Publications

@article{2022,

title = {Personalizing Environmental Awareness through Smartphones Using AHP and PROMETHEE II},

author = {Akrivi Krouska and Katerina Kabassi and Christos Troussas and Cleo Sgouropoulou},

url = {http://dx.doi.org/10.3390/fi14020066},

doi = {10.3390/fi14020066},

issn = {1999-5903},

year  = {2022},

date = {2022-02-01},

journal = {Future Internet},

volume = {14},

number = {2},

pages = {66},

publisher = {MDPI AG},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{2022c,

title = {Evaluating Remote Task Assignment of an Online Engineering Module through Data Mining in a Virtual Communication Platform Environment},

author = {Zoe Kanetaki and Constantinos Stergiou and Georgios Bekas and Christos Troussas and Cleo Sgouropoulou},

url = {http://dx.doi.org/10.3390/electronics11010158},

doi = {10.3390/electronics11010158},

issn = {2079-9292},

year  = {2022},

date = {2022-01-01},

journal = {Electronics},

volume = {11},

number = {1},

pages = {158},

publisher = {MDPI AG},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{2022b,

title = {Enriching Mobile Learning Software with Interactive Activities and Motivational Feedback for Advancing Users’ High-Level Cognitive Skills},

author = {Christos Troussas and Akrivi Krouska and Cleo Sgouropoulou},

url = {http://dx.doi.org/10.3390/computers11020018},

doi = {10.3390/computers11020018},

issn = {2073-431X},

year  = {2022},

date = {2022-01-01},

journal = {Computers},

volume = {11},

number = {2},

pages = {18},

publisher = {MDPI AG},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Kanetaki_Stergiou_Bekas_Troussas_Sgouropoulou_2021,

title = {Analysis of Engineering Student Data in Online Higher Education During the COVID-19 Pandemic},

author = {Zoe Kanetaki and Constantinos Stergiou and Georgios Bekas and Christos Troussas and Cleo Sgouropoulou},

url = {https://online-journals.org/index.php/i-jep/article/view/23259},

doi = {10.3991/ijep.v11i6.23259},

year  = {2021},

date = {2021-12-01},

journal = {International Journal of Engineering Pedagogy (iJEP)},

volume = {11},

number = {6},

pages = {pp. 27–49},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Krouska2021b,

title = {A Cognitive Diagnostic Module Based on the Repair Theory for a Personalized User Experience in E-Learning Software},

author = {A. Krouska and Ch. Troussas and C. Sgouropoulou},

doi = {https://doi.org/10.3390/computers10110140},

year  = {2021},

date = {2021-10-29},

urldate = {2021-10-29},

journal = {Computers },

volume = {10},

number = {11},

pages = {140},

abstract = {This paper presents a novel cognitive diagnostic module which is incorporated in e-learning software for the tutoring of the markup language HTML. The system is responsible for detecting the learners’ cognitive bugs and delivering personalized guidance. The novelty of this approach is that it is based on the Repair theory that incorporates additional features, such as student negligence and test completion times, in its diagnostic mechanism; also, it employs a recommender module that suggests students optimal learning paths based on their misconceptions using descriptive test feedback and adaptability of learning content. Considering the Repair theory, the diagnostic mechanism uses a library of error correction rules to explain the cause of errors observed by the student during the assessment. This library covers common errors, creating a hypothesis space in that way. Therefore, the test items are expanded, so that they belong to the hypothesis space. Both the system and the cognitive diagnostic tool were evaluated with promising results, showing that they offer a personalized experience to learners.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Troussas2021e,

title = {Enhancing human-computer interaction in digital repositories through a MCDA-based recommender system},

author = {Ch. Troussas and A. Krouska and C. Sgouropoulou},

doi = {https://doi.org/10.1155/2021/7213246},

year  = {2021},

date = {2021-10-19},

journal = {Advances in Human-Computer Interaction},

pages = {7 pages},

abstract = {Digital repositories contain a large amount of content, which is available to heterogeneous groups of people. As such, in many cases people encounter difficulties in finding specific content which is related to their preferences. In view of this compelling need and towards advancing human-computer interaction, this paper presents a recommender system which is incorporated in a digital repository. The recommender system is designed using multiple-criteria decision analysis (MCDA) and more specifically the weighted sum model (WSM) in order to refine the delivered content to the users. It also considers several users’ characteristics (their preferences as depicted by the content they visited or searched and by the frequency of searches/visits) and features of the content (content types and traffic). The recommender system outputs the suggestions of content to users based on their preferences and interests. The presented recommender system was evaluated by real users, and the results show a high degree of accuracy in the recommended content and satisfaction by users.},

