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.

图/表 7

表 1

表 2

表 3

图 1

图 2

图 3

表 4

参考文献 0

	Bollen, K. A., & Curran, P. J Autoregressive latent trajectory (alt) models a synthesis of two traditions Sociological Methods & Research 2004 32 336 383 Bollen, K. A., & Curran, P. J. (2004). Autoregressive latent trajectory (alt) models a synthesis of two traditions. Sociological Methods & Research, 32, 336—383.
	Brown, T. A. (2006). Confirmatory Factor Analysis for Applied Research. The Guilford Press: New York, NY, USA.
	Cheung, G. W., & Rensvold, R. B Evaluating goodness-of-fit indexes for testing measurement invariance Structural Equation Modeling 2002 9 233 255 Cheung, G. W., & Rensvold, R. B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modeling, 9, 233—255. doi: 10.1207/S15328007SEM0902_5
	Deary, I. J., Strand, S., Smith, P., & Fernandes, C Intelligence and educational achievement Intelligence 2007 35 13 21 Deary, I. J., Strand, S., Smith, P., & Fernandes, C. (2007). Intelligence and educational achievement. Intelligence, 35, 13—21. doi: 10.1016/j.intell.2006.02.001
	De Feyter, T., Caers, R., Vigna, C., & Berings, D Unraveling the impact of the Big Five personality traits on academic performance: The moderating and mediating effects of self-efficacy and academic motivation Learning and Individual Differences 2012 22 439 448 De Feyter, T., Caers, R., Vigna, C., & Berings, D. (2012). Unraveling the impact of the Big Five personality traits on academic performance: The moderating and mediating effects of self-efficacy and academic motivation. Learning and Individual Differences, 22, 439—448. doi: 10.1016/j.lindif.2012.03.013
	De Raad, B., & Schouwenburg, H. C Personality in learning and education: A review European Journal of Personality 1996 10 303 336 De Raad, B., & Schouwenburg, H. C. (1996). Personality in learning and education: A review. European Journal of Personality, 10, 303—336. doi: 10.1002/(SICI)1099-0984(199612)10:5<303::AID-PER262>3.0.CO;2-2
	Digman, J. M Five robust trait dimensions: Development, stability, and utility Journal of Personality 1989 57 195 214 Digman, J. M. (1989). Five robust trait dimensions: Development, stability, and utility. Journal of Personality, 57, 195—214. doi: 10.1111/j.1467-6494.1989.tb00480.x
	Eccles, J. S., Midgley, C., Wigfield, A., Buchanan, C. M., Reuman, D., Flanagan, C., & Mac Iver, D Development during adolescence: The impact of stage-environment fit on young adolescents’ experiences in schools and in families American Psychologist 1993 48 90 101 Eccles, J. S., Midgley, C., Wigfield, A., Buchanan, C. M., Reuman, D., Flanagan, C., & Mac Iver, D. (1993). Development during adolescence: The impact of stage-environment fit on young adolescents’ experiences in schools and in families. American Psychologist, 48, 90—101. doi: 10.1037/0003-066X.48.2.90
	Greiff, S., & Neubert, J. C On the relation of complex problem solving, personality, fluid intelligence, and academic achievement Learning and Individual Differences 2014 36 37 48 Greiff, S., & Neubert, J. C. (2014). On the relation of complex problem solving, personality, fluid intelligence, and academic achievement. Learning and Individual Differences, 36, 37—48. doi: 10.1016/j.lindif.2014.08.003
	Heaven, P. C. L., & Ciarrochi, J When IQ is not everything: Intelligence, personality and academic performance at school Personality and Individual Differences 2012 53 518 522 Heaven, P. C. L., & Ciarrochi, J. (2012). When IQ is not everything: Intelligence, personality and academic performance at school. Personality and Individual Differences, 53, 518—522. doi: 10.1016/j.paid.2012.04.024
	Heineck, G., & Anger, S. (2010). The returns to cognitive abilities and personality traits in Germany. EconStor Open Access Articles and Book Chapters.
