Construction and initial validation of the Home Learning Environment Scale: an exploratory study
DOI:
https://doi.org/10.22399/ijcesen.2117Keywords:
Home Learning Environment Scale, Exploratory Factor Analysis, Social Learning TheoryAbstract
The purpose of this study is to develop a set of scientific and valid home learning environment scales to provide a quantitative tool for related research and practice. Based on social learning theory, this study modified the design of the questionnaire from previous studies and invited experts to review and evaluate the content of the items to ensure content validity. Through two pretests, the first with a sample size of 54 for initial exploration and the second with a sample size of 494 for in-depth validation, the performance of the scale was assessed using exploratory factor analysis, reliability analysis, descriptive analysis, discriminant analysis, and structural equation modeling. The results showed that the scale reliability and validity of the final five retained items were good and could measure the home learning environment more accurately. However, the study has problems such as incomplete dimension coverage, sample limitation and single method. Future research could expand the dimensions of the scale, enlarge the sample range, and combine multiple research methods. The scale developed in this study makes up for the shortcomings of the existing scales and is of great significance in promoting the research and optimization of the home learning environment.
References
[1] Amirhossein, H., Sebastian, B., Philipp, S., Paweł, Z., Patryk, C., & Núria, C. (2023). Low-cost sensors and Machine Learning aid in identifying environmental factors affecting particulate matter emitted by household heating. Atmospheric Environment. 314. https://doi.org/10.1016/j.atmosenv.2023.120108
[2] Burston, A., Puckering, C., & Kearney, E. (2005). At HOME in Scotland: validation of the home observation for measurement of the environment inventory. Child: Care, Health and Development. 31(5);533-538. https://doi.org/10.1111/j.1365-2214.2005.00546.x
[3] Berry, T. (2008). Pre-test assessment. American Journal of Business Education. 1(1);19-22. https://doi.org/10.19030/ajbe.v1i1.4633
[4] Brauchle, J., Unger, V., & Hochweber, J. (2025). Student wellbeing during COVID-19—Impact of individual characteristics, learning behavior, teaching quality, school system-related aspects and home learning environment. Frontiers in Education. 10;1518609-1518609. https://doi.org/10.3389/feduc.2025.1518609
[5] Chen, S. (2024). Research on Interactive Teaching of Ideological and Political Courses from the Perspective of Social Learning Theory. New Explorations in Education and Teaching. 2(12).
[6] Chee, K. N. (2024). Effectiveness of Computer Application in Improving Reading Skills in Chinese Language and Towards Post-Attitudes as Home-based Learning. Best Evidence in Chinese Education. 18(1). https://doi.org/10.15354/bece.24.or392
[7] Costa, A. R. (2025). Homing into school to create the ideal classroom: young people want to combine the best of home and school learning environments. CoDesign. 21(1);74-94. https://doi.org/10.1080/15710882.2024.2363925
[8] Ellis, A., O'Rear, C. D., Cosso, J., & Purpura, D. J. (2025). Examining the factor structure of the home learning environment. Journal of Experimental Child Psychology. 252;106186. https://doi.org/10.1016/j.jecp.2024.106186
[9] Emer, S., & Ivan, P. (2023). The long road to secondary school: background, home learning environment, and transition difficulties in Scotland. Research Papers in Education. 38(6);847-864. https://doi.org/10.1080/02671522.2022.2065520
[10] Giles, J. A., & Giles, D. E. (1993). Pre‐test estimation and testing in econometrics: recent developments. Journal of Economic Surveys. 7(2);145-197. https://doi.org/10.1111/j.1467-6419.1993.tb00163.x
[11] Hooijdonk, V. C. F. M., Marieke, V. D. P. M., Vries, B. M., Matthijs, C., Behrooz, A. Z., Simons, C. J. P., et al. (2023). The association between clinical, sociodemographic, familial, and environmental factors and treatment resistance in schizophrenia: A machine-learning-based approach. Schizophrenia Research. 262;132-141. https://doi.org/10.1016/j.schres.2023.10.030
