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M. Elena Rodriguez
Faculty of Computer Science, Multimedia and Telecommunications, Universitat Oberta de Catalunya and the e Learn Center, Rambla del Poblenou 156, Barcelona 08018, Spain

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Journal article
Published: 22 June 2021 in Applied Sciences
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Learning analytics is quickly evolving. Old fashioned dashboards with descriptive information and trends about what happened in the past are slightly substituted by new dashboards with forecasting information and predicting relevant outcomes about learning. Artificial intelligence is aiding this revolution. The accessibility to computational resources has increased, and specific tools and packages for integrating artificial intelligence techniques leverage such new analytical tools. However, it is crucial to develop trustworthy systems, especially in education where skepticism about their application is due to the risk of teachers’ replacement. However, artificial intelligence systems should be seen as companions to empower teachers during the teaching and learning process. During the past years, the Universitat Oberta de Catalunya has advanced developing a data mart where all data about learners and campus utilization are stored for research purposes. The extensive collection of these educational data has been used to build a trustworthy early warning system whose infrastructure is introduced in this paper. The infrastructure supports such a trustworthy system built with artificial intelligence procedures to detect at-risk learners early on in order to help them to pass the course. To assess the system’s trustworthiness, we carried out an evaluation on the basis of the seven requirements of the European Assessment List for trustworthy artificial intelligence (ALTAI) guidelines that recognize an artificial intelligence system as a trustworthy one. Results show that it is feasible to build a trustworthy system wherein all seven ALTAI requirements are considered at once from the very beginning during the design phase.

ACS Style

David Baneres; Ana Guerrero-Roldán; M. Rodríguez-González; Abdulkadir Karadeniz. A Predictive Analytics Infrastructure to Support a Trustworthy Early Warning System. Applied Sciences 2021, 11, 5781 .

AMA Style

David Baneres, Ana Guerrero-Roldán, M. Rodríguez-González, Abdulkadir Karadeniz. A Predictive Analytics Infrastructure to Support a Trustworthy Early Warning System. Applied Sciences. 2021; 11 (13):5781.

Chicago/Turabian Style

David Baneres; Ana Guerrero-Roldán; M. Rodríguez-González; Abdulkadir Karadeniz. 2021. "A Predictive Analytics Infrastructure to Support a Trustworthy Early Warning System." Applied Sciences 11, no. 13: 5781.

Journal article
Published: 17 June 2021 in IEEE Revista Iberoamericana de Tecnologias del Aprendizaje
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Online education is pushing universities to search for technologies that can support e-assessment. Opinions and behaviors of stakeholders are required in order to develop such technologies. This paper underlines the need for mechanisms to prevent cheating and increase security, by analyzing the differences between students’ perceptions of cheating and the acts of academic dishonesty they commit, contributing to fill a gap in the literature on cheating behaviors in online education. The research questions are: RQ1) Are students aware of what constitutes cheating in online education? RQ2) Do students believe that an e-authentication system may increase their security and prevent cheating? RQ3) Would the use of an e-authentication system for assessment increase students’ trust? RQ4) What are students’ real cheating behaviors? 154 students taking an online course from the Computer Engineering and Telecommunications degree consented to participate in the study. The research instruments were two surveys, and two tools of the course (an intelligent tutoring system and an image plagiarism detection tool). Results show that the fact students know an e-authentication and authoring system is used may prevent cheating and make students feel more confident. The findings have significant implications for institutions interested in e-assessment secure systems.

ACS Style

M. Elena Rodriguez; Ana-Elena Guerrero-Roldan; David Baneres; Ingrid Noguera. Students’ Perceptions of and Behaviors Toward Cheating in Online Education. IEEE Revista Iberoamericana de Tecnologias del Aprendizaje 2021, 16, 134 -142.

AMA Style

M. Elena Rodriguez, Ana-Elena Guerrero-Roldan, David Baneres, Ingrid Noguera. Students’ Perceptions of and Behaviors Toward Cheating in Online Education. IEEE Revista Iberoamericana de Tecnologias del Aprendizaje. 2021; 16 (2):134-142.

