Does Internet Entertainment Reduce the Cognitive Ability of Children? Evidence from the China Education Panel Survey
Abstract
:1. Introduction
2. Literature Review and Research Hypothesis
2.1. Internet Entertainment and Children’s Cognitive Ability
2.2. Heterogeneous Effects of Internet Entertainment in Different Family Environments
3. Methodology
3.1. Sample and Data Sources
3.2. Model
4. Results
4.1. Descriptive Statistics
4.2. Regression Results
4.3. Robustness Tests
4.3.1. Conducting the Robustness Test Based on Academic Performance
4.3.2. Using Panel Data to Conduct Robustness Tests
4.4. Influence Mechanism Analysis
4.5. Additional Analysis
5. Findings and Discussion
6. Implications and Limitations
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
Dimension | Variable | Explanation |
---|---|---|
Internet entertainment | Whether children use internet for entertainment | Yes = 1, No = 0 |
The weekly period of internet entertainment | Non-internet entertainment = 0, Only on weekends = 1, On both weekdays and weekends = 2 | |
Internet entertainment time | Average daily internet entertainment time during weekdays or weekends (unit: hours) | |
Cognitive ability | Cognitive score | Standardized scores on cognitive tests (using the 3PL model) |
Non-cognitive ability | Openness | React quickly, be able to learn new knowledge quickly and be curious about new things (four-level scale) |
Conscientiousness | Keep going to school and be able to do homework to the best of their ability (four scales) | |
Agreeableness | Be close and friendly to classmates or people around (four-level scale) | |
Family network | Internet at home | Whether there is internet at home? (Yes = 1, No = 0) |
Parents’ internet habits | Whether parents have internet habits after work? (Yes = 1, No = 0) | |
Parents’ internet supervision | Are parents very strict about children’s internet time? (Yes = 1, No = 0) | |
Family education | Father’s education | Years of father’s education background (unit: years) |
Mother’s education | Years of mother’s education background (unit: years) | |
Number of books at home | Few = 1, Relatively few = 2, Generally = 3, Relatively many = 4, Many = 5 | |
Parent’s reading habits | Whether parents have the reading habit after work? (Yes = 1, No = 0) | |
Family relationship | Parental company | Whether the children live with their parents? (Yes = 1, No = 0) |
Parental relationship | Whether parents maintain a good relationship? (Yes = 1, No = 0) | |
Family economic status | Family income | Very poor = 1, Relatively poor = 2, Medium = 3, Relatively rich = 4, Very rich = 5 |
Residential area | Central and marginal urban areas = 1, Towns and villages = 0 | |
Demographic characteristic | Gender | Male = 1, Female = 0 |
Age | Actual age by year of survey | |
Nationality | The Han nationality = 1, Others = 0 | |
Household registration | Non-agricultural registration = 1, Agricultural registration = 0 | |
Single child family | Yes = 1, No = 0 | |
School grade | Grade 9 = 1, Grade 7 = 0 | |
Health | Is your BMI normal? (Normal = 1, Underweight or overweight = 0) | |
School characteristics | School type | Whether it is a public school? (Yes = 1, Private and others = 0) |
References
- Barrow, L.; Markman, L.; Rouse, C.E. Technology’s edge: The educational benefits of computer-aided instruction. Am. Econ. J. 2009, 1, 52–74. [Google Scholar] [CrossRef]
- Malamud, O.; Pop-Eleches, C. Home computer use and the development of human capital. Q. J. Econ. 2011, 126, 987–1027. [Google Scholar] [CrossRef]
- Algan, Y.; Fortin, N.M. Computer gaming and the gender math gap: Cross-country evidence among teenagers: Work, occupation, earnings and retirement. In Transitions through the Labor Market; Emerald Publishing Limited: Bradford, UK, 2018; Volume 46, pp. 45–60. [Google Scholar] [CrossRef]
- Kuss, D.J.; Lopez-Fernandez, O. Internet addiction and problematic Internet use: A systematic review of clinical research. World J. Psychiatry 2016, 6, 143. [Google Scholar] [CrossRef] [PubMed]
- Ye, J.; Zhang, M. Where Will Left-behind Children be Taken by the Game? China Youth Daily, 7 January 2019; p. 6. Available online: https://mzqb.cyol.com/html/2019-01/07/content_260984.htm(accessed on 27 January 2019).
