility value). All these three values were mea-
sured on a 7-point Likert scale (1 = strongly disagree,
7 = strongly agreed), but only the attainment value subscale
was analyzed in the present study (α = .82).
Behavioral engagement. To measure students’ behavioral
engagement in learning EFL, we use the four-items in the
modified Engagement versus Dissatisfaction with Learning
Questionnaire (Skinner et al., 2009) to gauge their involve-
ment with the endeavor of studying English. These four
items were modified to refer to EFL (e.g., “In English class,
I study as hard as I can”). Both the construct validity and
internal consistency of this subscale has been demonstrated
by Skinner et al. (2009) and Skinner and Chi (2012) and it
has been used to go into relations with academic achieve-
ment and well-being (King & Gaerlan, 2014; King & Gano-
tice, 2015; Putwain et al., 2019). In this study, the internal
consistency of this scale was good for α = .82.
Foreign language achievement. We collected participants’ final
course exam scores to represent their foreign-language per-
formance. The course exams were proposed by the Foreign
Language Department affiliated to the Faculty of Foreign
Languages and graded jointly by the English teachers. The
examination paper was designed based on the course text-
book to measure their reading and writing skills which
include 20 multiple-choice items, 20 cloze test items, 20 sen-
tence translation items, and writing an English composition
(range 0–100; α = .85).
Data Analysis
In this study, both the Confirmatory Factor Analyses (CFAs)
and the Latent Moderated Structural equation modeling analy-
sis (Klein & Moosbrugger, 2000) were carried out to capture
the multiplicative effect of ESs and STVs on behavioral
engagement and FL performance. Both the CFAs and LMS
approaches were conducted with the Mplus 8.3 (Muthén &
Muthén, 2013). More specifically, some CFAs were initially
conducted to investigate the psychometric properties and valid-
ity of each construct. Moreover, the LMS approach was imple-
mented to evaluate the predictive effect of expectancy and
value interaction on behavioral engagement as well as FL per-
formance. Precisely, there are three mediational models, those
are, the indirect effect of expectancy, attainment value, and
their interaction on academic achievement through engage-
ment as well as the direct effects of engagement on achieve-
ment (see Figure 1). By examining these models, we estimated
conditional indirect effects of expectancy on achievement at
different levels of attainment value as mediated by behavioral
engagement. Moreover, all variables used in this study are nor-
mally distributed (see Table 2), thus Maximum Likelihood
(ML) was applied to test the parameters.
Results
Preliminary Analysis
Both the factor loadings and the goodness of fit indexes from
CFAs are documented in Table 1. The model fit was evaluated
based on the comparative fit index (CFI), the Tucker-Lewis
index (TLI), the root mean square error of approximation

6 SAGE Open
(RMSEA), and the standardized root mean square residual
(SRMR). According to the traditional cutoff criteria, the
hypothesized model had a perfect fit in the present study for
the CFI and TLI ≥ .95, the RESEA ≤ .06, and the SRMR ≤ .08
(Chen, 2007; Hu & Bentler, 1999).
Table 2 shows the descriptive statistics and bivariate cor-
relations for the study variables. The expectancy was posi-
tively correlated with engagement, attainment value, and
achievement. Besides, a positive, significant correlation was
also found between engagement and achievement.
Structural Equation Modeling
SEM was estimated to test the moderated mediational
model that is hypothesized in Figure 1. To inspect whether
the mediational LMS model is acceptable, the first step is
to examine whether the fitness of the base model, which
omitted interaction terms, is acceptable. The next step is to
examine whether the model fit of the mediational LMS
model is better than the base model. The Akaike Information
Criterion (AIC) was used as the criteria for it is the relative
quality of statistical models for a given data set (Aho et al.,
2014). The larger the value of AIC, the more information
loss (Sardeshmukh & Vandenberg, 2017). The base model,
which omitted interaction terms, provided an excellent
fit: χ260 152 001 0 055 0 044() ,.;.
,.
,=<
==
pRMSEA SRMR
CFI and TLI= =0 971 0 963.;
..
The AIC value of the media-
tional LMS model is a little bit less than the base model
(less 5), which suggests that the mediational LMS model
of the present study is acceptable and proceeded to inves-
tigate the beta coefficients (see Figure 2).
Effects of expectancy and attainment value on engage-
ment. Expectancy (
β= <
031 001., .p) and attainment value
(
β= <
044 001., .p) have predictive effects on behavioral
engagement. Also, the expectancy × attainment value
interaction also demonstrates significant predictive effects on
engagement (
β=−=
012 008., .p), supporting Hypothesis 1.
