Socioeconomic and Spatial Inequalities in English-Language Learning Opportunities in Bangladesh: A Harmonized Secondary-Data Synthesis

Sharmin Rahman Bipasha

doi:10.29407/jbsp.v10i2.29622

Authors

Sharmin Rahman Bipasha CCN University of Science & Technology https://orcid.org/0009-0009-8139-0437

DOI:

https://doi.org/10.29407/jbsp.v10i2.29622

Keywords:

bangladesh, english-language learning opportunity, secondary-data synthesis, socioeconomic inequality, spatial inequality

Abstract

Although English is a compulsory school subject in Bangladesh and is a key to higher education and job opportunities, it does not ensure equal opportunity to learn English. This research uses a cross-sectional secondary data synthesis (2017-2022) from four national secondary data sources: MICS 2019, the National Student Assessment, HIES 2022, and the BANBEIS school census to map national disparities in English-language learning opportunity (ELLO) across school, supplementary, and home domains. Five ELLO indicators (qualified English teacher, English-medium enrolment, private English tutoring, household internet-connected device, English reading materials at home) are thought of as enabling conditions, which proxy opportunity to learn, not as measures of instructional quality. Survey-weighted prevalence estimates, 95% confidence intervals and prevalence ratios were calculated by wealth quintile and residence and by gender (exploratory). The wealth gradients were large (Q5:Q1 ratios ranged from 6.3 to 57.4), and on all indicators, the prevalence of children in urban areas was higher than in rural areas, with the lowest prevalence consistently found in the poorest rural households. This trend is similar to what would be expected: Household-purchased resources are more unequally distributed than school-provided resources. Policy implications are related to equitable teacher deployment, learning support publicly provided, digital inclusion, and disaggregated monitoring of learning opportunity.

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References

Asadullah, M. N., & Bhattacharjee, A. (2022). Digital divide or digital provide? Technology, time use, and learning loss during COVID-19. The Journal of Development Studies, 58(10), 1934–1957. https://doi.org/10.1080/00220388.2022.2094253

Badiuzzaman, M., Rafiquzzaman, M., Rabby, M. I. I., & Rahman, M. M. (2021). The latent digital divide and its drivers in e-learning among Bangladeshi students during the COVID-19 pandemic. Information, 12(8), Article 287. https://doi.org/10.3390/info12080287

Bangladesh Bureau of Educational Information and Statistics. (2023). Bangladesh education statistics 2022. BANBEIS, Ministry of Education. https://banbeis.gov.bd/

Bangladesh Bureau of Statistics. (2023). Household income and expenditure survey (HIES) 2022: Final report. BBS, Ministry of Planning. https://bbs.gov.bd/

Bangladesh Bureau of Statistics, & UNICEF Bangladesh. (2019). Progotir Pathey, Bangladesh Multiple Indicator Cluster Survey 2019: Survey findings report. BBS & UNICEF Bangladesh. https://www.unicef.org/bangladesh/en/reports/progotir-pathey-bangladesh

Bray, M. (2023). Shadow education in Asia and the Pacific: Features and implications of private supplementary tutoring. In W. O. Lee, P. Brown, A. L. Goodwin, & A. Green (Eds.), International handbook on education development in the Asia-Pacific (pp. 159–181). Springer. https://doi.org/10.1007/978-981-19-6887-7_10

Chakraborty, T., & Bakshi, S. K. (2016). English language premium: Evidence from a policy experiment in India. Economics of Education Review, 50, 1–16. https://doi.org/10.1016/j.econedurev.2015.10.004

Directorate of Primary Education. (2023). The National Student Assessment 2022 in Bangladesh: Key findings and learnings. DPE, Ministry of Primary and Mass Education. https://research.acer.edu.au/ar_misc/70

Firdaus Umar, A. F., Yusuf, A., Amini, A. R., & Alhadi, A. (2023). Pengaruh motivasi belajar terhadap peningkatan prestasi akademik siswa [The influence of learning motivation on increasing student academic achievement]. Wacana: Jurnal Bahasa, Seni, dan Pengajaran, 7(2), 121–133. https://doi.org/10.29407/jbsp.v7i2.20670

