Mobile Applications for the Prediction of Learning Outcomes for Learning Strategies and Learning Achievement in Lifelong Learning

被引:4
作者
Nuankaew, Pratya [1 ]
Nuankaew, Wongpanya [2 ]
Phanniphong, Kanakarn [3 ]
Bussaman, Sittichai [4 ]
机构
[1] Univ Phayao, Sch Informat & Commun Technol, Mueang Phayao, Thailand
[2] Rajabhat Mahasarakham Univ, Fac Informat Technol, Mueang Maha Sarakham, Thailand
[3] Rajamangala Univ Technol, Fac Business Adm & Informat Technol, Tawan Ok, Si Racha, Thailand
[4] Rajabhat Mahasarakham Univ, Fac Sci & Technol, Mueang Maha Sarakham, Thailand
来源
TEACHING AND LEARNING IN A DIGITAL WORLD | 2018年 / 716卷
关键词
Learning strategies; Learning achievement; Lifelong learning; Data mining in education;
D O I
10.1007/978-3-319-73204-6_45
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In the age of the Internet and communication technology, changes in Technology Enhanced Learning (TEL) and Lifelong Learning Styles (LLS) are becoming a part of education and everyday life. The objectives of this paper were to develop a mobile application and provide perspectives for Learning Strategies (LS) and Learning Achievement (LA) in lifelong learning at the high school level in Maha Sarakham Province, Thailand. This research focused on the identification of the initial steps required to build academic achievement. Data collection was divided into two parts, comprised of (1) data sets for model analysis and application development from 668 students at Phadungnaree School in Maha Sarakham, and (2) data sets for application testing and level of satisfaction collected from 23 IT specialists and 72 general users at Rajabhat Mahasarakham University, Thailand. The research methodology consisted of five principal steps including (1) data collection, (2) model analysis, (3) model performance, (4) mobile application development, and (5) application implementation. The results from the model analysis showed that the research models displayed high accuracy equal to 94.51%. When developed as an association rule, the model could predict with increased accuracy equal to 98.35%. At the same time, the level of satisfaction for the developed applications was also high, equal to 4.61. Therefore, it could be concluded that this application is appropriate and reasonable for recommendation to interested parties in the future.
引用
收藏
页码:400 / 412
页数:13
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