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\n\n \n \n \n \n \n \n The ALOCOM Framework: Towards Scalable Content Reuse.\n \n \n \n \n\n\n \n Verbert, K.; Ochoa, X.; and Duval, E.\n\n\n \n\n\n\n
Journal of Digital Information, 9(26): 1–24. 2008.\n
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Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n
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@article{verbert_alocom_2008,\n\ttitle = {The {ALOCOM} {Framework}: {Towards} {Scalable} {Content} {Reuse}},\n\tvolume = {9},\n\tcopyright = {All rights reserved},\n\turl = {http://journals.tdl.org/jodi/article/view/225/199},\n\tabstract = {This paper presents a framework that enables flexible content reuse. Unlike the usual practice where document components, such as images, definitions, text fragments, tables or diagrams, are assembled manually through copy-and-paste, the framework enables on-the-fly access and reuse. Retrieval of relevant components is enabled by automatic decomposition of legacy documents and storage of individual components, enriched with metadata. Furthermore, the automatic assembly of these components in mainstream authoring tools is supported. The paper describes the framework and its current support for re-assembling PowerPoint, Wikipedia and SCORM components in authoring tools. In addition, an evaluation is presented that aims to assess the effectiveness and efficiency of such content reuse for presentations.},\n\tnumber = {26},\n\tjournal = {Journal of Digital Information},\n\tauthor = {Verbert, Katrien and Ochoa, Xavier and Duval, Erik},\n\tyear = {2008},\n\tpages = {1--24},\n}\n\n\n\n
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\n This paper presents a framework that enables flexible content reuse. Unlike the usual practice where document components, such as images, definitions, text fragments, tables or diagrams, are assembled manually through copy-and-paste, the framework enables on-the-fly access and reuse. Retrieval of relevant components is enabled by automatic decomposition of legacy documents and storage of individual components, enriched with metadata. Furthermore, the automatic assembly of these components in mainstream authoring tools is supported. The paper describes the framework and its current support for re-assembling PowerPoint, Wikipedia and SCORM components in authoring tools. In addition, an evaluation is presented that aims to assess the effectiveness and efficiency of such content reuse for presentations.\n
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\n\n \n \n \n \n \n \n Quantitative Analysis of Learning Object Repositories.\n \n \n \n \n\n\n \n Ochoa, X.; and Duval, E.\n\n\n \n\n\n\n In
Proceedings of World Conference on Educational Multimedia, Hypermedia and Telecommunications ED-Media 2008, pages 6031–6040, 2008. \n
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Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n
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@inproceedings{ochoa_quantitative_2008,\n\ttitle = {Quantitative {Analysis} of {Learning} {Object} {Repositories}},\n\tcopyright = {All rights reserved},\n\turl = {http://ariadne.cti.espol.edu.ec/xavier/papers/Ochoa-EDMedia2008.pdf},\n\tabstract = {Learning Objects Repositories are the backbone of the Learning Object Economy, however little is known about their operation and much less on how that operation should be measured. Some Learnometrics (metrics for Learning Objects) need to be researched and implemented. This paper is a first step in that direction, performing a quantitative analysis of several aspects of Learning Object Repositories and Referatories in order to answer questions on their size, growth, contributor base and popularity. The analysis is performed on data from live repositories and referatories. The result of the analysis provides confirmation to long held belief, but also point out singular characteristics not previously discussed. Some of the findings are that LORs grow linearly, contribution distribution follows a power law and popularity of objects follows a log- normal distribution. The paper finalizes giving answer to the raised questions as well as the implication that these answer have in LOR community.},\n\tbooktitle = {Proceedings of {World} {Conference} on {Educational} {Multimedia}, {Hypermedia} and {Telecommunications} {ED}-{Media} 2008},\n\tauthor = {Ochoa, Xavier and Duval, Erik},\n\tyear = {2008},\n\tpages = {6031--6040},\n}\n\n\n\n
