July 2007 Volume 10 Number 3 - Educational Technology & Society

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A data model is a collection of concepts that can be used to describe the structure of a database. In Figure 3, the ‘Isa’ relationship is used throughout. While this relationship type correctly describes most of the relationships between concepts, there are a few cases where this relation does not express the correct meaning for the relationship between the concepts. The concepts ‘Relational data model’ and ‘Oracle database’ are linked. However, as an Oracle database is an instance of a database that is built using the relational data model as its underlying model, it is incorrect to say that it is a subtype of the relational data model. The ‘Is-a’ relationship is also inappropriate in other cases. Entity and Relationship are not subtypes of the Relational data model. Instead, they are parts of the model. In order to rectify these misrepresentations, it was decided to define a number of other relationship types; see Figure 4, which represents the metamodel for our ontological modelling method. Instance/ example Relationship Types – a Rich Ontology mayHaveSynonym Name has Figure 4. Overview of the relationship types. Relationship Types: IsBasedOn HasPart HasSubtype HasFunction HasConstraint Concept has Definition mayHave mayHave has Relationship(s) with other concepts Further explanation As the ontology was being designed with delivery as a third-level educational course in mind, it was important to consider the type of information that would be required by a student that is not necessarily part of the concept ontology. For this reason, the approach used by Fischer (2001) was employed, whereby two sets of relationships were created for use in either the graphical representations (representing the concept space) or the associated content (creating the educational content space). An advantage of separating concepts from content is that content aspects in the system can be changed without affecting the overall structure or vice versa. The objective was to create a minimal set of relationships (for both concepts and the associated educational content) that would be sufficient to represent all relationships between concepts both clearly and fully. General ontology relationship types for the concept space: An important relationship type is the ‘Is-a’ relationship. Unfortunately, use of this relationship type caused some difficulties. The correct use of the ‘Is-a’ relationship is to indicate a generalization/specialization relationship between two concepts. However, because of its common English usage, it often resulted in the generation of inappropriate relationships, by being used inadvertently to indicate synonyms or to associate a concept with its definition. For this reason, the ‘Is-a’ relationship was replaced by its inverse relation, which was called the ‘HasSubtype’ relation. The use of the ‘HasSubtype’ relationship made it much easier to avoid the pitfalls associated with the ‘Is-a’ relation, while remaining analogous to it. Another important relation indicates that a concept comprises a number of parts. This was called the ‘HasPart’ relation. Other relations used to link the concepts within the ontology were named has 281
‘IsBasisOf’, ‘HasConstraint’ and ‘HasFunction’. These relations were included as the ‘HasSubtype’ and ‘HasPart’ relations did not always reflect the meaning of the relationship between two concepts adequately. Content relationship types for the educational content space: These are used to link a concept to some content. The relationship types used were ‘HasDefinition’, ‘HasSynonym’, ‘HasAsExample’ and ‘HasFurtherExplanation’. The concepts and their associated information were collated in separate tables, one for each relationship type. The ‘HasDefinition’ table contains an entry for each concept name used in the graphical representations. It also contains definitions for those domain-specific terms that are used in the definitions of concept terms. The other three relationships provide further information associated with the terms from the initial set (‘HasDefinition’). HasSubtype HasConstraint ER Diagram HasPart Schema construct Entity 1:1 N:M Relationship HasSubtype Weak entity HasSubtype Simple attribute HasPart HasPart Attribute HasConstraint Complex HasPart HasPart attribute Figure 5. Excerpt of an ER-diagram ontology. HasSubtype HasSubtype Identifying relationship HasSubtype HasSubtype Composite attribute The rationale behind the choice of relationship types led to the following definitions for the two categories of relationships in the two spaces. The relations used in the concept space are as follows: IsBasisOf: This is the most fundamental of relationship types, expressing dependency. It is used to show that a concept in the universe of discourse forms the theoretical foundation for a second concept. This normally occurs as an unconstrained relationship between concept classes. HasSubtype: This is by far the most common relationship type. It is used to indicate the relationship between a general concept and all specializations (subsumptions) of that concept that are themselves simple concepts (i.e. those not comprising more than one attribute). This relation is the inverse of the ‘Is-a’ relationship type. This is a relationship that forms a hierarchy, indicating that a superconcept can have one or more subconcepts. HasPart: This is used to indicate that a concept comprises two or more subconcepts in a part—whole relationship (aggregation), for example chairs have the parts seat, back and legs, but legs, however, can also be 282
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July 2007 Volume 10 Number 3
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Advertisements Educational Technolo
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Distinguishing between games and si
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“sometimes” is less demanding t
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Figure 2. From generic skill to lea
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The large window on the left presen
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define competencies of individual a
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competency is composed of a single
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Generic Skills Classes 1 2 3 Receiv
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Figure 6. Extension of the competen
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Competency scale By combining the g
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activities, and resources present i
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Conclusion The importance given to
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Ainsworth, S. (2007). Using a Singl
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different instruction. For example,
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Author-focused studies Studies 1 an
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egression showed that students were
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REDEEM is now a senior citizen in t
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Chieu, V. M. (2007). An Operational
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When students discuss with peers, t
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COFALE as a learning environment an
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COFALE supports a set of predefined
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Tom is asked to prepare a list of g
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45-minute-long lecture and 2-hour-l
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as an easy-to-use technological mea
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Spiro, R. J., & Jehng, J. C. (1990)
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learning settings. However, such a
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introduced in the LOCO-Cite ontolog
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‘virtual subsection’) of the LO
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Accordingly, TANGRAM provides stude
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learning environment is to define t
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Acknowledgment This work is support
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Dron, J. (2007). Designing the Unde
