@inproceedings{Kouvara2021,
title = {THE MASSIVE OPEN ONLINE COURSES OF THE HELLENIC OPEN UNIVERSITY: CONFIGURATION AND ANALYSIS OF SPECIFICATIONS FOR THE SELECTION OF THE MOST SUITABLE PLATFORM},
author = {T. Kouvara and C. Karachristos and D. Karakatsoulis and T. Orfanoudakis and D. Sideris},
url = {https://eeyem.eap.gr/wp-content/uploads/2022/06/29.pdf},
isbn = {-},
year = {2021},
date = {2021-01-01},
booktitle = {ICERI2021},
pages = {2830-2836},
keywords = {comparative study, Distance Learning, Lifelong learning, MOOC, Moodle, Open edΧ},
pubstate = {published},
tppubtype = {inproceedings}
}

@inproceedings{Verykios2019b,
title = {The Pursuit of Patterns in Educational Data Mining as a Threat to Student Privacy},
author = {Kyriaki H. Kyritsi and Vassilios Zorkadis and Elias C. Stavropoulos and Vassilios S. Verykios},
url = {https://eeyem.eap.gr/wp-content/uploads/2019/12/502-4024-1-PB.pdf},
doi = {http://doi.org/10.5334/jime.502},
year = {2019},
date = {2019-05-27},
booktitle = {Journal of Interactive Media in Education},
volume = {1},
number = {2},
pages = {1–10},
abstract = {Recent technological advances have led to tremendous capacities for collecting, storing and analyzing data being created at an ever-increasing speed from diverse sources. Academic institutions which offer open and distance learning programs, such as the Hellenic Open University, can benefit from big data relating to its students’ information and communication systems and the use of modern techniques and tools of big data analytics provided that the student’s right to privacy is not compromised. The balance between data mining and maintaining privacy can be reached through anonymisation methods but on the other hand this approach raises technical problems such as the loss of a certain amount of information found in the original data. Considering the learning process as a framework of interacting roles and factors, the discovery of patterns in that system can be really useful and beneficial firstly for the learners and furthermore, the ability to publish and share these results would be very helpful for the whole academic institution},
keywords = {anonymization, data publishing, Distance Learning, Learning Analytics, privacy, statistical disclosure control},
pubstate = {published},
tppubtype = {inproceedings}
}

@conference{Kyritsi2018,
title = {Privacy Issues in Learning Analytics},
author = {Kyriaki Kyritsi and Vasilios Zorkadis and Elias C. Stavropoulos, and Vassilios S. Verykios},
editor = {George Ubachs and Lizzie Konings},
url = {https://eeyem.eap.gr/wp-content/uploads/2019/12/Kyritsi_ProceedingsOOFHEC2018.pdf},
isbn = {978-90-79730-35-3},
year = {2018},
date = {2018-10-10},
booktitle = { Online, Open and Flexible Higher Education Conference 2018 (EADTU annual conference 2018)},
pages = {218-232},
address = {Aarhus Denmark},
abstract = {Today’s technological advances have led to tremendous advances in collecting, storing and analyzing data that come from diverse sources of information and may be represented in a wide variety of different formats (texts, photos, videos and many more). The term which perfectly describes this milestone in the history of computing is called big data and the task of analyzing these enormous amounts of data is called big data analytics. Academic institutions which offer open and distance learning programs such as the Hellenic Open University can profit from big data and the use of big data analytics by integrating it in their organizational support systems thus reflecting on their overall performance and planning competitive and attractive educational programs as well as improving in the delivery of their services. In the individual level, the modern lifestyle with the numerous networked devices and applications implies that all activities we are engaged in leave behind an imprint or a digital footprint. Combining thoroughly this variety of information creates a unique social genome (Kum et. al., 2014) for each and every one of us and understanding how to interpret it will bring major breakthroughs in many areas of our society such as improvements in social services, health and education. On the flip side, there are certain disadvantages concerning privacy issues arising from the inappropriate and illegitimate use of data containing personal information and ethical concerns about the basic right of individuals to have control over the amount and the extent of information they are willing to share. The systematic solution to this controversy is the design, application and evaluation of privacy-preserving data publishing methods in order to assure that the confidentiality of the subjects of projects is not compromised and a balance between the utility of the data and the privacy is accomplished.},
keywords = {anonymization, data publishing, Distance Learning, ethical issues, Learning Analytics, privacy, statistical disclosure control},
pubstate = {published},
tppubtype = {conference}
}