note = {Article ID 7213246 },

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Krouska2021,

title = {Mobile game-based learning as a solution in COVID-19 era: Modeling the pedagogical affordance and student interactions},

author = {A. Krouska and Ch. Troussas and C. Sgouropoulou},

doi = {https://doi.org/10.1007/s10639-021-10672-3},

year  = {2021},

date = {2021-07-23},

journal = {Education and Information Technologies},

abstract = {The closure of educational institutions due to the COVID-19 pandemic leads imperatively to the utilization of technological advances and the Internet for enabling the continuity of learning. To this direction, Mobile Game-based Learning (MGbL) can be beneficial to teaching and learning; since, from technological perspective, most students prefer to use their mobile devices, such as smartphones or tablets, and from pedagogical perspective, incorporating gaming in educational process can boost students’ motivation for learning and improve their learning outcomes. Hence, this study investigates learners’ intention to use MGbL as an alternative educational practice during the COVID-19 pandemic, by modeling the pedagogical affordance of this technology and student interactions with it. As a testbed for this research, a MGbL application was used for the instruction of the programming language C# in higher education, during the lockdown period of 2020. The findings reveal that the MGbL technology has a significant and positive impact on student engagement and academic performance.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Giannakas2021,

title = {A deep learning classification framework for early prediction of team-based academic performance},

author = {F. Giannakas and Ch. Troussas and I. Voyiatzis and C. Sgouropoulou},

doi = {https://doi.org/10.1016/j.asoc.2021.107355},

year  = {2021},

date = {2021-07-01},

journal = {Applied Soft Computing},

volume = {106},

pages = {107355},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Papakostas2021,

title = {Measuring User Experience, Usability and Interactivity of a Personalized Mobile Augmented Reality Training System},

author = {Ch. Papakostas and Ch. Troussas and A. Krouska and C. Sgouropoulou},

doi = {https://doi.org/10.3390/s21113888},

year  = {2021},

date = {2021-06-04},

journal = {Sensors},

volume = {21},

number = {11},

pages = {3888},

abstract = {Innovative technology has been an important part of firefighting, as it advances firefighters’ safety and effectiveness. Prior research has examined the implementation of training systems using augmented reality (AR) in other domains, such as welding, aviation, army, and mathematics, offering significant pedagogical affordances. Nevertheless, firefighting training systems using AR are still an under-researched area. The increasing penetration of AR for training is the driving force behind this study, and the scope is to analyze the main aspects affecting the acceptance of AR by firefighters. The current research uses a technology acceptance model, extended by the external constructs of perceived interactivity and personalization, to consider both the system and individual level. The proposed model was evaluated by a sample of 200 users, and the results show that both the external variables of perceived interactivity and perceived personalization are prerequisite factors in extending the TAM model. The findings reveal that the usability is the strongest predictor of firefighters’ behavioral intentions to use the AR system, followed by the ease of use with smaller, yet meaningful, direct and indirect effects on firefighters’ intentions. The identified acceptance factors help AR developers enhance the firefighters’ experience in training operations.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Troussas2021b,

title = {Improving Learner-Computer Interaction through Intelligent Learning Material Delivery Using Instructional Design Modeling},