- Zheng, L.; Weng, Q.; Gong, X. Does preschool attendance affect the urban-rural cognition gap among middle school students? Evidence from China Education Panel Survey. J. Chin. Sociol. 2021, 8, 122–145. [Google Scholar] [CrossRef]
- Fang, C.; Wang, G.; Huang, B. Can information technology promote the development of students’ cognitive ability? Net effect estimation based on CEPS. Open Educ. Res. 2019, 25, 100–110. Available online: http://en.cnki.com.cn/Article_en/CJFDTotal-JFJJ201904012.htm (accessed on 27 August 2019).
- Akee, R.; Copeland, W.; Costello, E.J.; Simeonova, E. How does household income affect child personality traits and behaviors? Am. Econ. Rev. 2018, 108, 775–827. [Google Scholar] [CrossRef] [PubMed]
- Fang, G.; Hou, Y. How family socioeconomic status affects the cognitive development of junior high school students. Glob. Educ. Outlook 2019, 48, 68–76. [Google Scholar] [CrossRef]
- Donoso, G.; Casas, F.; Rubio, A.; Céspedes, C. Mediation of problematic use in the relationship between types of internet use and subjective well-being in schoolchildren. Front. Psychol. 2021, 12, 641178. [Google Scholar] [CrossRef]
- Jackson, L.A.; Von Eye, A.; Biocca, F.A.; Barbatsis, G.; Zhao, Y.; Fitzgerald, H.E. Does home internet use influence the academic performance of low-income children? Dev. Psychol. 2006, 42, 429. [Google Scholar] [CrossRef]
- Zheng, L.; Qi, X.; Zhu, Z.; Zhang, D.Q. Family Internet access and the cognitive gap between urban and rural junior high school students. Educ. Dev. Res. 2021, 41, 10–18. [Google Scholar] [CrossRef]
- Wang, J.N.; Zhang, Z. The influence of mobile Internet new media on the cognition and behavior of the second generation left behind children. New Media Res. 2019, 5, 9–11. [Google Scholar] [CrossRef]
- Kalenkoski, C.M.; Pabilonia, S.W. Time to work or time to play: The effect of student employment on homework, sleep, and screen time. Labour Econ. 2012, 19, 211–221. [Google Scholar] [CrossRef]
- Heckman, J.J. The economics, technology, and neuroscience of human capability formation. Proc. Natl. Acad. Sci. USA 2007, 104, 13250–13255. [Google Scholar] [CrossRef] [PubMed]
- Vigdor, J.L.; Ladd, H.F.; Martinez, E. Scaling the digital divide: Home computer technology and student achievement. Econ. Inq. 2014, 52, 1103–1119. [Google Scholar] [CrossRef]
- Ophir, E.; Nass, C.; Wagner, A.D. Cognitive control in media multitaskers. Proc. Natl. Acad. Sci. USA 2009, 106, 15583–15587. [Google Scholar] [CrossRef]
- Beuermann, D.W.; Cristia, J.; Cueto, S.; Malamud, O.; Cruz-Aguayo, Y. One laptop per child at home: Short-term impacts from a randomized experiment in Peru. Am. Econ. J. Appl. Econ. 2015, 7, 53–80. [Google Scholar] [CrossRef]
- Walsh, J.L.; Fielder, R.L.; Carey, K.B.; Carey, M.P. Female college students’ media use and academic outcomes: Results from a longitudinal cohort study. Emerg. Adulthood 2013, 1, 219–232. [Google Scholar] [CrossRef]
- Gentile, D.A. The multiple dimensions of video game effects. Child Dev. Perspect. 2011, 5, 75–81. [Google Scholar] [CrossRef]