Chicago/Turabian Style

M. Elena Rodriguez; Ana-Elena Guerrero-Roldan; David Baneres; Ingrid Noguera. 2021. "Students’ Perceptions of and Behaviors Toward Cheating in Online Education." IEEE Revista Iberoamericana de Tecnologias del Aprendizaje 16, no. 2: 134-142.

Review
Published: 15 January 2021 in Sustainability
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Artificial intelligence (AI) has penetrated every layer of our lives, and education is not immune to the effects of AI. In this regard, this study examines AI studies in education in half a century (1970–2020) through a systematic review approach and benefits from social network analysis and text-mining approaches. Accordingly, the research identifies three research clusters (1) artificial intelligence, (2) pedagogical, and (3) technological issues, and suggests five broad research themes which are (1) adaptive learning and personalization of education through AI-based practices, (2) deep learning and machine Learning algorithms for online learning processes, (3) Educational human-AI interaction, (4) educational use of AI-generated data, and (5) AI in higher education. The study also highlights that ethics in AI studies is an ignored research area.

ACS Style

Aras Bozkurt; Abdulkadir Karadeniz; David Baneres; Ana Guerrero-Roldán; M. Rodríguez. Artificial Intelligence and Reflections from Educational Landscape: A Review of AI Studies in Half a Century. Sustainability 2021, 13, 800 .

AMA Style

Aras Bozkurt, Abdulkadir Karadeniz, David Baneres, Ana Guerrero-Roldán, M. Rodríguez. Artificial Intelligence and Reflections from Educational Landscape: A Review of AI Studies in Half a Century. Sustainability. 2021; 13 (2):800.

Chicago/Turabian Style

Aras Bozkurt; Abdulkadir Karadeniz; David Baneres; Ana Guerrero-Roldán; M. Rodríguez. 2021. "Artificial Intelligence and Reflections from Educational Landscape: A Review of AI Studies in Half a Century." Sustainability 13, no. 2: 800.

Journal article
Published: 30 September 2020 in Hacettepe University Journal of Education
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ACS Style

Ana Elena Guerrero-Roldán; M. Elena Rodríguez-González; Abdulkadir Karadeniz; Serpil Kocdar; Lyubka Aleksieva; Roumiana Peytcheva-Forsyth. Students Experiences on Using an Authentication and Authorship Checking System in E-Assessment. Hacettepe University Journal of Education 2020, 1 -19.

AMA Style

Ana Elena Guerrero-Roldán, M. Elena Rodríguez-González, Abdulkadir Karadeniz, Serpil Kocdar, Lyubka Aleksieva, Roumiana Peytcheva-Forsyth. Students Experiences on Using an Authentication and Authorship Checking System in E-Assessment. Hacettepe University Journal of Education. 2020; ():1-19.

Chicago/Turabian Style

Ana Elena Guerrero-Roldán; M. Elena Rodríguez-González; Abdulkadir Karadeniz; Serpil Kocdar; Lyubka Aleksieva; Roumiana Peytcheva-Forsyth. 2020. "Students Experiences on Using an Authentication and Authorship Checking System in E-Assessment." Hacettepe University Journal of Education , no. : 1-19.

Journal article
Published: 27 June 2020 in Applied Sciences
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Artificial intelligence has impacted education in recent years. Datafication of education has allowed developing automated methods to detect patterns in extensive collections of educational data to estimate unknown information and behavior about the students. This research has focused on finding accurate predictive models to identify at-risk students. This challenge may reduce the students’ risk of failure or disengage by decreasing the time lag between identification and the real at-risk state. The contribution of this paper is threefold. First, an in-depth analysis of a predictive model to detect at-risk students is performed. This model has been tested using data available in an institutional data mart where curated data from six semesters are available, and a method to obtain the best classifier and training set is proposed. Second, a method to determine a threshold for evaluating the quality of the predictive model is established. Third, an early warning system has been developed and tested in a real educational setting being accurate and useful for its purpose to detect at-risk students in online higher education. The stakeholders (i.e., students and teachers) can analyze the information through different dashboards, and teachers can also send early feedback as an intervention mechanism to mitigate at-risk situations. The system has been evaluated on two undergraduate courses where results shown a high accuracy to correctly detect at-risk students.