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wikis and blogs (or at least, colle
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The darker side of social software
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for the beetles, whose guts act as
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The principle of sociability The pr
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Bonabeau, E., Dorigo, M., & Theraul
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Klamma, R., Chatti, M. A., Duval, E
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We perceive adaptivity and personal
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Mixed-method evaluation approach tr
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Garden of Knowledge - with a commun
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equirements for collaborative adapt
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Law, E. L.-C., & Hvannberg, E. T. (
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Wang, T. I., Tsai, K. H., Lee, M. C
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2.3 Recommendation Model Survey In
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Figure 1. The portion of the concep
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STEP4: Associated with concepts in
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A modified TF-IDF approach is used
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P(CK j x LOM ) = k NW max ∀ T∈
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4.2.2 Correlation-based algorithm I
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content feedback, it can be intuiti
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66% improvement in average, and, wh
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(a) (b) (c) Figure 10. Comparisons
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index.aspx. ADL-2 (2001). Advanced
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Wolpers, M., Najjar, J., Verbert, K
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activity is taking place. For examp
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Figure 2: The CAM schema elements (
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• Context: the context element ca
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4.1 Generation of Attention Metadat
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addition, such keywords can be extr
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Action related data, data about sea
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Braun, S., & Schmidt, A. (2006). Do
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El-Bishouty, M. M., Ogata, H., & Ya
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collaboration (Ogata, et al., 1999)
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In case of LOI value is equal or cl
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Also, the learner can click on an e
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System Evaluation An experiment was
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In the fifth phase, 89% of the stud
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Fischer, G., & Konomi, S. (2005). I
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application for specific needs, whi
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(4) Multimedia: The truth is that e
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Program Company Price OS 6 eZediaMX
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Program Text editor Text import for
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Program Sound Formats Image Formats
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Program Image Painting Export Scrip
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Program Effects Needs player 5 Easy
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Program WYSIWYG Design Interactivit
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the grades awarded to the programs
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Grade Image formats Sound formats V
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Figure 3. Adequacy of image formats
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Animating objects, pictures, etc.,
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Educational overview Having taken m
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In summary, the final outcome is th
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Developing the Interactivity Survey
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technique. be treated as a desired
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55. A lecture in which student lear
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specific conclusions that researche
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Discussion and conclusion Although
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Juwah, C. (2003). Using peer assess
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Publish results Set a few goals for
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familiarity with computer terms, ex
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provide a framework for the integra
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tool themselves, and then gauge its
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associated with the effective use o
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portrayed as even more time-consumi
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Clarke, B. (2001). Corporate curric
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Neal, E. (1998). Using technology i
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Yearwood, J., & Stranieri, A. (2007
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entertaining (Neuhauser 1993). The
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in being addressed with the sequent
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The GAAM represents reasoning to a
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Other situations have more serious
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Figure 6. NARRATE phase screen afte
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The narration at Step 10 informs th
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very large degree of free-will has
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Rumelhart, D. E. (1975). Notes on a
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The School of Business at Universit
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Authentic assessment and OBOW exams
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iii. The assessment asks the studen
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world problems in relation to the s
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Herrington, J., & Herrington, A. (1
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services required by most clients i
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Wisdom. J. P., White, N., Goldsmith
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Work outside the U.S. has also prom
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of the Telecommunication Act, and t
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Parent-advocate respondents also re
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Page 249 and 250: Conclusion This study examined the
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Page 259 and 260: Bain, C., & Newton, C. (2003). Art
Page 261 and 262: Prensky, M. (2005). Adopt and Adapt
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Page 279 and 280: Soller, A., & Lesgold, A. (2000). K
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Page 301 and 302: Figures 2-5 display screenshots of
Page 303 and 304: Results of the study reveal the imp
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Page 307 and 308: Dede, C., Salzman, M., Loftin, R. B
Page 309 and 310: Trumper, R. (2000). University stud
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Page 323 and 324: easily take lessons in a good learn
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Page 331 and 332: and concise manner (e.g. Weeding =
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July 2007 Volume 10 Number 3 - Educational Technology & Society

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