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Ηλεκτρονική μάθηση και αξιολόγηση στην εκπαίδευση μηχανικών: καινοτόμες προσεγγίσεις μέσω τεχνητής νοημοσύνης και εξόρυξης εκπαιδευτικών δεδομένων ; E-learning and e-assesment in engineering education: innovative approaches through artificial intelligence and educational data mining

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Název: Ηλεκτρονική μάθηση και αξιολόγηση στην εκπαίδευση μηχανικών: καινοτόμες προσεγγίσεις μέσω τεχνητής νοημοσύνης και εξόρυξης εκπαιδευτικών δεδομένων ; E-learning and e-assesment in engineering education: innovative approaches through artificial intelligence and educational data mining
Autoři: Charitopoulos, Angelos, Χαριτόπουλος, Άγγελος
Informace o vydavateli: Democritus University of Thrace (DUTH)
Δημοκρίτειο Πανεπιστήμιο Θράκης (ΔΠΘ)
Rok vydání: 2025
Sbírka: National Archive of PhD Theses (National Documentation Centre Greece)
Témata: Ηλεκτρονική μάθηση, Ηλεκτρονική αξιολόγηση, Εκπαίδευση μηχανικών, Σύστημα Διαχείρισης Μάθησης moodle, Soft Computing, Αλγόριθμοι μηχανικής μάθησης, Τεχνητά νευρωνικά δίκτυα, Εξόρυξη Εκπαιδευτικών Δεδομένων, Εξόρυξη Εκπαιδευτικού Κειμένου, Αλγόριθμος Latent Dirichlet Allocation, E-learning, e-assessment, Engineering education, LMS moodle, Machine learning algorithms, Artificial neural networks, Educational data mining, Educational Text Mining, Latent Dirichlet Allocation Algorithm, Επιστήμη Ηλεκτρολόγου Μηχανικού, Ηλεκτρονικού Μηχανικού, Μηχανικού Η/Υ, Επιστήμες Μηχανικού και Τεχνολογία, Ηλεκτρική και Ηλεκτρονική μηχανική, Electrical Engineering, Electronic Engineering, Information Engineering, Engineering and Technology, Electrical and Electronic Engineering
Popis: This PhD thesis examines the affordances and opportunities that digital educational technologies offer for higher quality and more effective education, with emphasis on the introduction and utilization of Artificial Intelligence (AI) and Machine Learning (ML) methods and algorithms. The thesis focuses on higher education, with a specific, though not exclusive, interest in engineering education. First, the use of AI/ML methods in the field of educational technologies is explored through a literature review. On the basis of results of this review, the thesis focuses on specific educational problems. To address these problems, experimental educational activities are designed, developed and evaluated using real data. Finally, the thesis concludes by suggesting directions for future research. From the point of view of the AI/ML algorithms selected and used in the thesis, the following can be distinguished (a) data mining algorithms, which analyse educational data in their more classical form (numerical, quantitative, time stamps, student-platform interaction event counts, user activity counts, etc.) and (b) text mining algorithms, which analyse educational texts (of sufficient length; not short texts such as social network posts) based on Natural Language Processing (NLP) methods. The thesis consists of seven chapters. The first chapter presents the evolution of e-learning and e-assessment, the basic learning theories (behaviourism, constructivism, socio-cultural theories) and the platforms that support e-learning and e-assessment, such as Moodle and Massive Open Online Courses (MOOCs). It also examines the advantages, disadvantages and challenges of e-learning and e-assessment. The second chapter reviews the international literature on the use of Educational Data Mining (EDM) and Learning Analytics (LA) methods in e-learning and e-assessment. The algorithms of the broader family of Soft Computing, used for educational data analysis, are reviewed, along with research trends and future challenges in the field. Chapter ...
