adult education Assessment communities of practice Digital Educational content distance education Distance Learning E-commerce E-learning empirical research higher education intelligent tutoring systems Learning Analytics learning objects learning outcomes Lifelong learning MOOC Moodle ontologies Ontology Open and Distance Learning Personalized Learning Scratch εξ αποστάσεως εκπαίδευση οντολογίες ψηφιακό εκπαιδευτικό υλικό
2015 |
Antonelou, Georgia; Karachristos, Christoforos; Stavropoulos, Elias; Verykios, Vassilios S Enhancing self-learning in a Web-Based Course using Predefined Learning Paths Inproceedings In Proc. of the 8th annual International Conference of Education, Research and Innovation (ICERI 2015), pp. 3930-3939, Seville, Spain, 2015, ISBN: 978-84-608-2657-6. Abstract | Links | BibTeX | Ετικέτες: Distance Learning, Elias Stavropoulos, Moodle, Personalized Learning, Predefined Learning Path, Self-Learning, Vassilios S. Verykios Adult Learning @inproceedings{Antonelou2015, title = {Enhancing self-learning in a Web-Based Course using Predefined Learning Paths}, author = {Georgia Antonelou and Christoforos Karachristos and Elias Stavropoulos and Vassilios S. Verykios}, url = {http://eeyem.eap.gr/wp-content/uploads/2017/06/ICERI2016Antonelou.pdf}, isbn = {978-84-608-2657-6}, year = {2015}, date = {2015-11-01}, booktitle = {In Proc. of the 8th annual International Conference of Education, Research and Innovation (ICERI 2015)}, pages = {3930-3939}, address = {Seville, Spain}, abstract = {In this paper we propose a general framework that composes Predefined Learning Paths, i.e., predefined sequences of learning steps, making up a graph of learning "nodes" followed by potential learners. Predefined Learning Paths were developed to support not only potential designers (tutors), but also to provide learners (students) with both ad-hoc learning and supportive activities that are based on sound pedagogical strategies. Thus, the goal of our work is three-fold: (i) to support potential designers to enrich their teaching process (teaching procedure), (ii) to effectively support students in their study (especially in the framework of Distance and Adult Education), and (iii) to promote good practices by employing e-tools that are easy to use and understand. We have implemented Predefined Learning Paths by effectively and efficiently integrating e-learning tools that are available in LMS Moodle. Finally, we present preliminary evaluation results and we demonstrate our thoughts for future work.}, keywords = {Distance Learning, Elias Stavropoulos, Moodle, Personalized Learning, Predefined Learning Path, Self-Learning, Vassilios S. Verykios Adult Learning}, pubstate = {published}, tppubtype = {inproceedings} } In this paper we propose a general framework that composes Predefined Learning Paths, i.e., predefined sequences of learning steps, making up a graph of learning "nodes" followed by potential learners. Predefined Learning Paths were developed to support not only potential designers (tutors), but also to provide learners (students) with both ad-hoc learning and supportive activities that are based on sound pedagogical strategies. Thus, the goal of our work is three-fold: (i) to support potential designers to enrich their teaching process (teaching procedure), (ii) to effectively support students in their study (especially in the framework of Distance and Adult Education), and (iii) to promote good practices by employing e-tools that are easy to use and understand. We have implemented Predefined Learning Paths by effectively and efficiently integrating e-learning tools that are available in LMS Moodle. Finally, we present preliminary evaluation results and we demonstrate our thoughts for future work. |
2012 |
Panagiotopoulos, Ioannis; Kalou, Aikaterini; Pierrakeas, Christos; Kameas, Achilles Springer Berlin Heidelberg, Halkidiki, Greece, IFIP AICT 381 , 2012. Abstract | Links | BibTeX | Ετικέτες: intelligent tutoring systems, Ontology, Personalized Learning, stereotypes, student model @proceedings{Panagiotopoulos2012b, title = {An Ontology-Based Model for Student Representation in Intelligent Tutoring Systems for Distance Learning}, author = {Ioannis Panagiotopoulos and Aikaterini Kalou and Christos Pierrakeas and Achilles Kameas}, url = {http://link.springer.com/chapter/10.1007/978-3-642-33409-2_31 http://eeyem.eap.gr/wp-content/uploads/2017/06/12_AIAI2012.pdf}, year = {2012}, date = {2012-05-08}, journal = {8th Artificial Intelligence Applications and Innovations (AIAI 2012).