- Cardoso-Leite, P.; Green, C.S.; Bavelier, D. On the impact of new technologies on multitasking. Dev. Rev. 2015, 35, 98–112. [Google Scholar] [CrossRef]
- Bulman, G.; Fairlie, R.W. Technology and education: Computers, software, and the Internet. In Handbook of the Economics of Education; Elsevier: Amsterdam, The Netherlands, 2016; Volume 5, pp. 239–280. [Google Scholar] [CrossRef] [Green Version]
- Vaala, S.E.; Bleakley, A. Monitoring, mediating, and modeling: Parental influence on adolescent computer and Internet use in the United States. J. Child. Media 2015, 9, 40–57. [Google Scholar] [CrossRef]
- Zou, H.; Jin, S.; Wu, S. The relationship between family economic status and Internet addiction among adolescents: The moderating effect of interpersonal relationship. Educ. Res. Exp. 2014, 2, 90–94. [Google Scholar]
- Deng, L.; Fang, X.; Wu, M.; Zhang, J.; Liu, Q. Family Environment, Parent-Child Attachment and Adolescent Internet Addiction. Psychol. Dev. Educ. 2013, 29, 305–311. [Google Scholar]
- Mathiesen, K. The Internet, children, and privacy: The case against parental monitoring. Ethics Inf. Technol. 2013, 15, 263–274. [Google Scholar] [CrossRef]
- Phillipson, S.; Phillipson, S.N. Academic expectations, belief of ability, and involvement by parents as predictors of child achievement: A cross-cultural comparison. Educ. Psychol. 2007, 27, 329–348. [Google Scholar] [CrossRef]
- Yang, C. Social class difference in education expectation: The relationship between social status and parental education expectation. Tsinghua Univ. Educ. Res. 2006, 4, 71–76+83. Available online: http://en.cnki.com.cn/Article_en/CJFDTOTAL-QHDJ200604011.htm (accessed on 27 January 2019).
- Biagi, F.; Loi, M. Measuring ICT use and learning outcomes: Evidence from recent econometric studies. Eur. J. Educ. 2013, 48, 28–42. [Google Scholar] [CrossRef]
- Frey, M.C.; Detterman, D.K. Scholastic assessment or g? the relationship between the scholastic assessment test and general cognitive ability. Psychol. Sci. 2004, 15, 641. [Google Scholar] [CrossRef]
- LePine, J.A. Team adaptation and postchange performance: Effects of team composition in terms of members’ cognitive ability and personality. J. Appl. Psychol. 2003, 88, 27–39. [Google Scholar] [CrossRef]
- Danovitch, J.H. Growing up with Google: How children’s understanding and use of internet-based devices relates to cognitive development. Human Behav. Emer. Tech. 2019, 2, 81–90. [Google Scholar] [CrossRef]
- Liang, W.Y.; Xiao-Mei, Y.E.; Tao, L.I. How does parental involvement affect the cognitive ability of migrant children:an empirical study based on CEPS database. J. Educ. Stud. 2018, 14, 1–11. Available online: http://en.cnki.com.cn/Article_en/CJFDTOTAL-XKJY201801013.htm (accessed on 25 February 2018).
- Billari, F.C.; Giuntella, O.; Stella, L. Broadband internet, digital temptations, and sleep. J. Econ. Behav. Organ. 2018, 153, 58–76. [Google Scholar] [CrossRef]
- Jiang, S.; Dong, L. Association between deprivation and cognitive ability among Chinese adolescents: Examining the mechanisms of parental involvement in a rural–urban dual system. Curr. Psychol. 2020, 7, 1–10. [Google Scholar] [CrossRef]
