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Machine learning model to predict an adult learner’s decision to continue ESOL course

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Abstract

This study investigated the ability of the demographic and the affective variables to predict the adult learners’ decision to continue ESOL courser. 278 adult learners, enrolled on ESOL course at FLS institution in Istanbul, Turkey, participated in the study. The result showed that the continued or dropped out groups, demonstrated statistical differences in the demographic variable (the placement test score) with a magnitude of large effect size (.378). Additionally, the result showed the effect size in the perception of the affective variables (motivation, attitude, and anxiety), accounts for about 50% of the variation between the continuation and dropout groups. Following that, three machine learning models were proposed; all possible subset regression analysis was used to compare the three models. The adequate model, which fitted the demographic variable (the placement test score) and the affective variables (motivation, attitude, and anxiety), correctly predicted 83.3% of the adult learners’ decision to continue ESOL course. The model showed about 68% goodness-of-fit. The cultural implications of these findings are discussed, along with suggestions for future research.

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Abbreviations

L2:

Second Language

ESOL:

English for speakers of other languages

FLS:

Fatih Language School

AMTB:

Attitude Motivation Test Battery

FLCAS:

Foreign Language Learning Anxiety Scale

ML:

Machine Learning

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Acknowledgements

This study was supported by Semiha Sünnetci Dahman as the language editor and personal motivator. Ms. Havva Emre as the language translator. G. Tarcan KUMKALE, PhD and Prof Dr. Mustafa BAĞRIYANIK as committee advisors.

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Authors and Affiliations

  1. Faculty of Engineering and Natural Science, Kadir Has University, Cibali Mahallesi, Kadir Has Ünv., 34083, Fatih/İstanbul, Turkey

    Mohammed R. Dahman & Hasan Dağ

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  1. Mohammed R. Dahman
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  2. Hasan Dağ
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Corresponding author was responsible for the experimental work and paper authoring. co-author was responsible for setting the framework for the study, as well as supervising the research process.

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Correspondence to Mohammed R. Dahman.

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Dahman, M.R., Dağ, H. Machine learning model to predict an adult learner’s decision to continue ESOL course. Educ Inf Technol 24, 2429–2452 (2019). https://doi.org/10.1007/s10639-019-09884-5

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