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HOW CAN GENERATIVE AI BE ADAPTED FOR LEARNING CONTEXT SUPPORT IN CONTEXTUAL VOCABULARY ACQUISITION?

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Title: HOW CAN GENERATIVE AI BE ADAPTED FOR LEARNING CONTEXT SUPPORT IN CONTEXTUAL VOCABULARY ACQUISITION?
Authors: Hasnine, Mohammad Nehal1, Yamada, Mirai1, Akçapınar, Gökhan2
Source: Proceedings of the IADIS International Conference on Cognition & Exploratory Learning in Digital Age. 2024, p371-374. 4p.
Subject Terms: *Artificial intelligence, *Vocabulary, *Educational technology, *Educational innovations, ChatGPT
Abstract: Learning contexts play a crucial role in the acquisition of new vocabulary and its use in other contexts. Language learners use contextual clues, such as relevant expressions, small sentences, multimedia annotations, or images, to keep a learning context in memory. However, contextualizing vocabulary is exceedingly challenging even with multimedia contents, as learning contexts are very personal and involve learners making personal connections to the vocabulary. This paper explores how Generative Artificial Intelligence (GenAI) can foster learning context support for foreign language learners within multimedia-aided language learning frameworks. This paper introduces a new approach and a custom version of ChatGPT, Wordhyve-Glc, to assist language learners in constructing learning contexts for learning new vocabulary. Wordhyve-Glc also generates an image representing the learning context to be used as a contextual clue to memorize the learning context. Wordhyve-Glc will be integrated with Wordhyve, a multimedia-supported vocabulary learning app on Google Play, to foster contextual vocabulary acquisition. [ABSTRACT FROM AUTHOR]
Copyright of Proceedings of the IADIS International Conference on Cognition & Exploratory Learning in Digital Age is the property of International Association for Development of the Information Society (IADIS) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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  Data: Learning contexts play a crucial role in the acquisition of new vocabulary and its use in other contexts. Language learners use contextual clues, such as relevant expressions, small sentences, multimedia annotations, or images, to keep a learning context in memory. However, contextualizing vocabulary is exceedingly challenging even with multimedia contents, as learning contexts are very personal and involve learners making personal connections to the vocabulary. This paper explores how Generative Artificial Intelligence (GenAI) can foster learning context support for foreign language learners within multimedia-aided language learning frameworks. This paper introduces a new approach and a custom version of ChatGPT, Wordhyve-Glc, to assist language learners in constructing learning contexts for learning new vocabulary. Wordhyve-Glc also generates an image representing the learning context to be used as a contextual clue to memorize the learning context. Wordhyve-Glc will be integrated with Wordhyve, a multimedia-supported vocabulary learning app on Google Play, to foster contextual vocabulary acquisition. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Proceedings of the IADIS International Conference on Cognition & Exploratory Learning in Digital Age is the property of International Association for Development of the Information Society (IADIS) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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            – D: 01
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              Text: 2024
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