As shown in Figure 3, simple slopes for the relationship
between expectancy and engagement at low (−1 SD), mean (0
SD), and high (+1 SD) levels of attainment value were dem-
onstrated to give proof of the interactive effect between expec-
tancy and attainment (Cohen et al., 2013). As shown in Figure
3, there is a positive relationship between expectancy and
engagement at the mean value (
β= <
026 001., .p). The rela-
tionship became stronger at low value (
β= <
039 001., .p),
and this relationship between these two variables became
weaker at high value (.
,.
β= =014 011p).
Effects of expectancy, attainment value, and engagement on
achievement. The engagement has a significant predictive
effect on academic achievement (
β= <
028 001., .p).
Besides, the direct predictive effect between expec-
tancy and academic achievement is also significant
(
β= <
031 001., .p), while the predictive effect of attain-
ment value (
β= =
001 821., .p) and β=
−=
()
004 419., .p
on academic achievement are not significant. Nevertheless,
the present study aims to explore the indirect effects of expec-
tancy, attainment value, expectancy × attainment value
interaction on academic achievement through engage-
ment. Expectancy (
β= =
033009 95 017055., ., %[.,
.]
SE CIs),
attainment value (
β= =
063016 95 034097., ., %[.,
.]
SE CIs),
and the expectancy × attainment value interaction
(
β=−= −−
013006 95 028004., ., %[.,
.]
SE CIs) showed sig-
nificant indirect effect on achievement via engagement. To
interpret the indirect predictive effect of expectancy ×
attainment value interaction on achievement, Figure 4 pres-
ents indirect simple slopes of attainment value at different
levels. As shown in Table 3, the indirect simple slopes esti-
mated for low and high achievement values were ±1 SD. It
can be seen from Figure 4 when the attainment value is
low, the indirect correlations between expectancy and
Table 2. Descriptive Statistics and Bivariate Correlations of the Study Variables.
Range M SD Skewness Kurtosis 1 2 3 4
1. Expectancy 1–7 3.68 1.30 .05 –.37
2. Engagement 1–7 4.45 1.09 −.32 –.38 .417**
3. Attainment Value 1–7 5.38 1.02 −.54 .26 .347** .478**
4. Achievement 0–100 81.91 5.15 −1.00 1.04 .414** .400** .287**
Note. **p < .01.
Table 1. Results of the Confirmatory Factor Analyses.
Factor loadings χ2
()
df CFI TLI RESEA SRMR
Expectancy 0.76–0.89 2.29 (2) 1.000 .999 .017 .006
Engagement 0.60–0.82 1.27 (2) 1.000 1.003 .000 .007
Attainment Value 0.64–0.85 5.14 (2) .996 .987 .055 .014
Note. Factor loadings are standardized coefficients. All factor loadings are significant at p<
..
001

Wu and Xia 7
achievement are more significant than that the attainment
value is at the mean level or high level. To put it another
way, the indirect correlations between expectancy and
achievement weakens as the levels of attainment value rise.
Discussion
The current study investigated the relationships among
expectancy, attainment value, behavioral engagement, and
FL performance in a sample of 18 to 22-year-old Chinese
sophomores. In this structural model, behavioral engagement
was contemplated to be the mediator between expectancy,
attainment value, and FL achievement. Meanwhile, the rela-
tionships between expectancy-attainment value interaction
and FL achievement were also examined by substituting dif-
ferent levels of attainment value in the mediation model of
“expectancy-value interaction→ behavioral engagement→FL
achievement.” In the context of foreign language learning in
China, strong support was found for the pathway of expec-
tancy and value appraisals→engagement→achievement that
was firstly proposed by Putwain et al. (2019).
The finding that expectancy and attainment value predict
behavioral engagement both in additive and interactive man-
ners was consistent with previous studies examining ETVs
Figure 2. LMS to investigate the moderated mediational model. The solid lines and the dashed line represent the standardized
coefficients for structural paths and correlation, respectively ( *..**..*** .pp p
<< <
05 01 001).
Figure 3. Interactive effect of expectancy and attainment value on engagement.

8 SAGE Open
in the education research domain (e.g., Putwain et al., 2019;
Wang & Eccles, 2013) and add on work utilizing latent mod-
erated mediation model to explore how expectancy and
attainment value interactively predict academic achievement
(e.g., Guo et al., 2016, 2017; Trautwein et al., 2012). Classic
EVT emphasizes that both expectancy and value are indis-
pensable for motivating students’ engagement (e.g.,
Atkinson, 1957; Eccles(Parsons) et al., 1983; Meece et al.,
1990). However, our results are consistent with the research
of Guo, Parker et al. (2015), Guo, Marsh et al. (2015), and
Putwain et al. (2019) and found that high attainment value
would compensate for low expectancy to a certain extent.