author = {Ch. Troussas and A. Krouska and C. Sgouropoulou},

doi = {https://doi.org/10.3390/e23060668},

year  = {2021},

date = {2021-05-26},

urldate = {2021-05-26},

journal = {Entropy},

volume = {23},

number = {6},

pages = {668},

abstract = {This paper describes an innovative and sophisticated approach for improving learner-computer interaction in the tutoring of Java programming through the delivery of adequate learning material to learners. To achieve this, an instructional theory and intelligent techniques are combined, namely the Component Display Theory along with content-based filtering and multiple-criteria decision analysis, with the intention of providing personalized learning material and thus, improving student interaction. Until now, the majority of the research efforts mainly focus on adapting the presentation of learning material based on students’ characteristics. As such, there is free space for researching issues like delivering the appropriate type of learning material, in order to maintain the pedagogical affordance of the educational software. The blending of instructional design theories and sophisticated techniques can offer a more personalized and adaptive learning experience to learners of computer programming. The paper presents a fully operating intelligent educational software. It merges pedagogical and technological approaches for sophisticated learning material delivery to students. Moreover, it was used by undergraduate university students to learn Java programming for a semester during the COVID-19 lockdown. The findings of the evaluation showed that the presented way for delivering the Java learning material surpassed other approaches incorporating merely instructional models or intelligent tools, in terms of satisfaction and knowledge acquisition.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Troussas2021d,

title = {Collaborative activities recommendation based on students’ collaborative learning styles using ANN and WSM},

author = {Ch. Troussas and F. Giannakas and C. Sgouropoulou and I. Voyiatzis},

doi = {10.1080/10494820.2020.1761835},

year  = {2021},

date = {2021-05-12},

journal = {Interactive Learning Environments},

abstract = {Computer-Supported Collaborative Learning is a promising innovation that ameliorates tutoring through modern technologies. However, the way of recommending collaborative activities to learners, by taking into account their learning needs and preferences, is an important issue of increasing interest. In this context, this paper presents a framework for providing recommendations of collaborative activities to learners by employing an Artificial Neural Network (ANN) and the Weighted Sum Model (WSM). In our approach, the Gardner and Korth framework is employed to identify the dimensions of the learners’ collaborative learning styles. For each dimension, different weights are assigned and used as input data for the ANN. Then, the WSM and the activation function determine the output vector by mapping the resulting values. The final output of the ANN is a different percentage of collaborative activities in which learners can participate. This output is used to recommend the activities to the learners. As a testbed for our research, we have developed an intelligent tutoring system for the programming language “Java”. Our system was evaluated using an established framework and the statistical hypothesis test. The results show a high degree of pedagogical affordance and usefulness of our approach as well as its positive impact on learning.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Troussas2021,

title = {A Novel Teaching Strategy Through Adaptive Learning Activities for Computer Programming},

author = {Ch. Troussas and A. Krouska and C. Sgouropoulou},

doi = {10.1109/TE.2020.3012744},

year  = {2021},

date = {2021-05-02},

journal = {IEEE Transactions on Education},

volume = {64},

number = {2},

pages = {103-109},

abstract = {Contribution: This article presents the instruction of computer programming using adaptive learning activities considering students' cognitive skills based on the learning theory of the Revised Bloom Taxonomy (RBT). To achieve this, the system converts students' knowledge level to fuzzy weights, and using rule-based decision making, delivers adequate learning activities regarding their kind and complexity degree. Background: Tutoring through adaptive learning activities can be a powerful tool to support learners in practical courses, like computer programming. However, published results from pertinent literature are not oriented to the adaptivity of the domain knowledge in terms of the volume, kind, and complexity of the learning activities delivered to students. There is scope for a lot of improvement to this direction. Intended Outcomes: Combining learning theories with adaptive tutoring enhances student-centered learning, promotes student engagement, and improves knowledge acquisition. Application Design: An adaptive tutoring system was developed for supporting undergraduate students in the C# programming language course for an academic semester. The system delivers adaptive learning activities to students' cognitive skills using the technology of fuzzy weights in a rule-based decision-making module and the learning theory of a RBT for designing the learning material. Findings: At the end of the academic semester, students' data have been collected and a detailed evaluation was conducted. The results showed that the presented approach outperforms others which lack adaptivity in domain knowledge and learning theories, improving significantly the students' learning outcomes.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Troussas2021c,

title = {Impact of social networking for advancing learners’ knowledge in E-learning environments},

