Language Education & Technology
Online ISSN : 2185-7814
Print ISSN : 2185-7792
ISSN-L : 2185-7792
Articles
Comparing Gap-Filling and Multiple-Choice Gloss Based on the Involvement Load Hypothesis:
A Bayesian Estimation of Homogeneity
Ryuya KOMURO
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JOURNAL OPEN ACCESS

2024 Volume 61 Pages 59-80

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Abstract
Laufer and Hulstijn (2001) proposed the involvement load hypothesis (ILH). The ILH assumes that incidental vocabulary learning activities are more effective when the combined involvement load index—need, search, and evaluation—is higher. According to the ILH, activities with identical involvement load indices should yield similar results in learning. The current study investigated this prediction using three activities: composition-level gap filling (CGF), sentence-level gap filling (SGF), and multiplechoice gloss (MCG). As these activities had equivalent involvement load indices, their effects were predicted to be the same. The null hypothesis significance testing merely confirms the absence of differences among the effects of the activities, rather than their equivalence. To address this limitation, this study employed Bayesian estimation. Fiftynine university students were randomly assigned to one of the CGF, SGF, and MCG tasks to learn five low-frequency nouns. Results revealed neither practical differences nor equivalence between the three tasks, showing that other variables, not included in the involvement load index, is influencing incidental vocabulary acquisition.
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© 2024 The Japan Association for Language Education and Technology
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