Exploring the effects of achievement emotions on online learning outcomes: A systematic review

Abstract

Recently, achievement emotions have attracted much scholarly attention since these emotions could play a pivotal role in online learning outcomes. Despite the importance of achievement emotions in online education, very few studies have been committed to a systematic review of their effects on online learning outcomes. This study aimed to systematically review studies examining the effects of achievement emotions on online learning outcomes in terms of motivation, performance, satisfaction, engagement, and achievement. According to the selection process of Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) principles, a total of 23 publications were included in this review. It was concluded that positive achievement emotions, such as enjoyment, pride, and relaxation, could generally exert a positive effect on online learning motivation, performance, engagement, satisfaction, and achievement. It should be noted that excessive positive emotions might be detrimental to online learning outcomes. On the other hand, it has been difficult to determine the effects of negative achievement emotions on online learning outcomes because of disagreement on the effects of negative achievement emotions. In order to improve online learners' learning outcomes, instructors should implement interventions that help online learners control and regulate their achievement emotions. Teaching interventions, technological interventions, and treatment interventions could benefit online learners emotionally and academically. Future studies could examine the moderating roles of contextual factors and individual variables in the effects of achievement emotions on online learning outcomes.

Full text

TYPE Systematic Review
PUBLISHED 09 September 2022
DOI 10.3389/fpsyg.2022.977931
OPEN ACCESS
EDITED BY
Rong Lian,
Fujian Normal University, China
REVIEWED BY
Yajun Wu,
Yunnan Normal University, China
Melanie Stephan,
University of Erlangen
Nuremberg, Germany
Xia Kang,
The University of Hong Kong, Hong
Kong SAR, China
*CORRESPONDENCE
Zhonggen Yu
401373742@qq.com
SPECIALTY SECTION
This article was submitted to
Educational Psychology,
a section of the journal
Frontiers in Psychology
RECEIVED 25 June 2022
ACCEPTED 16 August 2022
PUBLISHED 09 September 2022
CITATION
Wu R and Yu Z (2022) Exploring the
eects of achievement emotions on
online learning outcomes: A
systematic review.
Front. Psychol. 13:977931.
doi: 10.3389/fpsyg.2022.977931
COPYRIGHT
©2022 Wu and Yu. This is an
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Attribution License (CC BY). The use,
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or reproduction is permitted which
does not comply with these terms.
Exploring the eects of
achievement emotions on
online learning outcomes: A
systematic review
Rong Wu and Zhonggen Yu *
Faculty of Foreign Studies, Beijing Language and Culture University, Beijing, China
Recently, achievement emotions have attracted much scholarly attention since
these emotions could play a pivotal role in online learning outcomes. Despite
the importance of achievement emotions in online education, very few studies
have been committed to a systematic review of their eects on online learning
outcomes. This study aimed to systematically review studies examining the
eects of achievement emotions on online learning outcomes in terms
of motivation, performance, satisfaction, engagement, and achievement.
According to the selection process of Preferred Reporting Items for Systematic
Review and Meta-analysis (PRISMA) principles, a total of 23 publications
were included in this review. It was concluded that positive achievement
emotions, such as enjoyment, pride, and relaxation, could generally exert
a positive eect on online learning motivation, performance, engagement,
satisfaction, and achievement. It should be noted that excessive positive
emotions might be detrimental to online learning outcomes. On the other
hand, it has been dicult to determine the eects of negative achievement
emotions on online learning outcomes because of disagreement on the
eects of negative achievement emotions. In order to improve online learners’
learning outcomes, instructors should implement interventions that help
online learners control and regulate their achievement emotions. Teaching
interventions, technological interventions, and treatment interventions could
benefit online learners emotionally and academically. Future studies could
examine the moderating roles of contextual factors and individual variables
in the eects of achievement emotions on online learning outcomes.
KEYWORDS
positive achievement emotions, negative achievement emotions, online learning
outcomes, interventions, online learners
Introduction
The importance of achievement emotions
Achievement emotions could not only be the consequences of achievement activities
and outcomes but also play an important role in subsequent learning (Pekrun et al.,
2017;Pan et al., 2022). The effects of achievement emotions on learning have attracted
considerable attention, both scholarly and popular (Camacho-Morles et al., 2021).
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Evidence has suggested that achievement emotions could
exert an important influence on learners’ problem-solving
ability (Lee and Chei, 2020), learning persistence (Tang et al.,
2021), engagement (Luo and Luo, 2022), motivation (Feraco
et al., 2022), satisfaction (Wu et al., 2021b), and achievement
(Putwain et al., 2022).
Achievement emotions in online learning
Online learners’ achievement emotions have caught
attention since online learning has become a new norm in
recent years (Wang et al., 2022). Compared to traditional
face-to-face learning, online learning has brought learners
new opportunities and challenges, such as flexibility, isolation,
and technical problems (Kim et al., 2014;Yu, 2021). Facing
opportunities and challenges specific to online learning,
learners may experience achievement emotions more frequently
than those in traditional face-to-face learning (Moneta and
Kekkonen-Moneta, 2007;D’Mello and Graesser, 2012;Lee
and Chei, 2020). Students were more likely to experience a
high level of frustration in online learning due to technical
problems, compared to face-to-face learning (Hamilton et al.,
2021). Nevertheless, the extant literature has mainly focused
on achievement emotions in traditional face-to-face learning
(Raccanello et al., 2020). Research on achievement emotions in
online learning has been relatively scarce (Yang et al., 2021).
Roles of achievement emotions in online
learning outcomes
Recent research has suggested that achievement emotions
could play a crucial role in online learning outcomes (Lee and
Chei, 2020). Generally, positive emotions could be conducive
to online learning outcomes, while negative emotions could
be detrimental to online learning outcomes (Pan et al., 2022).