author = {Ch. Troussas and A. Krouska and C. Sgouropoulou},

doi = {https://doi.org/10.1007/s10639-021-10483-6 },

year  = {2021},

date = {2021-03-02},

journal = {Education and Information Technologies},

volume = {26},

pages = {4285–4305},

abstract = {Social networking has modernized digital education through the provision of novel functionalities, such as reacting, commenting, motivation or group formation. In the light of the new developments, this paper presents SNAKE (Social Networking for Advancing Knowledge in E-learning environment), which is an e-learning software incorporating social characteristics for the tutoring of computer programming. However, investigating the impact of e-learning software holding social characteristics is yet a quite under-researched area. To this end, an extensive exploration of SNAKE has been conducted which examined different factors affecting social networking-based learning. The population of this study included 200 undergraduate students of computer science. To analyze the disposable data, the structural equation modeling was utilized. Upon analysis and structural model validities, the experimentation led to an extended Technology Acceptance Model (TAM) utilized for estimating the impact of the various variables. In more detail, the research model consisted of the TAM core constructs and three external variables. Concluding, the study confirmed that the model adequately explained causal relationships between variables and presented direct and indirect significant impacts of them on SNAKE which can promote learners’ better academic performance and knowledge acquisition.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Papakostas2021b,

title = {Exploration of Augmented Reality in Spatial Abilities Training: A Systematic Literature Review for the Last Decade},

author = {Ch. Papakostas and Ch. Troussas and A. Krouska and Cleo Sgouropoulou},

doi = {10.15388/infedu.2021.06. 24.},

year  = {2021},

date = {2021-03-01},

journal = {Informatics in Education},

volume = {20},

number = {1},

pages = {107-130},

abstract = {This review paper presents a systematic literature review on the use of Augmented Reality (AR) in engineering education, and specifically in student’s spatial ability training, for the last decade. Researchers have explored the benefits of AR, and its application has been of increasing interest in all levels of education. Engineering students tend to have difficulties in acquiring visualization skills, and hence, AR is gaining momentum in enhancing students’ learning achievements. This paper aims to present valuable information to researchers, tutors and software developers of learning technology systems concerning the advantages and limitations of AR in spatial ability training, the incorporation of adaptivity and personalization in AR applications as well as the aspects of spatial ability having been evaluated using AR and the prevalent evaluation methods for AR applications. To this direction, a total of thirty-two (32) studies were reviewed, having been published since 2010. The findings reveal an increase in the number of studies during the last three years. One major conclusion is the improvement of learners’ spatial ability using AR in educational settings, and the noted challenge is the need for more learning content. One research gap that has been identified is the lack of personalization in the developed applications, offering space for future research. Concluding, this area is under-researched, and thus, there is scope for a lot of improvement.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Papakostas2021c,

title = {User acceptance of augmented reality welding simulator in engineering training},

author = {Ch. Papakostas and Ch. Troussas and A. Krouska and C. Sgouropoulou},

doi = {https://doi.org/10.1007/s10639-020-10418-7},

year  = {2021},

date = {2021-01-07},

journal = {Education and Information Technologies},

abstract = {The integration of Augmented Reality (AR) in welding training is considered to increase the efficiency, security and time gain in operations, reducing consumable and infrastructures costs. Prior research has examined the integration of AR-simulation in applications, like medical operations or aviation, showing the need for greater usability of these systems. However, research on AR integration in welding training is yet limited. It can help new welders learn effectively and be prepared to work in the industry. The motivation of this study was the ongoing use of AR in manufacturing training and its novelty is the analysis of the most significant factors affecting the actual AR system use. The main objective of this research is to evaluate the use of AR technology in welding training using an innovative model, appropriately extended to consider pedagogy and technology. The contribution of this paper is the exploration and understanding of the factors associated with the AR welding training which can lead to goal fulfillment and, subsequently, impact users’ choice. This study is based on a modified Technology Acceptance Model, extending it by two external variables (perceived enjoyment and system quality) and the sample is 200 trainees. The findings show that the external variables are predictors of perceived usefulness and ease of use. The intention to use AR simulator is positively influenced directly by system quality and perceived ease of use. The findings help AR developers enhance the quality of AR-simulation training systems to enhance users’ experience and their behavioral intention to use them.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{article,

title = {The impact of different learning approaches based on MS Teams and Moodle on students’ performance in an on-line mechanical CAD module},

author = {Z. Kanetaki and C. Stergiou and G. Bekas and C. Troussas and C. Sgouropoulou},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {Global Journal of Engineering Education},

volume = {23},

pages = {185-190},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Troussas2020c,

title = {Ensemble Learning Using Fuzzy Weights to Improve Learning Style Identification for Adapted Instructional Routines},

