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EFFECTS OF ACADEMIC EMOTIONS ON ACHIEVEMENT AMONG MAINLAND CHINESE STUDENTS:

A META-ANALYSIS

HAO LEI AND YUNHUO CUI East China Normal University

We undertook a meta-analysis to explore the relationship between academic emotions (comprising positive high-arousal [PHA], positive low-arousal [PLA], negative high-arousal [NHA], and negative low-arousal [NLA] emotions) and academic performance among mainland Chinese students, and analyzed the moderating effects of regional location, age, achievement domain match, and gender on these associations. Included in the research were 35 primary studies with 17,548 participants. Results of the meta-analysis showed overwhelming support for the positive correlations between PHA, PLA, and academic achievement (r

PHA =

.312, r PLA

= .376), and negative correlations between NHA, NLA, and academic achievement (r

NHA = -.179, r

NLA = -.371). Furthermore, moderation analyses suggested that these effects

were influenced by regional location, age, achievement domain match, and gender. Practical and theoretical implications of the findings are discussed.

Keywords: academic emotions, emotion arousal, academic achievement, academic performance, meta-analysis.

Academic emotions are defined as students’ emotional experiences related to the academic processes of teaching and learning, including enjoyment, hopelessness, boredom, anxiety, anger, and pride (Pekrun, Goetz, Titz, & Perry, 2002). On the basis of the concepts of arousal and enjoyment, academic emotions have been divided into four types: positive high-arousal (PHA), positive low-arousal (PLA), negative high-arousal (NHA), and negative low-arousal (NLA; Dong

1541

Hao Lei and Yunhuo Cui, Institute of Curriculum and Instruction, East China Normal University. This research was supported by the Humanities and Social Sciences Key Project of the Ministry of Education in China (11JJD880003), and the 2015 Excellent Doctoral Training Program of East China Normal University (PY2015003). Correspondence concerning this article should be addressed to Yunhuo Cui, Institute of Curriculum and Instruction, East China Normal University, 3663 North Zhongshan Road, Shanghai 200062, People’s Republic of China. Email: [email protected]

EFFECTS OF ACADEMIC EMOTIONS ON ACHIEVEMENT1542

& Yu, 2007; Pekrun et al., 2002). PHA emotions include enjoyment, hope, and pride; PLA emotions include satisfaction, calm, and relief; NHA emotions include anger, anxiety, and shame; and NLA emotions include hopelessness, boredom, depression, and exhaustion–upset (Dong & Yu, 2007). According to these emotion types, Dong and Yu (2010) developed the Adolescents’ Academic Emotions Questionnaire—Chinese version, which many Chinese researchers now use. In addition, Li (2010) and Ma (2010) developed questionnaires to assess Chinese college students’ academic emotions. Academic emotions have been associated with, among other variables, cognitive activity, learning motivation and strategies, and academic achievement (Pekrun et al., 2002; Turner & Schallert, 2001).

Academic achievement has been found to be a successful way to evaluate education systems, schools, teachers’ class-management level, and changes in students’ success or failure (Lei, Xu, Shao, & Sang, 2015). Therefore, many researchers have focused on the effects of academic emotions on achievement, and the associated effects have been explored in a considerable body of empirical research (see, e.g., Dong & Yu, 2010; Kim & Hodges, 2012); however, the obtained results have been inconsistent. In general, in an academic context positive emotions have positive effects, such as high grades and high examination performance (Kim & Hodges, 2012; Villavicencio & Bernardo, 2013), and negative emotions have negative effects, such as low grades and low examination performance (Lam, Chen, Zhang, & Liang, 2015; Villavicencio, 2011). Positive emotions help students to sustain their interest in learning over time (Dong & Yu, 2007), thus improving motivation for and effort put into learning, promoting creative learning strategies, and helping students to manifest self-regulated learning. However, negative emotions (e.g., hopelessness and boredom) can reduce levels of motivation for and effort put into learning, cause students to use mechanical learning strategies (e.g., repetitive memorizing), and stimulate students’ learning in ways that depend on external, as opposed to internal, motivational factors (Pekrun et al., 2002).