- Deci, E.L.; Ryan, R.M.; Williams, G.C. Need satisfaction and the self-regulation of learning. Learn. Individ. Differ. 1996, 8, 165–183. [Google Scholar] [CrossRef]
Variables | All Samples | Internet Entertainment | Non-Internet Entertainment | T-Test | |||
---|---|---|---|---|---|---|---|
Mean | S.D. | Mean | S.D. | Mean | S.D. | ||
Cognitive score | 0.124 | 0.837 | 0.160 | 0.836 | 0.045 | 0.832 | −0.115 *** |
Internet at home | 0.663 | 0.473 | 0.792 | 0.406 | 0.387 | 0.487 | −0.405 *** |
Parents’ internet habit | 0.624 | 0.484 | 0.704 | 0.457 | 0.456 | 0.498 | −0.248 *** |
Parents’ internet supervision | 0.652 | 0.476 | 0.597 | 0.491 | 0.769 | 0.422 | 0.171 *** |
Father’s education | 10.65 | 3.152 | 10.89 | 3.126 | 10.14 | 3.146 | −0.753 *** |
Mother’s education | 9.948 | 3.495 | 10.29 | 3.375 | 9.225 | 3.635 | −1.061 *** |
Number of books at home | 3.304 | 1.178 | 3.398 | 1.135 | 3.102 | 1.241 | −0.295 *** |
Parent’s reading habits | 0.749 | 0.434 | 0.783 | 0.413 | 0.677 | 0.468 | −0.106 *** |
Parental company | 0.871 | 0.335 | 0.881 | 0.324 | 0.851 | 0.357 | −0.030 *** |
Parental relationship | 0.85 | 0.357 | 0.844 | 0.363 | 0.863 | 0.344 | 0.019 ** |
Family income | 3.029 | 0.522 | 3.088 | 0.493 | 2.902 | 0.557 | −0.186 *** |
Residential area | 0.564 | 0.496 | 0.617 | 0.486 | 0.450 | 0.498 | −0.167 *** |
Gender | 0.488 | 0.500 | 0.512 | 0.500 | 0.434 | 0.496 | −0.078 *** |
Household registration | 0.479 | 0.500 | 0.518 | 0.500 | 0.395 | 0.489 | −0.123 *** |
Single-child family | 0.479 | 0.500 | 0.513 | 0.500 | 0.407 | 0.491 | −0.107 *** |
School grade | 0.496 | 0.500 | 0.486 | 0.500 | 0.519 | 0.500 | 0.033 *** |
Openness | 3.195 | 0.596 | 3.211 | 0.599 | 3.163 | 0.589 | −0.047 *** |
Conscientiousness | 3.345 | 0.655 | 3.307 | 0.665 | 3.425 | 0.626 | 0.117 *** |
Agreeableness | 3.185 | 0.681 | 3.193 | 0.674 | 3.167 | 0.695 | −0.026 * |
No. of observations | 10,934 | 7447 | 3487 | —— |
Variables | (1) | (2) | (3) | (4) |
---|---|---|---|---|
Internet entertainment | 0.028 * (0.016) | 0.002 (0.017) | ||
Internet entertainment on weekends | 0.089 *** (0.019) | 0.059 *** (0.02) | ||
Internet entertainment on weekdays and weekends | −0.024 (0.018) | −0.048 ** (0.019) | ||
Gender | 0.017 (0.015) | 0.028 * (0.015) | 0.014 (0.015) | 0.025 * (0.015) |
Age | −0.142 *** (0.011) | −0.122 *** (0.011) | −0.140 *** (0.011) | −0.120 *** (0.011) |
Ethnic group | 0.014 (0.035) | 0.015 (0.035) | 0.014 (0.035) | 0.015 (0.035) |
Household registration | 0.088 *** (0.018) | 0.017 (0.019) | 0.085 *** (0.018) | 0.015 (0.019) |
Single-child family | 0.046 ** (0.018) | 0.006 (0.018) | 0.042 ** (0.018) | 0.002 (0.018) |
School grade | 0.28 *** (0.027) | 0.249 *** (0.027) | 0.272 *** (0.027) | 0.242 *** (0.027) |
Health | 0.027 * (0.015) | 0.029 ** (0.015) | 0.026 * (0.015) | 0.028 * (0.015) |
Openness | 0.099 *** (0.014) | 0.079 *** (0.014) | 0.100 *** (0.014) | 0.080 *** (0.014) |
Conscientiousness | 0.044 *** (0.013) | 0.049 *** (0.013) | 0.040 *** (0.013) | 0.045 *** (0.013) |
Agreeableness | 0.067 *** (0.011) | 0.052 *** (0.011) | 0.065 *** (0.011) | 0.051 *** (0.011) |
Internet at home | 0.031 (0.020) | 0.032 (0.02) | ||