author = {Christos Troussas and Akrivi Krouska and Cleo Sgouropoulou and Ioannis Voyiatzis},

doi = {https://doi.org/10.3390/e22070735},

year  = {2020},

date = {2020-12-01},

journal = {Entropy },

volume = {22},

number = {7},

pages = {735},

abstract = { Mobile personalized learning can be achieved by the identification of students’ learning styles; however, this happens with the completion of large questionnaires. This task has been reported as tedious and time-consuming, causing random selection of the questionnaires’ choices, and thus, erroneous adaptation to students’ needs, endangering knowledge acquisition. Moreover, mobile environments render the selection of questionnaires’ choices impractical due to confined mobile user interfaces. In view of the above, this paper presents Learnglish, a fully developed mobile language learning system incorporating automatic identification of students’ learning styles according to the Felder-Silverman model (FSLSM) using ensemble classification. In particular, three classifiers, namely SVM, NB and KNN, are combined based on the majority voting rule. The major innovation of this task, apart from the ensemble classification and the mobile learning environment, is that Learnglish takes as input a minimum number of personal (i.e., age and gender) and cognitive characteristics (i.e., prior academic performance categorized using fuzzy weights), and solely four questions pertaining to the FSLSM dimensions, to identify the learning style. Furthermore, Learnglish incorporates adapted instructional routines to create an individualized learning environment based on students’ learning preferences as determined by their style. Learnglish was fully evaluated with very encouraging results.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Troussas2020b,

title = {Collaboration and fuzzy-modeled personalization for mobile game-based learning in higher education},

author = {Christos Troussas and Akrivi Krouska and Cleo Sgouropoulou},

doi = {https://doi.org/10.1016/j.compedu.2019.103698},

issn = {103698},

year  = {2020},

date = {2020-12-01},

journal = {Computers & Education},

volume = {144},

pages = {19},

abstract = {Mobile game-based learning constitutes a hot issue in the related scientific literature since it promotes learning through an entertaining way and fosters student motivation to increase engagement in the educational process. As such, it can enhance the learning process and improve student participation. Towards this direction, this paper investigates how mobile learning and game-based learning can be utilized in higher education settings and analyzes the pedagogical affordance of their adoption. As a testbed for our research, we designed and implemented Quiz Time! which is an intelligent mobile game-based learning application for assessing and advancing learners' knowledge in the programming language C#. Quiz Time! employs an assessing knowledge module for testing the knowledge of learners, a vectorial-based recommendation module for proposing personalized collaboration in group playing, a dynamic fuzzy logic-based advice generator for tailored assistance to learners' profile and misconceptions, and a cognitive learner modeler supporting the aforementioned modules. Quiz Time! was used in a higher education institution for an academic semester and was evaluated by students and computer science experts using an established framework and the statistical hypothesis test. Regarding the evaluation results, the computer science experts validated the pedagogical adequacy of the application and the students highlighted its positive impact on learning and its usefulness. A major conclusion is that incorporating personalization and collaboration in mobile game-based learning can further assist students in higher education towards advancing their knowledge level.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Krouska2019,

title = {Fuzzy Logic for Refining the Evaluation of Learners’ Performance in Online Engineering Education},

