A semantic-rich framework for learning software patterns

被引:0
|
作者
Jeremic, Zoran [1 ]
Jovanovic, Jelena [1 ]
Gasevic, Dragan [2 ]
机构
[1] Univ Belgrade, FON School Business Adm, Belgrade 11001, Serbia
[2] Athabasca Univ, Sch Comp & Informat Syst, Athabasca, AB, Canada
关键词
D O I
10.1109/ICALT.2008.258
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Current approaches to learning software patterns are based on individual use of different learning systems and tools. With this 'fragmented' approach it is very hard to provide support for context-aware learning and offer personalized learning experience to students. In this paper, we propose a new approach to learning software patterns that integrates existing Learning Management Systems, domain specific tools for software modeling and relevant online repositories of software patterns into a complex learning framework that supports collaborative learning. This framework is based on the semantic web technologies.
引用
收藏
页码:120 / +
页数:2
相关论文
共 50 条
  • [1] Towards a Semantic-Rich Collaborative Environment for Learning Software Patterns
    Jeremic, Zoran
    Jovanovic, Jelena
    Gasevic, Dragan
    TIMES OF CONVERGENCE: TECHNOLOGIES ACROSS LEARNING CONTEXTS, PROCEEDINGS, 2008, 5192 : 155 - +
  • [2] Towards semantic-rich word embeddings
    Beringer, Grzegorz
    Jablonski, Mateusz
    Januszewski, Piotr
    Sobecki, Andrzej
    Szymanski, Julian
    PROCEEDINGS OF THE 2019 FEDERATED CONFERENCE ON COMPUTER SCIENCE AND INFORMATION SYSTEMS (FEDCSIS), 2019, : 273 - 276
  • [3] Semantic-Rich Facial Emotional Expression Recognition
    Chen, Keyu
    Yang, Xu
    Fan, Changjie
    Zhang, Wei
    Ding, Yu
    IEEE TRANSACTIONS ON AFFECTIVE COMPUTING, 2022, 13 (04) : 1906 - 1916
  • [4] Semantic-rich Markov Models for Web Prefetching
    Mabroukeh, Nizar R.
    Ezeife, C. I.
    2009 IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOPS (ICDMW 2009), 2009, : 465 - 470
  • [5] A semantic-rich similarity measure in heterogeneous information networks
    Zhou, Yu
    Huang, Jianbin
    Li, He
    Sun, Heli
    Peng, Yan
    Xu, Yueshen
    KNOWLEDGE-BASED SYSTEMS, 2018, 154 : 32 - 42
  • [6] InteractNet: Social Interaction Recognition for Semantic-rich Videos
    Lyu, Yuanjie
    Qin, Penggang
    Xu, Tong
    Zhu, Chen
    Chen, Enhong
    ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS, 2024, 20 (08)
  • [7] Exploring Representations for Semantic-Rich Part of Speech Tagging
    Qu, Weidong
    Yue, Sicong
    PROCEEDINGS OF THE 2015 INTERNATIONAL INDUSTRIAL INFORMATICS AND COMPUTER ENGINEERING CONFERENCE, 2015, : 999 - 1002
  • [8] ECG Biometrics via Enhanced Correlation and Semantic-rich Embedding
    Wang, Kui-Kui
    Yang, Gong-Ping
    Yang, Lu
    Huang, Yu-Wen
    Yin, Yi-Long
    MACHINE INTELLIGENCE RESEARCH, 2023, 20 (05) : 697 - 706
  • [9] Building a semantic-rich service-oriented manufacturing environment
    Yang, ZH
    Zhang, JB
    Gay, R
    Zhuang, LQ
    Lee, HM
    WEB INFORMATION SYSTEMS ENGINEERING - WISE 2005, 2005, 3806 : 623 - 632
  • [10] Multi-label space reshape for semantic-rich label-specific features learning
    Cheng, Yusheng
    Zhang, Chao
    Pang, Shufang
    INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS, 2022, 13 (04) : 1005 - 1019