Emotional intelligence predicts academic performance: A meta-analysis.

心理学 情商 荟萃分析 认知心理学 社会心理学 应用心理学 医学 内科学
作者
Carolyn MacCann,Yixin Jiang,Luke E. R. Brown,Kit S. Double,Micaela Bucich,Amirali Minbashian
出处
期刊:Psychological Bulletin [American Psychological Association]
卷期号:146 (2): 150-186 被引量:743
标识
DOI:10.1037/bul0000219
摘要

Schools and universities devote considerable time and resources to developing students' social and emotional skills, such as emotional intelligence (EI). The goals of such programs are partly for personal development but partly to increase academic performance. The current meta-analysis examines the degree to which student EI is associated with academic performance. We found an overall effect of ρ = .20 using robust variance estimation (N = 42,529, k = 1,246 from 158 citations). The association is significantly stronger for ability EI (ρ = .24, k = 50) compared with self-rated (ρ = .12, k = 33) or mixed EI (ρ = .19, k = 90). Ability, self-rated, and mixed EI explained an additional 1.7%, 0.7%, and 2.3% of the variance, respectively, after controlling for intelligence and big five personality. Understanding and management branches of ability EI explained an additional 3.9% and 3.6%, respectively. Relative importance analysis suggests that EI is the third most important predictor for all three streams, after intelligence and conscientiousness. Moderators of the effect differed across the three EI streams. Ability EI was a stronger predictor of performance in humanities than science. Self-rated EI was a stronger predictor of grades than standardized test scores. We propose that three mechanisms underlie the EI/academic performance link: (a) regulating academic emotions, (b) building social relationships at school, and (c) academic content overlap with EI. Different streams of EI may affect performance through different mechanisms. We note some limitations, including the lack of evidence for a causal direction. (PsycINFO Database Record (c) 2020 APA, all rights reserved).
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
mm发布了新的文献求助10
1秒前
轻舟发布了新的文献求助10
2秒前
jianxin发布了新的文献求助10
2秒前
momokop完成签到,获得积分10
3秒前
手动阀完成签到 ,获得积分10
3秒前
Zz完成签到,获得积分10
3秒前
YRHM发布了新的文献求助150
4秒前
爆米花应助WGQ采纳,获得10
5秒前
everything发布了新的文献求助10
5秒前
Tohka发布了新的文献求助10
5秒前
5秒前
杨lan发布了新的文献求助10
5秒前
Shaylee完成签到,获得积分10
7秒前
林天完成签到,获得积分10
7秒前
生动的向日葵完成签到,获得积分10
7秒前
8秒前
Owen应助满意的天采纳,获得10
8秒前
研友_VZG7GZ应助文斯采纳,获得10
8秒前
10秒前
Singularity应助yihoxu采纳,获得10
11秒前
Ava应助生动的向日葵采纳,获得10
12秒前
大方的问寒关注了科研通微信公众号
12秒前
13秒前
April发布了新的文献求助10
14秒前
Akim应助嘉佳采纳,获得10
14秒前
科目三应助mm采纳,获得10
15秒前
青岑发布了新的文献求助10
15秒前
爆米花应助jianxin采纳,获得10
17秒前
创创发布了新的文献求助10
18秒前
清爽老九完成签到,获得积分10
19秒前
19秒前
19秒前
健忘的tao完成签到,获得积分10
20秒前
爱撒娇的朋友完成签到,获得积分10
21秒前
科研通AI2S应助sunshine采纳,获得10
21秒前
23秒前
超级碧曼完成签到,获得积分10
23秒前
YMH完成签到,获得积分10
23秒前
荆佳怡完成签到,获得积分10
23秒前
24秒前
高分求助中
Malcolm Fraser : a biography 700
Signals, Systems, and Signal Processing 610
天津市智库成果选编 600
Climate change and sports: Statistics report on climate change and sports 500
Forced degradation and stability indicating LC method for Letrozole: A stress testing guide 500
Organic Reactions Volume 118 400
A Foreign Missionary on the Long March: The Unpublished Memoirs of Arnolis Hayman of the China Inland Mission 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6466511
求助须知:如何正确求助?哪些是违规求助? 8273005
关于积分的说明 17639479
捐赠科研通 5541257
什么是DOI,文献DOI怎么找? 2907964
邀请新用户注册赠送积分活动 1884937
关于科研通互助平台的介绍 1732988