author = {Akrivi Krouska and Christos Troussas and Cleo Sgouropoulou},

doi = {https://doi.org/10.24018/ejers.2019.4.6.1369},

issn = {2736-576X},

year  = {2019},

date = {2019-12-01},

urldate = {2019-12-01},

journal = {European Journal of Engineering Research and Science},

volume = {4},

number = {6},

pages = {50-56},

abstract = {



Intelligent tutoring systems have been widely used for optimizing the educational process by creating a student-centered learning environment. As a matter of fact, an integral part of intelligent tutoring systems is the evaluation of the learners’ performance. In traditional learning, the instructors calculate the grade of the students derived from the assessment units and other factors, such as the difficulty of the exercises or their effort, in order to produce the final students’ score in the course. However, in most cases, the evaluation of learners’ performance in intelligent tutoring systems takes place by calculating an average grade of students without taking into account the aforementioned factors. In view of the above, this paper presents a novel way for refining the evaluation of students’ performance using fuzzy logic. As a testbed for our research, we have designed and implemented an intelligent tutoring system holding social networking characteristic for teaching the engineering course of “Compilers”. More specifically, the system is responsible for acquiring information about students such as their grades, the kinds of misconceptions, the level of tests’ difficulty as well as their effort including their social interaction, i.e. participation in forums, making comments in posts and posting regarding the educational process. Taking these into consideration, fuzzy logic model diagnoses the accuracy of students’ grade and the system suggests that the instructor redefine students’ grade properly. Our system was evaluated using t-test and the results show high accuracy and objectivity in the evaluation of students’ performance.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {COMPASS: Standards-based Tools and Services for Building Lifelong Learning Pathways},

author = {Sgouropoulou C. and Niari M. and Vogiatzis I. },

issn = {1027-5207},

year  = {2018},

date = {2018-09-01},

journal = {European Journal of Open, Distance and E-Learning (EURODL)},

note = {EDEN, 2018},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Visual-aided Ontology-based Ranking on Multidimensional Data: A case Study in Academia},

author = {Triperina E. and Sgouropoulou C.},

url = {https://www.emerald.com/insight/content/doi/10.1108/DTA-03-2017-0014/full/html},

issn = {2514-9288},

year  = {2018},

date = {2018-09-01},

urldate = {2018-09-01},

journal = {Data Technologies and Applications (DTA)},

abstract = {Purpose

The purpose of this paper is to introduce a novel framework for visual-aided ontology-based multidimensional ranking and to demonstrate a case study in the academic domain.



Design/methodology/approach

The paper presents a method for adapting semantic web technologies on multiple criteria decision-making algorithms to endow to them dynamic characteristics. It also showcases the enhancement of the decision-making process by visual analytics.



Findings

The semantic enhanced ranking method enables the reproducibility and transparency of ranking results, while the visual representation of this information further benefits decision makers into making well-informed and insightful deductions about the problem.



Research limitations/implications

This approach is suitable for application domains that are ranked on the basis of multiple criteria.



Originality/value

The discussed approach provides a dynamic ranking methodology, instead of focusing only on one application field, or one multiple criteria decision-making method. It proposes a framework that allows integration of multidimensional, domain-specific information and produces complex ranking results in both textual and visual form.},

note = {Emerald, 2018},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {An e-Learning System for Extracting Text Comprehension and Learning Style Characteristics},

author = {Samarakou M. and Tsaganou G. and Papadakis A.},

year  = {2018},

date = {2018-09-01},

urldate = {2018-09-01},

journal = {Journal of Educational Technology & Society},

volume = {21},

number = {1},

pages = {125-136},

abstract = {Technology - mediated learning is very actively and widely researched, with numerous e-learning environments designed for different educational purposes developed during the past few decades. Still, their organization and texts are not structured according to any theory of educational comprehension. Modern education is even more flexible and, thus, demanding, requiring the combination of multiple educational theories for effective results. In this paper we present the combination of two educational theories for text comprehension and learning styles, that are in use by the newly developed Student Diagnosis, Assistance, Evaluation System based on Artificial Intelligence (StuDiAsE) an open learning system for unattended student diagnosis, assistance and evaluation based on artificial intelligence. A trial test about the role of learning styles in student profiling for text comprehension in the educational environment StuDiAsE is described. Research was run with participation of students using the environment for prior knowledge test and text activities. The process revealed remarkable results about the role of learning styles in students' profiles for text comprehension. Three dimensions for learning styles were identified: conceptualization, visualization and progression dimension and were used for profiling. Refinement of profiles incorporates learning styles by decoding student behavior, which reflects student learning styles for text comprehension.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Higher Education Provision Using Systems Thinking Approach – Case Studies},

author = {Dhukaram A. and Sgouropoulou C. and Feldman G. and Amini A.},

url = {https://www.researchgate.net/publication/306361753_Higher_education_provision_using_systems_thinking_approach_-_case_studies},

