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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- 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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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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DOI: https://doi.org/10.1007/s10639-019-09884-5