This implies that the associations between expectancy and
attainment value could be both interactive (e.g., Nagengast
et al., 2011; Trautwein et al., 2012) and additive (Eccles,
2009; Eccles(Parsons) et al., 1983). Besides, the predictive
effects of Chinese college students’ expectancy and value to
their engagement in FL learning were different. Unlike
Meece et al. (1990) work that emphasizes the importance of
expectancy to educational outcomes, we found that expec-
tancy plays a moderating role in the relationship between
attainment value and behavioral engagement but not vice
versa. These findings support H1.
The finding that behavioral engagement predicted the
ensuing academic achievement, supports previous research
using samples of university students (De Clercq et al., 2013;
Hu & McCormick, 2012; King & Gaerlan, 2014). Moreover,
our results indicate that expectancy, attainment value, and
their interaction have an indirect positive predictive effect on
FL achievement through the mediator of behavioral engage-
ment (see Figure 2). Taken together, our results support H2.
Based on our information, the present empirical study is the
first to explore the interactive effect between expectancy and
value within the framework of EVTs with the English educa-
tion of Chinese college students as respondents.
The finding that expectancy × attainment value interac-
tion has a positive predictive effect on FL achievement
makes up for the lack of literature in the field of language
learning. Taking elementary school students as participants,
Putwain et al. (2019) explored the predictive effect of expec-
tancy-value interaction on mathematics achievement.
However, the interactive effect of these two variables has not
been empirically investigated in the context of language
learning (Shao et al., 2020). As shown in Figure 4, attain-
ment value plays a moderating role between expectancy and
FL achievement. That is, at low levels of expectancy, the lev-
els of students’ attainment value are proportional to their FL
achievement; at higher levels of expectancy, the significance
concerning the difference in FL achievement caused by high
and low attainment values is reduced. In sum, we concluded
that only when expectancy is at low levels, attainment value
can compensate for low expectancy in the context of lan-
guage learning.
Limitation and Future Directions
The current study has certain limitations that can be used to
clarify directions for future research. First, we adopted a
Figure 4. Relationship between expectancy and achievement under different levels of attainment value.
Table 3. Indirect and Total Effects of Expectancy on Achievement via Engagement under Different Levels of Attainment Value.
Low attainment value (−1 SD) Mean attainment value High attainment value (+1 SD)
B SE 95% CIs B SE 95% CIs B SE 95% CIs
Indirect Effect 0.46 0.13 0.26, 0.78 0.33 0.10 0.17, 0.55 0.20 0.09 0.06, 0.41
Total Effect 1.88 0.36 1.25, 2.69 1.56 0.22 1.17, 2.06 1.24 0.25 0.77, 1.73
Note. Effects are represented by unstandardized coefficients.

Wu and Xia 9
cross-sectional design to examine the joint influence of ESs
and AV on FL performance via behavioral engagement. A
prospective longitudinal design that measures all variables at
several waves is preferable to draw a firmer conclusion con-
cerning the moderated-mediation mechanisms. Second, we
only investigated the attainment value that is deemed to be
the most germane one for Chinese foreign language learners.
However, the other two types of value, namely intrinsic and
utility, may also interact with expectancy to affect behavioral
engagement and FL performance. Third, the proportion of
female participants in the present study is high. Although the
gender ratio reflects the actual situation of the current gender
ratio of normal university students in China, the gender dis-
tribution will be more balanced if participants were chosen
from multiple types of universities such as the polytechnic
university, finance universities, comprehensive universities.
Moreover, we highly relied on self-reported surveys. Self-
report is a nigh ubiquitous data collection method in the field
of education research, but this data gathering method is
prone to pose the problem of common method variance
(Podsakoff & Organ, 1986). Future research should also uti-
lize the methods of peer or teacher assessments rather than
self-reported data during the data collection phase (Conway
& Lance, 2010).
Implications for Educational Practice
This study has potential educational implications, especially
for those students with low expectancy or attainment value.
That is, college students’ expectancy and attainment values
could complement each other in the context of foreign lan-
guage learning. More specifically, high ESs can buffer the
adverse effects of low attainment value on FL achievement
and high attainment value can also buffer the adverse effects
of low ESs on FL achievement. Therefore, it is advised that
focusing on raising attainment value would be an effective
way to improve FL achievement of low-expectation students.
