An Empirical Study of Parents’ Participation Behavior in the Home-Based Online Learning of Primary School Students
Abstract
:1. Introduction
- What are the main internal and external factors that influence parents’ participation in the home-based online learning of primary school students?
- How do these factors affect parents’ behavioral intentions and actual participation behavior?
2. Literature Review and Research Hypotheses
2.1. Relationship between the Behavioral Attitude, Subjective Norm, Perceived Behavioral Control, and Behavioral Intention of Parents Participating in the Home-Based Online Learning of Primary School Students and Their Actual Participation Behavior
2.2. The Influence of Behavioral Belief and Result Evaluation of Parents Participating in the Home-Based Online Learning of Primary School Students on Behavioral Attitude
2.3. The Influence on the Subjective Norm of the Normative Belief and Obedience Motivation of Parents Participating in the Home-Based Online Learning of Primary School Students
2.4. The Influence of Parent Network Self-Efficacy and Family Network Conditions on Perceived Behavioral Control
3. Research Design
3.1. Research Framework
3.2. Research Samples and Collection Methods
3.3. Measuring Tools
4. Data Analysis
4.1. Descriptive Statistics
4.2. Measurement Model Evaluation
4.3. Structural Model Evaluation and Hypothesis Testing
5. Discussion
5.1. Objectives and Hypotheses That Have Been Achieved or Have Not Been Achieved with This Research
5.2. Main Findings of This Work
- The behavioral attitudes, subjective norms, and perceived behavioral control of parents participating in the home-based online learning of primary school students have significantly positive influences on participation behavior intention. This result is consistent with prior research [14,15].As for the order of influence on the behavioral intention of parents participating in the home-based online learning of primary school students, perceived behavioral control has the greatest influence, followed by subjective norms, and finally behavioral attitudes. This order of influence found in this study is different from that found in prior studies [15].
- The behavioral intention of parents participating in the home-based online learning of primary school students has a significantly positive influence on their actual participation behavior. This result is consistent with prior studies examining adults’ participation in online learning communities [32], which reflects the universal influence of behavioral intention on actual participation behavior;
- Behavioral belief is found to have a significantly positive influence on behavioral attitude. This finding is consistent with those of prior studies [20]. However, the result evaluation with regard to parents’ participation in the home-based online learning of primary school students has no evident influence on their behavioral attitude, and this finding is inconsistent with other research results to date [20];
- Normative belief and obedience motivation both have significantly positive influences on the subjective norm of parents participating in the home-based online learning of primary school students. In addition, the influence of normative belief clearly exceeds that of obedience motivation. This finding echoes the conclusions of prior studies [7], namely that school teachers and children have been found to play a key role in terms of communication and interaction in parents’ use of information technology at home;
- Parents’ network self-efficacy and conditions have an evident influence on the perceived behavioral control over their participation in children’s home-based online learning. These findings are consistent with the corresponding theoretical explanation provided by Taylor et al., which uses corresponding theoretical interpretation on the competitive model matching of information technology [26];
- The R-square value of each structural model has reached a moderate or high level of influence (see Table 6 for details). This verifies the high applicability of TPB to the issue of parents’ behavior of participating in the home-based online learning of primary school students.
5.3. The Implications of These Results in the Field of Study of the Research