Previous researchers have not observed these associations between academic emotions and academic achievement or even considered that positive emotions may negatively impact academic achievement and that negative emotions may positively impact academic achievement (Turner & Schallert, 2001; Wang & Chen, 2005). Reasons for this possible effect might be that PHA emotions lead to self-satisfaction and that negative emotions can also improve learning motivation by turning pressure into a motivating force (Wang & Chen, 2005). Thus, the effects of academic emotions on achievement remain inexplicit. This might be because prior researchers have employed small samples; therefore, we used a meta-analysis in this study to explore the effects of academic emotions on achievement among mainland Chinese students.

EFFECTS OF ACADEMIC EMOTIONS ON ACHIEVEMENT 1543

Inconsistent results in previous studies might also be attributable to participants’ demographic factors moderating the effects of academic emotions on achievement, for example, differences in cultural values, age, achievement domain match, and gender. When reviewing previous empirical studies, we found many effect sizes to be heterogeneous, indicating that moderators might play an important role. Therefore, we hypothesized that the effects of academic emotions on achievement would be moderated by (a) regional location, (b) age, (c) achievement domain match, and (d) gender.

Several researchers have suggested that regional differences might moderate the relationship between PHA, PLA, NHA, and NLA emotions and academic achievement, especially because China is divided into eastern, central, and western regions (Cai, Wang, & Du, 2002). For example, Xu, Wei, and Cai (2013) investigated eastern region students and found that correlations between the four types of academic emotions and academic achievement were weak (r

PHA

= .109, r PLA

= .274, r NHA

= -.201, r NLA

= -.281), and Deng (2013) found similar weak correlations among western region students (r

PHA = .190, r

PLA = .277, r

NHA

= -.110 r NLA

= -.318), but Wang (2013) found medium or stronger correlations among central region students (r

PHA = .341, r

PLA = .665, r

NHA = -.360, r

NLA = -.422).

Accordingly, we presumed that correlations between the four types of academic emotions and academic achievement would be stronger for students from the central region than for those from eastern and western regions.

As mentioned previously, the effects of academic emotions on achievement might be influenced by age. Pan, Yang, and Li (2013) investigated 780 middle school students, finding that correlations between PHA, PLA, and NLA emotions and academic achievement were strong (r

PHA = .540, r

PLA = .510, and r

NLA = -.480),

but the correlation between NHA emotions and academic achievement was weak (r

NHA = -.080). Jiang, Bai, and Zhang (2014) found that correlations between the

four types of academic emotions and academic achievement were weak among high school students (r

PHA = .192, r

PLA = .271, r

NHA = -.134, and r

NLA = -.234).

However, Gao (2014), whose sample included university students, found that correlations between PHA, PLA, and NLA emotions and academic achievement were strong (r

PHA = .763, r

PLA = .726, and r

NLA = -.691), but the correlation between

NHA emotions and academic achievement was weak (r NHA

= -.279). Accordingly, we expected that age would moderate the relationship between the four types of academic emotions and academic achievement.

Kim and Seo (2015) stated that the main academic achievement indicators worldwide are quiz scores, examination scores, course grades, and grade point average, but in China the only indicator is examination scores. Therefore, we did not compute the effect sizes of academic emotions on achievement, as influenced by academic indicators. However, in several studies it has been implied that achievement domain match might influence the effect sizes of academic emotions

EFFECTS OF ACADEMIC EMOTIONS ON ACHIEVEMENT1544

on achievement (Zhang & Chen, 2015; Zhao, 2014). Achievement domain match means that academic achievement and academic emotions are mutually consistent (Dong & Yu, 2010). Some, of course, are inconsistent, resulting in a mismatch. For example, Zhang and Chen (2015) found weak correlations between the four types of academic emotions and academic achievement among achievement domain matches (r

PHA = .096, r

PLA = .210, r

NHA = -.135, and r

NLA = -.169). However, Zhao

(2014), whose sample included a mismatched group, found moderate or close to strong correlations between the four types of academic emotions and academic achievement (r

PHA = .384, r

PLA = .457, r

NHA = -.304, and r

NLA = -.499). Accordingly,

we predicted that the correlation between the four types of academic emotions and academic achievement would be stronger for achievement domain mismatch than for achievement domain match.