	Hu, L. T., & Bentler, P. M Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives Structural Equation Modeling-a Multidisciplinary Journal 1999 6 1 55 Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling-a Multidisciplinary Journal, 6, 1—55. doi: 10.1080/10705519909540118
	Kim, L. E., Poropat, A. E., & MacCann, C. (2016). Conscientiousness in education: Its conceptualization, assessment, and utility. In A. A. Lipnevich, F. Preckel, & R. D. Roberts (Eds. ), Springer series on human exceptionality. Psychosocial skills and school systems in the 21st century: Theory, research, and practice (pp. 155−185). Switzerland: Springer.
	Klein, A., & Moosbrugger, H Maximum likelihood estimation of latent interaction effects with the lms method Psychometrika 2000 65 457 474 Klein, A., & Moosbrugger, H. (2000). Maximum likelihood estimation of latent interaction effects with the lms method. Psychometrika, 65, 457—474. doi: 10.1007/BF02296338
	Lechner, C., Danner, D., & Rammstedt, B How is personality related to intelligence and achievement? A replication and extension of Borghans et al. and Salkever Personality and Individual Differences 2017 111 86 91 Lechner, C., Danner, D., & Rammstedt, B. (2017). How is personality related to intelligence and achievement? A replication and extension of Borghans et al. and Salkever. Personality and Individual Differences, 111, 86—91. doi: 10.1016/j.paid.2017.01.040
	Little, T. D., Rhemtulla, M., Gibson, K., & Schoemann, A. M Why the items versus parcels controversy needn't be one Psychological Methods 2013 18 285 300 Little, T. D., Rhemtulla, M., Gibson, K., & Schoemann, A. M. (2013). Why the items versus parcels controversy needn't be one. Psychological Methods, 18, 285—300. doi: 10.1037/a0033266
	Lu, L., Weber, H. S., Spinath, F. M., & Shi, J Predicting school achievement from cognitive and non-cognitive variables in a Chinese sample of elementary school children Intelligence 2011 39 130 140 Lu, L., Weber, H. S., Spinath, F. M., & Shi, J. (2011). Predicting school achievement from cognitive and non-cognitive variables in a Chinese sample of elementary school children. Intelligence, 39, 130—140. doi: 10.1016/j.intell.2011.02.002
	Lubbers, M. J., van der Werf, M. P. C., Kuyper, H., & Hendriks, A. J. Does homework behavior mediate the relation between personality and academic performance? Learning and Individual Differences 2010 20 203 208 Lubbers, M. J., van der Werf, M. P. C., Kuyper, H., & Hendriks, A. J. (2010). Does homework behavior mediate the relation between personality and academic performance?. Learning and Individual Differences, 20, 203—208.
	Marsh, H. W. (2007). Self-concept theory, measurement and research into practice: The role of self-concept in educational psychology. Leicester, UK: British Psychological Society.
	Muthén, L. K. , & Muthén, B. O. (1998—2017). Mplus User’s Guide: 8th Edition. Los Angeles, CA: Muthén & Muthén.
	Poropat, A. E A meta-analysis of the five-factor model of personality and academic performance Psychological Bulletin 2009 135 322 338 Poropat, A. E. (2009). A meta-analysis of the five-factor model of personality and academic performance. Psychological Bulletin, 135, 322—338. doi: 10.1037/a0014996
	Raven, J. (1981). Manual for Raven’s Progressive Matrices and Mill Hill Vocabulary Scales. Oxford, UK: Oxford Psychologists Press.
	Revelle, W., & Zinbarg, R. E Coefficients alpha, beta, omega, and the glb: Comments on sijtsma Psychometrika 2009 74 145 154 Revelle, W., & Zinbarg, R. E. (2009). Coefficients alpha, beta, omega, and the glb: Comments on sijtsma. Psychometrika, 74, 145—154. doi: 10.1007/s11336-008-9102-z