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\n Learning Objects Repositories are the backbone of the Learning Object Economy, however little is known about their operation and much less on how that operation should be measured. Some Learnometrics (metrics for Learning Objects) need to be researched and implemented. This paper is a first step in that direction, performing a quantitative analysis of several aspects of Learning Object Repositories and Referatories in order to answer questions on their size, growth, contributor base and popularity. The analysis is performed on data from live repositories and referatories. The result of the analysis provides confirmation to long held belief, but also point out singular characteristics not previously discussed. Some of the findings are that LORs grow linearly, contribution distribution follows a power law and popularity of objects follows a log- normal distribution. The paper finalizes giving answer to the raised questions as well as the implication that these answer have in LOR community.\n
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\n\n \n \n \n \n \n \n Times of Convergence. Technologies Across Learning Contexts.\n \n \n \n \n\n\n \n Ochoa, X.; and Duval, E.\n\n\n \n\n\n\n In
Times of Convergence. Technologies Across Learning Contexts, pages 322–325. Springer, 2008.\n
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Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n
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@incollection{ochoa_times_2008,\n\ttitle = {Times of {Convergence}. {Technologies} {Across} {Learning} {Contexts}},\n\tcopyright = {All rights reserved},\n\turl = {http://ariadne.cti.espol.edu.ec/xavier/papers/Ochoa-EC℡2008.pdf},\n\tabstract = {This paper presents a quantitative analysis of the reuse of learning objects in real world settings. The data for this analysis was obtained from three sources: Connexions‚Äô modules, University courses and Presentation components. They represent the reuse of learning objects at different granularity levels. Data from other types of reusable components, such as software libraries, Wikipedia images and Web APIs, were used for comparison purposes. Finally, the paper discusses the implications of the findings in the field of Learning Object research.},\n\tbooktitle = {Times of {Convergence}. {Technologies} {Across} {Learning} {Contexts}},\n\tpublisher = {Springer},\n\tauthor = {Ochoa, Xavier and Duval, Erik},\n\tyear = {2008},\n\tpages = {322--325},\n}\n\n\n\n
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\n This paper presents a quantitative analysis of the reuse of learning objects in real world settings. The data for this analysis was obtained from three sources: Connexions’ modules, University courses and Presentation components. They represent the reuse of learning objects at different granularity levels. Data from other types of reusable components, such as software libraries, Wikipedia images and Web APIs, were used for comparison purposes. Finally, the paper discusses the implications of the findings in the field of Learning Object research.\n
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\n\n \n \n \n \n \n \n Relevance Ranking Metrics for Learning Objects.\n \n \n \n \n\n\n \n Ochoa, X.; and Duval, E.\n\n\n \n\n\n\n
IEEE Transactions on Learning Technologies, 1(1): 34–48. 2008.\n
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Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n
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@article{ochoa_relevance_2008,\n\ttitle = {Relevance {Ranking} {Metrics} for {Learning} {Objects}},\n\tvolume = {1},\n\tcopyright = {All rights reserved},\n\tissn = {1939-1382},\n\turl = {http://ariadne.cti.espol.edu.ec/xavier/papers/Ochoa-TLT2009a.pdf},\n\tdoi = {http://doi.ieeecomputersociety.org/10.1109/TLT.2008.1},\n\tabstract = {The main objetive of this paper is to improve the current status of learning object search. First, the current situation is analyzed and a theretical solution, based on relevance ranking is pruposed. To implement this solution, the paper develops the concept of relevance in the context of learning object search. Based on this concept, it proposes a set of metrics to estimate the topical, personal and situational relevance dimensions. These metrics are calculated mainly from usage and contextual information and do not require any explicit information from users. An exploratory evaluation of the metrics shows that even the simplest ones provide statistically significant improvement in the ranking order over the most common algorithmic relevance metric. Moreover, combining the metrics through learning algorithms sorts the result list 50\\% better than the base-line ranking.},\n\tnumber = {1},\n\tjournal = {IEEE Transactions on Learning Technologies},\n\tauthor = {Ochoa, Xavier and Duval, Erik},\n\tyear = {2008},\n\tpages = {34--48},\n}\n\n\n\n