Several researchers have implied that gender could influence the relationship between students’ emotions and academic achievement. For example, Fang (2015) found weak correlations between PHA, PLA, NHA, and NLA emotions and academic performance among majority male samples (r

PHA = .192, r

PLA =

.180, r NHA

= -.030, and r NLA

= -.132). However, Zhang (2012) observed medium correlations between PHA, PLA, NHA, and NLA emotions and academic performance among a majority female sample (r

PHA = .219, r

PLA = .385, r

NHA =

-.266, and r NLA

= -.377). Accordingly, we presumed that the correlation between PLA, NHA, and NLA emotions and academic achievement would be stronger for females than for males.

Study Purpose We examined the effect sizes of academic emotions on academic achievement

of mainland Chinese students using a meta-analysis, and determined the factors that affect the effect sizes of academic emotions on academic achievement. Specifically, we had two main purposes: (a) to confirm the effect sizes between the four types of academic emotions and academic achievement, and (b) to investigate whether correlations between academic emotions and academic achievement are impacted by students’ regional location, age, achievement domain match, and gender.

Method

Literature Search To locate studies on academic emotions and achievement indices, we searched

the literature from January 2005 (because a database search revealed that research on academic emotions in China first appeared in 2005) to January 2016, which appeared in three databases: the China National Knowledge Internet,

EFFECTS OF ACADEMIC EMOTIONS ON ACHIEVEMENT 1545

Chongqing VIP Information, and Wanfang Database. Indexed keywords we used comprised “academic emotions,” “achievement emotions,” and “achievement and performance.” Initially, 365 articles were retrieved, which we screened according to the following criteria: (a) the article must include research on the relationship between the four types of academic emotions and academic achievement; (b) the article must include an overall sample; (c) the article must include explicit reporting on the Pearson product-moment correlation coefficient or a t or F value that could be transformed into r; and (d) articles including replicated published data were used only if the data also appeared in an academic journal. In the case of point (d), if reported data were incomplete, we used those shown in the academic paper. According to these criteria, 35 Chinese studies (including 39 independent samples) were retained for analysis, and the complete articles were read.

Study Coding To facilitate meta-analysis, feature coding was conducted on the 35 selected

articles, with consideration given to the following variables: author information, demographics (e.g., the proportion of gender and age groups), type of academic emotion assessed, achievement domain match, and r effect size. To generate effect sizes, the independent sample was regarded as a unit, and each independent sample was encoded once, using the following process: (a) the correlation between the four types of academic emotions and academic achievement was encoded and, when academic emotion and academic achievement measures in the same sample had several effect sizes, only one effect size for each study was considered for measurement of that academic emotion; and (b) the relationship between the two variables of different groups was encoded, for example, age and regional location.

Data Analysis All data were analyzed using Comprehensive Meta-Analysis software,

Version 2.0. A fixed effects model was used to conduct the homogeneity test and calculate each mean effect. Averaged weighted (within- and between-inverse variance weights) correlation coefficients of independent samples were used to compute mean effect sizes. Moderators were decided by the homogeneity test, which revealed variance in effect sizes between different samples’ char- acteristics. When the homogeneity test was significant (QBet > .05), post hoc tests were implemented to confirm statistically significant group differences. For assessment of the moderation effect of continuous variables, we used a meta-analysis to examine variation in effect sizes as explained by the moderator.

EFFECTS OF ACADEMIC EMOTIONS ON ACHIEVEMENT1546

Results

Relationship Between Academic Emotions and Academic Achievement After filtering the literature, we used 39 independent samples (N = 17,548;

sample size range: 100–1,135 mainland Chinese students) and calculated 154 effect sizes.

To test the hypothesis, we calculated weighted effect sizes (r), sample sizes (k), 95% confidence intervals (CI), and homogeneity statistics using a fixed effects model. As predicted, the results showed significant positive correlations between both PHA (r = .312, z = 42.551, p < .001, k = 39, 95% CI [.298, .325]) and PLA (r = .376, z = 50.624, p < .001, k = 37, 95% CI [.361, .388]) emotions and academic achievement, and significant negative correlations between both NHA (r = -.179, z = -23.865, p < .001, k = 39, 95% CI [-.193, -.164]) and NLA (r = -.371, z = -51.393, p < .001, k = 39, 95% CI [-.383, -.289]) emotions and academic achievement. These effect sizes were determined to be suitable for moderation analysis.