Druh dokumentu: doctoral or postdoctoral thesis
Jazyk: Greek, Modern (1453-)
Relation: https://hdl.handle.net/10442/hedi/59341
DOI: 10.12681/eadd/59341
Dostupnost: https://hdl.handle.net/10442/hedi/59341
https://doi.org/10.12681/eadd/59341
Přístupové číslo: edsbas.DC133177
Databáze: BASE
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  – Url: https://hdl.handle.net/10442/hedi/59341#
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  Data: Ηλεκτρονική μάθηση και αξιολόγηση στην εκπαίδευση μηχανικών: καινοτόμες προσεγγίσεις μέσω τεχνητής νοημοσύνης και εξόρυξης εκπαιδευτικών δεδομένων ; E-learning and e-assesment in engineering education: innovative approaches through artificial intelligence and educational data mining
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  Data: Democritus University of Thrace (DUTH)<br />Δημοκρίτειο Πανεπιστήμιο Θράκης (ΔΠΘ)
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  Data: 2025
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  Data: National Archive of PhD Theses (National Documentation Centre Greece)
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  Data: <searchLink fieldCode="DE" term="%22Ηλεκτρονική+μάθηση%22">Ηλεκτρονική μάθηση</searchLink><br /><searchLink fieldCode="DE" term="%22Ηλεκτρονική+αξιολόγηση%22">Ηλεκτρονική αξιολόγηση</searchLink><br /><searchLink fieldCode="DE" term="%22Εκπαίδευση+μηχανικών%22">Εκπαίδευση μηχανικών</searchLink><br /><searchLink fieldCode="DE" term="%22Σύστημα+Διαχείρισης+Μάθησης+moodle%22">Σύστημα Διαχείρισης Μάθησης moodle</searchLink><br /><searchLink fieldCode="DE" term="%22Soft+Computing%22">Soft Computing</searchLink><br /><searchLink fieldCode="DE" term="%22Αλγόριθμοι+μηχανικής+μάθησης%22">Αλγόριθμοι μηχανικής μάθησης</searchLink><br /><searchLink fieldCode="DE" term="%22Τεχνητά+νευρωνικά+δίκτυα%22">Τεχνητά νευρωνικά δίκτυα</searchLink><br /><searchLink fieldCode="DE" term="%22Εξόρυξη+Εκπαιδευτικών+Δεδομένων%22">Εξόρυξη Εκπαιδευτικών Δεδομένων</searchLink><br /><searchLink fieldCode="DE" term="%22Εξόρυξη+Εκπαιδευτικού+Κειμένου%22">Εξόρυξη Εκπαιδευτικού Κειμένου</searchLink><br /><searchLink fieldCode="DE" term="%22Αλγόριθμος+Latent+Dirichlet+Allocation%22">Αλγόριθμος Latent Dirichlet Allocation</searchLink><br /><searchLink fieldCode="DE" term="%22E-learning%22">E-learning</searchLink><br /><searchLink fieldCode="DE" term="%22e-assessment%22">e-assessment</searchLink><br /><searchLink fieldCode="DE" term="%22Engineering+education%22">Engineering education</searchLink><br /><searchLink fieldCode="DE" term="%22LMS+moodle%22">LMS moodle</searchLink><br /><searchLink fieldCode="DE" term="%22Machine+learning+algorithms%22">Machine learning algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+neural+networks%22">Artificial neural networks</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+data+mining%22">Educational data mining</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Text+Mining%22">Educational Text Mining</searchLink><br /><searchLink fieldCode="DE" term="%22Latent+Dirichlet+Allocation+Algorithm%22">Latent Dirichlet Allocation Algorithm</searchLink><br /><searchLink fieldCode="DE" term="%22Επιστήμη+Ηλεκτρολόγου+Μηχανικού%22">Επιστήμη Ηλεκτρολόγου Μηχανικού</searchLink><br /><searchLink fieldCode="DE" term="%22Ηλεκτρονικού+Μηχανικού%22">Ηλεκτρονικού Μηχανικού</searchLink><br /><searchLink fieldCode="DE" term="%22Μηχανικού+Η%2FΥ%22">Μηχανικού Η/Υ</searchLink><br /><searchLink fieldCode="DE" term="%22Επιστήμες+Μηχανικού+και+Τεχνολογία%22">Επιστήμες Μηχανικού και Τεχνολογία</searchLink><br /><searchLink fieldCode="DE" term="%22Ηλεκτρική+και+Ηλεκτρονική+μηχανική%22">Ηλεκτρική και Ηλεκτρονική μηχανική</searchLink><br /><searchLink fieldCode="DE" term="%22Electrical+Engineering%22">Electrical Engineering</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+Engineering%22">Electronic Engineering</searchLink><br /><searchLink fieldCode="DE" term="%22Information+Engineering%22">Information Engineering</searchLink><br /><searchLink fieldCode="DE" term="%22Engineering+and+Technology%22">Engineering and Technology</searchLink><br /><searchLink fieldCode="DE" term="%22Electrical+and+Electronic+Engineering%22">Electrical and Electronic Engineering</searchLink>