Learners experienced positive achievement emotions (e.g., joy
and relief) when gaining a great deal of the flexibility of
online learning (Zembylas et al., 2008). Learners with positive
achievement emotions possibly had more online learning
satisfaction (Wu et al., 2021b). In contrast, many learners were
less likely to attend online classes when feeling boring and
disengaged due to the lack of interactive activities and emotional
support in online learning (Tzafilkou et al., 2021).
However, literature has emerged that offered contradictory
findings on the effects of achievement emotions (e.g., Golding
and Jackson, 2021). The effects of achievement emotions on
online learning outcomes may be more complex than once
thought, resulting from close intertwinement with affective,
cognitive, and contextual factors. (Artino and Jones, 2012;
Marchand and Gutierrez, 2012). On one aspect, empirical
evidence seemed to suggest the positive effects of negative
emotions on online learning outcomes (e.g., Hilliard et al.,
2020). On the other aspect, recent research found that positive
achievement emotions had a negative influence on online
learners’ learning outcomes (Liu et al., 2021). Therefore, there
has been little agreement on whether achievement emotions
could be beneficial or detrimental to online learning outcomes.
Although recent years have witnessed an exponential
growth in research on achievement emotions, one of the
biggest challenges might be to summarize and synthesize the
contradictory findings in this field (Camacho-Morles et al.,
2021). Relatively little research has conducted a systematic
review of achievement emotions, and even less on the effects
of achievement emotions on online learning outcomes in
terms of motivation, engagement, achievement, satisfaction,
and performance. This study, aiming to synthesize available
findings on the effects of achievement emotions on online
learning motivation, engagement, performance, satisfaction, and
achievement, is thus meaningful.
Theoretical framework
The control-value theory (CVT) is the main theoretical
framework for understanding achievement emotions (Pekrun,
2006). CVT integrates assumptions from several theories,
including the expectance value theory of emotions, transactional
approaches, attributional theories, and models of the effects of
emotions (Pekrun et al., 2017). CVT explains how achievement
emotions subsequently influence learners’ motivation,
performance, engagement, satisfaction, and achievement
in various academic contexts (Pekrun et al., 2011). Moreover,
CVT suggests that individuals’ achievement emotions may
vary in intensity and frequency due to gender, age, and culture
(Camacho-Morles et al., 2021). This study attempted to use
CVT as the theoretical framework to analyze the effects
of achievement emotions on online learning outcomes in
terms of motivation, engagement, performance, satisfaction,
and achievement.
Literature review, aims, and research
questions
Achievement emotions
Definitions of achievement emotions
Achievement emotions, also known as academic emotions,
could be defined as emotions in relation to achievement
activities and achievement outcomes, such as disappointment
about unattainable learning goals (Pekrun, 2006). Achievement
emotions could be deemed as either state emotions or
trait emotions typically experienced in various academic
environments (Pekrun et al., 2011). For instance, some
learners might experience a high level of anxiety when taking
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TABLE 1 A three-dimensional taxonomy of achievement emotions
(Adapted from Pekrun and Stephens, 2010).
Object
focus
Positive emotions Negative emotions
Activating Deactivating Activating Deactivating
Activity Enjoyment Relaxation Anger
Frustration
Boredom
Outcome/
Prospective
Joy*
Hope
Relief* Anxiety Hopelessness
Outcome/
Retrospective
Joy
Pride
Gratitude
Contentment
Relief
Shame
Anger
Sadness
Disappointment
*Anticipatory joy/relief.
exams, others when attending face-to-face classes. Achievement
emotions are multifaceted processes that consist of cognitive,
psychological, and motivational components (Fraschini and
Tao, 2021). Unlike other emotions in educational contexts,
achievement emotions involve specific object focuses and
appraisal-driven psychological processes (Putwain et al., 2018).
Classifications of achievement emotions
Emotions could be categorized according to three
dimensions, i.e., object focus, valence, and activation (Pekrun
et al., 2011). In terms of object focus, activity emotions could
be distinguished from outcome emotions. Regarding valence,
positive emotions could be differentiated from negative
emotions. As regards activation, activating emotions could be
distinguished from deactivating emotions (Pekrun et al., 2002).
According to the three dimensions, achievement emotions
could thus be grouped into different categories, such as
positive activating emotions and negative outcome emotions
(Pekrun and Stephens, 2010;Pekrun et al., 2017). Table 1
displays an overview of a three-dimensional taxonomy of
achievement emotions.
Previous reviews of achievement emotions
Recently, there have been some reviews of the effects of
achievement emotions in education. In a comprehensive review,
boredom experienced in traditional learning contexts was
proven detrimental to achievement, motivation, and learning
strategies (Tze et al., 2016). A systematic review revealed
that enjoyment positively influenced learning outcomes in
technology-enhanced contexts. It also mentioned that anger,
frustration, and boredom merely had a slightly negative
influence on learning outcomes (Loderer et al., 2020). Similarly,
another literature review concluded that a positive correlation
was found between enjoyment and performance, and negative
correlations were found for both anger and boredom (Camacho-
Morles et al., 2021). Meanwhile, Tan et al. (2021) reported that
positive emotions were better than negative ones at enhancing
learning effects.
Despite the increasing importance of achievement emotions
in online learning (Yu et al., 2020), very few published studies
have synthesized the effects of achievement emotions on online
learning outcomes (see Table 2). Given that the effects of
achievement emotions on online learning outcomes have been
unclear, it is meaningful to systematically review publications
reporting the effects of achievement emotions on online learning
outcomes in terms of motivation, performance, engagement,
satisfaction, and achievement.
