Machine Learning Support for Human Articulation of Concepts from Examples - A Learning Framework

被引:0
|
作者
Pavel, Gabriela [1 ]
机构
[1] Open Univ, Knowledge Media Inst KMi, Milton Keynes MK7 6AA, Bucks, England
关键词
concept learning; machine learning; visual environment; learning framework;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We aim to show that machine learning methods can provide meaningful feedback to help the student articulate concepts from examples, in particular from images. Therefore we present here a framework to support the learning through human visual classifications and machine learning methods.
引用
收藏
页码:80 / 84
页数:5
相关论文
共 50 条
  • [21] LEARNING DESIGN CONCEPTS USING MACHINE LEARNING TECHNIQUES
    MAHER, ML
    LI, H
    AI EDAM-ARTIFICIAL INTELLIGENCE FOR ENGINEERING DESIGN ANALYSIS AND MANUFACTURING, 1994, 8 (02): : 95 - 111
  • [22] The Power of Examples: Illustrative Examples Enhance Conceptual Learning of Declarative Concepts
    Rawson, Katherine A.
    Thomas, Ruthann C.
    Jacoby, Larry L.
    EDUCATIONAL PSYCHOLOGY REVIEW, 2015, 27 (03) : 483 - 504
  • [23] The Power of Examples: Illustrative Examples Enhance Conceptual Learning of Declarative Concepts
    Katherine A. Rawson
    Ruthann C. Thomas
    Larry L. Jacoby
    Educational Psychology Review, 2015, 27 : 483 - 504
  • [24] A Human-like Approach to Learning from Examples
    Remy, Sekou L.
    2014 IEEE 4TH ANNUAL INTERNATIONAL CONFERENCE ON CYBER TECHNOLOGY IN AUTOMATION, CONTROL, AND INTELLIGENT SYSTEMS (CYBER), 2014, : 37 - 42
  • [25] LEARNING FROM EXAMPLES - A REVIEW OF MACHINE LEARNING, NEURAL NETWORKS AND FUZZY-LOGIC PARADIGMS
    QUIROGA, LA
    RABELO, LC
    COMPUTERS & INDUSTRIAL ENGINEERING, 1995, 29 : 561 - 565
  • [26] Adaptive robust learning framework for twin support vector machine classification
    Ma, Jun
    Yang, Liming
    Sun, Qun
    KNOWLEDGE-BASED SYSTEMS, 2021, 211
  • [27] Machine Learning Prediction and Recommendation Framework to Support Introductory Programming Course
    Khan, Ijaz
    Ahmad, Abdul Rahim
    Jabeur, Nafaa
    Mahdi, Mohammed Najah
    INTERNATIONAL JOURNAL OF EMERGING TECHNOLOGIES IN LEARNING, 2021, 16 (17) : 42 - 59
  • [28] Enclosing machine learning: concepts and algorithms
    Xun-Kai Wei
    Ying-Hong Li
    Yu-Fei Li
    Dong-Fang Zhang
    Neural Computing and Applications, 2008, 17 : 237 - 243
  • [29] Machine learning and application of inaccurate concepts
    Han, Xi-Wu
    Zhao, Tie-Jun
    Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology, 2006, 38 (10): : 1736 - 1739
  • [30] Enclosing machine learning: concepts and algorithms
    Wei, Xun-Kai
    Li, Ying-Hong
    Li, Yu-Fei
    Zhang, Dong-Fang
    NEURAL COMPUTING & APPLICATIONS, 2008, 17 (03): : 237 - 243