	Richardson, M., Abraham, C., & Bond, R Psychological correlates of university students’ academic performance: A systematic review and meta-analysis Psychological Bulletin 2012 138 353 387 Richardson, M., Abraham, C., & Bond, R. (2012). Psychological correlates of university students’ academic performance: A systematic review and meta-analysis. Psychological Bulletin, 138, 353—387. doi: 10.1037/a0026838
	Rosander, P., Bäckström, M., & Stenberg, G Personality traits and general intelligence as predictors of academic performance: A structural equation modelling approach Learning and Individual Differences 2011 21 590 596 Rosander, P., Bäckström, M., & Stenberg, G. (2011). Personality traits and general intelligence as predictors of academic performance: A structural equation modelling approach. Learning and Individual Differences, 21, 590—596. doi: 10.1016/j.lindif.2011.04.004
	Roth, B., Becker, N., Romeyke, S., Schäfer, S., Domnick, F., & Spinath, F. M Intelligence and school grades: A meta-analysis Intelligence 2015 53 118 137 Roth, B., Becker, N., Romeyke, S., Schäfer, S., Domnick, F., & Spinath, F. M. (2015). Intelligence and school grades: A meta-analysis. Intelligence, 53, 118—137. doi: 10.1016/j.intell.2015.09.002
	Spinath, B., Freudenthaler, H., & Neubauer, A. C Domain-specific school achievement in boys and girls as predicted by intelligence, personality and motivation Personality and Individual Differences 2010 48 481 486 Spinath, B., Freudenthaler, H., & Neubauer, A. C. (2010). Domain-specific school achievement in boys and girls as predicted by intelligence, personality and motivation. Personality and Individual Differences, 48, 481—486. doi: 10.1016/j.paid.2009.11.028
	Taub, G. E., Keith, T. Z., Floyd, R. G., & Mcgrew, K. S Effects of general and broad cognitive abilities on mathematics achievement School Psychology Quarterly 2008 23 187 198 Taub, G. E., Keith, T. Z., Floyd, R. G., & Mcgrew, K. S. (2008). Effects of general and broad cognitive abilities on mathematics achievement. School Psychology Quarterly, 23, 187—198. doi: 10.1037/1045-3830.23.2.187
	Tweed, R. G., & Lehman, D. R Learning considered within a cultural context American Psychologist 2002 57 89 99 Tweed, R. G., & Lehman, D. R. (2002). Learning considered within a cultural context. American Psychologist, 57, 89—99.
	Tett, R. P., & Burnett, D. D. A personality trait-based interactionist model of job performance Journal of Applied Psychology 2003 88 500 517 Tett, R. P., & Burnett, D. D. (2003). A personality trait-based interactionist model of job performance. Journal of Applied Psychology, 88, 500—517.
	Vedel, A. , & Poropat, A. E. (2017). Personality and academic performance. In V. Zeigler-Hill, & T. Shackelford (Eds. ), Encyclopedia of personality and individual differences (pp. 1−9). Springer.
	Yao, R. S., & Liang, L. Y The application and analysis of NEO-FFI in Chinese college students Chinese Journal of Clinical Psychology 2010 18 457 459 Yao, R. S., & Liang, L. Y. (2010). The application and analysis of NEO-FFI in Chinese college students. Chinese Journal of Clinical Psychology, 18, 457—459.
	Zhang, J., & Ziegler, M Interaction effects between openness and fluid intelligence predicting scholastic performance Journal of Intelligence 2015 3 91 110 Zhang, J., & Ziegler, M. (2015). Interaction effects between openness and fluid intelligence predicting scholastic performance. Journal of Intelligence, 3, 91—110. doi: 10.3390/jintelligence3030091
	Ziegler, M., Danay, E., Heene, M., Asendorpf, J., & Bühner, M Openness, fluid intelligence, and crystallized intelligence: Toward an integrative model Journal of Research in Personality 2012 46 173 183 Ziegler, M., Danay, E., Heene, M., Asendorpf, J., & Bühner, M. (2012). Openness, fluid intelligence, and crystallized intelligence: Toward an integrative model. Journal of Research in Personality, 46, 173—183. doi: 10.1016/j.jrp.2012.01.002