}, volume = {IFIP AICT 381}, publisher = {Springer Berlin Heidelberg}, address = {Halkidiki, Greece}, abstract = {An Intelligent Tutoring System (ITS) offers personalized education to each student in accordance with his/her learning preferences and his/her background. One of the most fundamental components of an ITS is the student model, that contains all the information about a student such as demographic information, learning style and academic performance. This information enables the system to be fully adapted to the student. Our research work intends to propose a student model and enhance it with semantics by developing (or via) an ontology in order to be exploitable effectively within an ITS, for example as a domain-independent vocabulary for the communication between intelligent agents. The ontology schema consists of two main taxonomies: (a) student’s academic information and (b) student’s personal information. The characteristics of the student that have been included in the student model ontology were derived from an empirical study on a sample of students.}, keywords = {intelligent tutoring systems, Ontology, Personalized Learning, stereotypes, student model}, pubstate = {published}, tppubtype = {proceedings} } An Intelligent Tutoring System (ITS) offers personalized education to each student in accordance with his/her learning preferences and his/her background. One of the most fundamental components of an ITS is the student model, that contains all the information about a student such as demographic information, learning style and academic performance. This information enables the system to be fully adapted to the student. Our research work intends to propose a student model and enhance it with semantics by developing (or via) an ontology in order to be exploitable effectively within an ITS, for example as a domain-independent vocabulary for the communication between intelligent agents. The ontology schema consists of two main taxonomies: (a) student’s academic information and (b) student’s personal information. The characteristics of the student that have been included in the student model ontology were derived from an empirical study on a sample of students. |
Panagiotopoulos, Ioannis; Kalou, Aikaterini; Pierrakeas, Christos; Kameas, Achilles Adult Student Modeling for Intelligent Distance Learning Systems Proceeding Halkidiki, Greece, 2012. Abstract | Links | BibTeX | Ετικέτες: intelligent tutoring systems, Learner Model, Ontology, Personalized Learning, stereotypes @proceedings{Panagiotopoulos2012b, title = {Adult Student Modeling for Intelligent Distance Learning Systems}, author = {Ioannis Panagiotopoulos and Aikaterini Kalou and Christos Pierrakeas and Achilles Kameas}, url = {http://eeyem.eap.gr/wp-content/uploads/2017/06/17_eiseec_2013.pdf}, year = {2012}, date = {2012-04-11}, journal = {Special Issue on AIAI 2012 of the International Journal of Engineering Intelligent Systems for Electrical Engineering and Communications (EISEEC)}, address = {Halkidiki, Greece}, abstract = {One of the most important components in a learning support system is the learner model, as it contains useful information about an individual such as learning preferences and academic performance. The goal of the research presented in this paper is to define how a learner model can be distributed with the help of semantic web technologies, based on stereotypes as a useful mechanism for the initialization of an intelligent learning system. These stereotypes have been derived from an empirical study on a sample of adult learners at a distance learning University, while the proposed model also reflects features from several standards for a learner modeling. Finally, a web application is presented, in order to evaluate the learner model and test the automatic categorization of learners into stereotypes according to their basic characteristics.}, keywords = {intelligent tutoring systems, Learner Model, Ontology, Personalized Learning, stereotypes}, pubstate = {published}, tppubtype = {proceedings} } One of the most important components in a learning support system is the learner model, as it contains useful information about an individual such as learning preferences and academic performance. The goal of the research presented in this paper is to define how a learner model can be distributed with the help of semantic web technologies, based on stereotypes as a useful mechanism for the initialization of an intelligent learning system. These stereotypes have been derived from an empirical study on a sample of adult learners at a distance learning University, while the proposed model also reflects features from several standards for a learner modeling. Finally, a web application is presented, in order to evaluate the learner model and test the automatic categorization of learners into stereotypes according to their basic characteristics. |