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Designing personalized curricula based on student preferences
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ACM Special Interest Group for Design of Communication archive
Proceedings of the 25th annual ACM international conference on Design of communication table of contents
El Paso, Texas, USA
SESSION: Teaching and learning DOC table of contents
Pages: 55 - 62  
Year of Publication: 2007
ISBN:978-1-59593-588-5
Authors
Periklis Georgiadis  Univeresity of Crete, Heraklion, Greece
Vassilis Christophides  Foundation for Research and Technology - Hellas, Heraklion, Greece
Nicolas Spyratos  Université Paris Sud, Paris, France
Sponsors
SIGDOC: ACM Special Interest Group for Design of Communications
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

We address the problem of generating entire course sequences, given a set of target skills along with possibly prioritized student preferences over course descriptions. Compared to logic frameworks formulating course sequencing as a planning problem, our work relies on a set-theoretic framework for generating course sequences using preference-based queries. We introduce the concept of ordered partition for sequencing, and the ordered product of partitions, when it is necessary to combine more than one preference orderings. In our context, ordered partitions originate from preferences expressed over general relations, rather than on functional attributes of traditional database tuples (or objects) addressed by other approaches. We believe that the proposed framework is expressive enough to produce course sequences from descriptions expressed in diverse data models (e.g., XML, RDF/S) with respect to a variety of user preferences, also including priorities over the preferences.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
Antoniou, G., Baldoni, M., Baroglio, C., et al. Reasoning Methods for Personalization on the Semantic Web 2004. Annals of Mathematics, Computing & Teleinformatics 2,1 (2004), 1--24.
 
2
Andreka H., Ryan M., and Schlobbens P.-Y. Operators and Laws for Combining Preferential Relations. Journal of Logic and Computation, 12(1) (2002), 13--53.
 
3
Aroyo, L., Mizoguchi, R., and Tzolov, C. OntoAIMS: Ontological Approach to Courseware Authoring. In Proc. of ICCE'03.
 
4
 
5
 
6
 
7
Börzsönyi S., Kossman D., and Stocker K. The Skyline Operator. In Proc. of ICDE'01.
 
8
 
9
10
 
11
Christophides, V., Karvounarakis, G., Plexousakis D., Scholl M., and Tourtounis S. Optimizing Taxonomic Semantic Web Queries Using Labeling Schemes. In Web Semantics: Science, Services and Agents on the World Wide Web, Vol. 1(2) (2004), 207--228.
 
12
Dagger, D., Wade, V., and Conlan O. Personalization for All: Making Adaptive Course Composition Easy. Education Technology & Society, 8 (3), 9--25.
 
13
Davey B. A., Priestly H. A. Introduction to Lattices and Order (2nd edition). Cambridge University Press (2002).
 
14
Dolog, P., Henze, N., Nejdl, W., and Sintek, M. The Personal Reader: Personalizing and Enriching Learning Resources Using Semantic Web Technologies. In Proc. of the Third International Adaptive Hypermedia and Adaptive Web-based Systems Conference (AH'04).
 
15
Georgiadis, P. Foundations of Preference-based Queries. Doctoral Forum HDMS'05, Greece, 2005.
 
16
 
17
Henze, N., Dolog, P., and Nejdl, W. Reasoning and Ontologies for Personalized e-Learning in the Semantic Web. Educational Technology & Society, 7(4)(2004), 82--97.
 
18
Karampiperis, P., and Sampson D. Adaptive Learning Resources Sequencing in Educational Hypermedia Systems. Educational Technology & Society Journal, vol. 8(4), (2005), 128--147.
 
19
 
20
Kravcik, M., and Specht, M. Flexible Navigation Support in the WINDS Learning Environment for Architecture and Design. In Proc. of 3rd Int'al Adaptive Hypermedia and Adaptive Web-based Systems Conference (AH'04).
 
21
Spyratos, N. The Partition Model: A Functional Approach. INRIA Research Report No 430 (1985).
 
22
Spyratos, N., and Christophides V. Querying with Preferences in a Digital Library. Dagstuhl Seminar (N0 05182) Federation over the Web LNAI 3847, 2005.
 
23
Spyratos, N. Concepts and Algorithms for Decision Support, LRI Research Report, May 2006.
 
24
Torlone, R. and Ciaccia, P. Which Are My Preferred Items? In Proc. of the Workshop on Recommendation and Personalization in E-Commerce, Malaga, Spain (2002).
 
25
Weber, G., and Brusilovsky, P. ELM-ART: An Adaptive Versatile System for Web-based Instruction. IJAIED Special Issue on Adaptive and Intelligent Web-Based Systems 12(4): (2001) 351--384.

Collaborative Colleagues:
Periklis Georgiadis: colleagues
Vassilis Christophides: colleagues
Nicolas Spyratos: colleagues