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\n The main objetive of this paper is to improve the current status of learning object search. First, the current situation is analyzed and a theretical solution, based on relevance ranking is pruposed. To implement this solution, the paper develops the concept of relevance in the context of learning object search. Based on this concept, it proposes a set of metrics to estimate the topical, personal and situational relevance dimensions. These metrics are calculated mainly from usage and contextual information and do not require any explicit information from users. An exploratory evaluation of the metrics shows that even the simplest ones provide statistically significant improvement in the ranking order over the most common algorithmic relevance metric. Moreover, combining the metrics through learning algorithms sorts the result list 50% better than the base-line ranking.\n
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\n\n \n \n \n \n \n \n Quantitative Analysis of User-Generated Content on the Web.\n \n \n \n \n\n\n \n Ochoa, X.; and Duval, E.\n\n\n \n\n\n\n In De Roure, D.; and Hall, W., editor(s),
Proceedings of the First International Workshop on Understanding Web Evolution (WebEvolve2008), pages 19–26, 2008. \n
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Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n
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@inproceedings{ochoa_quantitative_2008,\n\ttitle = {Quantitative {Analysis} of {User}-{Generated} {Content} on the {Web}},\n\tcopyright = {All rights reserved},\n\turl = {http://journal.webscience.org/34/},\n\tabstract = {User-generated content (UGC) is becoming the most popular and valuable information available on the WWW. However, little serious research has been conducted to measure the properties of its production process. This paper presents an in-depth quantitative analysis of 9 popular websites that are based on different UGC types. The Information Production Process is used as a framework for the analysis. The findings provide for first time strong scientific evidence for previously anecdotic knowledge: UGC production follows “long-tail” distributions and it is marked with a strong “participation inequality”. Also, the analysis arrived to unexpected findings: not all the UGC types follow the inverse power-law distribution, and large content collections could be dominated by the presence of ultraproductive users. The analysis results also have implications for the administration of UGC-based websites.},\n\tbooktitle = {Proceedings of the {First} {International} {Workshop} on {Understanding} {Web} {Evolution} ({WebEvolve2008})},\n\tauthor = {Ochoa, Xavier and Duval, Erik},\n\teditor = {De Roure, David and Hall, Wendy},\n\tyear = {2008},\n\tpages = {19--26},\n}\n\n\n\n
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\n User-generated content (UGC) is becoming the most popular and valuable information available on the WWW. However, little serious research has been conducted to measure the properties of its production process. This paper presents an in-depth quantitative analysis of 9 popular websites that are based on different UGC types. The Information Production Process is used as a framework for the analysis. The findings provide for first time strong scientific evidence for previously anecdotic knowledge: UGC production follows “long-tail” distributions and it is marked with a strong “participation inequality”. Also, the analysis arrived to unexpected findings: not all the UGC types follow the inverse power-law distribution, and large content collections could be dominated by the presence of ultraproductive users. The analysis results also have implications for the administration of UGC-based websites.\n
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\n\n \n \n \n \n \n \n Learnometrics: Metrics for Learning Objects.\n \n \n \n \n\n\n \n Ochoa, X\n\n\n \n\n\n\n Ph.D. Thesis, Katholieke Universiteit Leuven, September 2008.\n
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Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n
\n