@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}
}

@proceedings{529,
title = {A Correlation Verb (CorrVerb) Ontology for Object Properties Specification within Knowledge Domain Representations},
author = {Christos Pierrakeas and Ioannis Panagiotopoulos and Achilles Kameas},
year = {2013},
date = {2013-01-01},
journal = {6th Balkan Conference in Informatics (BCI 2013)},
address = {Thessaloniki, Greece},
abstract = {},
keywords = {Distance Learning, Domain Knowledge Representation, e- Learning, Formal Ontology, SUMO, WordNet},
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{Nikolopoulos2012b,
title = {Creating a Learning Object metadata profile for Distance Learning: An ontological approach},
author = {Georgios Nikolopoulos and Aikaterini Kalou and Christos Pierrakeas and Achilles Kameas},
url = {http://link.springer.com/chapter/10.1007%2F978-3-642-35233-1_4
http://eeyem.eap.gr/wp-content/uploads/2017/06/15_MTSR2012.pdf},
year = {2012},
date = {2012-03-07},
journal = {6th Metadata and Semantics Research Conference (MTSR 2012)},
publisher = {Springer Berlin Heidelberg},
address = {Cádiz, Spain},
abstract = {The importance of Learning Objects (LOs) in the learning process - especially in the case of distance education - has been underlined significantly in the literature. The ability of administrating LOs in terms of accessibility, reusability and interoperability seems to be ensured by adopting an appropriate metadata schema which fully and adequately describes them. Several metadata standards have been developed such as DC (Dublin Core) and IEEE-LOM. In the context of our work, we explore them and conclude that none of these standards does completely meet the requirements of distance learning material. Therefore, we propose a new metadata schema that is actually an application profile of the widely adopted IEEE LOM and has special orientation in distance education. We also enrich this subset with some additional attributes that represent concepts like learning outcomes. Then, we create an ontological representation of this new educational schema with a view to improving the potential of LOs’ discovery and retrieval within an intelligent e-learning system.},
keywords = {Distance Learning, ontological approach},
pubstate = {published},
tppubtype = {proceedings}
}

@proceedings{Nikolopoulos2012,
title = {Modeling the Characteristics of a Learning Object for Use within e-Learning Applications Πρωτεύουσες καρτέλες},
author = {Georgios Nikolopoulos and Georgia Solomou and Christos Pierrakeas and Achilles Kameas},
url = {http://dl.acm.org/citation.cfm?id=2371338
http://eeyem.eap.gr/wp-content/uploads/2017/06/10_BCI2012.pdf},
year = {2012},
date = {2012-02-16},
journal = {5th Balkan Conference in Informatics},
publisher = {ACM New York},
address = {Novi Sad, Serbia},
abstract = {Educational content plays a significant role in the process of delivering knowledge, that’s why it needs to be designed carefully, following designated principles. Learning Objects (LOs) constitute a novel approach in the educational content’s organization, bearing features that if effectively used could lead to enhanced e-learning services. What is missing from literature, though, is a common agreement about the LO’s attributes and structure. For this reason, we initially try to specify the main characteristics of a LO and determine its functionality, especially in the context of distance education. Having realized its fundamental role in the instructional design process, we make explicit its correlation with educational objectives and other aspects of learning. Finally, in an attempt to capture all LO’s characteristics and make them utilizable by e-learning applications, we propose a metadata schema, reflecting all features of a LO, as described in this work.},
keywords = {Distance Learning, E-learning, Educational Metadata, learning objects},
pubstate = {published},
tppubtype = {proceedings}
}