ACS Style

David Bañeres; M. Elena Rodríguez; Ana Elena Guerrero-Roldán; Abdulkadir Karadeniz. An Early Warning System to Detect At-risk Students in Online Higher Education. Applied Sciences 2020, 10, 4427 .

AMA Style

David Bañeres, M. Elena Rodríguez, Ana Elena Guerrero-Roldán, Abdulkadir Karadeniz. An Early Warning System to Detect At-risk Students in Online Higher Education. Applied Sciences. 2020; 10 (13):4427.

Chicago/Turabian Style

David Bañeres; M. Elena Rodríguez; Ana Elena Guerrero-Roldán; Abdulkadir Karadeniz. 2020. "An Early Warning System to Detect At-risk Students in Online Higher Education." Applied Sciences 10, no. 13: 4427.

Journal article
Published: 23 April 2019 in IEEE Transactions on Learning Technologies
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Identifying at-risk students as soon as possible is a challenge in educational institutions. Decreasing the time lag between identification and real at-risk state, it may significantly reduce the risk of failure or disengage. In small courses, their identification is relatively easy, but it is impractical on larger ones. Current Learning Management Systems store a large amount of data that could help to generate predictive models to early identify those students in online and blended learning. The contribution of this paper is twofold: First, a new adaptive predictive model is presented based only on students' grades specifically trained for each course. A deep analysis has been performed in the whole institution to evaluate its performance accuracy. Second, an early warning system has been developed focusing on dashboards visualization for stakeholders (i.e., students and teachers) and an early feedback prediction system to intervene in the case of at-risk identification. The early warning system has been evaluated in two case studies on first-year undergraduate courses in Computer Science. We show the accuracy of the correct identification of at-risk students, the students' appraisal and the most common factors which lead to at-risk level.

ACS Style

David Baneres; M. Elena Rodriguez-Gonzalez; Montse Serra. An Early Feedback Prediction System for Learners At-Risk Within a First-Year Higher Education Course. IEEE Transactions on Learning Technologies 2019, 12, 249 -263.

AMA Style

David Baneres, M. Elena Rodriguez-Gonzalez, Montse Serra. An Early Feedback Prediction System for Learners At-Risk Within a First-Year Higher Education Course. IEEE Transactions on Learning Technologies. 2019; 12 (2):249-263.

Chicago/Turabian Style

David Baneres; M. Elena Rodriguez-Gonzalez; Montse Serra. 2019. "An Early Feedback Prediction System for Learners At-Risk Within a First-Year Higher Education Course." IEEE Transactions on Learning Technologies 12, no. 2: 249-263.

Journal article
Published: 21 July 2016 in International Journal of Emerging Technologies in Learning (iJET)
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On any type of course (on site or online), a learner is evaluated whether he has acquired the knowledge and competences provided in the course. The evaluation should be performed by evaluating his progression by means of the interaction in the classroom or assessment activities. Mostly, assessment activities are used to check the level of expertise of the learner. Typically, the assessment model and assessment activities of subjects in official programmes are the same for all the learners, since they should be evaluated having the same opportunities and conditions. However, when the learner is evaluated based on a continuous assessment model, he is demonstrating on each activity his knowledge and proficiency level and, at the same time, his reputation could be also built based on the actions he is performing within the course. Therefore, the assessment model can be particularly adapted for each learned based on this information. In this paper, we present a general system to adapt any component of the assessment process (model, activity, question…) based on different evidences gathered from the learning process of the learner.

ACS Style

David Baneres; Xavi Baró; Ana-Elena Guerrero-Roldán; M. Elena Rodriguez. Adaptive e-Assessment System: A General Approach. International Journal of Emerging Technologies in Learning (iJET) 2016, 11, 16 -23.