[12] Hawrot, A., & Nusser, L. (2025). How does the home learning environment contribute to private tutoring attendance? A study among Grade 8 students in Germany. Scandinavian Journal of Educational Research. 69(1);122-137. https://doi.org/10.1080/00313831.2023.2266707
[13] Hawrot, A., & Nusser, L. (2024). The home environment during the COVID-19 pandemic and changes in learning enjoyment and learning effort: A study of German lower secondary school students. Children and Youth Services Review. 158;107481. https://doi.org/10.1016/j.childyouth.2024.107481
[14] Guo, Y., Yang, S., Boonyamalik, P., Powwattana, A., Zhu, W., & Xu, L. (2025). Development of a social learning theory-based pressure injury training program for nursing assistants in Chinese nursing homes. Frontiers in Public Health. 12;1478147-1478147. https://doi.org/10.3389/fpubh.2024.1478147
[15] Gangi, S. D., Senn, O., & Plate, A. (2024). Family Medicine Practice as Learning Environment: A Medical Student Evaluation in Switzerland. Advances in Medical Education and Practice. 15;1255-1270. https://doi.org/10.2147/amep.s492834
[16] Hartley, J. (1973). The effect of pre-testing on post-test performance. Instructional Science. 2(2);193-214. https://doi.org/10.1007/bf00139871
[17] Liu, S., Zhou, Y., Zhong, W., Zhang, L., Lai, Y., & Du, B. (2025). Analysis of Positive Parenting Styles Among Rural Primary School Students' Parents: A Case Study of Qingxi Village, Fujian Province. Humanities and Social Science Research. 8(1);123-123. https://doi.org/10.30560/hssr.v8n1p123
[18] Li, H., Fu, T., & Zhou, X. (2023). The Influence of Family Learning Environment on Preschool Children's Social Adaptability: The Mediating Role of Learning Quality. Frontiers in Educational Research. 6(30). https://doi.org/10.25236/fer.2023.063013
[19] Lu, P., & Li, Y. (2025). Agent-based fire evacuation model using social learning theory and intelligent optimization algorithms. Reliability Engineering and System Safety. 260; 111000. https://doi.org/10.1016/j.ress.2025.111000
[20] Lyimo, A. J. (2023). Understanding How Home Conditions Shape Early Grade Learners Literacy Acquisition Skills: A Tanzanian Perspective. Asian Journal of Education and Social Studies. 49(4);265-277. https://doi.org/10.9734/ajess/2023/v49i41206
[21] Monn, E., Beavis, H. S., & McComas, J. J. (2024). Social Communication During Play Across Language Environments in Nonvocal Preschool-Age Children with ASD from English and Non-English Speaking Families. Journal of Behavioral Education. 1-22. https://doi.org/10.1007/s10864-024-09574-4
[22] Nelson, G., Carter, H., Boedeker, P., & Tuin, M. V. (2024). Investigating measurement of the home learning environment in early math intervention studies. Learning Environments Research. 27(3);1-16. https://doi.org/10.1007/s10984-024-09513-0
[23] Pietropoli, H., & Gracia, P. (2025). Social inequalities in children's cognitive and socioemotional development: The role of home learning environments and early childhood education. Research in Social Stratification and Mobility. 97;101034-101034. https://doi.org/10.1016/j.rssm.2025.101034
[24] Popa, D., Pop, F., Serbanescu, C., & Castiglione, A. (2024). Retraction Note: Deep learning model for home automation and energy reduction in a smart home environment platform. Neural Computing and Applications. 1-1. https://doi.org/10.1007/s00521-024-10345-5
[25] Park, Y. R., Duhon, M., Kwon, K. A., Beisly, A. H., Walker, M., & Miguel, E. (2025). Parent psychological well-being, home learning environment, and child development among Kenyan families. Journal of Applied Developmental Psychology. 97;101760-101760. https://doi.org/10.1016/j.appdev.2025.101760
[26] Ren, J., Wang, M., Zhang, X., Romeo, R., & Arciuli, J. (2025). Statistical learning as a buffer: Investigating its impact on the link between home environment and reading achievement. Journal of Experimental Child Psychology. 253;106201. https://doi.org/10.1016/j.jecp.2025.106201
[27] Rivera, H. H., Chang, H., Zhu, Y., Jimenez, D. D., Bemani, M., & Taheri, M. (2024). Examining the Home Learning Environment Practices for Emergent Bilinguals: Insights from Parental Survey. Education Sciences. 14(11);1152-1152. https://doi.org/10.3390/educsci14111152
[28] Raiyan Jahangir. (2023). CNN‐SCNet: A CNN net‐based deep learning framework for infant cry detection in household setting. Engineering Reports. 6(6). https://doi.org/10.1002/eng2.12786