@phdthesis{ochoa_learnometrics:_2008,\n\ttype = {{PhD} {Thesis}},\n\ttitle = {Learnometrics: {Metrics} for {Learning} {Objects}},\n\tcopyright = {All rights reserved},\n\turl = {http://ariadne.cti.espol.edu.ec/xavier/papers/ThesisFinal2.pdf},\n\tabstract = {Information technology have been changing and improving the way in which teaching and learning is conducted. One aspect where the Information Technology is having profound impact is the creation and reuse of digital learning materials or more commonly called Learning Objects. Thanks to its digital nature, these objects are easy to copy, distribute and adapt. This means that teachers and learners do not need to create all their learning material, but they can share what they already have and obtain and repurpose existing content made by their peers. This economy based in sharing leads to considerable saving in time and effort and provide learning materials of better quality to an expanded population. However useful this Learning Object Economy is, little is known about how it works. How many learning objects are published and reused? how many objects each teacher produce? what is the optimal size of the objects? are basic questions that did not have an answer. Also, the tools used to create, publish, search and reuse learning objects are not smart enough and require a considerable amount of work from the users. This dissertation study the inner workings of the Learning Object Economy and propose small calculations (metrics) that can be used to improve current tools. The main findings of this research reveal that the Learning Object Economy exist but it is still immature and that the application of simple metrics could greatly improve the way in which learning objects are shared and reused.},\n\tschool = {Katholieke Universiteit Leuven},\n\tauthor = {Ochoa, X},\n\tmonth = sep,\n\tyear = {2008},\n}\n\n\n\n
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\n Information technology have been changing and improving the way in which teaching and learning is conducted. One aspect where the Information Technology is having profound impact is the creation and reuse of digital learning materials or more commonly called Learning Objects. Thanks to its digital nature, these objects are easy to copy, distribute and adapt. This means that teachers and learners do not need to create all their learning material, but they can share what they already have and obtain and repurpose existing content made by their peers. This economy based in sharing leads to considerable saving in time and effort and provide learning materials of better quality to an expanded population. However useful this Learning Object Economy is, little is known about how it works. How many learning objects are published and reused? how many objects each teacher produce? what is the optimal size of the objects? are basic questions that did not have an answer. Also, the tools used to create, publish, search and reuse learning objects are not smart enough and require a considerable amount of work from the users. This dissertation study the inner workings of the Learning Object Economy and propose small calculations (metrics) that can be used to improve current tools. The main findings of this research reveal that the Learning Object Economy exist but it is still immature and that the application of simple metrics could greatly improve the way in which learning objects are shared and reused.\n
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\n\n \n \n \n \n \n Project JARDIN: Just an Assistant for instructional DesIgN.\n \n \n \n\n\n \n Motz, R.; Viola, A.; Oliveira, J. P. d.; Lima, J. V. d.; Ochoa, X.; Deco, C.; Casali, A.; Bender, C.; and Alvarez, M. A. P.\n\n\n \n\n\n\n In
Proceedings of the Third Latin American Conference on Learning Objects, pages 223–227, 2008. \n
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\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n
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@inproceedings{motz_project_2008,\n\ttitle = {Project {JARDIN}: {Just} an {Assistant} for instructional {DesIgN}},\n\tcopyright = {All rights reserved},\n\tbooktitle = {Proceedings of the {Third} {Latin} {American} {Conference} on {Learning} {Objects}},\n\tauthor = {Motz, Regina and Viola, Alfredo and Oliveira, José Palazzo de and Lima, José Valdení de and Ochoa, Xavier and Deco, Claudia and Casali, Ana and Bender, Cristina and Alvarez, Miguel Angel Pérez},\n\tyear = {2008},\n\tpages = {223--227},\n}\n\n\n\n
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\n\n \n \n \n \n \n \n An online operational alert system for the early detection of shrimp epidemics at the regional level based on real-time production.\n \n \n \n \n\n\n \n Bayot, B.; Sonnenholzner, S.; Ochoa, X.; Johanna Guerrerro; Vera, T.; Calderon, J.; Blas, I. d.; Cornejo-Grunauer, M. d. P.; Stern, S.; and Ollevier, F.\n\n\n \n\n\n\n
Aquaculture, 277(3-4): 164–173. 2008.\n
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Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n