Parents’ internet habit | 0.018 (0.018) | 0.020 (0.018) | ||
Parents’ internet supervision | −0.002 (0.016) | −0.007 (0.015) | ||
Father’s education | 0.019 *** (0.003) | 0.019 *** (0.003) | ||
Mother’s education | 0.006 * (0.003) | 0.006 * (0.003) | ||
Number of books at home | 0.042 *** (0.008) | 0.042 *** (0.008) | ||
Parents’ reading habits | 0.043 ** (0.019) | 0.041 ** (0.019) | ||
Parental company | 0.039 * (0.022) | 0.037 * (0.022) | ||
Parental relationship | −0.015 (0.02) | −0.016 (0.02) | ||
Family income | −0.001 (0.016) | −0.0004 (0.015) | ||
Residential area | 0.045 ** (0.019) | 0.042 ** (0.019) | ||
School characteristics | YES | YES | YES | YES |
District fixed effect | YES | YES | YES | YES |
Adjusted R2 | 0.198 | 0.210 | 0.201 | 0.212 |
N | 10,934 | 10,934 | 10,934 | 10,934 |
Panel A: The Heterogeneous Effect in Different Family Internet Environments | ||||||
---|---|---|---|---|---|---|
Variables | (1) Internet at Home | (2) Parents’ Internet Habit | (3) Parents’ Internet Supervision | |||
Yes | No | Yes | No | Strict | Relaxed | |
Internet entertainment on weekends | 0.063 ** (0.025) | 0.069 ** (0.034) | 0.063 ** (0.025) | 0.073 ** (0.032) | 0.049 ** (0.023) | 0.073 ** (0.037) |
Internet entertainment on weekdays and weekends | −0.043 * (0.026) | −0.032 (0.031) | −0.033 (0.025) | −0.057 * (0.031) | −0.027 (0.023) | −0.083 ** (0.036) |
Adjusted R2 | 0.186 | 0.161 | 0.179 | 0.191 | 0.197 | 0.240 |
N | 7246 | 3688 | 6828 | 4106 | 7127 | 3807 |
Panel B: The Heterogeneous Effect in Different Family Characteristics | ||||||
Variables | (1) Parents’ Education | (2) Parents’ Relationship | (3) Residential Area | |||
High | Low | Good | Bad | City | Town and Rural Area | |
Internet entertainment on weekends | 0.116 *** (0.041) | 0.045 ** (0.022) | 0.085 *** (0.021) | −0.101 ** (0.05) | 0.071 *** (0.026) | 0.063 ** (0.03) |
Internet entertainment on weekdays and weekends | −0.006 (0.043) | −0.056 *** (0.022) | −0.031 (0.021) | −0.151 *** (0.049) | −0.037 (0.026) | −0.049 * (0.028) |
Adjusted R2 | 0.146 | 0.190 | 0.211 | 0.224 | 0.201 | 0.158 |
N | 2400 | 8534 | 9295 | 1639 | 6167 | 4767 |
Variables | QR_10 | QR_25 | QR_35 | QR_50 | QR_65 | QR_75 | QR_90 |
---|---|---|---|---|---|---|---|
Internet entertainment on weekends | 0.097 *** (0.034) | 0.046 * (0.027) | 0.023 (0.028) | 0.036 (0.027) | 0.067 ** (0.029) | 0.075 ** (0.031) | 0.059 * (0.035) |
Internet entertainment on weekdays and weekends | −0.053 (0.037) | −0.064 ** (0.028) | −0.077 *** (0.027) | −0.083 *** (0.026) | −0.050 * (0.027) | −0.041 (0.029) | −0.012 (0.033) |
Adjusted R2 | 0.082 | 0.132 | 0.136 | 0.140 | 0.138 | 0.129 | 0.084 |
N | 10,934 | 10,934 | 10,934 | 10,934 | 10,934 | 10,934 | 10,934 |
Variables | (1) Self-Rated Scores | (2) Chinese Scores | (3) Math Scores | (4) English Scores |
---|---|---|---|---|
Internet entertainment on weekends | 0.047 * (0.027) | 0.477 ** (0.222) | 0.751 *** (0.232) | 0.490 ** (0.23) |
Internet entertainment on weekdays and weekends | −0.136 *** (0.027) | −1.027 *** (0.224) | −1.384 *** (0.235) | −1.078 *** (0.225) |
Adjusted R2 | 0.045 | 0.133 | 0.056 | 0.131 |
