Dataset on Enhancing Vocabulary Retention and Pronunciation Accuracy with AI-Driven Animated Characters: A Mixed-Methods Approach
Published: 29 October 2024| Version 1 | DOI: 10.17632/sk3n6hpypd.1
Contributors:
, , , Description
This dataset supports the study "Enhancing Vocabulary Retention and Pronunciation Accuracy through Personalized AI-Driven Animated Characters in Language Learning: A Mixed-Methods Approach". It includes quantitative and qualitative data from 150 participants who used the AI-driven character, ABIM, to improve vocabulary retention and pronunciation in Indonesian. The dataset covers metrics on engagement, perceived improvements, ease of use, and participant feedback on usability and challenges. This data is valuable for research on AI in education, language learning, and user experience in digital tools.
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Institutions
Universitas Negeri Yogyakarta, Universitas Negeri Padang
Categories
Artificial Intelligence, Educational Technology, Applied Linguistics, Language Learning, Mixed Research Method, User Experience