{"title":"Factors Affecting the use of Smartphones for Learning: A Proposed Model","authors":"Sithembiso Dyubele, S. Soobramoney, D. Heukelman","doi":"10.1109/icABCD59051.2023.10220478","DOIUrl":null,"url":null,"abstract":"Increased functionalities of smartphones, such as providing easy access to the internet, have offered multiple learning opportunities, especially in a world surrounded by unprecedented periods like COVID'19. Despite the benefits of smartphones mentioned above, academics still have significant concerns about the effective utilisation of these technological devices by students for learning purposes. This paper aims to examine the factors affecting the use of smartphones for learning. The study utilised a quantitative method to pursue its aim and objectives. Data were gathered from 80 academic staff members from five Departments under the Faculty of Accounting & Informatics. A stratified sampling approach was applied to ensure a more realistic and accurate estimation of the population had been used. After applying the above approach, a simple random sampling method was used for this population according to the number of academic staff members in the above-mentioned departments. The data were analysed to ensure reliability and validity, and descriptive statistics were applied, and correlations identified to develop the proposed model. The outcomes indicate that academic staff members believe that Attitudes towards Smartphones, Facilitating Conditions, Perceived Ease of Use, Perceived Usefulness, and Performance Expectations significantly impact the use of smartphones for learning. This study was limited to academic staff from five departments of a single faculty at a South African University of Technology.","PeriodicalId":51314,"journal":{"name":"Big Data","volume":"1 1","pages":"1-7"},"PeriodicalIF":2.6000,"publicationDate":"2023-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Big Data","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1109/icABCD59051.2023.10220478","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Increased functionalities of smartphones, such as providing easy access to the internet, have offered multiple learning opportunities, especially in a world surrounded by unprecedented periods like COVID'19. Despite the benefits of smartphones mentioned above, academics still have significant concerns about the effective utilisation of these technological devices by students for learning purposes. This paper aims to examine the factors affecting the use of smartphones for learning. The study utilised a quantitative method to pursue its aim and objectives. Data were gathered from 80 academic staff members from five Departments under the Faculty of Accounting & Informatics. A stratified sampling approach was applied to ensure a more realistic and accurate estimation of the population had been used. After applying the above approach, a simple random sampling method was used for this population according to the number of academic staff members in the above-mentioned departments. The data were analysed to ensure reliability and validity, and descriptive statistics were applied, and correlations identified to develop the proposed model. The outcomes indicate that academic staff members believe that Attitudes towards Smartphones, Facilitating Conditions, Perceived Ease of Use, Perceived Usefulness, and Performance Expectations significantly impact the use of smartphones for learning. This study was limited to academic staff from five departments of a single faculty at a South African University of Technology.
Big DataCOMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-COMPUTER SCIENCE, THEORY & METHODS
CiteScore
9.10
自引率
2.20%
发文量
60
期刊介绍:
Big Data is the leading peer-reviewed journal covering the challenges and opportunities in collecting, analyzing, and disseminating vast amounts of data. The Journal addresses questions surrounding this powerful and growing field of data science and facilitates the efforts of researchers, business managers, analysts, developers, data scientists, physicists, statisticians, infrastructure developers, academics, and policymakers to improve operations, profitability, and communications within their businesses and institutions.
Spanning a broad array of disciplines focusing on novel big data technologies, policies, and innovations, the Journal brings together the community to address current challenges and enforce effective efforts to organize, store, disseminate, protect, manipulate, and, most importantly, find the most effective strategies to make this incredible amount of information work to benefit society, industry, academia, and government.
Big Data coverage includes:
Big data industry standards,
New technologies being developed specifically for big data,
Data acquisition, cleaning, distribution, and best practices,
Data protection, privacy, and policy,
Business interests from research to product,
The changing role of business intelligence,
Visualization and design principles of big data infrastructures,
Physical interfaces and robotics,
Social networking advantages for Facebook, Twitter, Amazon, Google, etc,
Opportunities around big data and how companies can harness it to their advantage.