N | 10,198 | 10,934 | 10,934 | 10,934 |
Variables | (1) | (2) | (3) | (4) | (5) |
---|---|---|---|---|---|
Matched Sample in Base Period | Matched Sample in Later Period | Mixed Section Data in Two Periods | Panel Data in Two Periods | Inter-Temporal Effect | |
Internet entertainment on weekends | 0.083 *** (0.031) | 0.132 *** (0.031) | 0.104 *** (0.022) | 0.073 *** (0.022) | 0.113 *** (0.026) |
Internet entertainment on weekdays and weekends | −0.050 * (0.03) | −0.059 ** (0.029) | −0.058 *** (0.021) | −0.036 * (0.02) | −0.098 *** (0.026) |
Year control | NO | NO | YES | YES | NO |
Adjusted R2 | 4783 | 4783 | 9566 | 9566 | 4783 |
N | 0.190 | 0.238 | 0.229 | 0.2312 | 0.240 |
Panel A: Cognitive effort | ||||
---|---|---|---|---|
Variables | (1) Higher Education Expectation | (2) Mathematics Is Helpful | (3) Chinese Is Helpful | (4) English Is Helpful |
Internet entertainment | −0.294 *** (0.038) | −0.074 *** (0.020) | −0.021 (0.019) | −0.046 ** (0.021) |
Internet entertainment on weekends | 0.189 *** (0.034) | 0.084 *** (0.019) | 0.039 ** (0.017) | 0.012 (0.019) |
Adjusted R2 | 0.185 | 0.139 | 0.106 | 0.157 |
N | 10,603 | 10,926 | 10,926 | 10,914 |
Panel B: Continuous learning and life attitude | ||||
Variables | (1) Always Late for Class | (2) Always Skip Class | (3) Feeling Life Is Boring | (4) Feeling Life Is Sad |
Internet entertainment | 0.080 *** (0.015) | 0.018 * (0.010) | 0.087 *** (0.026) | 0.045 * (0.026) |
Internet entertainment on weekends | −0.046 *** (0.014) | −0.012 (0.008) | −0.061 ** (0.024) | −0.066 *** (0.023) |
Adjusted R2 | 0.052 | 0.020 | 0.084 | 0.075 |
N | 10,929 | 10,925 | 10,934 | 10,934 |
Variables | (1) | (2) | (3) | (4) |
---|---|---|---|---|
Average weekly internet entertainment time | −0.009 *** (0.001) | |||
Daily internet entertainment time during weekdays | −0.061 *** (0.006) | −0.061 *** (0.007) | −0.060 *** (0.007) | |
Daily internet entertainment time on weekends | 0.0003 (0.005) | 0.028 ** (0.011) | ||
The square of daily internet entertainment time on weekends/100 | −0.444 *** (0.162) | |||
Adjusted R2 | 0.216 | 0.217 | 0.217 | 0.218 |
N | 10,934 | 10,934 | 10,934 | 10,934 |
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Hu, W.; Mao, Y.; Huang, K.; Sun, Y. Does Internet Entertainment Reduce the Cognitive Ability of Children? Evidence from the China Education Panel Survey. Behav. Sci. 2022, 12, 364. https://doi.org/10.3390/bs12100364
Hu W, Mao Y, Huang K, Sun Y. Does Internet Entertainment Reduce the Cognitive Ability of Children? Evidence from the China Education Panel Survey. Behavioral Sciences. 2022; 12(10):364. https://doi.org/10.3390/bs12100364
Chicago/Turabian StyleHu, Wenxin, Yufei Mao, Kevin Huang, and Yanqi Sun. 2022. "Does Internet Entertainment Reduce the Cognitive Ability of Children? Evidence from the China Education Panel Survey" Behavioral Sciences 12, no. 10: 364. https://doi.org/10.3390/bs12100364
APA StyleHu, W., Mao, Y., Huang, K., & Sun, Y. (2022). Does Internet Entertainment Reduce the Cognitive Ability of Children? Evidence from the China Education Panel Survey. Behavioral Sciences, 12(10), 364. https://doi.org/10.3390/bs12100364