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***

[1]	姜怡. 高中生学习动机发展模态及其对学业成绩的影响[J]. 华东师范大学学报(教育科学版), 2022, 40(11): 80-91.
[2]	雷浩, 李雪. 数字工具支持的教学对学生学习结果有何影响？——来自137项实验与准实验的元分析证据[J]. 华东师范大学学报(教育科学版), 2022, 40(11): 92-109.
[3]	成刚, 杜思慧, 余倩. “望子成龙”有效吗？——基于亲子教育期望偏差对学业成绩的影响研究[J]. 华东师范大学学报(教育科学版), 2022, 40(1): 74-87.
[4]	袁振国, 黄忠敬, 李婧娟, 张静. 中国青少年社会与情感能力发展水平报告[J]. 华东师范大学学报(教育科学版), 2021, 39(9): 1-32.
[5]	李佳哲, 胡咏梅. 家长学习参与和中小学生学业成绩的关系研究——基于亲子关系和学习自信心的有中介的调节模型分析[J]. 华东师范大学学报(教育科学版), 2021, 39(7): 72-83.
[6]	魏易, 罗滨, 林秀艳, 杨智君, 王梦. 区域教研对学生学业成绩影响的实证研究——以北京市海淀区为例[J]. 华东师范大学学报(教育科学版), 2021, 39(5): 12-54.
[7]	方超, 黄斌. 体育锻炼能够促进青少年的认知能力发展吗？——基于中国教育追踪调查数据的实证研究[J]. 华东师范大学学报(教育科学版), 2021, 39(3): 84-98.
[8]	胡咏梅, 元静. 学校投入与家庭投入哪个更重要？——回应由《科尔曼报告》引起的关于学校与家庭作用之争[J]. 华东师范大学学报(教育科学版), 2021, 39(1): 1-25.
[9]	曾昭炳, 姚继军. 寻找“最佳证据”：如何运用元分析进行文献综述——以STEM教育对学生成绩的影响研究为例[J]. 华东师范大学学报(教育科学版), 2020, 38(6): 70-85.
[10]	刘坚, 赵利曼, 杜宵丰, 徐冠兴. 高中生睡眠时间与高学业成绩的理想匹配模式探究及预警[J]. 华东师范大学学报(教育科学版), 2020, 38(3): 71-79.
[11]	唐一鹏, 王闯, 胡咏梅. 如何提升中小学生的学业成绩？——基于学习策略与教学策略改进的视角[J]. 华东师范大学学报(教育科学版), 2020, 38(3): 93-105.
[12]	赵晨, 陈思, 曹艳, [美]凯瑟琳·斯诺, 卢迈. 教育精准扶贫：“一村一园”计划对农村儿童学业成绩的长效影响研究[J]. 华东师范大学学报(教育科学版), 2020, 38(2): 114-125.
[13]	李永占. 幼儿教师工作家庭冲突对工作投入的影响：情绪智力的调节作用[J]. 华东师范大学学报(教育科学版), 2015, 33(4): 80-88.
[14]	1、周丽华, 2、李晓文, 2、乌阿茹娜. 动力系统观视野下的青少年发展研究[J]. 华东师范大学学报(教育科学版), 2012, 30(3): 55-59.
[15]	何安明, 刘华山, 惠秋平. 基于特质感恩的青少年感恩量表的编制 ——以自陈式量表初步验证感恩三维结构理论[J]. 华东师范大学学报(教育科学版), 2012, 30(2): 62-69.