@proceedings{697,
title = {Ontological Modelling for Intelligent e-Learning},
author = {Niki Aggelopoulou and Christos Pierrakeas and Alexander Artikis and Dimitris Kalles},
year = {2014},
date = {2014-01-01},
journal = {14th IEEE International Conference on Advanced Learning Technologies (ICALT 2014)},
address = {Athens, Greece},
abstract = {},
keywords = {artificial intelligence {–} applications, distance education, Lifelong learnig, ontologies},
pubstate = {published},
tppubtype = {proceedings}
}

@proceedings{638,
title = {An Instructional Design Methodology for Building Distance Learning Courses},
author = {Georgios Nikolopoulos and Georgia Solomou and Christos Pierrakeas and Achilles Kameas},
year = {2013},
date = {2013-01-01},
journal = {7th International Conference in Open and Distance Learning (ICODL 2013)},
address = {Athens, Greece},
abstract = {

The importance of a distance learning program heavily depends on the type and quality of the provided digital content. The Hellenic Open University (HOU) offers distance learning courses and therefore the volume of the provided digital learning content is significantly large. This fact establishes essential the need for an efficient and effective mechanism for searching, managing and retrieving the educational content. A modern approach for the organization of the digital learning material is the Learning Objects (LOs) paradigm, the use of which is adopted by many e-learning systems and applications nowadays. In this work we try to take advantage of all of the good characteristics of LOs and propose an instructional design methodology that builds courses based on these particular chunks of educational material. The aim of the proposed methodology is exactly to provide guidelines for the design and creation of courses based on LOs. Secondly, it intends to exploit semantic technologies in order to capture and represent the knowledge that is produced during each step. This semantically enriched information, regarding a course, is could be ideally utilized during the creation of LOs.

},
keywords = {Distance Learning, instructional design methodology, learning objects, Lifelong learning, ontologies},
pubstate = {published},
tppubtype = {proceedings}
}

@proceedings{Kalou2012,
title = {An Ontology Model for Building, Classifying and Using Learning Outcomes},
author = {Aikaterini Kalou and Georgia Solomou and Christos Pierrakeas and Achilles Kameas},
url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6268037
http://eeyem.eap.gr/wp-content/uploads/2017/06/9_ICALT2012.pdf},
year = {2012},
date = {2012-05-09},
journal = {12th IEEE International Conference on Advanced Learning Technologies (ICALT 2012)},
publisher = {IEEE Conference Publications},
address = {Rome, Italy},
abstract = {Learning outcomes are statements that should accompany any type of educational material intended for lifelong learning. These statements deliver important information, which works as an indicator for students in the process of learning. However, in order for this information to be further utilizable within the context of intelligent e-learning applications, a more fine-grained definition and structure should be adopted. Having these in mind, we initially assign a strict and rather technical definition for the notion of learning outcomes, which is fully aligned, though, with their educational purpose. We then propose an ontological model for their representation and classification, which fully adheres to this definition. Our ultimate goal is to provide the mean for exploiting all aspects of knowledge implied by such statements within intelligent applications. To bear out this possibility, we apply our model to a selected piece of educational material provided by the Hellenic Open University.},
keywords = {Bloom Taxonomy, learning outcomes, Lifelong learning, ontologies},
pubstate = {published},
tppubtype = {proceedings}
}

@proceedings{Pierrakeas2012,
title = {An Ontological Approach in Learning Programming Languages},
author = {Christos Pierrakeas and Georgia Solomou and Achilles Kameas},
url = {http://eeyem.eap.gr/wp-content/uploads/2017/06/14_PCI2012.pdf},
year = {2012},
date = {2012-05-03},
journal = {PCI 2012 – 16th Panhellenic Conference on Informatics},
publisher = {IEEE Computer Society Conference Publishing Services.},
address = {Piraeus, Greece},
abstract = {The learning of programming languages requires the student to develop systematic representations of the lexical constructs and semantic principles of the languages. At the same time, tutors are expected to develop the appropriate training content. In this paper we propose the combination of two techniques to make the above tasks more efficient. Firstly, we propose to use Learning Objects (LOs), for the organization of educational content. At the same time, ontologies are rich knowledge representation structures that can be utilized for modeling the domain concepts. We then present how we can take advantage of the ontological models for two very popular programming languages – that is Java and C – in an attempt to provide tutors with the possibility to better organize their educational material.},
keywords = {C, distance education, java, learning objects, ontologies, programming languages},
pubstate = {published},
tppubtype = {proceedings}
}