Analogously, efforts to cultivate students’ ESs could be a
resultful strategy to better students’ low level of attainment
value and in turn improve their FL achievement. In view of
Priniski et al. (2018), both students’ motivation and educa-
tional outcomes can be improved via building a connection
between academic tasks (e.g., lesson activities) and personal
relevance. To achieve this goal, Acee et al. (2018) argued
that students could achieve personal significance once they
combine the academic activities with task-value messages,
and thereby they are more motivated to engage in the learn-
ing activities and obtain good grades.
Conclusion
To conclude, the present study provides evidence for the
effect mechanism of expectancy and value on the subsequent
behavioral engagement, and achievement in the process of
Chinese college students’ English learning. Expectancy has
both a direct and indirect relationship with subsequent
achievement through the mediational role of behavioral
engagement. The theoretical significance of this study is to
clarify the synergies between research on expectancy and
value, that is, expectancy and attainment value in the field of
expectancy-value theory can operate both additively and
interactively. In addition to clarifying the additive effect
between expectancy and value on foreign language achieve-
ment via the mediator of behavioral engagement, this study
also elucidated the interactive relationship between these
two variables that the negative effect of students’ low expec-
tancy for foreign language achievement can be ameliorated
by high attainment value. These findings indicate that attain-
ment value would be considered as a target goal of foreign
language education intervention given its protective effect
on low expectancy. That is, for those students with low
expectancy for foreign language achievement, improving
their attainment value and motivating them to engage more
in foreign language learning activities may be an effective
way to solve the problem.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect
to the research, authorship, and/or publication of this article.
Funding
The author(s) received no financial support for the research, author-
ship, and/or publication of this article.
ORCID iD
Yajun Wu https://orcid.org/0000-0002-3174-7575
References
Acee, T. W., Weinstein, C. E., Hoang, T. V., & Flaggs, D. A.
(2018). Value reappraisal as a conceptual model for task-value
interventions. Journal of Experiential Education, 86(1), 69–85.
https://doi.org/10.1080/00220973.2017.1381830
Aho, K., Derryberry, D., & Peterson, T. (2014). Model selection
for ecologists: The worldviews of AIC and BIC. Ecology,
95(3), 631–636. http://www.esajournals.org/doi/full/10.1890/
13-1452.1
Arens, A. K., Schmidt, I., & Preckel, F. (2019). Longitudinal rela-
tions among self-concept, intrinsic value, and attainment value
across secondary school years in three academic domains.
Journal of Education & Psychology, 111(4), 663–684. https://
doi.org/10.1037/edu0000313
Arens, A. K., Yeung, A. S., Craven, R. G., & Hasselhorn, M.
(2011). The twofold multidimensionality of academic self-con-
cept: Domain specificity and separation between competence
and affect components. Journal of Education & Psychology,
103(4), 970–981. https://doi.org/10.1037/a0025047
Atkinson, J. W. (1957). Motivational determinants of risk-taking
behavior. Psychological Review, 64, Part 1(6), 359–372.
https://doi.org/10.1037/14156-004
Bollen, K. A. (1989). Structural equations with latent variables.
Wiley.

10 SAGE Open
Bolton, K., & Botha, W. (2015). Researching English in contem-
porary China. World Englishes, 34(2), 169–174. https://doi.
org/10.1111/weng.12131
Chen, F. F. (2007). Sensitivity of goodness of fit indexes to lack
of measurement invariance. Structural Equation Modeling A
Multidisciplinary Journal, 14(3), 464–504.
Cheng, L. (2008). The key to success: English language test-
ing in China. Language Testing, 25(1), 15–37. https://doi.
org/10.1177/0265532207083743
Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2013). Applied
multiple regression/correlation analysis for the behavioral sci-
ences. Routledge.
Conway, J. M., & Lance, C. E. (2010). What reviewers should
expect from authors regarding common method bias in organi-
zational research. Journal of Business and Psychology, 25(3),
325–334. https://doi.org/10.1007/s10869-010-9181-6
De Clercq, M., Galand, B., Dupont, S., & Frenay, M. (2013).
Achievement among first-year university students: An inte-
grated and contextualised approach. European Journal
of Psychology of Education, 28(3), 641–662. https://doi.
org/10.1007/s10212-012-0133-6
Dörnyei, Z. (2000). Motivation in action: Towards a process-
oriented conceptualisation of student motivation. British
Journal of Educational Psychology, 70, 519–538. https://doi.
org/10.1348/000709900158281
Eccles(Parsons), J. S., Adler, T. F., Futterman, R., Goff, S.
B., Kaczala, C. M., Meece, J. L., & Midgley, C. (1983).
Expectancies, values, and academic behaviors. In J. T. Spence
(Ed.), Achievement and achievement motivation: Psychological
and sociological approaches (pp. 75–146). Freeman.
