Learning Object Recommendations for Teachers Based On Elicited ICT Competence Profiles

被引:26
作者
Sergis, Stylianos [1 ,2 ]
Sampson, Demetrios G. [2 ,3 ]
机构
[1] Univ Piraeus, Dept Digital Syst, GR-18532 Piraeus, Greece
[2] Ctr Res & Technol Hellas, Inst Informat Technol, Athens, Greece
[3] Curtin Univ, Sch Educ, Bentley, WA, Australia
来源
IEEE TRANSACTIONS ON LEARNING TECHNOLOGIES | 2016年 / 9卷 / 01期
关键词
Learning objects; personalized E-learning; web services; recommender systems; SYSTEMS; RESOURCES; MODEL;
D O I
10.1109/TLT.2015.2434824
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Recommender systems (RS) offer personalized services for facilitating the process of appropriate item selection. To perform this task, user profiling mechanisms should be implemented to automatically construct and update meaningful user profiles. These profiles can drive the RS in providing informed recommendations suited to the unique characteristics of each user. In the context of technology enhanced learning (TeL) Recommender Systems, the majority of research focus directly on learners' profiling and ignore the potential benefits of profiling teachers' professional capacities too. As a result, limited previous works exist on effectively capturing and utilizing individual teachers' particular professional characteristics, such as their Digital Competences (commonly referred to as ICT Competences) and exploiting these in systems that support their teaching preparation and practice, for example in the selection of appropriate educational resources. This paper proposes a RS which targets to support teachers in selecting learning objects (LO) from existing LO repositories (LORs) in a unified manner, namely by (a) automatically constructing their ICT Competence Profiles based on their actions within these LORs and (b) exploiting these profiles for more efficient LO selection. Experiments with data from three real-life LORs are presented and evaluation results are discussed to demonstrate the benefits of the proposed system.
引用
收藏
页码:67 / 80
页数:14
相关论文
共 72 条
  • [1] Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions
    Adomavicius, G
    Tuzhilin, A
    [J]. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2005, 17 (06) : 734 - 749
  • [2] Impact of Data Characteristics on Recommender Systems Performance
    Adomavicius, Gediminas
    Zhang, Jingjing
    [J]. ACM TRANSACTIONS ON MANAGEMENT INFORMATION SYSTEMS, 2012, 3 (01)
  • [3] Fuzzy-genetic approach to recommender systems based on a novel hybrid user model
    Al-Shamri, Mohammad Yahya H.
    Bharadwaj, Kamal K.
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2008, 35 (03) : 1386 - 1399
  • [4] Folksonomy-based fuzzy user profiling for improved recommendations
    Anand, Deepa
    Mampilli, Bonson Sebastian
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2014, 41 (05) : 2424 - 2436
  • [5] [Anonymous], 2001, WWW, DOI 10.1145/371920.372071
  • [6] [Anonymous], 2013, SpringerBriefs in electrical and computer engineering
  • [7] Athanasiadis N., 2014, Digital Systems for Open Access to Formal and Informal Learning, P11
  • [8] Avancini H., 2005, International Journal of Web Based Communities, V1, P163, DOI 10.1504/IJWBC.2005.006061
  • [9] Modeling users on the World Wide Web based on cognitive factors, navigation behavior and clustering techniques
    Belk, Marios
    Papatheocharous, Efi
    Germanakos, Panagiotis
    Samaras, George
    [J]. JOURNAL OF SYSTEMS AND SOFTWARE, 2013, 86 (12) : 2995 - 3012
  • [10] Recommender systems survey
    Bobadilla, J.
    Ortega, F.
    Hernando, A.
    Gutierrez, A.
    [J]. KNOWLEDGE-BASED SYSTEMS, 2013, 46 : 109 - 132