智商与情商哪个对学习更重要？

doi:10.16382/j.cnki.1000-5560.2022.11.006

摘要/Abstract

摘要：

本研究对860名中学生进行为期一年共三次的追踪研究，旨在考察学生的智商和情商对其语文、数学、英语三科学业成绩的预测作用。交叉滞后模型分析表明: （1）学生先前的智力水平（即智商）能够显著正向预测其三科学业成绩，也即智力水平高的学生，其三科学业成绩也越高；（2）学生的人格特质（即情商的重要指标），尤其是开放性人格也显著正向预测其学科成绩; （3）从长远来看，学生的智力与开放性人格存在交互作用，二者可以相互弥补彼此的不足，从而影响学生以后的学习成绩。可见，智商和情商对学生的学习都十分重要，教育在重视学生潜力开发和智力发展的同时，也应注重培养学生健全的人格。

关键词: 青少年, 智力, 大五人格, 学业成绩, 交叉滞后模型

Abstract:

This study of a sample of 860 Chinese secondary school students used Raven reasoning test and Big Five personality scale to investigate the longitudinal relationship between intelligence, personality and students’ academic performance in three subjects (Chinese, Math, and English). This is a three-wave longitudinal study covering one school year. The cross-lagged panel model analyses indicated that: (1) students’ previous intelligence level can significantly and positively predicted their academic performance in all three subjects. That is, students with high intelligence level tended to achieve higher academic performance in three subjects; (2) students’ personality traits, especially openness, also significantly and positively predicted their academic performance in all three subjects; (3) in the long-term run, there is a compensatory interaction between students’ intelligence and openness in the prediction of academic performance. In this regard, both intelligence and personality traits are very important for students’ learning. Educators should not only pay attention to the development of students’ potential and intelligence, but also to the cultivation of students’ personality traits.

Key words: adolescents, intelligence, Big Five personality traits, academic performance, cross-lagged panel model

张静. 智商与情商哪个对学习更重要？[J]. 华东师范大学学报(教育科学版), 2022, 40(11): 69-79.

Jing Zhang. IQ or EQ: Which is More Important for Students’ Learning ?[J]. Journal of East China Normal University(Educational Sciences), 2022, 40(11): 69-79.

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参考文献 0

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变量	平均数	标准差	1	2	3	4	5	6	7
		T1
1. 情绪稳定性	35.16	7.69	(0.85)
2. 外向性	42.28	6.43	?0.38***	(0.81)
3. 开放性	41.60	5.57	?0.10**	0.21***	(0.69)
4. 宜人性	29.70	5.11	0.38***	?0.22***	?0.11*	(0.65)
5. 尽责性	38.34	6.25	?0.43***	0.25***	0.26***	?0.36***	(0.83)
6. 数学成绩	98.07	30.80	?0.14**	0.09*	0.22***	?0.02	0.17**
7. 语文成绩	101.19	20.49	?0.09*	0.17**	0.23***	?0.04	0.10**	0.51***
8. 英语成绩	100.56	32.29	?0.03	0.11**	0.27***	0.07	0.07*	0.55**	0.59***
		T2
1. 情绪稳定性	35.11	7.86	(0.86)
2. 外向性	42.21	6.49	?0.37***	(0.82)
3. 开放性	41.83	5.62	?0.10**	0.21***	(0.70)
4. 宜人性	29.81	5.28	0.43***	?0.28***	?0.23**	(0.68)
5. 尽责性	38.24	6.33	?0.46***	0.28***	0.32***	?0.43***	(0.83)
6. 数学成绩	96.62	32.36	?0.10**	0.10**	0.24***	?0.10**	0.14**
7. 语文成绩	97.93	18.87	?0.03	0.13**	0.20***	?0.06	0.12**	0.52***
8. 英语成绩	98.78	31.86	0.02	0.08*	0.25***	?0.03	0.07*	0.66***	0.60***
		T3
1. 情绪稳定性	35.37	7.33	(0.85)
2. 外向性	42.45	6.11	?0.39***	(0.80)
3. 开放性	41.32	5.36	?0.12**	0.18***	(0.69)
4. 宜人性	29.49	5.08	0.42***	?0.19***	?0.18***	(0.67)
5. 尽责性	39.51	6.02	?0.41***	0.26***	0.37***	?0.37***	(0.83)
6. 数学成绩	89.01	29.14	?0.10**	0.02	0.23***	0.02	0.15**
7. 语文成绩	100.72	18.41	?0.03	0.00	0.16***	?0.04	0.12**	0.55***
8. 英语成绩	93.18	30.54	?0.04	0.02	0.22***	0.04	0.09*	0.72***	0.59***