General Economics Division. (2020). Making Vision 2041 a reality: Perspective Plan of Bangladesh 2021–2041. Bangladesh Planning Commission, Ministry of Planning. http://oldweb.lged.gov.bd/UploadedDocument/UnitPublication/1/1049/vision%202021-2041.pdf

Hamid, M. O. (2016). The linguistic market for English in Bangladesh. Current Issues in Language Planning, 17(1), 36–55. https://doi.org/10.1080/14664208.2016.1105909

Hamid, M. O., & Erling, E. J. (2016). English-in-education policy and planning in Bangladesh: A critical examination. In R. Kirkpatrick (Ed.), English language education policy in Asia (pp. 25–48). Springer. https://doi.org/10.1007/978-3-319-22464-0_2

Heeringa, S. G., West, B. T., & Berglund, P. A. (2017). Applied survey data analysis (2nd ed.). Chapman & Hall/CRC. https://doi.org/10.1201/9781315153278

Islam, M. N., & Inan, T. T. (2021). Exploring the fundamental factors of digital inequality in Bangladesh. SAGE Open, 11(2), Article 21582440211021407. https://doi.org/10.1177/21582440211021407

Islam, M. S., Hasan, M. K., Sultana, S., Karim, A., & Rahman, M. M. (2021). English language assessment in Bangladesh today: Principles, practices, and problems. Language Testing in Asia, 11, Article 1. https://doi.org/10.1186/s40468-020-00116-z

Mahmud, R. (2019). Mixed implications of private supplementary tutoring for students' learning: Urban and rural disparities in Bangladesh. International Journal of Comparative Education and Development, 21(1), 61–75. https://doi.org/10.1108/IJCED-05-2018-0008

Mahmud, R. (2021). Family socioeconomic determinants and students' demand for private supplementary tutoring in English in urban and rural Bangladesh. Education and Urban Society, 53(7), 831–851. https://doi.org/10.1177/0013124520974332

Mahmud, R., & Bray, M. (2017). School factors underlying demand for private supplementary tutoring in English: Urban and rural variations in Bangladesh. Asia Pacific Journal of Education, 37(3), 299–309. https://doi.org/10.1080/02188791.2017.1321525

Mahmud, R., & Kenayathulla, H. B. (2018). Shadow education: Patterns and scale of private supplementary tutoring in English in secondary education at urban Dhaka in Bangladesh. Compare: A Journal of Comparative and International Education, 48(5), 702–716. https://doi.org/10.1080/03057925.2017.1340827

Rahman, M. M., Islam, M. S., Karim, A., Chowdhury, T. A., Rahman, M. M., Seraj, P. M. I., & Singh, M. K. M. (2019). English language teaching in Bangladesh today: Issues, outcomes and implications. Language Testing in Asia, 9, Article 9. https://doi.org/10.1186/s40468-019-0085-8

Scheerens, J. (Ed.). (2017). Opportunity to learn, curriculum alignment and test preparation: A research review. Springer. https://doi.org/10.1007/978-3-319-43110-9

Schmidt, W. H., Burroughs, N. A., Zoido, P., & Houang, R. T. (2015). The role of schooling in perpetuating educational inequality: An international perspective. Educational Researcher, 44(7), 371–386. https://doi.org/10.3102/0013189X15603982

Van Buuren, S. (2018). Flexible imputation of missing data (2nd ed.). Chapman & Hall/CRC. https://doi.org/10.1201/9780429492259

Vania, E. P., & Rizal, M. A. S. (2024). Inovasi pendidikan: Menerapkan konsep inklusi dalam pembelajaran bahasa Indonesia untuk mewujudkan kemandirian dan keberagaman siswa [Educational innovation: Implementing the concept of inclusion in Indonesian language learning to achieve student independence and diversity]. Wacana: Jurnal Bahasa, Seni, dan Pengajaran, 8(1), 1–10. https://doi.org/10.29407/jbsp.v8i1.21511

Yang Hansen, K., & Strietholt, R. (2018). Does schooling actually perpetuate educational inequality in mathematics performance? A validity question on the measures of opportunity to learn in PISA. ZDM Mathematics Education, 50(4), 643–658. https://doi.org/10.1007/s11858-018-0935-3