{"title":"利用人工智能驱动的 Oyomi 应用程序,在独角鲸学习中丰富对日语语篇的语法理解","authors":"Nisrina Ishmah Mahira, Iswi Nur Pratiwi, Evlyn Jane Putri, Sevia Dwi Yanti, Najla Putri Afifah, Daffala Viro Hidayat, Husni Mubarok Ramadhan, Humannisa Rubina Lestari","doi":"10.47134/pjise.v1i2.2617","DOIUrl":null,"url":null,"abstract":"This research focuses on the impact of the Oyomi application on the comprehension of Japanese word classes (part of speech) and sentence structures. The primary issue addressed is the need for efficient and effective language learning tools. The objective is to explore the role of artificial intelligence (AI) within the application in enhancing Dokkai learning. The methodology encompasses a comprehensive analysis of the two principal features contributing to Dokkai learning, the utilization of AI technologies, and a comparison between traditional learning vs AI-powered mobile learning methods. Data collection involved simple linear regression statistical analysis using an F-test and correlation coefficient to gauge the relationship between the usage of the AI-powered Oyomi application and the comprehension of word classes in Dokkai learning. The F test results of 0.01 < 0.05 indicate a significant contribution and a correlation coefficient of 0.8 means the strength of the relationship is very strong. These findings show that AI, when integrated into language learning applications like Oyomi, can provide a more efficient and effective learning experience, especially in Japanese reading comprehension.","PeriodicalId":504384,"journal":{"name":"Journal of Internet and Software Engineering","volume":"23 12","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Enriching Grammatical Understanding of Using Japanese Part of Speech in Dokkai Learning with the AI-Powered Oyomi Application\",\"authors\":\"Nisrina Ishmah Mahira, Iswi Nur Pratiwi, Evlyn Jane Putri, Sevia Dwi Yanti, Najla Putri Afifah, Daffala Viro Hidayat, Husni Mubarok Ramadhan, Humannisa Rubina Lestari\",\"doi\":\"10.47134/pjise.v1i2.2617\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This research focuses on the impact of the Oyomi application on the comprehension of Japanese word classes (part of speech) and sentence structures. The primary issue addressed is the need for efficient and effective language learning tools. The objective is to explore the role of artificial intelligence (AI) within the application in enhancing Dokkai learning. The methodology encompasses a comprehensive analysis of the two principal features contributing to Dokkai learning, the utilization of AI technologies, and a comparison between traditional learning vs AI-powered mobile learning methods. Data collection involved simple linear regression statistical analysis using an F-test and correlation coefficient to gauge the relationship between the usage of the AI-powered Oyomi application and the comprehension of word classes in Dokkai learning. The F test results of 0.01 < 0.05 indicate a significant contribution and a correlation coefficient of 0.8 means the strength of the relationship is very strong. These findings show that AI, when integrated into language learning applications like Oyomi, can provide a more efficient and effective learning experience, especially in Japanese reading comprehension.\",\"PeriodicalId\":504384,\"journal\":{\"name\":\"Journal of Internet and Software Engineering\",\"volume\":\"23 12\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-06-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Internet and Software Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.47134/pjise.v1i2.2617\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Internet and Software Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47134/pjise.v1i2.2617","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Enriching Grammatical Understanding of Using Japanese Part of Speech in Dokkai Learning with the AI-Powered Oyomi Application
This research focuses on the impact of the Oyomi application on the comprehension of Japanese word classes (part of speech) and sentence structures. The primary issue addressed is the need for efficient and effective language learning tools. The objective is to explore the role of artificial intelligence (AI) within the application in enhancing Dokkai learning. The methodology encompasses a comprehensive analysis of the two principal features contributing to Dokkai learning, the utilization of AI technologies, and a comparison between traditional learning vs AI-powered mobile learning methods. Data collection involved simple linear regression statistical analysis using an F-test and correlation coefficient to gauge the relationship between the usage of the AI-powered Oyomi application and the comprehension of word classes in Dokkai learning. The F test results of 0.01 < 0.05 indicate a significant contribution and a correlation coefficient of 0.8 means the strength of the relationship is very strong. These findings show that AI, when integrated into language learning applications like Oyomi, can provide a more efficient and effective learning experience, especially in Japanese reading comprehension.