{"title":"影响数字化个性化学习使用的因素","authors":"Noraisikin Sabani, Anita Jimmie, S. Salleh","doi":"10.1109/ICIET56899.2023.10111345","DOIUrl":null,"url":null,"abstract":"This study aims to explore the different factors that may influence undergraduates' behavioural intention to use digital technology to personalize their learning, both in formal and informal spheres. The data collection included a survey questionnaire, inculcating items relating to the respondents' demographic profiling, and twenty-two items based on The Unified Theory of Acceptance and Use of Technology 2 theoretical framework. The sampling involves 203 East Malaysian undergraduates studying in two public universities in Sabah. The findings indicated that the respondents are of various demographic profiling. In addition, factor analysis extraction indicated only 6 components of the 7 variables are deemed significant, based on Promax rotation. Multiple linear regression analysis showed only three factors significantly correlated to the behavioural intention of using digital learning personalization: performance expectancy, facilitating conditions and social influence.","PeriodicalId":332586,"journal":{"name":"2023 11th International Conference on Information and Education Technology (ICIET)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Factors Influencing the Use of Digital Learning Personalisation\",\"authors\":\"Noraisikin Sabani, Anita Jimmie, S. Salleh\",\"doi\":\"10.1109/ICIET56899.2023.10111345\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study aims to explore the different factors that may influence undergraduates' behavioural intention to use digital technology to personalize their learning, both in formal and informal spheres. The data collection included a survey questionnaire, inculcating items relating to the respondents' demographic profiling, and twenty-two items based on The Unified Theory of Acceptance and Use of Technology 2 theoretical framework. The sampling involves 203 East Malaysian undergraduates studying in two public universities in Sabah. The findings indicated that the respondents are of various demographic profiling. In addition, factor analysis extraction indicated only 6 components of the 7 variables are deemed significant, based on Promax rotation. Multiple linear regression analysis showed only three factors significantly correlated to the behavioural intention of using digital learning personalization: performance expectancy, facilitating conditions and social influence.\",\"PeriodicalId\":332586,\"journal\":{\"name\":\"2023 11th International Conference on Information and Education Technology (ICIET)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 11th International Conference on Information and Education Technology (ICIET)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIET56899.2023.10111345\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 11th International Conference on Information and Education Technology (ICIET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIET56899.2023.10111345","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Factors Influencing the Use of Digital Learning Personalisation
This study aims to explore the different factors that may influence undergraduates' behavioural intention to use digital technology to personalize their learning, both in formal and informal spheres. The data collection included a survey questionnaire, inculcating items relating to the respondents' demographic profiling, and twenty-two items based on The Unified Theory of Acceptance and Use of Technology 2 theoretical framework. The sampling involves 203 East Malaysian undergraduates studying in two public universities in Sabah. The findings indicated that the respondents are of various demographic profiling. In addition, factor analysis extraction indicated only 6 components of the 7 variables are deemed significant, based on Promax rotation. Multiple linear regression analysis showed only three factors significantly correlated to the behavioural intention of using digital learning personalization: performance expectancy, facilitating conditions and social influence.