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Vol 6, No 1 (2005)
Articles
Designing Adaptable Learning Resources with Learning Object Patterns
Constructing courses of study from learning objects is an attractive proposition, but for this to be feasible learning objects need to be designed to be reusable. While considerable work has been done in producing technical standards to promote compatibility in learning objects, more work is required in designing learning objects for reuse. Aspects of cohesion, coupling and freedom from specific contexts can be used in designs to help ensure that learning objects are reusable, and these aspects can be captured as design patterns that may be employed to produce reusable designs for learning objects. However, the requirements for reusability may be in conflict with those for effective learning so the patterns used must ensure that the learning objects constructed are adaptable to different contexts and remain pedagogically sound within those contexts. The paper shows how patterns can be used to create learning resources that are both reusable and adaptable.
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Digital Text Cycles: From Medieval Manuscripts to Modern Markup
The paper argues that the current implementation of digital publishing is a minor step in a long development of digital text cycles. Rather than being a revolution, the digital transformation of text is an evolutionary process heavily influenced by social and cultural factors. The paper introduces the concept of a "text cycle". An examination of basic features of paper-based text cycles and features of digital text cycles demonstrates that digital technology has a potential for change that far exceeds that of the "Gutenberg revolution". However, by applying a historical perspective, I will try to show how the deep and enduring cultural heritage of print is impeding the radical potential of digital texts.
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A Text Categorization Technique based on a Numerical Conversion of a Symbolic Expression and an Onion Layers Algorithm
The dramatic increase in the amount of content available in digital forms gives rise to large-scale digital libraries, targeted at millions of users. As a result, it has become a necessary to categorize large texts (documents). The paper develops a novel method where text categorization is achieved via a reduction in the original data information using numerical conversion of a symbolic expression and an onion layers algorithm. Three different semantic categories were considered and five texts selected from each category for submission to a text categorization procedure using the proposed method. The results and the statistical evaluation of this procedure showed that the proposed method may be characterized as highly accurate for text categorization purposes.
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Capturing Content for Virtual Museums: from Pieces to Exhibits
Virtual museums provide ways to capture the content of a real museum in a digital (electronic) form and make this digital form more universally available. This paper describes a novel method for digitally recording not only individual museum pieces, but entire museum exhibits (consisting of one or more rooms or spaces). The methodology allows anyone with access to the Internet or a PC to experience anywhere, anytime, any part of the museum's collection or exhibits (past, present and future). Users can explore the museum exhibits in a virtual reality that is both spatially accurate and visually compelling. All objects and 3D scenes are seen in precise full color photographic quality detail. The scene and objects are polygonal meshes representing the surfaces of objects. This permits making measurements directly on the scene with millimeter precision. The methodology, its application to capturing museum exhibits, and examples of exhibits recorded using this technique are described. This work is part of the Virseum project (http://ils.unc.edu/bmh/virseum) at the School of Information and Library Science at the University of North Carolina at Chapel Hill (UNC). In addition to the capture of items and exhibits for virtual access, this methodology opens the door for many other applications, including capturing a record of an exhibit for archival purposes and for communication between curators, and for the design of virtual (never physically implemented) exhibits and pieces based on actual pieces and settings.
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Fault-tolerant Fulltext Search for Large Multilingual Scientific Text Corpora
In the work reported here, we present a new way of performing fault-tolerant fulltext retrieval on large text corpora, such as scientific encyclopedias. The weighted pattern morphing (WPM) technique introduced in this paper overcomes disadvantages of both the popular edit distance measure and the Soundex code approaches, yet keeping their flexibility. This algorithm handles phonetic similarities; common typing errors such as omission or transposition of letters, and inconsistent usage of abbreviations and hyphenation. After showing how WPM can be implemented efficiently, we present a novel method of how the weights of the internal penalty matrix can be automatically adjusted for even better results. Though the described technique can be applied without prior knowledge of actual user patterns, re-examination with a large number of online-user's patterns proves the portability of this fine-tuning approach. We further show how shifting the penalty matrix from one language to another can be accomplished. The described WPM technique is integrated into a large commercial pharmaceutical encyclopedia CDROM, an online dermatological encyclopedia, and an online-reference encyclopedia of parasitology research, thus also proving its "road capability".
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