5.4. Limitations of This Study
5.5. Future Lines of Research
6. Conclusions and Recommendations
Funding
Informed Consent Statement
Conflicts of Interest
References
- Li, Z.T. Post-Pandemic Era of Basic Education is the New Era of “Integration of Online and Offline Teaching”. J. Chin. Soc. Educ. 2020, 41, 5. [Google Scholar]
- Liu, J.; Qian, M.C.; Huang, Y.; Chen, W. An Analysis of Mediating Effect of Autonomous Learning in Network Learning Space of Primary and Secondary School Students. e-Educ. Res. 2018, 39, 59–65. [Google Scholar]
- Wang, Q.; Song, X.; Hong, J.C.; Li, S.; Zhang, M.; Yang, X. Impact of social comparison on perceived online academic futility: A perspective from parents. Educ. Inf. Technol. 2022, 1–28. [Google Scholar] [CrossRef] [PubMed]
- Davidson, G.V.; Ritchie, S.D. How do Attitudes of Parents, Teachers, and Students Affect the Integration of Technology into Schools? A Case Study; ERIC Database: Washington, DC, USA, 1994; pp. 161–172. [Google Scholar]
- Li, Y.; Hu, T.; Ge, T.; Auden, E. The relationship between home-based parental involvement, parental educational expectation and academic performance of middle school students in mainland china: A mediation analysis of cognitive ability—Science direct. Int. J. Educ. Res. 2019, 97, 139–153. [Google Scholar] [CrossRef]
- Zheng, Q.H.; Xu, J.Y. Students’ Online Learning Competency and Its Influencing Factors. Open Educ. Res. 2020, 26, 77–85. [Google Scholar]
- Olmstead, C. Using Technology to Increase Parent Involvement in Schools. TechTreads 2013, 57, 28–37. [Google Scholar] [CrossRef]
- An, G.Q.; Yang, Y. Differences in the Influence of Parental Involvement with Different Family Socioeconomic Stats on their Children’s Academic Achievements. Res. Educ. Dev. 2018, 39, 17–24. [Google Scholar]
- Plowman, L.; McPake, J. Seven Myths about Young Children and Technology. Child. Educ. 2013, 89, 27–33. [Google Scholar] [CrossRef] [Green Version]
- Ajzen, I. From Intentions to Actions: A Theory of Planned Behavior; Springer: Berlin/Heidelberg, Germany, 1985; pp. 11–39. [Google Scholar]
- Zhu, T.T.; He, Y. Analysis on the Status and Hotspot with Application of Theory of Planned Behavior Overseas and Domestic in Recent Ten Years. J. Nanjing Med. Univ. (Soc. Sci.) 2020, 21, 77–83. [Google Scholar]
- Ajzen, I. The Theory of Planned Behavior. Organ. Behav. Hum. Decis. Process 1991, 50, 179–211. [Google Scholar] [CrossRef]
- Scott, J. Consciousness on the Edge: The Intentional Nature of Experience. Sci. Conscious. Rev. 2003, 1, 1–7. [Google Scholar]
- Zhang, C.H.; Jiao, J.L. A Study on the Influencing Factors in Local University Undergraduates’ Acceptance of MOOCs. China Educ. Technol. 2015, 36, 64–68, 91. [Google Scholar]
- Xu, L.L.; Zhu, D.Q. An Empirical Study on the Acceptance of Network Learning Space among Vocational School Student. Tsinghua J. Educ. 2019, 40, 109–116. [Google Scholar]
- Wei, Y.M.; Fan, G.R. An Empirical Study on the Influencing Factors of Teachers’ Willingness to Participate in School Governance: Analysis Based on the Theory of Planned Behavior. J. East China Norm. Univ. (Educ. Sci.) 2021, 39, 73–82. [Google Scholar]
- Zhang, C.X. Educational Psychology; Zhejiang Education Publishing House: Hangzhou, China, 2003; p. 293. [Google Scholar]
- Bao, Q.W.; Gu, L.P.; Zhang, X.Y. Factors Influencing Open Research Data Behaviors: Earth Science Researchers’ Perspective. Inf. Stud. Theory Appl. 2019, 42, 51–57. [Google Scholar]
- Brogan, P. A Parent’s Perspective: Educating the Digital Generation. Educ. Leadersh. 2000, 58, 57–59. [Google Scholar]
- Tim, G.; Ortiz, R.W.; Lim, H.J. Korean Parents’ Perspectives on the Importance of Computer Usage for Themselves and Their Children: An Exploratory Study. Int. Electron. J. Elem. Educ. 2009, 1, 54–66. [Google Scholar]
- Chen, S.; Xu, G.T.; Zhang, S.J. Parents’ Attitudes and Influence Factors on Preschool Children’s Online Learning. Mod. Educ. Technol. 2019, 29, 101–107. [Google Scholar]
- Fishbein, M.; Ajzen, I. Belief, Attitude, Intention and Behaviour: An Introduction to Theory and Research. Addison-wesley, Reading Ma. Philos. Rhetor. 1977, 41, 842–844. [Google Scholar]
- Liu, J.; Liu, Q.M. The COVID-19 Broke the Comfort Zone of Family Education; China Youth Daily: Beijing, China, 2020; 2020-03-23(08). [Google Scholar]