AMA Style

David Baneres, Xavi Baró, Ana-Elena Guerrero-Roldán, M. Elena Rodriguez. Adaptive e-Assessment System: A General Approach. International Journal of Emerging Technologies in Learning (iJET). 2016; 11 (7):16-23.

Chicago/Turabian Style

David Baneres; Xavi Baró; Ana-Elena Guerrero-Roldán; M. Elena Rodriguez. 2016. "Adaptive e-Assessment System: A General Approach." International Journal of Emerging Technologies in Learning (iJET) 11, no. 7: 16-23.

Conference paper
Published: 01 September 2015 in 2015 International Conference on Intelligent Networking and Collaborative Systems
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The monitoring process and evaluation of an official higher education degree or master is performed by an annual report based on a set of requirements defined by the quality agencies which are responsible to evaluate such quality. Taking into account that these reports are made up by a set of evidences that are gathered during the whole instructional process, we propose the use of a support tool. This tool will allow the improvement of the efficiency of the process and will facilitate the quality evaluation. This paper introduces the collaborative evaluation process applied in our faculty and how the supportive tool helps to enhance the evaluation process.

ACS Style

David Baneres; Montse Serra; M. Elena Rodriguez; M. Elena Rodriguez-Gonzalez. Collaborative Tool to Enhance Quality Evaluation of Higher Education Programmes. 2015 International Conference on Intelligent Networking and Collaborative Systems 2015, 14 -20.

AMA Style

David Baneres, Montse Serra, M. Elena Rodriguez, M. Elena Rodriguez-Gonzalez. Collaborative Tool to Enhance Quality Evaluation of Higher Education Programmes. 2015 International Conference on Intelligent Networking and Collaborative Systems. 2015; ():14-20.

Chicago/Turabian Style

David Baneres; Montse Serra; M. Elena Rodriguez; M. Elena Rodriguez-Gonzalez. 2015. "Collaborative Tool to Enhance Quality Evaluation of Higher Education Programmes." 2015 International Conference on Intelligent Networking and Collaborative Systems , no. : 14-20.

Conference paper
Published: 01 September 2015 in 2015 International Conference on Intelligent Networking and Collaborative Systems
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Assessment is an important part of the learning process. The instructor should be able to evaluate whether a learner has acquired the knowledge and competences provided in the course. Moreover, assessment activities also help a learner to check his level of expertise. Typically, the assessment model and assessment activities of subjects in official programmes are the same for all the learners, since they should be evaluated having the same opportunities and conditions. However, when the learner is evaluated by means of a continuous assessment model, he is proving on each activity his knowledge and proficiency level and, at the same time, his reputation could be also built based on the actions he is performing within the course. Therefore, the assessment model can be adapted based on this information. In this paper, we present a general system to adapt the assessment based on different evidences gathered from the learning process of the learner.

ACS Style

David Baneres; Xavier Baro; Ana-Elena Guerrero-Roldán; M. Elena Rodriguez-Gonzalez. Towards a General Adaptive e-Assessment System. 2015 International Conference on Intelligent Networking and Collaborative Systems 2015, 314 -321.

AMA Style

David Baneres, Xavier Baro, Ana-Elena Guerrero-Roldán, M. Elena Rodriguez-Gonzalez. Towards a General Adaptive e-Assessment System. 2015 International Conference on Intelligent Networking and Collaborative Systems. 2015; ():314-321.

Chicago/Turabian Style

David Baneres; Xavier Baro; Ana-Elena Guerrero-Roldán; M. Elena Rodriguez-Gonzalez. 2015. "Towards a General Adaptive e-Assessment System." 2015 International Conference on Intelligent Networking and Collaborative Systems , no. : 314-321.