issn = {0304-3797},

year  = {2016},

date = {2016-09-01},

urldate = {2016-09-01},

journal = {European Journal of Engineering Education},

pages = {1-23},

abstract = {The purpose of this paper is to highlight the complexities involved in higher education provision and how systems thinking and socio-technical systems (STS) thinking approach can be used to understand the education ecosystem. Systems thinking perspective is provided using two case studies: the development of European Learner Mobility (EuroLM) service and the delivery of Enterprise System Management (ESM) course at the Birmingham City University, UK. The case studies present how systems thinking using STS approaches like applied organisational change and Cognitive Work Analysis can be used to capture a conceptual model of the education system for understanding the interactions and relationships between the people, technology, processes and the organisations. Using systems thinking perspective, EuroLM has developed a set of technical standards addressed to the European systems developers and ESM delivery ensures that students communicate and collaborate.},

note = {Online ISSN: 1469-5898, Taylor & Francis, published Aug. 2016},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Evaluation of an intelligent open learning system for engineering education},

author = {Samarakou M. and Fylladitakis E. and Karolidis D. and Früh W.G. and Hatziapostolou A. and Athineos S. and Grigoriadou M.},

doi = {https://doi.org/10.34105/j.kmel.2016.08.031},

year  = {2016},

date = {2016-09-01},

urldate = {2016-09-01},

journal = {Knowledge Management & E-Learning: An International Journal},

volume = {8},

number = {3},

pages = {153-169},

abstract = {In computer-assisted education, the continuous monitoring and assessment of the learner is crucial for the delivery of personalized education to be effective. In this paper, we present a pilot application of the Student Diagnosis, Assistance, Evaluation System based on Artificial Intelligence (StuDiAsE), an open learning system for unattended student diagnosis, assistance and evaluation based on artificial intelligence. The system demonstrated in this paper has been designed with engineering students in mind and is capable of monitoring their comprehension, assessing their prior knowledge, building individual learner profiles, providing personalized assistance and, finally, evaluating a learner's performance both quantitatively and qualitatively by means of artificial intelligence techniques. The architecture and user interface of the system are being exhibited, the results and feedback received from a pilot application of the system within a theoretical engineering course are being demonstrated and the outcomes are being discussed.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{M.2015,

title = {An Advanced eLearning Environment Developed for Engineering Learners},

author = {Samarakou M. and Fylladitakis E. and Früh W.G. and Hatziapostolou A. and Gelegenis J.J },

url = {https://online-journals.org/index.php/i-jet/article/view/4484},

doi = {http://dx.doi.org/10.3991/ijet.v10i3.4484},

year  = {2015},

date = {2015-09-01},

urldate = {2015-09-01},

journal = {International Journal of Emerging Technologies in Learning},

volume = {10},

number = {3},

abstract = {Monitoring and evaluating engineering learners through computer-based laboratory exercises is a difficult task, especially under classroom conditions. A complete diagnosis requires the capability to assess both the competence of the learner to use the scientific software and the understanding of the theoretical principles. This monitoring and evaluation needs to be continuous, unobtrusive and personalized in order to be effective. This study presents the results of the pilot application of an eLearning environment developed specifically with engineering learners in mind. As its name suggests, the Learner Diagnosis, Assistance, and Evaluation System based on Artificial Intelligence (StuDiAsE) is an Open Learning Environment that can perform unattended diagnostic, evaluation and feedback tasks based on both quantitative and qualitative parameters. The base architecture of the system, the user interface and its effect on the performance of postgraduate engineering learners are being presented.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {How an Open Learning Environment Affects the Motivation of Secondary and Higher Education Students},

author = {Samarakou M. and Fylladitakis E. D. and Karolidis D. and Papadakis A. and Prentakis P. and Tsaganou G. },

doi = {http://doi.acm.org/10.1145/2801948.2802002},

year  = {2015},

date = {2015-09-01},

urldate = {2015-09-01},

journal = {In Proceedings of the 19th Panhellenic Conference on Informatics},

pages = {50-54},

abstract = {Technology mediated learning is very actively and widely researched, yet there are few studies on if and how open learning environments (OLEs) affect the motivation of students. It is very important to showcase not only the effect on different groups of students but on students in various educational levels. This paper is a report on the findings of a study conducted in parallel, using the same OLE, on the students of a postgraduate engineering course and on the lyceum students attending their mandatory secondary education curriculum. The students used the Student Diagnosis, Assistance, Evaluation System based on Artificial Intelligence (StuDiAsE), an open learning system for unattended student diagnosis, assistance and evaluation based on artificial intelligence. The report indicates that the use of the OLE has particularly beneficial effects on the performance of certain student groups.},