- Correa, T. Acquiring a New Technology at Home: A Parent-child Study about Youths’ Influence on Digital Media Adoption in a Family. J. Broadcast. Electron. Media 2016, 60, 123–139. [Google Scholar] [CrossRef]
- Yan, Y. A Review on the Origins and Development of the Theory of Planned Behavior. Chin. J. Commun. 2014, 36, 113–129. [Google Scholar]
- Taylor, S.; Todd, P.A. Understanding Information Technology Usage: A Test of Competing Models. Inf. Syst. Res. 1995, 5, 91–108. [Google Scholar] [CrossRef]
- Bandura, A. Self-efficacy: Toward a Unifying Theory of Behavioral Change. Psychol. Rev. 1977, 84, 191–215. [Google Scholar] [CrossRef]
- Wang, C.; Gu, X.Q. The Promotion of OMO Education: Breaking Through the Predicament of Online Teaching by Taking Primary and Secondary School Students’ Participation Willingness of Online Learning as Penetration Point. Mod. Educ. Technol. 2022, 32, 72–80. [Google Scholar]
- Yee, A.Z.H.; Lwin, M.O.; Lau, J. Parental guidance and children’s healthy food consumption: Integrating the theory of planned behavior with interpersonal communication antecedents. J. Health Commun. 2019, 24, 183–194. [Google Scholar] [CrossRef] [PubMed]
- Justin, P.; Ashwin, M.; Jayesh, P. Predicting green product consumption using theory of planned behavior and reasoned action. J. Retail. Consum. Serv. 2016, 29, 123–134. [Google Scholar]
- Yadav, R.; Pathak, G.S. Determinants of Consumers’ Green Purchase Behavior in a Developing Nation: Applying and Extending the Theory of Planned Behavior. Ecol. Econ. 2017, 134, 114–122. [Google Scholar] [CrossRef]
- Yu, S.; Liu, F.Y. The Internal influence Mechanism of Adults’ Participation Willingness in Online Learning Community. Mod. Distance Educ. Res. 2018, 31, 86–94. [Google Scholar]
- Song, L.Q.; Xu, L.; Li, Y.X. Precision 0nline Teaching + Home Study Model: A Feasible Way to Improve the Quality of Study for Students during Epidemic. China Educ. Technol. 2020, 41, 114–122. [Google Scholar]
- Hong, J.C.; Juan, H.C.; Hung, W.C. The role of family intimacy in playing collaborative e-sports with a switch device to predict the experience of flow and anxiety during COVID-19 lockdown. Comput. Hum. Behav. 2022, 132, 107244. [Google Scholar] [CrossRef]
Category | Project | Sample Size | Percentage |
---|---|---|---|
Guardian completing survey | Mother | 383 | 77.5% |
Father | 111 | 22.5% | |
City | Shenzhen | 215 | 43.5% |
Dongguan | 133 | 26.9% | |
Huizhou | 146 | 29.6% |
Dimension | Examples of Measurement Questions | Source of References | Number of Questions | Cronbach α |
---|---|---|---|---|
Behavioral belief | I think children learning online is very important to improving their academic performance. | Fishbein, M. and Ajzen, I. (1977) [22] | 5 | 0.916 |
Result evaluation | I think online learning can broaden children’s horizons. | Chen S. et al. (2019) [21] Fishbein, M. and Ajzen, I. (1977) [22] | 3 | 0.872 |
Normative belief | Teachers at school require me to participate in my child’s online learning from home. | Fishbein, M.& Ajzen, I. (1977) [22] | 3 | 0.775 |
Obedience motivation | When I participate in my child’s online learning from home, I will consider my child’s ideas. | Ajzen, I. (1991) [12] Fishbein, M. and Ajzen, I. (1977) [22] | 3 | 0.706 |
Network self-efficacy | If I am willing to, I can solve most problems with Internet operation by myself. | Taylor, S. and Todd, P. A. (1995) [26] | 3 | 0.905 |
Network conditions | I often use electronic equipment to find information online. | Wang C. and Gu X. (2022) [28] | 3 | 0.718 |
Behavioral attitude | Parents should actively participate in their children’s home-based online learning. | Fishbein, M. and Ajzen, I. (1977) [22] Yee, A. Z. H. et al.(2019) [29] | 4 | 0.799 |
Subjective norm | Friends suggest that I participate in my child’s online learning from home. | Ajzen, I. (1991) [12] | 3 | 0.707 |
Perceived behavioral control | I believe I’m able to participate in my child’s home-based online learning. | Ajzen, I. (1991) [12] Justin P. et al. (2016) [30] | 6 | 0.869 |
Behavioral intention | I am strongly willing to participate in my child’s online learning from home. | Fishbein, M. and Ajzen, I. (1977) [22] Taylor, S. and Todd, P. A. (1995) [26] | 4 | 0.831 |
