The Approach of Device Independence for Mobile Learning System

被引:3
|
作者
Pu Haitao [1 ]
Lin Jinjiao [2 ]
Song Yanwei [3 ]
Liu Fasheng [1 ]
机构
[1] Shandong Univ Sci & Technol, Dept Elect Engn & Informat Technol, Jinan 250031, Peoples R China
[2] Shandong Econ Univ, Sch Informat Management, Jinan 250014, Peoples R China
[3] Shandong Univ, Sch Comp Sci & Technol, Jinan 250001, Peoples R China
关键词
Mobile Learning; Context; Device Independence;
D O I
10.1109/ITIME.2009.5236356
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Mobile learning is transforming the way of tradition education. But most of e-learning system and contents are not suitable for mobile device. In order to provide suitable mobile learning services, the approach for self-adaptation is proposed in this paper. Firstly, the formal definitions of context and its influence on learning service, including NCxt, side S, weighing Q and adaptation coefficient E, are presented Then, using the approach, the mobile learning system is constructed The example implies this approach can detect the contextual environment of mobile computing and adapt the mobile learning service to the mobile learners' device automatically.
引用
收藏
页码:575 / +
页数:3
相关论文
共 50 条
  • [1] Providing device independence to mobile services
    Nylander, Stina
    Bylund, Markus
    Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 2003, 2615 : 465 - 473
  • [2] Providing device independence to mobile services
    Nylander, S
    Bylund, M
    UNIVERSAL ACCESS: THEORETICAL PERSPECTIVES, PRACTICE, AND EXPERIENCE, 2003, 2615 : 465 - 473
  • [3] Mobile Device Monitoring System in the Plant by an Innovative Approach
    Lian, Kuang-Yow
    Hsiao, Sung-Jung
    Sung, Wen-Tsai
    Chen, Jui-Ho
    APPLIED MECHATRONICS AND ANDROID ROBOTICS, 2013, 418 : 104 - +
  • [4] Deep Learning Approach for Estimating a Human Pose on a Mobile Device
    Moder, Martin
    Schellenbach, Michael
    AMBIENT INTELLIGENCE, AMI 2018, 2018, 11249 : 100 - 105
  • [5] Physics mobile learning with scaffolding approach in simple harmonic motion to improve student learning independence
    Tuada, R. N.
    Kuswanto, H.
    Saputra, A. T.
    Aji, S. H.
    5TH INTERNATIONAL SEMINAR ON SCIENCE EDUCATION, 2020, 1440
  • [6] A device-independent system architecture for adaptive mobile learning
    Zhao, Xinyou
    Okamoto, Toshio
    8TH IEEE INTERNATIONAL CONFERENCE ON ADVANCED LEARNING TECHNOLOGIES, PROCEEDINGS, 2008, : 23 - 25
  • [7] Constructing an Adaptive Mobile Learning System for the Support of Personalized Learning and Device Adaptation
    Huang, Ho-Chuan
    Wang, Tsui-Ying
    Hsieh, Fu-Ming
    12TH INTERNATIONAL EDUCATIONAL TECHNOLOGY CONFERENCE - IETC 2012, 2012, 64 : 332 - 341
  • [8] Data Transmission System for Mobile Device by Audio Hiding Approach
    Fang, Wen-Pinn
    Wang, Ran-Zan
    Liao, Tzu-Hsuan
    Chen, Shang-Kuan
    Lee, Yeuan-Kuen
    2014 TENTH INTERNATIONAL CONFERENCE ON INTELLIGENT INFORMATION HIDING AND MULTIMEDIA SIGNAL PROCESSING (IIH-MSP 2014), 2014, : 385 - 387
  • [9] Mobile Device Training Strategies in Federated Learning: An Evolutionary Game Approach
    Zou, Yuze
    Feng, Shaohan
    Niyato, Dusit
    Jiao, Yutao
    Gong, Shimin
    Cheng, Wenqing
    2019 INTERNATIONAL CONFERENCE ON INTERNET OF THINGS (ITHINGS) AND IEEE GREEN COMPUTING AND COMMUNICATIONS (GREENCOM) AND IEEE CYBER, PHYSICAL AND SOCIAL COMPUTING (CPSCOM) AND IEEE SMART DATA (SMARTDATA), 2019, : 874 - 879
  • [10] Mobile Activation Learning System Using Gamification Approach
    Emets, V. F.
    Rogowski, Jan
    Krasiukianis, Jacek
    ADVANCES IN INTELLIGENT SYSTEMS AND COMPUTING, CSIT 2016, 2017, 512 : 101 - 114