Motivation
Motivation, as a crucial variable in online learning, is the
mental state that stimulates and maintains online learning
behaviors (Yu, 2022). Motivation is generally divided into
extrinsic and intrinsic motivation. The former refers to
individuals’ desire to do an activity in order to obtain some
separable outcome, whereas intrinsic motivation refers to
individuals’ desire to do an activity in order to gain a sense
of inherent satisfaction (Ryan and Deci, 2000). Motivation, in
this study, was defined as the desire to participate in online
learning activities.
Achievement emotions are important factors influencing
learners’ motivation (Pekrun, 2006). With the exponential
growth in online learning, there has been a growing academic
interest in the precise effects of achievement emotions on
learning motivation (Lee J. et al., 2021). Evidence has suggested
that different achievement emotions had diverse mechanisms
for online learning motivation (Murphy and Rodriguez, 2008;
Lee J. et al., 2021). However, not enough studies systematically
reviewed the related literature. Considering the importance of
motivation, it is meaningful to review and synthesize the effects
of achievement emotions on online learning motivation.
Performance
Performance is one of the most significant factors
influencing online educational quality and success (Zhu et al.,
2022). Performance could be generally described as individuals’
learning attitudes and behaviors (Lu and Lin, 2016). Specifically,
performance refers to how learners deal with their studies and
how they accomplish learning tasks assigned by their instructors
(Kayode, 2015). Performance also refers to the degree to which
learners are continuing to learn in order to achieve learning
goals (Eid and Al-Jabri, 2016). Performance in this study refers
to how online learners cope with their learning materials
and tasks.
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TABLE 2 Previous reviews of achievement emotions.
Source Date range Emotion(s) Finding(s) Context
Tze et al. (2016) 1990–2014 Boredom Achievement; Motivation; learning
strategies
Traditional learning contexts
Loderer et al. (2020) 1965–2018 Enjoyment, curiosity/interest, anxiety,
anger/frustration, confusion
Engagement; learning strategy;
achievement
Technology–based learning contexts
Camacho-Morles et al. (2021) 1986–2019 Enjoyment, anger, frustration, and
boredom,
performance Not specified
Tan et al. (2021) 2012–2020 Not specified Learning effects Not specified
Innovation of this study 1986–2022 All emotions included in selected studies Motivation; Performance; Satisfaction;
Engagement; Achievement
Online learning contexts
Much of the available literature has focused on the influence
of achievement emotions on performance in online learning
contexts. However, inconsistent findings are still present
with regard to the effects of achievement emotions. Online
learners could improve their performance because they have
experienced positive achievement emotions (Parker et al., 2021).
Nevertheless, some students feeling positive emotions have
performed poorly in online learning (Liu et al., 2021). To
date, the effects of achievement emotions on online learning
performance have still not been systematically reviewed.
Engagement
Engagement could be deemed as sustaining efforts that
learners make to achieve goals in academic learning (Jung
and Lee, 2018). It is a multidimensional structure consisting
of behavioral, cognitive, and emotional aspects. Behavioral
engagement refers to an individual’s participation in learning
activities. Cognitive engagement is deemed as an individual’s
willingness to perform difficult tasks. Emotional engagement
includes an individual’s emotional reactions to learning
(Fredricks et al., 2004). Engagement is regarded as a significant
indicator of the quality of online education (Xu et al., 2020).
Engagement in this study was defined as learners’ involvement
in online learning activities.
Numerous studies have examined whether achievement
emotions could influence learners’ engagement in online
learning (e.g., Golding and Jackson, 2021). The existing findings
on the precise effects of achievement emotion, however,
have been contradictory. On the one hand, certain studies
claimed that learners’ engagement may be subject to learners’
achievement emotions in online courses (D’Errico et al., 2016).
More recently, certain studies have emerged that provided
inconsistent findings. No significant relationship was found
between learners’ achievement emotions and their engagement
in online learning (Wu et al., 2021a). The inconsistent
findings were also supported by Wang et al. (2022). Given
the inconsistent findings, it was necessary to conduct a
systematic review.
Satisfaction
Satisfaction could be operationally defined as the range of
mental states where learners have the feeling of contentment
with online learning experiences and online courses. Satisfaction
also is an affective outcome influencing learners’ intention
to participate in online learning (Taghizadeh et al., 2021).
Meanwhile, satisfaction is an important variable, as it is closely
associated with stronger motivation, higher engagement, better
performance, and even greater achievement in all learning
contexts (Pike, 1991;Wu et al., 2021a). More importantly,
learning satisfaction is an important indicator of learning
outcomes (Alqurashi, 2018;Al-Fraihat et al., 2020). Therefore, it
is of great significance to explore influencing factors in learning
satisfaction (Yu, 2015).
Current literature has paid attention to the effects of
achievement emotions on online learning satisfaction. The
existing research reported that achievement emotions exerted
a negative (Artino, 2009), positive (Golding and Jackson,
2021), and even non-significant (Wu et al., 2021a) influence
on online learning satisfaction. In conclusion, these studies
showed that the effects of achievement emotions on satisfaction
were complex. One way to further understand the complex
effects was to conduct a systematic review to summarize these
existing findings.
Achievement
Achievement could be deemed as learners’ improvement
in skills and comprehension of information (Ebel and Frisbie,
1986). Achievement is a criterion for the assessment of learners’
competencies (Madigan and Curran, 2021). Achievement in
this study could be deemed as online learners’ academic
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success and learning gains. Achievement might be identified by
two measures, i.e., perceived success and actual achievement.
Perceived success refers to online learners’ perceptions regarding
their actual attainment while actual achievement refers to online
learners’ test scores.
Numerous studies have examined the effects of achievement
emotions on online learning achievement (e.g., Pan et al., 2022).
