Time Series Forecasting of English Proficiency in Libya: A Longitudinal Analysis Using Education First Standard English Test

Authors

  • Mussa Omar Computer Science Department, Faculty of Computing and Information Technology, University of Ajdabiya, Ajdabiya, Libya

DOI:

https://doi.org/10.36602/ijeit.v14i2.634

Keywords:

english language proficiency, libya, time series analysis, education first standard english test (EF SET), longitudinal study.

Abstract

English proficiency has become increasingly important in non-English-speaking nations for professional, educational, and cultural development. However, there is a notable gap in the research on empirical trends in the development of English language proficiency in Libya. This study aims to conduct an overall assessment of English language proficiency levels in Libya and to forecast future trends by utilising time-series analysis to predict English proficiency levels over the coming decade. The study used data from the Education First Standard English Test to measure English proficiency in Libya. Advanced statistical techniques were used to analyse time series to forecast future proficiency levels and assess current proficiency levels. The analysis revealed the intricate relationships among systemic, pedagogical, and socio-cultural factors affecting English language acquisition in Libya. Time-series projections proved useful for developing insights into potential trends in expected proficiency development. The study aims to identify gaps in knowledge of English proficiency in Libya by providing empirical evidence and projecting future trends. The findings of this study emphasise the need for longitudinal studies and interventions to improve English language learning in the country's specific socio-cultural setting.

 

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References

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Published

2026-06-28

How to Cite

Time Series Forecasting of English Proficiency in Libya: A Longitudinal Analysis Using Education First Standard English Test. (2026). The International Journal of Engineering & Information Technology (IJEIT), 14(2), 211-218. https://doi.org/10.36602/ijeit.v14i2.634

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