Eccles, J. (2009). Who am I and what am I going to do with my
life? Personal and collective identities as motivators of
action. Educational Psychologist, 44(2), 78–89. https://doi.
org/10.1080/00461520902832368
Eccles, J. S., O’Neill, S. A., & Wigfield, A. (2005). Ability self-
perceptions and subjective task-values in adolescents and chil-
dren. In K. A. Moore & L. H. Lippman (Eds.), What do children
need to flourish? Conceptualizing and measuring indicators of
positive development (pp. 237–249). Springer.
Eccles, J. S., & Wigfield, A. (2002). Motivational beliefs, values,
and goals. Annual Review of Psychology, 53, 109–132. https://
doi.org/10.1146/annurev.psych.53.100901.135153
Eccles, J. S., & Wigfield, A. (2020). From expectancy-value the-
ory to situated expectancy-value theory: A developmental,
social cognitive, and sociocultural perspective on motivation.
Contemporary Educational Psychology, 61, 101859. https://
doi.org/10.1016/j.cedpsych.2020.101859
Eccles, J., Wigfield, A., Harold, R. D., & Blumenfeld, P. (1993).
Age and gender differences in children’s self- and task per-
ceptions during elementary school. Child Development, 64(3),
830–847. https://doi.org/10.1111/j.1467-8624.1993.tb02946.x
Ericsson, A., & Pool, R. (2016). Peak: Secrets from the new science
of expertise. Houghton Mifflin Harcourt.
Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School
engagement: Potential of the concept, state of the evidence.
Review of Educational Research, 74(1), 59–109. https://doi.
org/10.3102/00346543074001059
Fredricks, J. A., & Eccles, J. S. (2002). Children’s competence and
value beliefs from childhood through adolescence: Growth
trajectories in two male-sex-typed domains. Developmental
Psychology, 38(4), 519–533. https://doi.org/10.1037/0012-
1649.38.4.519
Frenzel, A. C., Pekrun, R., & Goetz, T. (2007). Girls and mathemat-
ics —A “hopeless” issue? A control-value approach to gen-
der differences in emotions towards mathematics. European
Journal of Psychology of Education, 22(4), 497–514.
Fryer, L. K. (2019). Getting interested: Developing a sustainable
source of motivation to learn a new language at school. System,
86, 102120. https://doi.org/10.1016/j.system.2019.102120
Galla, B. M., Amemiya, J., & Wang, M. T. (2018). Using expec-
tancy-value theory to understand academic self-control.
Learning and Instruction, 58, 22–33. https://doi.org/10.1016/j.
learninstruc.2018.04.004
González, A., Paoloni, P.-V., Donolo, D., & Rinaudo, C. (2015).
Behavioral engagement and disaffection in school activities:
Exploring a model of motivational facilitators and performance
outcomes. Anales de Psicologia, 31(3), 869–878. https://doi.
org/10.6018/analesps.32.1.176981
Griffiths, C., Oxford, R. L., Kawai, Y., Kawai, C., Park, Y. Y.,
Ma, X., Meng, Y., & Yang, N. D. (2014). Focus on context:
Narratives from East Asia. System, 43(1), 50–63.
Gu (Michelle), M. (2009). College English learners’ discursive
motivation construction in China. System, 37(2), 300–312.
https://doi.org/10.1016/j.system.2008.11.006
Guilherme, M. (2007). English as a global language and educa-
tion for cosmopolitan citizenship. Language and Intercultural
Communication, 7(1), 72–90. https://doi.org/10.2167/laic184.0
Guo, J., Marsh, H. W., Parker, P. D., Morin, A. J. S., & Dicke,
T. (2017). Extending expectancy-value theory predictions of
achievement and aspirations in science: Dimensional compari-
son processes and expectancy-by-value interactions. Learning
and Instruction, 49, 81–91. https://doi.org/10.1016/j.learnin-
struc.2016.12.007
Guo, J., Marsh, H. W., Parker, P. D., Morin, A. J. S., & Yeung, A. S.
(2015). Expectancy-value in mathematics, gender and socioeco-
nomic background as predictors of achievement and aspirations:
A multi-cohort study. Learning and Individual Differences, 37,
161–168. https://doi.org/10.1016/j.lindif.2015.01.008
Guo, J., Nagengast, B., Marsh, H. W., Kelava, A., Gaspard, H.,
Brandt, H., Cambria, J., Flunger, B., Dicke, A.-L., Häfner, I.,
Brisson, B., & Trautwein, U. (2016). Probing the unique contri-
butions of self-concept, task values, and their interactions using
multiple value facets and multiple academic outcomes. AERA
Open, 2(1), 1–20. https://doi.org/10.1177/2332858415626884
Guo, J., Parker, P. D., Marsh, H. W., & Morin, A. J. (2015).