It was demonstrated that achievement emotions could in the
least exert an influence on online learning achievement as other
psychological factors. However, not enough evidence suggested
which achievement emotions could lead to significantly higher
online learning achievement, nor did evidence suggest whether
the effects of achievement emotions on achievement might vary
in different online courses.
Aims and research questions
This study set out to systematically review and synthesize
findings on the effects of achievement emotions on learners’
online learning outcomes in terms of motivation, performance,
engagement, satisfaction, and achievement. We proposed
the five questions: (1) Could achievement emotions
influence learners’ online learning motivation? (2) Could
achievement emotions influence learners’ online learning
performance? (3) Could achievement emotions influence
learners’ online learning engagement? (4) Could achievement
emotions influence learners’ online learning satisfaction?
(5) Could achievement emotions influence learners’ online
learning achievement?
Research methods
Research design
This study is a systematic review of the effects of
achievement emotions on learners’ motivation, performance,
engagement, satisfaction, and achievement in online learning
contexts. This study took a four-step approach to identify
and synthesize prior literature, providing a comprehensive
understanding of the effects of achievement emotions on
online learning outcomes. Firstly, this review searched
Web of Science to collect relevant literature. Secondly,
this review identified hot research themes and proposed
research questions, using clustering and mapping techniques
in the program VOSviewer. Thirdly, this review selected
literature based on Preferred Reporting Items for Systematic
Review and Meta-analysis (PRISMA) principles (Page et al.,
2021). Finally, this review provided a comprehensive
understanding of the effects of achievement emotions on
online learning outcomes after synthesizing and analyzing the
included literature.
Research corpus
The researchers initially collected relevant studies by
searching Web of Science on May 25th, 2022. Web of
Science consists of various databases such as Science Citation
Index Expanded (SCI-EXPANDED), Social Sciences Citation
Index (SSCI), Arts and Humanities Citation Index (AandHCI),
Conference Proceedings Citation Index-Science (CPCI-S),
Conference Proceedings Citation Index-Social Science and
Humanities (CPCI-SSH), Emerging Sources Citation Index
(ESCI), Current Chemical Reactions (CCR-EXPANDED), and
Index Chemicus (IC). It could, therefore, minimize selection
bias and improve the representativeness of included studies
(Yu et al., 2022).
The researchers initially obtained a total of 3143 results
by keying in “distance learn∗” OR “distance teach∗” OR “e-
learning” OR “remote learn∗” OR “remote teach” OR “online
learn∗” OR “online teach∗” OR “digital learn∗” OR “digital
teach∗” OR “massive open online courses” OR “MOOC” (topic)
and “anxiety” OR “shame” OR “anger” OR “enjoyment” OR
“boredom” OR “hope” OR “pride” OR “joy” OR “frustration” OR
“relief” OR “relaxation” OR “hopelessness” OR “contentment”
OR “disappointment” OR “sadness” OR “gratitude” OR “positive
affect∗” OR “positive emotion∗” OR “negative affect∗” OR
“negative emotion∗” OR “achievement emotions” OR “academic
emotions” OR “emotion∗” (topic), ranging from the inception to
May 25th, 2022.
To identify hot research themes in the collected literature,
the researchers conducted a bibliographic network study using
the program VOSviewer. Specifically, the researchers extracted
the bibliographic data of the results (N=3143) from Web
of Science. Then, the researchers employed the program
VOSviewer to interpret the bibliographic data, choosing co-
occurrences as the analysis type, all keywords as the analysis
unit, and full counting as the counting methods. The minimum
number of occurrences of a keyword was set at 10. A total of 281
keywords met the threshold. Figure 1 provides an overview of
the bibliographic network.
A total of 281 keywords were classified into 7 clusters.
Cluster 1 included 71 items, e.g., academic emotion,
achievement emotions, e-learning, massive open online
courses, and virtual learning environments. Cluster 2 included
60 items, e.g., adolescents, adults, anxiety, burnout, children,
and college students. Cluster 3 included 51 items, e.g.,
acceptance, adoption, attitudes, behavioral intention, and
ease. Cluster 4 included 48 items, e.g., adaption, challenges,
feedback, language, and knowledge. Cluster 5 included 45
items, e.g., satisfaction, performance, achievements, motivation,
and student engagement. Cluster 6 included 4 items, e.g.,
accessibility, perspective, support, and teacher. Cluster 7
included 2 items, e.g., beliefs and instructional design.
The researchers identified the hot research themes based on
a list of keywords with the top number of the co-occurrence
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FIGURE 1
The bibliographic network.
links. The link strength of motivation (N=960), performance
(N=873), satisfaction (N=744), and engagement (N=561)
were highly ranked. The item achievement also had a strong
link strength (N=480). From the link strength, motivation,
performance, engagement, satisfaction, and achievement are hot
themes in this particular field.
Inclusion and exclusion criteria
We followed the PRISMA principles to include and exclude
the literature. Inclusion and exclusion criteria were formal
categories. Publications were only included in the research if
they (1) shed light on the effects of achievement emotions
on motivation, engagement, performance, satisfaction, and
achievement in online learning contexts, (2) provided adequate
information and full texts for this research, (3) were written
in English, (4) were well-designed journals or conference
proceedings, (5) had reliable and valid findings, and (6) reached
convincing conclusions. Publications were excluded if they (1)
were duplicates, (2) were written in other languages, (3) did
not include an acceptable abstract, (4) were reviewers, book
chapters, books, book reviewers, data papers, editorial materials,
meeting abstracts and unpublished articles, (5) focused on
achievement emotions rather than their effects on motivation,
engagement, performance, satisfaction, and achievement, and
(6) could not provide enough statistical information.