Moderation Analysis To examine whether the effects of academic emotions on achievement were

moderated by certain factors, we used homogeneity tests to examine average effect sizes of the relationship between PHA, PLA, NHA, and NLA emotions and academic performance. Results showed a significant homogeneity coefficient between the four types of academic emotions and academic achievement (QT(38) = 617.113, p < .001 for PHA; QT(36) = 613.612, p < .001 for PLA; QT(38) = 1024.288, p < .001 for NHA; QT(38) = 2030.698, p < .001 for NLA). This indicates that regional location, age, achievement domain match, and gender factors moderated the effects of academic emotions on achievement (Card, 2011).

Regional location. As indicated in Table 1, results of the homogeneity test (QB = 23.074, df = 3, p < .001; QB = 28.127, df = 3, p < .001; QB = 30.348, df = 3, p < .001; QB = 110.082, df = 3, p < .001) demonstrated that regional location significantly moderated the relationship between PHA, PLA, NHA, and NLA emotions and academic performance. Further, academic emotions and academic achievement showed significant correlations for eastern (rPHA = .265, rPLA = .306, rNHA = -.140, rNLA = -.233, all ps < .001), central (rPHA = .328, rPLA = .400, rNHA = -.192, rNLA = -.421; all ps < .001), and western (rPHA = .276, rPLA = .344, rNHA = -.129, rNLA = -.327, all ps < .001) students.

Age. Four homogeneity tests (QB = 161.105, df = 4, p < .001; QB = 103.087, df = 4, p < .001; QB = 14.649, df = 4, p < .01; QB = 91.617, df = 4, p < .001) revealed significant differences in mean effect sizes for correlations between PHA, PLA, NHA, and NLA emotions and academic achievement across age groups. Middle school (M), high school (H), and university (U) students’ academic emotions

EFFECTS OF ACADEMIC EMOTIONS ON ACHIEVEMENT 1547

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EFFECTS OF ACADEMIC EMOTIONS ON ACHIEVEMENT 1549

were significantly correlated with academic achievement (rPHA,M = .340, rPHA,H = .216, rPHA,U = .452, rPHA,M = .404, rPLA,H = .279, rPLA,U = .467, rNHA,M = -.162, rNHA,H = -.204, rNHA,U = -.220, rNLA,M = -.392, rNLA,H = -.345, rNLA,U = -.461, all ps < .001); however, this relationship was nonsignificant for elementary school students.

Achievement domain match. As indicated in Table 1, results of the homogeneity test (QB = 6.158, df = 1, p < .05; QB = 56.865, df = 1, p < .001; QB = 18.052, df = 1, p < .001) suggested that achievement domain match moderated the relationship between PHA, NHA, and NLA emotions and academic achievement. There were significant correlations between PHA, NHA, and NLA emotions and academic achievement for groups with achievement domain mismatch and achievement domain match (rPHA,mismatch = .321, rPHA,match = .280, rNHA,mismatch = -.209, rNHA,match = -.076, rNLA,mismatch = -.386, rNLA,match = -.319, all ps < .001). In particular, compared with matched students, mismatched students had a stronger correlation between the three types of academic emotions and academic achievement.

Gender. To examine whether gender moderated the effect sizes of academic emotions on achievement, the r effect size was metaregressed onto the percentage of male mainland Chinese participants in each sample. As indicated in Table 2, metaregression analysis (QModel = 6.266, p < .05; QModel = 43.185, p < .001; QModel = 15.271, p < .001) suggested that gender moderated the relationship between PLA, NHA, and NLA emotions and academic performance. Specifically, as the proportion of female participants increased, a stronger effect size was observed. Effect sizes of academic emotions on academic achievement for an all-female sample (r = .511 for PLA, r = -.465 for NHA, r = -.572 for NLA) were stronger than those for an all-male sample (r = .304 for PLA, r = .074 for NHA, r = -.251 for NLA).