Achievement, motivation, and educational choices: A longi-
tudinal study of expectancy and value using a multiplicative
perspective. Developmental Psychology, 51(8), 1163–1176.
https://doi.org/10.1037/a0039440
He, Q. (2001). English language education in China. In S. J. Baker
(Ed.), Language policy: Lessons from global models (pp. 225–
231). Monterey Institute of International Studies.
Huang, H. T., Hsu, C. C., & Chen, S. W. (2015). Identification
with social role obligations, possible selves, and L2 motiva-
tion in foreign language learning. System, 51, 28–38. https://
doi.org/10.1016/j.system.2015.03.003
Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in
covariance structure analysis: Conventional criteria versus new
alternatives. Structural Equation Modeling A Multidisciplinary
Journal, 6(1), 1–55.

Wu and Xia 11
Hu, S., & McCormick, A. C. (2012). An engagement-based student
typology and its relationship to college outcomes. Research in
Higher Education, 53(7), 738–754. https://doi.org/10.1007/
s11162-012-9254-7
Jiang, Y., Rosenzweig, E. Q., & Gaspard, H. (2018). An expectancy-
value-cost approach in predicting adolescent students’ aca-
demic motivation and achievement. Contemporary Educational
Psychology, 54, 139–152. https://doi.org/10.1016/j.cedpsych.
2018.06.005
King, R. B., & Gaerlan, M. J. M. (2014). High self-control pre-
dicts more positive emotions, better engagement, and higher
achievement in school. European Journal of Psychology of
Education, 29(1), 81–100.
King, R. B., & Ganotice, F. A. (2015). Does family obliga-
tion matter for students’ motivation, engagement, and well-
being?: It depends on your self-construal. Personality and
Individual Differences, 86, 243–248. https://doi.org/10.1016/j.
paid.2015.06.027
Klein, A., & Moosbrugger, H. (2000). Maximum likelihood estimation
of latent interaction effects with the LMS method. Psychometrika,
65(4), 457–474. https://doi.org/10.1007/bf02296338
Kuh, G. D., Cruce, T. M., Shoup, R., Kinzie, J., & Gonyea, R. M.
(2008). Unmasking the effects of student engagement on first-
year college grades and persistence. The Journal of Higher
Education, 79(5), 540–563. https://doi.org/10.1080/00221546
.2008.11772116
Kumar, R., Zusho, A., & Bondie, R. (2018). Weaving cultural rel-
evance and achievement motivation into inclusive classroom
cultures. Educational Psychologist, 53(2), 78–96. https://doi.
org/10.1080/00461520.2018.1432361
Ladd, G. W., & Dinella, L. M. (2009). Continuity and change in
early school engagement: Predictive of children’s achievement
trajectories from first to eighth grade? Journal of Education
& Psychology, 101(1), 190–206. https://doi.org/10.1037/
a0013153
Lam, S., Wong, B. P. H., Yang, H., & Liu, Y. (2012). Understanding
student engagement with a contextual model. In S. L.
Christenson, A. L. Reschly, & C. Wylie (Eds.), Handbook of
research on student engagement (pp. 403–420). Springer.
Lei, H., Cui, Y., & Zhou, W. (2018). Relationships between stu-
dent engagement and academic achievement: A meta-analysis.
Social Behavior and Personality, 46(3), 517–528. https://doi.
org/10.2224/sbp.7054
Liem, G. A. D., McInerney, D. M., & Yeung, A. S. (2015). Academic
self-concepts in ability streams: Considering domain specific-
ity and same-stream peers. Journal of Experiential Education,
83(1), 83–109. https://doi.org/10.1080/00220973.2013.876227
Li, G., Chen, W., & Duanmu, J. L. (2010). Determinants of interna-
tional students’ academic performance: A comparison between
Chinese and other international students. Journal of Studies in
International Education, 14(4), 389–405.
Li, Y., Lerner, J. V., & Lerner, R. M. (2010). Personal and ecologi-
cal assets and academic competence in early adolescence: The
mediating role of school engagement. Journal of Youth and
Adolescence, 39(7), 801–815. https://doi.org/10.1007/s10964-
010-9535-4
Loh, E. K. Y. (2019). What we know about expectancy-value the-
ory, and how it helps to design a sustained motivating learning
environment. System, 86, 102–119. https://doi.org/10.1016/j.
system.2019.102119
Marsh, H. W. (2007). Self-concept theory, measurement and
research into practice: The role of self-concept in educational
psychology. British Psychological Society.