Study selection
Two researchers screened the collected literature
independently based on formal inclusion and exclusion
criteria. There were four phases, as shown in Figure 2. The
researchers initially obtained 3,143 publications from Web of
Science. After checking the document types, the researchers
removed reviewer articles (N=88), book chapters (N=50),
editorial materials (N=20), meeting abstracts (N=5), data
papers (N=4), books (N=1), and book reviewers (N=1).
After screening titles and abstracts, the researchers selected 450
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FIGURE 2
A flow diagram of the study selection based on PRISMA.
publications for full-text review. Through evaluation of full-text
publications for eligibility, the researchers finally included 23
publications for this systematic review. The Cohen’s Kappa
value was 0.93, which indicates high inter-rater reliability
between the two researchers.
Quality assessment
A quality assessment tool proposed by Kmet et al. (2004)
was used to evaluate the quality of these selected publications.
It includes two systems that could be applied to the evaluation
of qualitative research and quantitative research respectively.
Quantitative studies could be assessed by using 14 formal
criteria, such as appropriate sample size and analytic methods.
A total of 10 formal criteria were applied to the assessment
of qualitative studies, such as sampling strategy and use of
verification procedures. Categories of criteria were formal. Two
researchers scored each publication independently (“yes” =2,
“partial” =1, “no” =0). The inter-rater agreement ranged from
60 % to 100%, suggesting acceptable quality.
Data abstraction and synthesis
This review adopted the data abstraction and synthesis
method designed by Bridges et al. (2020). Content analysis
was applied to synthesize and extract the findings of included
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publications. There were three stages. In the first stage, two
researchers carefully read the findings and results of included
publications and extracted all data on samples, methods, analytic
techniques, strengths and weaknesses of studies, and the effects
of achievement emotions. Two researchers inductively coded
data. High inter-coder reliability was found between two
researchers (α=0.90). In the second stage, researchers grouped
codes together and put them into the following categories,
i.e., engagement, satisfaction, motivation, satisfaction, and
achievement. In the third stage, researchers provided a
systematic understanding of the effects of achievement emotions
on online learning motivation, performance engagement,
satisfaction, and achievements.
Descriptive information
Included publications were categorized based on their
publication years (see Appendix). It could be seen that included
publications were published from 2009 to 2022. The number
of publications increased steadily before 2021. However, the
number of publications has been rising more quickly since
2021. A possible explanation for this might be that the rapid
transition to online education during the pandemic has led to
an exponential growth of research on achievement emotions in
online learning contexts.
The findings of descriptive statistics were shown in terms
of samples, methods, and analytical techniques. Of the 23
publications reviewed, the majority of publications (N=20)
selected university students as samples, and two studies selected
primary school students and high school students as samples
respectively. Only one study selected students’ forum posts as
samples. Studies were conducted in the United States (N=
5), China (N=4), Germany (N=3), Italy (N=3). There
was one study in each of the following countries: Australia,
Canada, Indonesia, Jamacia, the Netherlands, South Korea, and
the United Kingdom (in alphabetical order). The sample sizes
varied from 64 students to 400,000 forum posts. Correlation and
regression analysis (N=16) was found to be the most popular
analytical technique to investigate the effects of achievement
emotion on online learning outcomes. Other techniques used to
a lesser extent were structural equation modeling (N=8), factor
analysis (N=6), ANOVA (N=5), and t-test (N=3). Many
scholars also employed qualitative approaches, such as latent
profile analysis (N=2), content analysis (N=2), association
rule mining techniques (N=1), and sentiment analysis (N=1).
Results
This section concluded the effects of achievement emotions
on online learning outcomes in terms of motivation,
engagement, satisfaction, performance, and achievement.
Table 3 shows the effects in detail. The symbol “+” shows that
there is a positive effect. The symbol “–” suggests that there is a
negative effect. The symbol “/” means that the research does not
find the effects. The symbol “&” indicates that there are different
findings. Blank space suggests that the relationships between
factors were not discussed in the included studies.
RQ 1: Could achievement emotions
influence online learning motivation?
The influence of achievement emotions on
motivation
Generally, positive achievement emotions, such as
enjoyment, pride, and joy, could increase online learning
motivation. Promoting undergraduates’ positive emotions
of enjoyment and pride could be useful for the increase of
their motivation in online medical mathematics courses (Kim
and Hodges, 2012). Having a higher motivation, high school
students reported a higher level of enjoyment and pride in
online math courses (Kim et al., 2014).
In the contrast, negative emotions, such as anxiety, boredom,
and frustration, have a detrimental impact on online learners’
motivation. Being bored and frustrated, service academy
undergraduates were not motivated to enroll in future online
courses (Artino, 2009). Similarly, college students feeling bored
reported that they lacked motivation in online courses (Parker
et al., 2021). College students with negative emotions had a low
level of learning motivation which may reduce the opportunities
to gain an academic qualification (Heckel and Ringeisen, 2019).
RQ2: Could achievement emotions
influence online learning performance?
Complex eects
Evidence has suggested that in online learning contexts,
the effects of achievement emotions on performance might be
more complex. Evidence has suggested that positive emotions
could be better than negative ones at enhancing online learning
performance. Experiencing enjoyment in a virtual learning
environment, international business students achieved better
performance (Noteborn et al., 2012). Chinese college students
also improved their learning performance in online learning
environments when experiencing positive emotions of joy, hope,
relaxation, and pride, similar to those in traditional classrooms
(Zhu et al., 2022). Consistent with this finding, Parker et al.
(2021) reported that high control-enjoyment students perceived
themselves as successful and outperformed those with low
control-boredom in a two-semester online course.
Nevertheless, different arguments still exist regarding
the influence of achievement emotions on online learning
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TABLE 3 A summary of eects of dierent emotions.
