{"title":"整合TAM和IS成功模型:探索区块链和人工智能在预测电子学习中学习者参与度和表现方面的作用","authors":"Damien Tyron Naidoo","doi":"10.3389/fcomp.2023.1227749","DOIUrl":null,"url":null,"abstract":"This study innovatively intertwines technology adoption and e-learning by integrating blockchain and AI, offering a novel perspective on how cutting-edge technologies revolutionize learning processes. The present study investigates the factors that influence the behavioral use of learners to use blockchain and artificial intelligence (AI) in e-learning. The study proposes the integrated model of Technology Acceptance Model (TAM) and Information System (IS) success Model that include perceived usefulness, perceived ease of use, system quality, information quality, and service quality as antecedents to behavioral use of blockchain and AI in e-learning. The model also examines the moderating effect of learner self-efficacy on the relationship between behavioral use and e-learning engagement and performance. The study collected data from 322 respondents and analyzed the data using partial least squares structural equation modeling (PLS-SEM) with a bootstrapping technique. The results show that the factors of TAM model and IS model have the significant and positive effects on behavior to use blockchain and AI in e-learning. Additionally, learner self-efficacy has a significant positive effect on e-learning engagement and performance, but it does not moderate the relationship between behavior to use blockchain or AI and e-learning engagement and performance. Overall, the study provides insights into the factors that influence the adoption of blockchain and AI in e-learning and offers practical implications for educators and policymakers.","PeriodicalId":52823,"journal":{"name":"Frontiers in Computer Science","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2023-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Integrating TAM and IS success model: exploring the role of blockchain and AI in predicting learner engagement and performance in e-learning\",\"authors\":\"Damien Tyron Naidoo\",\"doi\":\"10.3389/fcomp.2023.1227749\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study innovatively intertwines technology adoption and e-learning by integrating blockchain and AI, offering a novel perspective on how cutting-edge technologies revolutionize learning processes. The present study investigates the factors that influence the behavioral use of learners to use blockchain and artificial intelligence (AI) in e-learning. The study proposes the integrated model of Technology Acceptance Model (TAM) and Information System (IS) success Model that include perceived usefulness, perceived ease of use, system quality, information quality, and service quality as antecedents to behavioral use of blockchain and AI in e-learning. The model also examines the moderating effect of learner self-efficacy on the relationship between behavioral use and e-learning engagement and performance. The study collected data from 322 respondents and analyzed the data using partial least squares structural equation modeling (PLS-SEM) with a bootstrapping technique. The results show that the factors of TAM model and IS model have the significant and positive effects on behavior to use blockchain and AI in e-learning. Additionally, learner self-efficacy has a significant positive effect on e-learning engagement and performance, but it does not moderate the relationship between behavior to use blockchain or AI and e-learning engagement and performance. Overall, the study provides insights into the factors that influence the adoption of blockchain and AI in e-learning and offers practical implications for educators and policymakers.\",\"PeriodicalId\":52823,\"journal\":{\"name\":\"Frontiers in Computer Science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2023-09-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Frontiers in Computer Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3389/fcomp.2023.1227749\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Computer Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/fcomp.2023.1227749","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Integrating TAM and IS success model: exploring the role of blockchain and AI in predicting learner engagement and performance in e-learning
This study innovatively intertwines technology adoption and e-learning by integrating blockchain and AI, offering a novel perspective on how cutting-edge technologies revolutionize learning processes. The present study investigates the factors that influence the behavioral use of learners to use blockchain and artificial intelligence (AI) in e-learning. The study proposes the integrated model of Technology Acceptance Model (TAM) and Information System (IS) success Model that include perceived usefulness, perceived ease of use, system quality, information quality, and service quality as antecedents to behavioral use of blockchain and AI in e-learning. The model also examines the moderating effect of learner self-efficacy on the relationship between behavioral use and e-learning engagement and performance. The study collected data from 322 respondents and analyzed the data using partial least squares structural equation modeling (PLS-SEM) with a bootstrapping technique. The results show that the factors of TAM model and IS model have the significant and positive effects on behavior to use blockchain and AI in e-learning. Additionally, learner self-efficacy has a significant positive effect on e-learning engagement and performance, but it does not moderate the relationship between behavior to use blockchain or AI and e-learning engagement and performance. Overall, the study provides insights into the factors that influence the adoption of blockchain and AI in e-learning and offers practical implications for educators and policymakers.