Natural Language Processing (NLP) and EFL Learning: A Case Study Based on Deep Learning
DOI:
https://doi.org/10.17507/jltr.1501.22Keywords:
natural language processing, voice recognition device, deep learning, EFL learning, Saudi ArabiaAbstract
The enhancement of artificial intelligence (AI) and related machine learning represents one of many recent technological developments, causing educators to consider the potential of AI for teaching and learning. In this case study, opinions were gathered from six mature students of English as a foreign language (EFL) in a university in Saudi Arabia. The researcher especially explored the use of a voice recognition device (Amazon’s virtual assistant, Alexa) based on natural language processing (NLP) for deep learning. The participants were instructed to interact with Alexa individually for 30 minutes each, over the course of one week, including a game of ‘hide-and-seek’. Structured observations were performed of this activity, and semi-structured interviews were subsequently conducted to gather the participants’ opinions of the device. Main and sub-themes emerged from the results, related to deep learning through NLP. This theoretical perspective was adopted because Alexa was found to develop its voice recognition across different language structures and styles. Moreover, Alexa was very responsive to the participants, sometimes asking them to reword or modify their questions, so that it could find answers. The game also proved helpful for presenting the language, reflecting a real game of hide-and-seek. The participants mentioned that such technology could be useful in language labs, as it was fun, entertaining, convenient, and easy to use. It is therefore recommended to invest in these devices for learning activities in education. Furthermore, statistical studies are recommended to test the impact of voice recognition devices on teaching and learning for generalisable results.
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