Online learning outcomes
Emotions Motivation Performance Engagement Satisfaction Achievement
Enjoyment + + + and / +
Pride +–+ +
joy + + +
Relaxation –+
Relief –+
Hope + +
Gratitude
Boredom –+and– / – –
Anxiety –+ + and– –
Frustration –+/ – –
Anger –
Shame –
Hopelessness –
Sadness
The effects of achievement emotions on online learning outcomes are on the horizontal axes; discrete achievement emotions and indicators of online learning outcomes are on the
vertical axes.
performance. On the one hand, it was found that positive
emotions were detrimental to online learners’ performance.
Positive deactivating emotions, such as relief and relaxation,
reduced students’ effort and use of proactive strategies,
eventually leading to a greater risk of poor performance in
MOOCs (Liu et al., 2021). Primary school students were likely
to feel pride when they had false perceptions of their own
performance in online learning. It might be detrimental to their
performance in online learning (Raccanello et al., 2020).
On the other hand, negative activating emotions could
be considered to be beneficial in terms of online learning
performance. A Low level of anxiety could enhance students’
performance and competence in online learning (Heckel and
Ringeisen, 2019). Students, who felt bored with theoretical
courses, performed better on practical assignments in virtual
learning (Noteborn et al., 2012). Frustration could exert a
positive influence on learners’ performance in MOOCs because
it could stimulate learners to make efforts to avoid failure
(Liu et al., 2021). Many part-time distance learners perceived
that anxiety could enhance their participation and performance
in online collaborative learning because they were motivated
by frustration to adopt problem-focused coping strategies
(Hilliard et al., 2020).
Age and gender dierences
Age could be the moderator between achievement emotions
and online learning performance. Compared with younger
learners, older learners had a lower level of pride but a better
performance in digital tasks (Raccanello et al., 2020). However,
gender seemed not to moderate the effects of achievement
emotions on online learning performance. There was no
significant difference between male students and female students
in terms of online learning performance, despite that male
students experienced a higher level of anxiety in online learning
than female students (Mahande et al., 2021).
RQ3: Could achievement emotions
influence online learning engagement?
A much-debated topic
The influence of achievement emotions on online learning
engagement might be a much-debated topic. Some studies
identified the positive effects of positive emotions and negative
effects of negative emotions. Positive achievement emotions
could help Italian university students to engage in different
online learning activities (D’Errico et al., 2016). Chinese college
students with enjoyment tended to actively construct knowledge
and avoid academic failure, thus having a higher level of
engagement in online learning (Wang et al., 2022). Jamaican
high school students, who felt frustrated and anxious, were less
likely to be engaged in online learning (Golding and Jackson,
2021). However, others found that both positive and negative
emotions could not influence online learners’ engagement. The
achievement emotions of enjoyment, boredom, and frustration
did not exert an influence on students’ engagement in MOOCs
(Wu et al., 2021a). Similarly, Wang et al. (2022) found
that frustration could not influence Chinese college students’
engagement in online learning.
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RQ4: Could achievement emotions
influence online learning satisfaction?
The influence of achievement emotions
The influence of achievement emotions on online learning
satisfaction was examined. Several studies have established that
positive emotions could play a crucial role in improving online
learning satisfaction. Negative emotions negatively impacted
online learning satisfaction. High school students, who have
experienced joy, hope, pride, and relief, were more satisfied with
online learning than those feeling frustrated, anxious, and bored
(Golding and Jackson, 2021). Experiencing more enjoyment as
well as less anxiety and boredom in online learning, Chinese
pre-service teachers reported a higher level of satisfaction in
online learning (Wu et al., 2021b). Also, college students, who
felt happiness and pride in online learning, were much more
satisfied with online learning (Zhu et al., 2022). By contrast,
negative achievement emotions, such as sadness, frustration,
and anxiety, have led undergraduate nursing students to feel
dissatisfied with online courses (Santo et al., 2022). Similarly,
undergraduates who reported boredom and frustration were not
satisfied with online courses (Artino, 2009).
Contradictory evidence
Nevertheless, much literature has emerged that offered
contradictory findings on the effects of negative emotions
on satisfaction. University Students feeling a sense of pride
were satisfied with online learning, whereas students who
have experienced a low level of anxiety in online learning
also reported a high level of learning satisfaction (Heckel and
Ringeisen, 2019). Similarly, Korean undergraduates having a
high level of negative emotions had a higher level of online
learning satisfaction, compared to those reporting a medium
level of negative emotions (Lee and Chei, 2020). Contrary to
previous findings, Wu et al. (2021a) found no significant effects
of achievement emotions on students’ satisfaction with MOOCs.
RQ5: Could achievement emotions
influence achievement?
The eects of achievement emotions
Achievement emotions could play a crucial role in students’
achievement in online learning. Positive achievement emotions
were beneficial to learners’ achievement, while negative
emotions were detrimental to their achievement. Specifically,
enjoyment was positively correlated to online learners’ success
in programs and technology use (Butz et al., 2015). On the
other hand, evidence supported that negative achievement
emotions were detrimental to online learning achievement.
Anxiety and frustration may result in a low level of achievement
for university students, particularly during the full-on digital
semester (Stockinger et al., 2021). Korean undergraduates with
a high level of boredom showed a lower level of perceived
achievement in online learning than those with a high level of
enjoyment (Lee and Chei, 2020).