Conference paper
Published: 01 October 2014 in 2014 IEEE Frontiers in Education Conference (FIE) Proceedings
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European Universities are developing Bachelor degrees according the European Higher Education Area which focuses on the acquisition of a set of cross curricula and specific competences. The educational models are now centered on activities as a means for learners to achieve new competences improving their performance and skills. The purpose of this article is to analyze the online learner profile, through an initial assessment, in order to know if there is a gap between the expected competences and the real ones. This study focuses on some online courses with a set of specific Computer Engineering competences related to Math, Logic and Programming. Using a mixed methodology that combines a qualitative and quantitative data, the online learner profile is analyzed. The paper provides a detailed description about findings, seeking causes and providing guidelines, for improving the learning process based on competences. To conclude, it is introduced some recommendations and learning strategies to teachers in order to reduce the gap.

ACS Style

Ana-Elena Guerrero-Roldán; M. Elena Rodriguez; M. Elena Rodriguez-Gonzalez; Guerrero-Roldan A.-E.; Rodriguez M.E.. A learner profile analysis based on competences to improve online teaching strategies. 2014 IEEE Frontiers in Education Conference (FIE) Proceedings 2014, 1 -6.

AMA Style

Ana-Elena Guerrero-Roldán, M. Elena Rodriguez, M. Elena Rodriguez-Gonzalez, Guerrero-Roldan A.-E., Rodriguez M.E.. A learner profile analysis based on competences to improve online teaching strategies. 2014 IEEE Frontiers in Education Conference (FIE) Proceedings. 2014; ():1-6.

Chicago/Turabian Style

Ana-Elena Guerrero-Roldán; M. Elena Rodriguez; M. Elena Rodriguez-Gonzalez; Guerrero-Roldan A.-E.; Rodriguez M.E.. 2014. "A learner profile analysis based on competences to improve online teaching strategies." 2014 IEEE Frontiers in Education Conference (FIE) Proceedings , no. : 1-6.

Conference paper
Published: 01 January 2014 in Proceedings of the 6th International Conference on Computer Supported Education
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ACS Style

Enosha Hettiarachchi; Enric Mor; Maria Antonia Huertas; M. Elena Rodriguez. A Technology Enhanced Assessment System for Skill and Knowledge Learning. Proceedings of the 6th International Conference on Computer Supported Education 2014, 184 -191.

AMA Style

Enosha Hettiarachchi, Enric Mor, Maria Antonia Huertas, M. Elena Rodriguez. A Technology Enhanced Assessment System for Skill and Knowledge Learning. Proceedings of the 6th International Conference on Computer Supported Education. 2014; ():184-191.

Chicago/Turabian Style

Enosha Hettiarachchi; Enric Mor; Maria Antonia Huertas; M. Elena Rodriguez. 2014. "A Technology Enhanced Assessment System for Skill and Knowledge Learning." Proceedings of the 6th International Conference on Computer Supported Education , no. : 184-191.

Conference paper
Published: 01 January 2012 in Programmieren für Ingenieure und Naturwissenschaftler
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In this paper we describe a proposal for defining the relationships between resources, users and services in a digital repository. Nowadays, virtual learning environments are widely used but digital repositories are not fully integrated yet into the learning process. Our final goal is to provide final users with recommendation systems and reputation schemes that help them to build a true learning community around the institutional repository, taking into account their educational context (i.e. the courses they are enrolled into) and their activity (i.e. system usage by their classmates and teachers). In order to do so, we extend the basic resource concept in a traditional digital repository by adding all the educational context and other elements from end-users’ profiles, thus bridging users, resources and services, and shifting from a library-centered paradigm to a learning-centered one.

ACS Style

Jordi Conesa; Julià Minguillón; M. Elena Rodriguez-Gonzalez. Relationships between Users, Resources and Services in Learning Object Repositories. Programmieren für Ingenieure und Naturwissenschaftler 2012, 127 -132.

AMA Style

Jordi Conesa, Julià Minguillón, M. Elena Rodriguez-Gonzalez. Relationships between Users, Resources and Services in Learning Object Repositories. Programmieren für Ingenieure und Naturwissenschaftler. 2012; ():127-132.

