Comparison of Learning Content Representations to Improve L2 Vocabulary Acquisition Using m-learning

Jorge Rodríguez-Arce, Esteban Vázquez-Cano, Juan Pablo Cobá Juárez-Pegueros and Salvador González-García

SAGE Open, 2023, vol. 13, issue 4, 21582440231216819

Abstract: Previous works reveal that there is potential in the use of mobile devices as a useful tool to help learn new vocabulary and it allows the learning materials can be displayed with different Learning Content Representation (LCR) types. Nevertheless, there are no conclusive results about which LCR type is better to improve L2 vocabulary acquisition using m-learning. The purpose of this study was to explore the effects of improving the students’ academic performance using two LCR types that promote different learning strategies in a vocabulary learning task. A mobile application with two LCR types was implemented and tested: the SRL type based on a self-regulated learning strategy, and the NSRL type based on a non-self-regulated learning strategy. Quantitative analyses indicated that there is a relationship between the LCR types and the word recall on vocabulary learning. The SRL type seems to be effective in improving the students’ learning abilities and students in this experimental group exhibited significantly better academic performance. The results are meant to draw that LCR-SRL types must be used in m-learning to L2 vocabulary acquisition. Future studies should focus on how to integrate these strategies in m-learning and understand their effects on improving students’ vocabulary acquisition.

Keywords: word learning; vocabulary acquisition; learning content representations; self-regulated learning; m-learning (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:sae:sagope:v:13:y:2023:i:4:p:21582440231216819

DOI: 10.1177/21582440231216819

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