Participating behavior | I will actively participate in my child’s home-based online learning. | Brogan, P. (2000) [19] Yadav R. and Pathak G. S. (2017) [31] | 3 | 0.839 |
Dimension | Number of Remaining Questions | Reliability of Questions | Composite Reliability | Convergence Validity | |
---|---|---|---|---|---|
Factor Loading | SMC | CR | AVE | ||
Behavioral belief | 5 | 0.709–0.860 | 0.503–0.745 | 0.896 | 0.634 |
Result evaluation | 3 | 0.679–0.810 | 0.461–0.656 | 0.805 | 0.580 |
Normative belief | 3 | 0.570–0.751 | 0.325-0.564 | 0.670 | 0.407 |
Obedience motivation | 2 | 0.836–0.945 | 0.699–0.893 | 0.886 | 0.796 |
Network self-efficacy | 3 | 0.751–0.789 | 0.564–0.623 | 0.819 | 0.601 |
Network conditions | 2 | 0.620–0.650 | 0.384–0.423 | 0.575 | 0.403 |
Subjective norm | 3 | 0.741–0.894 | 0.549–0.799 | 0.880 | 0.711 |
Behavioral attitude | 4 | 0.684–0.903 | 0.468–0.815 | 0.900 | 0.695 |
Perceived behavioral control | 6 | 0.664–0.837 | 0.441–0.701 | 0.898 | 0.596 |
Behavioral intention | 4 | 0.775–0.856 | 0.601–0.733 | 0.887 | 0.664 |
Actual participating behavior | 2 | 0.889–0.893 | 0.790–0.797 | 0.885 | 0.794 |
Dimension | Convergence Validity | Discriminant Validity | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
AVE | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | |
1. Behavioral belief | 0.634 | 0.796 | ||||||||||
2. Result evaluation | 0.580 | 0.343 | 0.762 | |||||||||
3. Normative belief | 0.580 | 0.609 | 0.087 | 0.762 | ||||||||
4. Obedience motivation | 0.796 | 0.254 | 0.015 | 0.589 | 0.892 | |||||||
5. Network self-efficacy | 0.601 | 0.352 | 0.047 | 0.455 | 0.092 | 0.775 | ||||||
6. Network conditions | 0.403 | 0.659 | 0.180 | 1.063 | 0.747 | 0.265 | 0.635 | |||||
7. Subjective norm | 0.711 | 0.572 | 0.088 | 0.880 | 0.301 | 0.460 | 0.896 | 0.843 | ||||
8. Behavioral attitude | 0.695 | 0.752 | 0.333 | 0.448 | 0.185 | 0.258 | 0.492 | 0.421 | 0.834 | |||
9. Perceived behavioral control | 0.596 | 0.484 | 0.110 | 0.731 | 0.414 | 0.570 | 0.616 | 0.649 | 0.359 | 0.772 | ||
10. Behavioral intention | 0.664 | 0.512 | 0.115 | 0.723 | 0.333 | 0.475 | 0.673 | 0.721 | 0.416 | 0.770 | 0.815 | |
11. Actual participating behavior | 0.794 | 0.352 | 0.079 | 0.497 | 0.229 | 0.327 | 0.463 | 0.496 | 0.286 | 0.530 | 0.688 | 0.891 |
Estimation Method | χ2 | df | χ2/df | CFI | TLI | RMSEA | SRMR |
---|---|---|---|---|---|---|---|
ML | 1698.066 | 604 | 2.811 | 0.871 | 0.841 | 0.086 | 0.061 |
MLM | 1465.968 * | 604 | 2.427 | 0.902 | 0.861 | 0.076 | 0.061 |
Dependent Variable | Independent Variable | Estimate | S.E. | Z-Value | p-Value | R2 | Results |
---|---|---|---|---|---|---|---|
Behavioral intention | Behavioral attitude | 0.083 | 0.029 | 2.900 | ** | 0.683 | Consistent |
Subjective norm | 0.355 | 0.045 | 7.965 | *** | Consistent | ||
Perceived behavioral control | 0.510 | 0.039 | 13.242 | *** | Consistent | ||
Actual participation behavior | Behavioral intention | 0.688 | 0.030 | 22.594 | *** | 0.473 | Consistent |
Behavioral attitude | Behavioral belief | 0.723 | 0.035 | 20.848 | *** | 0.572 | Consistent |
Result evaluation | 0.085 | 0.047 | 1.815 | 0.069 | Inconsistent | ||
Subjective norm | Normative belief | 0.870 | 0.051 | 17.059 | *** | 0.848 | Consistent |
Obedience motivation | 0.335 | 0.064 | 5.253 | *** | Consistent | ||
Perceived behavioral control | Network self-efficacy | 0.437 | 0.052 | 8.366 | *** | 0.557 | Consistent |
Network conditions | 0.500 | 0.045 | 11.228 | *** | Consistent |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Li, P. An Empirical Study of Parents’ Participation Behavior in the Home-Based Online Learning of Primary School Students. Sustainability 2023, 15, 4562. https://doi.org/10.3390/su15054562
Li P. An Empirical Study of Parents’ Participation Behavior in the Home-Based Online Learning of Primary School Students. Sustainability. 2023; 15(5):4562. https://doi.org/10.3390/su15054562
Chicago/Turabian StyleLi, Peng. 2023. "An Empirical Study of Parents’ Participation Behavior in the Home-Based Online Learning of Primary School Students" Sustainability 15, no. 5: 4562. https://doi.org/10.3390/su15054562
APA StyleLi, P. (2023). An Empirical Study of Parents’ Participation Behavior in the Home-Based Online Learning of Primary School Students. Sustainability, 15(5), 4562. https://doi.org/10.3390/su15054562