[29] Schwartz, M., & Ragnarsdóttir, H. (2025). Model for home-preschool continuity in linguistically and culturally diverse settings. Frontiers in Psychology. 15; 1408452. https://doi.org/10.3389/fpsyg.2024.1408452
[30] Schaack, D., Le, V., & Setodji, C. M. (2013). Examining the factor structure of the Family Child Care Environment Rating Scale—Revised. Early Childhood Research Quarterly. 28(4);936-946. https://doi.org/10.1016/j.ecresq.2013.01.002
[31] Sonali, N., Banu, V. S., May, D. K., Margaret, S., Enrica, D., & Monica, M. L. (2024). Home learning environments and children's language and literacy skills: A meta-analytic review of studies conducted in low- and middle-income countries. Psychological Bulletin. 150(2);132-153. https://doi.org/10.1037/bul0000417.supp
[32] Tian, G., Danton, B., Ewing, R., & Li, B. (2024). Varying influences of the built environment on household travel in the United States – An update with 36 diverse regions and machine learning. Cities. 155, 105490. https://doi.org/10.1016/j.cities.2024.105490
[33] Tao, J., Jin, F., Zhang, M., & C, Z. (2015). Validation of the Chinese version of the Family Environment Scale in the group of troubled adolescents. Chinese Journal of Clinical Psychology. 23(6);1024-1027. https://doi.org/10.16128/j.carol.carroll.nki.1005-3611.2015.06.015
[34] Venera, G., Qendresa, T., Mast, F. W., & Roebers, C. M. (2023). Foundations for future math achievement: Early numeracy, home learning environment, and the absence of math anxiety. Trends in Neuroscience and Education. 33, 100217. https://doi.org/10.1016/j.tine.2023.100217
[35] Widyaswari, M., & Fakhrudin, A. (2025). Integrating adaptive digital health and family education: A new approach to assessing psychomotor development in malnourished children. Journal of Clinical Neuroscience. 111186. https://doi.org/10.1016/j.jocn.2025.111186
[36] Wang, Y. (2016). Revision of the Chinese version of the Family Environment Scale and its application in New recruits with performing personality Tendency [Master's thesis, Guilin Medical College]. https://doi.org/10.27806/d.cnki.gglyx.2016.000001
[37] Wang, K., & Ogawa, K. (2024). Exploring the Trajectory of Home Learning Environment for Preschoolers in Bangladesh. Child & Youth Care Forum. 1-28. https://doi.org/10.1007/s10566-024-09834-4
[38] Xiao, W., Moncy, J. C., Woodham, R. D., Selvaraj, S., Lajmi, N., Hobday, H., & Fu, C. H. Y. (2025). Home-based transcranial direct current stimulation (tDCS) in major depressive disorder: Enhanced network synchronization with active relative to sham and deep learning-based predictors of remission. Personalized Medicine in Psychiatry. 49-50, 100147. https://doi.org/10.1016/j.pmip.2024.100147
[39] Xie, X., Wang, R., Fu, N., Ding, X., Liu, Z., Liu, X., & Zhang, Z. (2024). The relationships among family environment, teacher autonomy support and learning engagement in the context of home-based online learning among secondary school students during the COVID-19 pandemic: the mediating roles of psychological distress and learning motivation. Current Psychology. 44(1);1-17. https://doi.org/10.1007/s12144-024-07202-y
[40] Yu, E., Burns, S., Jegatheeswaran, C., & Perlman, M. (2025). Both Me and My Daughter Would Cry Sometimes: Parents' and Children's Experiences with Home Education During the Early and Later COVID-19 Pandemic. Early Childhood Education Journal. 1-21. https://doi.org/10.1007/s10643-025-01887-x
[41] Yang, C., Cai, R., Huang, W., Vijayaratnam, P. A., Wider, W., Udang, L. N., et al. (2024). Influence of Home Environment on Chinese Overseas Students' English Learning. Forum for Linguistic Studies. 6(5). https://doi.org/10.30564/fls.v6i5.6817
[42] Yang, Z. (2025). On the Role of Translators of Children's Literature from the Perspective of Social Learning Theory: A Case Study of Charlie and the Chocolate Factory. Frontiers in Educational Research. 8(1). https://doi.org/10.25236/fer.2025.080104
[43] Yunus, R. M., & Khan, S. (2011). Increasing the Power of the Test Through Pre-Test–A Robust Method. Communications in Statistics-Theory and Methods. 40(4);581-597. https://doi.org/10.1080/03610920903350572
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 International Journal of Computational and Experimental Science and Engineering

This work is licensed under a Creative Commons Attribution 4.0 International License.