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@article{bayot_online_2008,\n\ttitle = {An online operational alert system for the early detection of shrimp epidemics at the regional level based on real-time production},\n\tvolume = {277},\n\tcopyright = {All rights reserved},\n\turl = {http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6T4D-4S0PK4X-1&_user=10&_rdoc=1&_fmt=&_orig=search&_sort=d&view=c&_acct=C000050221&_version=1&_urlVersion=0&_userid=10&md5=311f1ee6c0b257f20b9b68c5d9292e02},\n\tabstract = {Diseases are among the greatest threats affecting the sustainability of shrimp aquaculture. In Ecuador, diseases of cultured shrimp have been quickly transmitted from one region to another. Therefore, an early detection system of impending epidemics could serve as an important management tool for the aquaculture sector. We developed a system for the early detection of shrimp epidemics for the largest shrimp zone of Ecuador based on production surveillance. The system, called Epidemiological Alert System and Aquaculture Management (SAEMA), uses a geographical information system (GIS) with an imaginary grid cartography (12,860 ha per grid) dividing the study area. A production and management index is calculated with the harvest data of each pond. A standardized deviation around the historical averages and an alert level is calculated per grid and month. Normal conditions of production and therefore the absence of disease are depicted in green and yellow. While, orange and red colours express a disease warning manifested through suboptimal production levels. As a result, a map of the study area with grid divisions is displayed, with a specific alert colour for each grid where information is available. SAEMA was developed as a Web application (http://www.saema.espol.edu.ec) that enables producers to record data via a worksheet format using any web browser. Instantaneously, the applications perform a calculation of the alert index and provide feedback to the alert levels displayed in an interactive map. A feedback process was initiated in May 2006 with 19 participating shrimp farms. The objective of this research is to develop a platform for an early detection of shrimp epidemics on a regional scale. The detection of an epidemic, expressed as suboptimal production in a specific region, can provide producers from other zones and government authorities to engage in time preventive and control measures in order to reduce the spread of diseases.},\n\tnumber = {3-4},\n\tjournal = {Aquaculture},\n\tauthor = {Bayot, Bonny and Sonnenholzner, Stanislaus and Ochoa, Xavier and {Johanna Guerrerro} and Vera, Teresa and Calderon, Jorge and Blas, Ignacio de and Cornejo-Grunauer, Maria del Pilar and Stern, Sam and Ollevier, Frans},\n\tyear = {2008},\n\tpages = {164--173},\n}\n\n\n\n
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\n Diseases are among the greatest threats affecting the sustainability of shrimp aquaculture. In Ecuador, diseases of cultured shrimp have been quickly transmitted from one region to another. Therefore, an early detection system of impending epidemics could serve as an important management tool for the aquaculture sector. We developed a system for the early detection of shrimp epidemics for the largest shrimp zone of Ecuador based on production surveillance. The system, called Epidemiological Alert System and Aquaculture Management (SAEMA), uses a geographical information system (GIS) with an imaginary grid cartography (12,860 ha per grid) dividing the study area. A production and management index is calculated with the harvest data of each pond. A standardized deviation around the historical averages and an alert level is calculated per grid and month. Normal conditions of production and therefore the absence of disease are depicted in green and yellow. While, orange and red colours express a disease warning manifested through suboptimal production levels. As a result, a map of the study area with grid divisions is displayed, with a specific alert colour for each grid where information is available. SAEMA was developed as a Web application (http://www.saema.espol.edu.ec) that enables producers to record data via a worksheet format using any web browser. Instantaneously, the applications perform a calculation of the alert index and provide feedback to the alert levels displayed in an interactive map. A feedback process was initiated in May 2006 with 19 participating shrimp farms. The objective of this research is to develop a platform for an early detection of shrimp epidemics on a regional scale. The detection of an epidemic, expressed as suboptimal production in a specific region, can provide producers from other zones and government authorities to engage in time preventive and control measures in order to reduce the spread of diseases.\n
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