Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

    We have a manual that explains all the features 

Record number 343314
Title Database functionality for learning objects
Author(s) Sessink, O.D.T.; Beeftink, H.H.; Hartog, R.J.M.
Source Technology, Instruction, Cognition and Learning 2 (2005)4. - ISSN 1540-0182 - p. 337 - 357.
Department(s) Bioprocess Engineering
Information Technology
Publication type Refereed Article in a scientific journal
Publication year 2005
Abstract The development of student-activating digital learning material in six research projects revealed several shortcomings in the current learning management systems. Once the SCORM 2004 and the IMS Sharable State Persistence specifications are implemented in learning management systems, some of these shortcomings will be obsolete. We have, however, identified six functionality clusters with significant added value for learning materials that are neither addressed by SCORM 2004 nor by IMS Sharable State Persistence. These clusters are: 1) support for adaptivity, 2) support for retrieval of current and previous states, 3) support for comparison of results, 4) support for student tracking for pedagogical research, 5) shared reference database functionality, and 6) problem scenario database functionality. The significance of each of these functionality clusters is discussed, and illustrated with examples from digital learning material. This article, furthermore, describes the workarounds needed to deploy these examples in the current learning management systems. A general solution that will support all six functionality clusters is presented: database functionality for learning objects. This is essentially an interface to database functionality with support for complex data models, data integrity, and concurrent access, in which authors can define the data model, and both learning objects and authors can query the database.
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