Chicago/Turabian Style

Jordi Conesa; Julià Minguillón; M. Elena Rodriguez-Gonzalez. 2012. "Relationships between Users, Resources and Services in Learning Object Repositories." Programmieren für Ingenieure und Naturwissenschaftler , no. : 127-132.

Conference paper
Published: 01 January 2010 in Computer Vision
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Learning objects have been the promise of providing people with high quality learning resources. Initiatives such as MIT OpenCourseWare, MERLOT and others have shown the real possibilities of creating and sharing knowledge through Internet. Thousands of educational resources are available through learning object repositories. We indeed live in an age of content abundance, and content can be considered as infrastructure for building adaptive and personalized learning paths, promoting both formal and informal learning. Nevertheless, although most educational institutions are adopting a more open approach, publishing huge amounts of educational resources, the reality is that these resources are barely used in other educational contexts. This paradox can be partly explained by the difficulties in adapting such resources with respect to language, e-learning standards and specifications and, finally, granularity. Furthermore, if we want our learners to use and take advantage of learning object repositories, we need to provide them with additional services than just browsing and searching for resources. Social networks can be a first step towards creating an open social community of learning around a topic or a subject. In this paper we discuss and analyze the process of using a learning object repository and building a social network on the top of it, with respect to the information architecture needed to capture and store the interaction between learners and resources in form of learning object metadata

ACS Style

Julià Minguillón; M. Elena Rodríguez; Jordi Conesa; M. Elena Rodriguez-Gonzalez. Extending Learning Objects by Means of Social Networking. Computer Vision 2010, 6483, 220 -229.

AMA Style

Julià Minguillón, M. Elena Rodríguez, Jordi Conesa, M. Elena Rodriguez-Gonzalez. Extending Learning Objects by Means of Social Networking. Computer Vision. 2010; 6483 ():220-229.

Chicago/Turabian Style

Julià Minguillón; M. Elena Rodríguez; Jordi Conesa; M. Elena Rodriguez-Gonzalez. 2010. "Extending Learning Objects by Means of Social Networking." Computer Vision 6483, no. : 220-229.

Conference paper
Published: 01 January 2009 in Communications in Computer and Information Science
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ACS Style

M. Elena Rodriguez-Gonzalez; Jordi Conesa; Miguel Ángel Sicilia. Clarifying the Semantics of Relationships between Learning Objects. Communications in Computer and Information Science 2009, 35 -47.

AMA Style

M. Elena Rodriguez-Gonzalez, Jordi Conesa, Miguel Ángel Sicilia. Clarifying the Semantics of Relationships between Learning Objects. Communications in Computer and Information Science. 2009; ():35-47.

Chicago/Turabian Style

M. Elena Rodriguez-Gonzalez; Jordi Conesa; Miguel Ángel Sicilia. 2009. "Clarifying the Semantics of Relationships between Learning Objects." Communications in Computer and Information Science , no. : 35-47.

Conference paper
Published: 01 January 2008 in 2008 Eighth IEEE International Conference on Advanced Learning Technologies
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In this paper we present LEARN-SQL, a system conforming to the IMS QTI specification that allows on-line learning and assessment of students on SQL skills in an automatic, interactive, informative, scalable and extensible manner.

ACS Style

Alberto Abelló; M. Elena Rodríguez; Toni Urpí; Xavier Burgués; M. José Casany; Carme Martin; Carme Quer; M. Elena Rodriguez-Gonzalez. LEARN-SQL: Automatic Assessment of SQL Based on IMS QTI Specification. 2008 Eighth IEEE International Conference on Advanced Learning Technologies 2008, 592 -593.

AMA Style

Alberto Abelló, M. Elena Rodríguez, Toni Urpí, Xavier Burgués, M. José Casany, Carme Martin, Carme Quer, M. Elena Rodriguez-Gonzalez. LEARN-SQL: Automatic Assessment of SQL Based on IMS QTI Specification. 2008 Eighth IEEE International Conference on Advanced Learning Technologies. 2008; ():592-593.