Marsh, H. W., & Martin, A. J. (2011). Academic self-concept and
academic achievement: Relations and causal ordering. British
Journal of Educational Psychology, 81(1), 59–77. https://doi.
org/10.1348/000709910x503501
Meece, J. L., Wigfield, A., & Eccles, J. S. (1990). Predictors of
Math Anxiety and Its Influence on Young Adolescents’ Course
Enrollment Intentions and Performance in Mathematics.
Journal of Education & Psychology, 82(1), 60–70. https://doi.
org/10.1037/0022-0663.82.1.60
Meyer, J., Fleckenstein, J., & Köller, O. (2019). Expectancy
value interactions and academic achievement: Differential
relationships with achievement measures. Contemporary
Educational Psychology, 58, 58–74. https://doi.org/10.1016/j.
cedpsych.2019.01.006
Mori, S., & Gobel, P. (2006). Motivation and gender in the
Japanese EFL classroom. System, 34(2), 194–210. https://doi.
org/10.1016/j.system.2005.11.002
Muthén, L. K., & Muthén, B. (2013). Mplus version 8.3: User’s
guide. Muthén & Muthén.
Nagengast, B., Marsh, H. W., Scalas, L. F., Xu, M. K., Hau,
K. T., & Trautwein, U. (2011). Who took the “×” out of
expectancy-value theory? A psychological mystery, a sub-
stantive-methodological synergy, and a cross-national general-
ization. Psychological Science, 22(8), 1058–1066. https://doi.
org/10.1177/0956797611415540
Oga-Baldwin, W. L. Q. (2019). Acting, thinking, feeling, making,
collaborating: The engagement process in foreign language
learning. System, 86, 1–10. https://doi.org/10.1016/j.system.
2019.102128
Pan, L., & Block, D. (2011). English as a “global language” in
China: An investigation into learners’ and teachers’ language
beliefs. System, 39(3), 391–402. https://doi.org/10.1016/j.sys-
tem.2011.07.011
Pekrun, R. (2009). Emotions at school. In K. R. Wentzel & A.
Wigfield (Eds.), Handbook of Motivation at School (pp. 575–
604). Routledge.
Pintrich, P. R., & de Groot, E. V. (1990). Motivational and self-
regulated learning components of classroom academic per-
formance. Journal of Education & Psychology, 82(1), 33–40.
https://doi.org/10.1037/0022-0663.82.1.33
Plante, I., O’Keefe, P. A., & Théorêt, M. (2013). The relation
between achievement goal and expectancy-value theories in
predicting achievement-related outcomes: A test of four the-
oretical conceptions. Motivation and Emotion, 37(1), 65–78.
https://doi.org/10.1007/s11031-012-9282-9
Podsakoff, P. M., & Organ, D. W. (1986). Self-Reports in Organizational
Research: Problems and Prospects. Journal of Management,
12(4), 531–544. https://doi.org/10.1177/014920638601200408
Priniski, S. J., Hecht, C. A., & Harackiewicz, J. M. (2018). Making
learning personally meaningful: A new framework for rel-
evance research. Journal of Experiential Education, 86(1),
11–29. https://doi.org/10.1080/00220973.2017.1380589
Putwain, D. W., Nicholson, L. J., Pekrun, R., Becker, S., &
Symes, W. (2019). Expectancy of success, attainment value,
engagement, and achievement: A moderated mediation
analysis. Learning and Instruction, 60, 117–125. https://doi.
org/10.1016/j.learninstruc.2018.11.005

12 SAGE Open
Safavian, N. (2019). What makes them persist? Expectancy-value
beliefs and the math participation, performance, and prepared-
ness of Hispanic youth. AERA Open, 5(3), 1–17. https://doi.
org/10.1177/2332858419869342
Salanova, M., Schaufeli, W., Martinez, I., & Breso, E. (2010).
How obstacles and facilitators predict academic perfor-
mance: The mediating role of study burnout and engage-
ment. Anxiety, Stress, and Coping, 23(1), 53–70. https://doi.
org/10.1080/10615800802609965
Sardeshmukh, S. R., & Vandenberg, R. J. (2017). Integrating
moderation and mediation: A structural equation modeling
approach. Organizational Research Methods, 20(4), 721–745.
https://doi.org/10.5465/AMBPP.2013.92
Shao, K., Pekrun, R., Marsh, H. W., & Loderer, K. (2020). Control-
value appraisals, achievement emotions, and foreign language
performance: A latent interaction analysis. Learning and
Instruction, 69, 101–356.