模型	χ² (df)	RMSEA (90% CI)	CFI	TLI	SRMR	BIC
情绪稳定性
M1: 形态等值模型	28.11 (15)	0.033 [0.013, 0.052]	0.997	0.994	0.019	8716.76
M2: 弱等值模型	42.13 (21)	0.036 [0.020, 0.051]	0.996	0.993	0.047	8690.77
M3: 强等值模型	45.13 (25)	0.032 [0.016, 0.047]	0.996	0.994	0.048	8667.09
外向性
M1: 形态等值模型	23.76 (15)	0.027 [0.000, 0.047]	0.998	0.996	0.022	7266.88
M2: 弱等值模型	26.16 (21)	0.018 [0.000, 0.037]	0.999	0.998	0.030	7229.27
M3: 强等值模型	31.97 (25)	0.019 [0.000, 0.036]	0.999	0.998	0.033	7208.40
开放性
M1: 形态等值模型	38.77 (15)	0.045 [0.028, 0.063]	0.994	0.986	0.032	7018.70
M2: 弱等值模型	44.18 (21)	0.037 [0.022, 0.053]	0.994	0.990	0.045	6984.10
M3: 强等值模型	58.72 (25)	0.041 [0.028, 0.055]	0.992	0.988	0.045	6971.97
宜人性
M1: 形态等值模型	30.30 (15)	0.036 [0.017, 0.054]	0.995	0.988	0.027	8132.77
M2: 弱等值模型	33.97 (21)	0.028 [0.007, 0.045]	0.996	0.993	0.029	8096.43
M3: 强等值模型	42.09 (25)	0.029 [0.012, 0.045]	0.994	0.992	0.028	8077.87
责任心
M1: 形态等值模型	37.97 (15)	0.044 [0.027, 0.062]	0.995	0.989	0.020	6447.70
M2: 弱等值模型	43.24 (21)	0.037 [0.021, 0.052]	0.996	0.992	0.038	6412.96
M3: 强等值模型	280.11 (25)	0.114 [0.102, 0.126]	0.949	0.926	0.136	6623.16
M4: 部分强等值	48.57 (24)	0.036 [0.021, 0.051]	0.995	0.993	0.041	6398.29

学科	模型	χ² (df)	RMSEA (90% CI)	CFI	SRMR	BIC
数学	M1	2254.87 (1011)	0.038[0.036, 0.040]	0.951	0.059	62861.351
	M2					33171.661
语文	M1	2422.20 (1011)	0.041[0.039, 0.043]	0.945	0.059	61008.866
	M2					31291.019
英语	M1	2379.17(1011)	0.040[0.038, 0.042]	0.948	0.060	62273.975
	M2					32577.727

	T1-T2			T2-T3
影响路径	数学	英语	语文	数学	英语	语文
交叉滞后效应—开放性(t-1)作用于学习成绩(t)	0.11***	0.06**	0.09***	0.13***	0.06***	0.09***
交叉滞后效应—尽责性(t-1)作用于学习成绩(t)	?0.01	0.04	0.03	?0.01	0.04	0.03
交叉滞后效应—宜人性(t-1)作用于学习成绩(t)	0.03	0.02	0.04	0.05	0.03	0.06
交叉滞后效应—外向性(t-1)作用于学习成绩(t)	?0.01	?0.03	0.02	?0.01	?0.03	0.02
交叉滞后效应—情绪稳定性(t-1)作用于学习成绩(t)	?0.03	?0.02	0.01	?0.04	?0.02	0.01
交叉滞后效应—智力(t1)作用于学习成绩(t)	0.10***	0.05**	0.02	0.07**	0.05**	0.06*
交互作用-智力(t1)与开放性人格(t)交互作用于学业成绩(t)	?0.05*	?.01	?0.12***	?0.06*	?0.01	?0.13***

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