Dierent online courses
Research on achievement emotions has been committed
to exploring the roles of achievement emotions in various
online courses, especially in language courses, business courses,
and math courses. Achievement emotions could play a similar
role in these online courses. In online language courses, Asia
language learners with a higher level of enjoyment and pride
had significantly higher achievement, compared to those with a
higher level of anxiety (Fraschini and Tao, 2021). The increasing
level of boredom was negatively associated with students’
perceived achievement and GPA in online business courses
(Butz et al., 2016). K-12 students, who got higher exam scores
on math tests, were more likely to report a lower level of anxiety,
anger, shame, and hopelessness but a higher level of enjoyment
and pride in online mathematics courses (Kim et al., 2014).
Dierent findings
Gender differences in the effects of achievement emotions
on achievement were investigated. Evidence showed that there
was no significant difference between male students and female
students with respect to online learning achievement, even
though female students showed a higher level of hope than male
students in online learning (Stephan et al., 2019).
Discussion
The aim of this review was to explore whether achievement
emotions could influence online learning outcomes in terms
of motivation, performance, satisfaction, engagement, and
achievement. A total of 23 publications were included in
this review. As indicated previously, achievement emotions
had different mechanisms for online learning motivation,
performance, engagement, satisfaction, and achievement.
The positive eects of positive
achievement emotions
It was not surprising that positive achievement emotions,
such as enjoyment, joy, pride, and relief, could exert a
positive influence on online learners’ motivation, engagement,
satisfaction, performance, and achievement. In other words,
positive achievement emotions are very important for
improving online learning outcomes. These results support
the findings of previous studies (e.g., Camacho-Morles et al.,
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2021). Experiencing positive achievement emotions, online
learners were willing to participate in learning activities and
interact with content, peers, and instructors. When they had
more effective interactions in the learning activities, they
were likely to actively construct knowledge, reflect on their
own online learning experiences, and develop a sense of
community and the ability to self-regulate (Wang et al., 2022).
Consequently, they had a high level of learning motivation,
engagement, satisfaction, performance, and achievement in
online learning.
Nevertheless, it is worth noting that excessive positive
emotions may lead to poor performance in online learning.
Relief and relaxation might also reduce online learners’ effort
and use of proactive strategies, eventually leading to poor
learning performance (Liu et al., 2021). Online learners, who
were filled with pride, might overestimate their performance
and then put less effort into learning activities, eventually
having a greater risk of poor performance. The younger
learners were more vulnerable to negative effects than the older
learners (Raccanello et al., 2020). Therefore, instructors need to
pay attention to online learners’ positive emotions, especially
younger learners.
Diculties in determining the eects of
negative achievement emotions
A growing body of research has been committed to
the effects of negative achievement emotions on online
learners’ motivation, engagement, performance, satisfaction,
and achievement. However, it might be hard to determine
the effects of negative achievement emotions. Some studies
reported the negative influence of negative achievement
emotions on motivation (Artino, 2009), engagement (Raccanello
et al., 2020), performance (Parker et al., 2021), satisfaction
(Golding and Jackson, 2021), and achievement (Stockinger
et al., 2021), while some found that negative emotions,
such as anxiety and frustration, could enhance learners’
performance (Liu et al., 2021) and satisfaction (Heckel and
Ringeisen, 2019). On the other hand, Wang et al. (2022) found
no significant correlation between learning engagement and
negative achievement emotions. These results broadly are in
agreement with previous reviews (e.g., Tan et al., 2021).
Although scholars have long debated the impact of
negative achievement emotions, it is important to notice that
keeping negative achievement emotions under control might
be conducive for online learners. A possible explanation might
be that adequate levels of negative achievement emotions could
stimulate learners to make efforts to practice and avoid failures,
especially when learners were eager to have better performance
and achievement in online learning (Loderer et al., 2020;
Liu et al., 2021). Therefore, instructors need to be aware of
online learners’ negative emotions and provide online help to
those learners.
Conclusion
Major findings
This study systematically reviewed research on the
effects of achievement emotions on motivation, engagement,
performance, satisfaction, and achievement in online learning
contexts. The findings suggested that in online learning
contexts, positive achievement emotions could be much
more effective to improve learners’ motivation, engagement,
performance, satisfaction, and achievement, compared to
negative achievement emotions. It is worth noting that negative
activating emotions, such as anxiety and frustration, could
be beneficial to online learners’ performance and satisfaction.
Keeping achievement emotions under control could have a
beneficial effect on online learning motivation, performance,
engagement, satisfaction, and achievement. Most importantly,
multiple intervention strategies, such as teaching interventions,
technological interventions, and treatment interventions, could
be used to intervene in online learners’ emotions and in turn
benefit online learners academically.
Educational implications
It would be more effective to adopt certain intervention
strategies to encourage online learners to control and regulate
achievement emotions, thereby mitigating their emotional
barriers and improving online learning outcomes. Effective
interventions include teaching interventions, technological
interventions, and treatment interventions.
Teaching interventions
It has been essential to adopt teaching interventions to help
learners control and regulate achievement emotions, which in
turn promote learners’ motivation, engagement, satisfaction,
performance, and achievement in online learning contexts.
Teaching intervention strategies could be provided in the
following areas: (a) online learning environments and (b)
course design.
One important approach to intervening in online learners’
achievement emotions is to provide friendly and supportive
online learning environments. To improve online learning
outcomes, instructors need to build encouraging and supportive
learning environments for online learners to express their
emotions and acquire emotion-based coping strategies (Hilliard
et al., 2020). Forming online peer support groups could
provide learners with emotional support and a learner-centered
atmosphere, which in turn positively influences learners’
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satisfaction (Lee M. et al., 2021). Teachers could create
collaborative learning environments where online learners could
develop a sense of community and experience enjoyment in
online learning (Kohnke et al., 2021).
