Numerous studies in educational psychology have analyzed the behaviors that comprise or contribute to the basic human
capacity for learning. Academic emotions have been widely studied as keys to the learning process (Pekrun & Stephens, 2010).
Academic emotions are the emotions experienced by learners that emerge due to their appraisals of control and value during the
learning process (Pekrun, 2000, 2006; Pekrun et al., 2002).
Most studies on academic emotions have primarily measured and categorized these emotions (e.g., Liu & Shen, 2015;
Pekrun et al., 2011). Additionally, several scholars have explored the antecedents and consequent variables associated with
academic emotions (e.g., Harley et al., 2019; Huang, 2016; Pekrun & Stephens, 2010; St Omer et al., 2023).
Pekrun (2006) proposed the control–value theory of achievement emotions, which posits that student appraisals of the value
of learning tasks and processes arouse emotions that influence the motivation to learn. The academic emotions discussed in
this paper—referred to as either “academic emotions” or “achievement emotions”—encompass emotions directly related to the
learning process. This study analyzed both distal and proximal variables related to such emotions.
In the current context, proximal variables are cognitive evaluations of control and value that are the immediate determinants
of academic emotions. By contrast, distal variables are environmental factors, such as students’ perceptions of classroom goals
and students’ perceptions of teacher autonomy support, that influence students’ perceptions of control and value and contribute
to the emergence of academic emotions. Academic emotions create a feedback loop that influences control and value appraisals
and environmental variables, which in turn influence the formation of academic emotions.
In contemporary educational psychology, considerable emphasis is placed on the dynamics of motivation in the learning
process. Furthermore, motivation and emotions are closely intertwined, collectively comprising the affective aspects of learning.
The expectancy–value model of motivation proposed by Eccles et al. (1983) comprises five components: The external
environment, cognitive processes, motivational processes, expectations, values, achievement, and performance. This model
illustrates how the external environment and cognitive and motivational processes influence student learning engagement
and performance through expectations of success and task values. Additionally, Eccles et al. argued that learner appraisals of
abilities and task values substantially affect learning engagement and performance. These expectations and value beliefs are
influenced by environmental factors that affect internal cognitive–motivational processes and generate expectations and value
beliefs, which affect learning engagement and performance in a perpetual feedback loop.
The environmental factors within this model encompass socializing agents such as teachers, peers, and parents. Socializing
agents influence learners through their expectations and behaviors, leading learners to internalize these expectations and
behaviors and directly affecting learning engagement and achievement.
In summary, the expectancy–value model of motivation proposed by Eccles et al. (1983) and Pekrun’s (2006) control–value
theory of academic emotions are similar frameworks for examining learning processes. Both theories underscore the influence of external environmental factors and learners’ cognitive appraisals of learning tasks as crucial elements affecting the learning
process. Driven by these influences, motivation and emotional experiences toward learning emerge that directly affect learning
engagement and performance.
With respect to analysis of the proximal factors that influence learning engagement and performance, the expectancy–value
model emphasizes the effect of expectations and beliefs on learning engagement and achievement but does not consider the
effects of academic emotions. However, more research (Ainley & Ainley, 2011; Downer et al., 2007; Yun et al., 2020) indicates
that rational cognitive appraisals are not the only influencers of learning engagement and achievement, a finding consistent with
the tenets of the control–value theory.
The control–value theory of academic emotions does not encompass appraisal of costs in cognitive evaluations, which are
often inherent in student decisions to perform learning tasks (Flake et al., 2015). Additionally, empirical research has indicated
that costs negatively predict positive emotions (Chen, 2015). Therefore, a balanced understanding of appraisals must include
an assessment of costs. Costs, control, and value appraisals are all precursors of and concomitant factors affecting academic
emotions.
Empirical research has explored the predictive effect of self-efficacy on academic emotions but has not investigated the
potential moderating role of self-efficacy, or an individual’s belief in their capability to accomplish a task; consequently, the
evaluation of whether a task involves costs influences an individual’s belief in their ability to complete the task (Nie et al.,
2011). However, studies have not determined whether self-efficacy exerts moderating effects on academic emotions or hope
emotions that influence task and cost appraisals.
Empirical research has demonstrated that self-efficacy can moderate task value appraisals and anxiety emotions.
Theoretically, cost appraisals fall under task value appraisals, and anxiety emotions are a subset of academic emotions.
Therefore, this study proposed that self-efficacy functions as a moderating variable and explored the moderating effects of “cost–
effort→academic emotions–hope” and “cost–sacrifice→academic emotions–hope.”
Data from a longitudinal study involving seventh- and eighth-grade junior high school students (n = 313; 152 boys) from
four schools in Tainan City, Taiwan, were examined. Data collection was conducted in three waves. Participants were asked to
complete an academic emotions subscale (the hope subscale), a peer mastery goal subscale, a peer performance goal subscale,
and a cost scale. All measures were related to the students’ experiences in English classes. All 313 participants participated at
the 3 measurement points.
The present study used LISREL 8.80 and SPSS for Windows 23.0 to perform structural equation modeling. To assess model
fit, we used well-established indices, such as a root mean square error of approximation (RMSEA) < .10, a standardized root
mean residual (SRMR) < .08, the Tucker–Lewis index (TLI) > .90, and a comparative fit index (CFI) > .90 in addition to the
chi-square test.
The results of the analysis indicated that the Academic Emotion Cost Model had a perfect fit with the data. The students
perceived that achieving the T1 peer mastery goal enhanced T2 cost–effort and reduced T2 cost–sacrifice. Additionally, students
perceived that achieving the T1 peer performance goal enhanced T2 cost–effort and T2 cost–sacrifice. These results demonstrate that the students’ cost–effort appraisal is positively associated with hope emotions, whereas their cost–sacrifice appraisal is
negatively associated with hope emotions. Furthermore, self-efficacy moderates the relationship between cost–effort and hope
emotions. On the basis of these results, recommendations are proposed as a reference for further research and instruction.
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