Predictive Power of Involvement Load Hypothesis and Technique Feature Analysis across L2 Vocabulary Learning Tasks

Document Type: Research Paper

Authors

1 Department of English Language Teaching, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran: Department of English Language Teaching, Khouzestan Science and Research Branch, Islamic Azad University, Ahvaz, Iran

2 Department of English Language Teaching, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran

Abstract

Involvement Load Hypothesis (ILH) and Technique Feature Analysis (TFA) are two frameworks which operationalize depth of processing of a vocabulary learning task. However, there is dearth of research comparing the predictive power of the ILH and the TFA across second language (L2) vocabulary learning tasks. The present study, therefore, aimed to examine this issue across four vocabulary learning tasks (i.e., reading with glosses, keyword techniques, word card, and reading and finding the words in text) ranked differently by the ILH and the TFA. To this end, 80 English as a foreign language (EFL) learners were randomly assigned to one of four tasks of learning 16 target words. The results of one-way ANOVA, LSD Post hoc tests, and multiple regression analyses showed that the TFA had a better explanatory power than the ILH in predicting vocabulary learning gains. The findings highlight the TFA as a more powerful framework.

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