Well-designed online courses are essential to intervene in
the potential issues associated with online learners’ emotional
experiences (Lee and Chei, 2020). To satisfy different emotional
requirements, instructors could implement effective blended
teaching strategies (Mahande et al., 2021). Providing detailed
information on online course design could be beneficial for
learners to perceive courses as useful and increase their positive
emotions (Gopal et al., 2021). Integrating interesting examples
and demanding activities into short clips of video lectures
is an effective teaching strategy to induce online learners’
positive emotions and increase their concentration (Lee J. et al.,
2021). Learning topics and forums integrated with confusing
information could foster online learners’ curiosity, improving
learners’ performance in online learning (Liu et al., 2022). Videos
with good instructor images could trigger learners’ positive
emotions and in turn help improve their satisfaction with online
learning (Yuan et al., 2021).
Technological interventions
Using technological interventions could generally benefit
online learners both emotionally and academically. Augmented
reality (AR) and virtual reality (VR) applications could create
fun and highly immersive learning experiences, which could
relieve online learners’ boredom and enhance their engagement
(Cesari et al., 2021). User-friendly online learning systems
could lead to positive emotions and engagement among
online learners, which contributes to their achievement in
online learning (Lee and Chei, 2020). Online educational
games could be deemed as effective educational technologies
not only to trigger positive emotions but also to improve
learning outcomes (Tzafilkou and Economides, 2021). Emotion
recognition technologies integrated with intelligent computing
functions could automatically detect facial expressions and
provide feedback on emotional states. It could be useful to help
online learners regulate their emotional states so that they could
be deeply immersed in online learning (D’Mello and Graesser,
2012;Kouahla et al., 2022).
Treatment interventions
Instructors could employ various treatment interventions
to reduce online learners’ negative emotions and increase
their positive emotions. Emotion control treatment intervention
could help online learners put more effort to learn how to control
their own emotions and in turn improve their motivation
in online learning (Kim et al., 2014). Attributional retraining
(AR) may encourage online learners to use more controllable
and usable causes for their failures, thus reducing their
anxiety and enhancing academic achievement in online learning
(Parker et al., 2021).
Limitations
A number of limitations need to be noted regarding the
present study. Firstly, this study could not collect all relevant
publications because of the limitations of library sources.
Moreover, the scope of the present study was limited. There
were reciprocal relationships between achievement emotions
and learning outcomes (Putwain et al., 2022). However, this
study only focused on the influence of achievement emotions
on online learning outcomes but did not discuss the influence of
online learning outcomes on achievement emotions. Thirdly, the
effects of achievement emotions on students’ learning outcomes
may vary across cultural-educational contexts (Liu et al., 2020).
However, the moderating effects of the cultural-educational
contexts were not analyzed in the present study, given that
included publications did not investigate the moderating roles
of cultural-educational factors. Finally, this study only collected
publications written in English, considering that English is
the most commonly used language in the world. Some high-
quality studies written in other languages were excluded from
this study.
Future research directions
Cultural-educational contexts might influence the intensity
of achievement emotions and modes of emotion display (Pekrun
and Stephens, 2010;Hagenauer et al., 2016). Nevertheless,
relatively little research has been committed to comparing
whether online learners’ emotional experiences would vary
in cultural-educational contexts, and even less to exploring
whether the effects of achievement emotions would vary
across cultural-educational contexts. Further studies need to
conduct more control experiments to investigate whether online
learners in different cultural-educational contexts had different
intensity of achievement emotions as well as emotion play
modes. Besides, future studies will need to pay particular
attention to whether the contextual factors could moderate
the effects of achievement emotions on online learning
outcomes. For example, researchers could explore whether
online learners in individualistic countries could express
positive emotions more frequently than those in collectivist
countries, and how these differences may contribute to online
learning outcomes.
Future studies could deepen our understanding by exploring
the moderating roles of individual variables in the relationships
between achievement emotions and online learning outcomes.
Individual variables, such as personality traits, genders, and age,
may play a crucial role in online learning outcomes. Individual
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Wu and Yu 10.3389/fpsyg.2022.977931
variables may moderate the relationships between achievement
emotions and online learning outcomes (Yu and Deng, 2022).
However, little current literature has paid attention to the
moderating roles of individual variables. It is an urgent need to
further explore these moderators.
Data availability statement
The original contributions presented in the study are
included in the article/Supplementary material, further inquiries
can be directed to the corresponding author/s.
Author contributions
RW: conceptualized, designed, collected, analyzed data,
wrote, proofed, and edited this article. ZY: conceptualized,
designed, revised, edited, proofed, and polished this article.
Both authors contributed to the article and approved the
submitted version.
Funding
This work was supported by MOOC of Beijing Language and
Culture University (MOOC201902) (Important) Introduction
to Linguistics; Introduction to Linguistics of online and offline
mixed courses in Beijing Language and Culture University
in 2020; Special fund of Beijing Co-construction Project-
Research and reform of the Undergraduate Teaching Reform
and Innovation Project of Beijing higher education in 2020-
innovative multilingual +excellent talent training system
(202010032003); The Fundamental Research Funds for the
Central Universities, and the Research Funds of Beijing
Language and Culture University (22YCX038).
Acknowledgments
We would like to extend our gratitude to reviewers
and funding.
Conflict of interest
The authors declare that the research was conducted in the
absence of any commercial or financial relationships that could
be construed as a potential conflict of interest.
Publisher’s note
All claims expressed in this article are solely those of the
authors and do not necessarily represent those of their affiliated
organizations, or those of the publisher, the editors and the
reviewers. Any product that may be evaluated in this article, or
claim that may be made by its manufacturer, is not guaranteed
or endorsed by the publisher.
Supplementary material
The Supplementary Material for this article can be
found online at: https://www.frontiersin.org/articles/10.3389/
fpsyg.2022.977931/full#supplementary-material
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