Chicago/Turabian Style

Alberto Abelló; M. Elena Rodríguez; Toni Urpí; Xavier Burgués; M. José Casany; Carme Martin; Carme Quer; M. Elena Rodriguez-Gonzalez. 2008. "LEARN-SQL: Automatic Assessment of SQL Based on IMS QTI Specification." 2008 Eighth IEEE International Conference on Advanced Learning Technologies , no. : 592-593.

Conference paper
Published: 03 August 2006 in Sixth IEEE International Conference on Advanced Learning Technologies (ICALT'06)
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ACS Style

M. Elena Rodriguez; Montse Serra; Jordi Cabot; Isabel Guitart. Evolution of the Teacher Roles and Figures in E-learning Environments. Sixth IEEE International Conference on Advanced Learning Technologies (ICALT'06) 2006, 1 .

AMA Style

M. Elena Rodriguez, Montse Serra, Jordi Cabot, Isabel Guitart. Evolution of the Teacher Roles and Figures in E-learning Environments. Sixth IEEE International Conference on Advanced Learning Technologies (ICALT'06). 2006; ():1.

Chicago/Turabian Style

M. Elena Rodriguez; Montse Serra; Jordi Cabot; Isabel Guitart. 2006. "Evolution of the Teacher Roles and Figures in E-learning Environments." Sixth IEEE International Conference on Advanced Learning Technologies (ICALT'06) , no. : 1.

Journal article
Published: 31 May 2006 in Data & Knowledge Engineering
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Ontologies have been recognized as a fundamental infrastructure for advanced approaches to Knowledge Management (KM) automation, and the conceptual foundations for them have been discussed in some previous reports. Nonetheless, such conceptual structures should be properly integrated into existing ontological bases, for the practical purpose of providing the required support for the development of intelligent applications. Such applications should ideally integrate KM concepts into a framework of commonsense knowledge with clear computational semantics. In this paper, such an integration work is illustrated through a concrete case study, using the large OpenCyc knowledge base. Concretely, the main elements of the Holsapple and Joshi KM ontology and some existing work on e-learning ontologies are explicitly linked to OpenCyc definitions, providing a framework for the development of functionalities that use the built-in reasoning services of OpenCyc in KM activities. The integration can be used as the point of departure for the engineering of KM-oriented systems that account for a shared understanding of the discipline and rely on public semantics provided by one of the largest open knowledge bases available.

ACS Style

Miguel-Ángel Sicilia; Miltiadis Lytras; Elena Rodríguez; Elena García-Barriocanal. Integrating descriptions of knowledge management learning activities into large ontological structures: A case study. Data & Knowledge Engineering 2006, 57, 111 -121.

AMA Style

Miguel-Ángel Sicilia, Miltiadis Lytras, Elena Rodríguez, Elena García-Barriocanal. Integrating descriptions of knowledge management learning activities into large ontological structures: A case study. Data & Knowledge Engineering. 2006; 57 (2):111-121.

Chicago/Turabian Style

Miguel-Ángel Sicilia; Miltiadis Lytras; Elena Rodríguez; Elena García-Barriocanal. 2006. "Integrating descriptions of knowledge management learning activities into large ontological structures: A case study." Data & Knowledge Engineering 57, no. 2: 111-121.

Conference paper
Published: 29 March 2001 in Computer Vision
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ACS Style

Klaus R. Dittrich; Giovanna Guerrini; Isabella Merlo; Marta Oliva; M. Elena Rodriguez-Gonzalez. Concluding Remarks. Computer Vision 2001, 197 -198.

AMA Style

Klaus R. Dittrich, Giovanna Guerrini, Isabella Merlo, Marta Oliva, M. Elena Rodriguez-Gonzalez. Concluding Remarks. Computer Vision. 2001; ():197-198.

Chicago/Turabian Style

Klaus R. Dittrich; Giovanna Guerrini; Isabella Merlo; Marta Oliva; M. Elena Rodriguez-Gonzalez. 2001. "Concluding Remarks." Computer Vision , no. : 197-198.