Keywords linking method for selecting educational web resources a la ZigZag

The authors of the web-based courseware typically face problems such as how to locate, select and semantically relate suitable learning resources. This paper proposes a tool that supports the authors in their tasks of selection and grouping the learning material. The 'a la' (Associative Linking of Attributes) in Education, enhances the search engine results by extracting the attributes (keywords and document formats) from the text. The relationships between the attributes are established and visualised in a novel hypertext paradigm using the ZigZag principles. Browsing the related metadata provides a quick summary of the document and can hence help in faster determining its relevancy. Also, the proposed solution enables better understanding of why some resources are grouped together as well as providing suggestions for the further searches. The results of a user trial indicate high levels of user satisfaction and effectiveness.

[1]  Prabhakar Raghavan,et al.  Mining the Link Structure of the World Wide Web , 1998 .

[2]  Monica M. C. Schraefel,et al.  A comparison of hyperstructures: zzstructures, mSpaces, and polyarchies , 2004, HYPERTEXT '04.

[3]  Dunja Mladenic,et al.  Text-learning and related intelligent agents: a survey , 1999, IEEE Intell. Syst..

[4]  Tim J. Brailsford,et al.  Unified Hyperstructures for Bioinformatics: Escaping the Application Prison , 2004, J. Digit. Inf..

[5]  Lora Aroyo,et al.  The New Challenges for E-learning: The Educational Semantic Web , 2004, J. Educ. Technol. Soc..

[6]  Stefan Trausan-Matu,et al.  Ontology-Centered Personalized Presentation of Knowledge Extracted from the Web , 2002, Intelligent Tutoring Systems.

[7]  Helen Ashman,et al.  Practical applitudes: case studies of applications of the ZigZag hypermedia system , 2004, HYPERTEXT '04.

[8]  Lora Aroyo,et al.  Authoring Support Framework for Intelligent Educational Systems , 2003 .

[9]  Theodor Holm Nelson Structure, tradition and possibility , 2003, HYPERTEXT '03.

[10]  Jaideep Srivastava,et al.  Web mining: information and pattern discovery on the World Wide Web , 1997, Proceedings Ninth IEEE International Conference on Tools with Artificial Intelligence.

[11]  Lora Aroyo,et al.  Ontological Support for Web Courseware Authoring , 2002, Intelligent Tutoring Systems.

[12]  Vladan Devedzic,et al.  "à la" in Education: Keywords Linking Method for Selecting Web Resources , 2005, AIED.

[13]  David Lowe,et al.  Hypermedia and the Web: An Engineering Approach , 1999 .

[14]  Tom Murray,et al.  Authoring Knowledge-Based Tutors: Tools for Content, Instructional Strategy, Student Model, and Interface Design , 1998 .

[15]  Vladan Devedzic,et al.  Key issues in next-generation Web-based education , 2003, IEEE Trans. Syst. Man Cybern. Part C.

[16]  Les Carr,et al.  Assisting artifact retrieval in software engineering projects , 2004, DocEng '04.

[17]  Jacqueline Bourdeau,et al.  Using Ontological Engineering to Overcome Common AI-ED Problems , 2000 .

[18]  Vladan Devedzic,et al.  Education and the Semantic Web , 2005, Int. J. Artif. Intell. Educ..

[19]  H. Chertkow,et al.  Semantic memory , 2002, Current neurology and neuroscience reports.

[20]  Peter Bruza,et al.  Hyperindices: A Novel Aid for Searching in Hypermedia , 1992, ECHT.

[21]  Ankush MITTAL,et al.  Enhanced Understanding and Retrieval of E-learning Documents through Relational and Conceptual Graphs , 2003 .

[22]  Dov M. Gabbay What's on My Mind , 1999, J. Log. Comput..

[23]  Les Carr,et al.  Linking in context , 2001, J. Digit. Inf..

[24]  Marek Hatala,et al.  Ontology mappings to improve learning resource search , 2006, Br. J. Educ. Technol..