Discussion

Our meta-analysis results revealed a significant positive correlation between PHA and PLA emotions and academic achievement, and a significant negative correlation between NHA and NLA emotions and academic achievement. This result supports the traditional view that high positive academic emotions lead to high academic achievement, and negative academic emotions lead to low academic achievement (Stratton, 2012; Villavicencio, 2011). This phenomenon could be caused by positive emotions, which arouse students’ learning motivation, improve their learning strategies, and promote their engagement in the learning process; conversely, negative emotions have the opposite effects.

We also found that the correlation between PLA emotions and academic achievement was stronger than that between PHA emotions and academic achievement, and that the correlation between NLA emotions and academic

EFFECTS OF ACADEMIC EMOTIONS ON ACHIEVEMENT1550

achievement was stronger than that between NHA emotions and academic achievement. These results demonstrate that low arousal had a stronger impact on academic achievement. Specifically, for positive emotions, low-arousal emotions led to students’ higher achievement because high-arousal emotions might lead to careless learning and excessive pride; further, for negative emotions, low-arousal emotions led to students’ lower achievement because high-arousal emotions might lead to a strong desire to change poor learning conditions or to reduce the degree of negative emotions’ influence on academic achievement.

Our results showed that, overall, the effects of academic emotions on achievement were moderated by regional location, age, achievement domain match, and gender. However, achievement domain match did not moderate the relationship between PLA emotions and academic achievement, and gender did not moderate the relationship between PHA emotions and achievement; thus, researchers should focus on these relationships in future studies.

We hypothesized that regional location would moderate the effects of academic emotions on achievement. Our meta-analysis results supported this hypothesis, showing that for positive emotions, correlations between PHA and PLA emotions and academic achievement were strongest among central, followed by western and then eastern region students. Correlations for NHA and NLA emotions and academic achievement were stronger among central than western or eastern region students. This might be attributable to the “testing culture” of China’s central region compared with western and eastern regions; that is, teachers, friends, parents, and other relatives focus on test results as the sole measure of academic achievement, which leads to various positive or negative emotions among the students. Therefore, students in China’s central region are more likely to be impacted by academic emotions.

Our results showed that age moderates the effects of academic emotions on achievement. Correlations between PHA and PLA emotions and academic achievement were highest among university, followed by middle school and then high school students. High school students’ academic achievement was mainly impacted by the pressures of university entrance examinations, whereas positive emotions only weakly affected the academic achievement of people in other age groups. In contrast, the academic achievement of middle school and, especially, of university students was more easily affected by others’ academic emotions. Further, correlations between NHA and NLA emotions and academic achievement were stronger for university students than for high school and middle school students.

Domain match was found to moderate the relationship between PHA, NHA, and NLA emotions and academic achievement, which is consistent with the results of other recent meta-analyses (Huang, 2012; Schwinger, Wirthwein, Lemmer, & Steinmayr, 2014). Causes of these outcomes might be small sample

EFFECTS OF ACADEMIC EMOTIONS ON ACHIEVEMENT 1551

sizes or differences in the academic achievement indicators used in previous studies for such subjects such as languages, mathematics, English, physical education, and chemistry. These results suggest that further research is needed to explore more representative indicators of academic achievement.

Finally, we found that the relationship between PLA, NHA, and NLA emotions and academic achievement was moderated by gender, with the all-female group showing a stronger correlation than the all-male group did, as predicted. This finding suggests that similar levels of NHA and NLA emotions might lead to lower academic achievement, and that a similar level of PLA emotions might lead to high academic achievement. Thus, considering both age and gender differences in the correlation between academic emotions and academic achievement, positive emotions have the greatest advantage for university student women, and negative emotions cause the greatest vulnerability among university student women. As such, we recommend focusing on this group for developing relevant interventions to promote academic achievement.

Study Limitations and Directions for Future Research Many Chinese scholars have found significant effects of academic emotions on

achievement (see, e.g., Dong & Yu, 2007, 2010; Zhang, 2012); however, these results have varied because different achievement indicators were utilized, as we found in this study. Moreover, some Chinese researchers reviewed other academic emotion dimensions, which means that our focus on PHA, PLA, NHA, and NLA emotions, in particular, might have limited the validity of this meta-analysis. Finally, in all studies that we included only direct effects were examined, but it has been found that academic emotions indirectly affect academic achievement across other variables (Kim & Hodges, 2012). Therefore, we recommend that future researchers test the indirect effects of academic emotions on academic achievement.

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