@proceedings{Panagiotopoulos2012b,
title = {An Ontological Approach for Domain Knowledge Modeling and Management in E-Learning Systems},
author = {Ioannis Panagiotopoulos and Aikaterini Kalou and Christos Pierrakeas and Achilles Kameas},
url = {link.springer.com/chapter/10.1007/978-3-642-33412-2_10
http://eeyem.eap.gr/wp-content/uploads/2017/06/13_AIeIA2012.pdf
},
year = {2012},
date = {2012-04-12},
journal = {1st AI in Education Workshop: Innovations and Applications (AIeIA 2012) in: 8th AIAI (Artificial Intelligence Applications and Innovations) Confence},
volume = {IFIP AICT 382},
publisher = {Springer Berlin Heidelberg},
address = {Halkidiki, Greece},
abstract = {One of the most important tasks in the process of designing educational material for distance learning is the representation and modeling of the cognitive domain to which the material refers. However, this representation should be formal, complete and reusable in order to be used by intelligent tutoring system applications, other knowledge domains or tutors. In the context of this work, we propose a methodology that relies on the notion of ontology so as to represent the knowledge domain. Moreover, this methodology has been applied to the educational material of the Hellenic Open University.},
keywords = {E-learning Systems, Knowledge modeling, Knowledge representation, ontologies, Ontology Development, Protege},
pubstate = {published},
tppubtype = {proceedings}
}

@proceedings{Kouneli2012,
title = {Modeling the Knowledge Domain of the Java Programming Language as an Ontology},
author = {Angeliki Kouneli and Georgia Solomou and Christos Pierrakeas and Achilles Kameas},
url = {http://eeyem.eap.gr/wp-content/uploads/2017/06/11_ICWL2012.pdf},
year = {2012},
date = {2012-04-12},
journal = {11th International Conference in Web-Based Learning (ICWL 2012)},
volume = {LNCS 7558},
publisher = {Springer - Verlag Berlin Heidelberg},
address = {Sinaia, Romania},
abstract = {Java is a very popular programming language and many study programs in Informatics worldwide include courses particularly designed for its learning. It is considered as the best paradigm for introducing students with object-oriented programming and concepts. Considering Java’s popularity, we initially make an attempt to model this language by using a quite expressing and rich knowledge representation structure, like is ontology. Our aim is to capture the semantics of Java concepts in a way that would render them utilizable by intelligent e-learning applications. Because the construction of an ontology is not an easy task, we follow very specific steps when building the Java ontology. We then take advantage of an already implemented model describing the structure of learning outcomes and combine it with our ontology, with a view to offer a more effective way in organizing the course of Java in the Hellenic Open University.},
keywords = {distance education, java, learning outcomes, ontologies, programming languages},
pubstate = {published},
tppubtype = {proceedings}
}

@proceedings{Bagiampou2012b,
title = {A Use Case Diagrams Ontology That Can Be Used as Common Reference for Software Engineering Education},
author = {Maria Bagiampou and Achilles Kameas},
url = {http://eeyem.eap.gr/wp-content/uploads/2017/06/21.A-Use-Case-Diagrams-Ontology-That-Can-Be-Used-as-Common-Reference-for-Software-Engineering-Education.pdf},
year = {2012},
date = {2012-04-02},
journal = {IEEE International Conference on Intelligent Systems},
address = {Sofia, Bulgaria},
abstract = {In recent years, several studies have shown that ontologies and technologies based on ontologies can be used to bridge the worlds of practice and education. These approaches are considered very important fields of educational technology research. In this paper, we present a domain ontology concerning Use Case Diagrams (UCD) that we developed in an attempt to provide common reference for the creators of training / educational material in a Software Engineering course. For its construction we used an approach that combines certain existing methodologies and includes the collaboration of expert software engineers, who eventually evaluated positively the ontology to cover adequately all aspects of UCD design. The proposed ontology can be used either as part of an experimental e-learning application for the description and management of competencies, learning goals and learning material about the cognitive field of Object-Oriented Analysis, or as a design reference for UCD terms and properties. In this paper we shortly describe our ontology and the methodology we used to create it.},
keywords = {Education, ontologies, Software Engineering, Use Case Diagrams},
pubstate = {published},
tppubtype = {proceedings}
}

@proceedings{Panagiotopoulos2011,
title = {An Alignable User Profile Ontology for Ambient Intelligence Environments},
author = {Ioannis Panagiotopoulos and Lambrini Seremeti and Achilles Kameas},
url = {http://eeyem.eap.gr/wp-content/uploads/2017/06/11.PID1817603.pdf},
year = {2011},
date = {2011-06-24},
journal = {7th IEEE/AAAI International Conference on Intelligent Environments (IE11)},
address = {Nottingham, UK},
abstract = {
One of the principal objectives of today’s ambient intelligence environments is to provide users with services according to their activity, i.e. preferences in order to accomplish a specific user goal. For this purpose, miscellaneous user information must be collected and structured into user profiles. These profiles offer the advantage of being easily enriched and exploitable by the environment, in order to deliver to the user, at any moment and at any place, the best fitted service, with regard to his activity. In this paper we present an ontology-based user profile model which provides the static data about a user but also the context of the user in a given situation in real time.},
keywords = {activity spheres, ambient intelligence, ontologies, user profile},
pubstate = {published},
tppubtype = {proceedings}
}