note = {PCI ’15, ACM, New York, NY, USA 1-3 October},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {How eLearning Affects The Motivation of Higher Education Students: A Case Study For StuDiAsE},

author = {Samarakou M. and Fylladitakis E.D. and Früh W.G. and Hatziapostolou A. and Grigoriadou M.},

url = {https://www.researchgate.net/publication/275581318_How_eLearning_Affects_The_Motivation_Of_Higher_Education_Students_A_Case_Study_For_StuDiAsE},

year  = {2015},

date = {2015-09-01},

journal = {Proceedings of Global Learn},

pages = {185-192b},

abstract = {Although eLearning and technology assisted education is being very widely researched these days, there are very few studies on how virtual learning environments affect the motivation on students and, more importantly, how different groups of students are being affected. This paper is a report on the findings of a study conducted on the students of a postgraduate engineering course at the T.E.I. of Athens. The students used the Student Diagnosis, Assistance, Evaluation System based on Artificial Intelligence (StuDiAsE), an open learning system for unattended student diagnosis, assistance and evaluation based on artificial intelligence. By analyzing the student data recorded and extracted by the software, we identify its impact on the motivation of the sixty students that participate in this study.},

note = {April 16-17},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Feasibility for the use of Flat Booster Reflectors in Various Photovoltaic Installations},

author = {Gelegenis J. and Axaopoulos P. and Misailidis S. and Giannakidis G. and Samarakou M. and Bonaros B.},

url = {https://www.researchgate.net/publication/275637317_Feasibility_for_the_use_of_Flat_Booster_Reflectors_in_Various_Photovoltaic_Installations},

year  = {2015},

date = {2015-09-01},

urldate = {2015-09-01},

journal = {International Journal of Renewable Energy Research},

volume = {5},

number = {1},

pages = {82-98},

abstract = {The feasibility for the addition of flat booster reflectors to PV panels is techno -economically investigated for various 

applications  (building  attached  PVs,  ground  installations, grid -connected or stand-alone units) and various  PV types (mono-

crystalline  and  amorphous  silicon  PV  panels).  A  model  developed  to  this  aim  is  applied  to  optimize  the  parameters  of  the 

PV/reflector  module  and  to  evaluate  its  applicability  according  to  the  solar radiation data of Athens (Greece). The refl ectors 

may  lead  to  significant  increase  of  total  incident  solar  radiation  annually,  without  however  to  equivalently  improve  the 

economy of the system. The several  reasons  for  this  are  identified  (uneven  illumination,  edge  effects,  increased  cell 

temperature,  cost  of  reflectors).  Promising  applications  of  flat  booster  reflector  proved  to  be  their  use  in  specific  building 

attached photovoltaics (at south facades) and in standalone applications, allowing  –in the latter- a better matching between the 

load and the energy source annual profiles.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Creating the Context for Exploiting Linked Open Data in Multidimensional Academic Ranking},

author = {Triperina E. and Sgouropoulou C. and Xydas I. and Terraz O. and Miaoulis G.},

url = {https://www.online-journals.org/index.php/i-jes/article/view/5023},

issn = {2197-8581},

year  = {2015},

date = {2015-09-01},

urldate = {2015-09-01},

journal = {International Journal of Recent Contributions from Engineering, Science & Technology (iJES)},

volume = {3},

number = {4},

pages = {33–43},

abstract = {Academia is a complex socio-technical system with multiple aspects and constituents that involve various stakeholders. In order to address stakeholders’ needs and to assist the institutional accountability, this complexity should be considered during the development of academic services. We have designed a dynamic multidimensional ranking approach, easily modifiable to address user requirements, so as to assess and compare the university performance with a clear view to the support of effective institutional strategic planning and policy making. Our approach comprises the following components: the AcademIS ontology to model the academic domain and its multiple dimensions, the AcademIS Information System to manage and display the academic information, published in Linked Open Data format and the visual-aided Multiple Criteria Decision Making component, to evaluate and rank the performance of the academic units. The data are aggregated from several sources, in different formats, LODified by our system, and presented to the user by the interface to ultimately assist the decision making process.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}