Iterative design of learning processes

被引:1
|
作者
Zarraonandia, Telmo [1 ]
Dodero, Juan Manuel [1 ]
Fernandez, Camino [1 ]
Aedo, Ignacio [1 ]
Diaz, Paloma [1 ]
机构
[1] Univ Carlos III Madrid, Dept Informat, Escuela Politecn Super, E-28903 Getafe, Spain
关键词
learning design; adaptation; runtime; iterative;
D O I
10.1007/978-1-4020-4914-9_15
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The aim of this work is to bring together the traditional way of teaching and working using a computer-supported environment. This means, increasing the flexibility of the learning processes application, giving instructors the chance to introduce variations on runtime. Besides, learning processes are refined through its use, by making permanent the modifications which have shown to improve the learners' performance on the different learning objectives. This approach is similar to the one followed for the development of user interfaces, where the interface design is obtained by an iterative process of prototyping, testing, analyzing and refining. This chapter describes the lifecycle of the iterative design of learning processes and proposes an architecture for implementing its runtime stages for processes described by means of the IMS Learning Design specification.
引用
收藏
页码:163 / +
页数:2
相关论文
共 50 条
  • [31] Iterative Learning Control Design for Switched Systems
    Pakshin, P. V.
    Emelianova, J. P.
    AUTOMATION AND REMOTE CONTROL, 2020, 81 (08) : 1461 - 1474
  • [32] Iterative Learning in Ballistic Control: Formulation of Spatial Learning Processes for Endpoint Control
    Xu, Jian-Xin
    Huang, Deqing
    JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME, 2013, 135 (02):
  • [33] Design of fuzzy iterative learning fault-tolerant control for batch processes with time-varying delays
    Wang, Limin
    Li, Bingyun
    Yu, Jingxian
    Zhang, Ridong
    Gao, Furong
    OPTIMAL CONTROL APPLICATIONS & METHODS, 2018, 39 (06): : 1887 - 1903
  • [34] Robust PD-type iterative learning control design for uncertain batch processes subject to nonrepetitive disturbances
    Maniarski, Robert
    Paszke, Wojciech
    Hao, Shoulin
    Tao, Hongfeng
    2022 41ST CHINESE CONTROL CONFERENCE (CCC), 2022, : 2266 - 2271
  • [35] Indirect iterative learning control design based on 2DOF IMC for batch processes with input delay
    Cui, Jiyao
    Wang, Zhihong
    Chen, Yueling
    Liu, Tao
    PROCEEDINGS OF THE 36TH CHINESE CONTROL CONFERENCE (CCC 2017), 2017, : 3587 - 3592
  • [36] Iterative learning fault-tolerant control for batch processes
    Wang, Youqing
    Shi, Jia
    Zhou, Donghua
    Gao, Furong
    INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2006, 45 (26) : 9050 - 9060
  • [37] Iterative Learning Control for Multiphase Batch Processes With Asynchronous Switching
    Wang, Limin
    Yu, Jingxian
    Zhang, Ridong
    Li, Ping
    Gao, Furong
    IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 51 (04): : 2536 - 2549
  • [38] Iterative learning reliable control of batch processes with sensor faults
    Wang, Youqing
    Zhou, Donghua
    Gao, Furong
    CHEMICAL ENGINEERING SCIENCE, 2008, 63 (04) : 1039 - 1051
  • [39] Nonlinear Monotonically Convergent Iterative Learning Control for Batch Processes
    Lu, Jingyi
    Cao, Zhixing
    Zhang, Ridong
    Gao, Furong
    IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2018, 65 (07) : 5826 - 5836
  • [40] Iterative Learning in Repetitive Optimal Control of Linear Dynamic Processes
    Rafajlowicz, Ewaryst
    Rafajlowicz, Wojciech
    ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING, ICAISC 2016, 2016, 9692 : 705 - 717