Skinner, E. A., & Chi, U. (2012). Intrinsic motivation and
engagement as “active ingredients” in garden-based edu-
cation: Examining models and measures derived from
self-determination theory. The Journal of Environmental
Education, 43(1), 16–36. https://doi.org/10.1080/00958964
.2011.596856
Skinner, E. A., Kindermann, T. A., & Furrer, C. J. (2009). A
motivational perspective on engagement and disaffection:
Conceptualization and assessment of children’s behavioral
and emotional participation in academic activities in the
classroom. Educational and Psychological Measurement,
69(3), 493–525.
Tan, J. B., & Yates, S. (2011). Academic expectations as sources
of stress in Asian students. Social Psychology of Education,
14(3), 389–407. https://doi.org/10.1007/s11218-010-9146-7
Televantou, I., Marsh, H. W., Dicke, T., & Nicolaides, C. (2021).
Phantom and big-fish-little-pond-effects on academic self-con-
cept and academic achievement: Evidence from English early
primary schools. Learning and Instruction, 71, 101399. https://
doi.org/10.1016/j.learninstruc.2020.101399
Tong, L. (2006). Findings and documents of the survey of language
situation in China. Language & Culture Press.
Tonks, S. M., Wigfield, A., & Eccles, J. S. (2018). Expectancy value
theory in cross-cultural perspective: What have we learned
in the last 15 years? In G. A. D. Liem & D. M. Macintyre
(Eds.), Big Theories Revisited (pp. 91–115). Information Age
Publishing.
Tran, T. T. (2013). Is the learning approach of students from the
Confucian heritage culture problematic? Educational Research
for Policy and Practice, 12(1), 57–65. https://doi.org/10.1007/
s10671-012-9131-3
Trautwein, U., Lüdtke, O., Kastens, C., & Köller, O. (2006). Effort
on homework in grades 5-9: Development, motivational ante-
cedents, and the association with effort on classwork. Child
Development, 77(4), 1094–1111. https://doi.org/10.1111/
j.1467-8624.2006.00921.x
Trautwein, U., Marsh, H. W., Nagengast, B., Lüdtke, O., Nagy, G.,
& Jonkmann, K. (2012). Probing for the multiplicative term in
modern expectancy–value theory: A latent interaction model-
ing study. Journal of Education & Psychology, 104(3), 763–
777. https://doi.org/10.1037/a0027470
Turner, J. E., & Schallert, D. L. (2001). Expectancy–value rela-
tionships of shame reactions and shame resiliency. Journal of
Education & Psychology, 93(2), 320–329.
Wang, J. (2015). On the sex-labeling of teaching occupation:
Discussing the gender imbalance of normal universities. The
Journal of Higher Education, 36(6), 65–72.
Wang, M. T., & Eccles, J. S. (2013). School context, achievement
motivation, and academic engagement: A longitudinal study
of school engagement using a multidimensional perspective.
Learning and Instruction, 28, 12–23. https://doi.org/10.1016/j.
learninstruc.2013.04.002
Wigfield, A. (1994). Expectancy-value theory of achievement moti-
vation: A developmental perspective. Educational Psychology
Review, 6(1), 49–78. https://doi.org/10.1007/bf02209024
Wigfield, A., & Cambria, J. (2010). Expectancy-value the-
ory: Retrospective and prospective. In T. C. Urdan & S. A.
Karabenick (Eds.), The decade ahead: Theoretical perspec-
tives on motivation and achievement (pp. 35–70). Emerald
Group Publishing Limited.
Wigfield, A., & Eccles, J. S. (1992). The development of achieve-
ment task values: A theoretical analysis. Developmental
Review, 12(3), 265–310.
Wigfield, A., & Eccles, J. S. (2000). Expectancy-value theory of
achievement motivation. Contemporary Educational Psychology,
25(1), 68–81. https://doi.org/10.1006/ceps.1999.1015
Wigfield, A., & Wagner, A. L. (2005). Competence, motivation,
and identity development during adolescence. In A. J. Elliot &
C. S. Dweck (Eds.), Handbook of competence and motivation
(pp. 222–239). The Guilford Press.
Wu, F., & Fan, W. (2017). Academic procrastination in linking
motivation and achievement-related behaviours: A perspective
of expectancy-value theory. Educational Psychologist, 37(6),
695–711. https://doi.org/10.1080/01443410.2016.1202901
Yli-Piipari, S., & Kokkonen, J. (2014). An application of the expec-
tancy-value model to understand adolescents’ performance and
engagement in physical education. Journal of Teaching in
Physical Education, 33(2), 250–268. https://doi.org/10.1123/
jtpe.2013-0067