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  Data: This PhD thesis examines the affordances and opportunities that digital educational technologies offer for higher quality and more effective education, with emphasis on the introduction and utilization of Artificial Intelligence (AI) and Machine Learning (ML) methods and algorithms. The thesis focuses on higher education, with a specific, though not exclusive, interest in engineering education. First, the use of AI/ML methods in the field of educational technologies is explored through a literature review. On the basis of results of this review, the thesis focuses on specific educational problems. To address these problems, experimental educational activities are designed, developed and evaluated using real data. Finally, the thesis concludes by suggesting directions for future research. From the point of view of the AI/ML algorithms selected and used in the thesis, the following can be distinguished (a) data mining algorithms, which analyse educational data in their more classical form (numerical, quantitative, time stamps, student-platform interaction event counts, user activity counts, etc.) and (b) text mining algorithms, which analyse educational texts (of sufficient length; not short texts such as social network posts) based on Natural Language Processing (NLP) methods. The thesis consists of seven chapters. The first chapter presents the evolution of e-learning and e-assessment, the basic learning theories (behaviourism, constructivism, socio-cultural theories) and the platforms that support e-learning and e-assessment, such as Moodle and Massive Open Online Courses (MOOCs). It also examines the advantages, disadvantages and challenges of e-learning and e-assessment. The second chapter reviews the international literature on the use of Educational Data Mining (EDM) and Learning Analytics (LA) methods in e-learning and e-assessment. The algorithms of the broader family of Soft Computing, used for educational data analysis, are reviewed, along with research trends and future challenges in the field. Chapter ...
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  Data: doctoral or postdoctoral thesis
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  Data: Greek, Modern (1453-)
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  Data: https://hdl.handle.net/10442/hedi/59341
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  Data: 10.12681/eadd/59341
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        Value: 10.12681/eadd/59341
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      – Text: Greek, Modern (1453-)
    Subjects:
      – SubjectFull: Ηλεκτρονική μάθηση
        Type: general
      – SubjectFull: Ηλεκτρονική αξιολόγηση
        Type: general
      – SubjectFull: Εκπαίδευση μηχανικών
        Type: general
      – SubjectFull: Σύστημα Διαχείρισης Μάθησης moodle
        Type: general
      – SubjectFull: Soft Computing
        Type: general
      – SubjectFull: Αλγόριθμοι μηχανικής μάθησης
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      – SubjectFull: Τεχνητά νευρωνικά δίκτυα
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      – SubjectFull: Εξόρυξη Εκπαιδευτικών Δεδομένων
        Type: general
      – SubjectFull: Εξόρυξη Εκπαιδευτικού Κειμένου
        Type: general
      – SubjectFull: Αλγόριθμος Latent Dirichlet Allocation
        Type: general
      – SubjectFull: E-learning
        Type: general
      – SubjectFull: e-assessment
        Type: general
      – SubjectFull: Engineering education
        Type: general
      – SubjectFull: LMS moodle
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      – SubjectFull: Machine learning algorithms
        Type: general
      – SubjectFull: Artificial neural networks
        Type: general
      – SubjectFull: Educational data mining
        Type: general
      – SubjectFull: Educational Text Mining
        Type: general
      – SubjectFull: Latent Dirichlet Allocation Algorithm
        Type: general
      – SubjectFull: Επιστήμη Ηλεκτρολόγου Μηχανικού
        Type: general
      – SubjectFull: Ηλεκτρονικού Μηχανικού
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      – SubjectFull: Μηχανικού Η/Υ
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      – SubjectFull: Επιστήμες Μηχανικού και Τεχνολογία
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      – SubjectFull: Ηλεκτρική και Ηλεκτρονική μηχανική
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      – SubjectFull: Electrical Engineering
        Type: general
      – SubjectFull: Electronic Engineering
        Type: general
      – SubjectFull: Information Engineering
        Type: general
      – SubjectFull: Engineering and Technology
        Type: general
      – SubjectFull: Electrical and Electronic Engineering
        Type: general
    Titles:
      – TitleFull: Ηλεκτρονική μάθηση και αξιολόγηση στην εκπαίδευση μηχανικών: καινοτόμες προσεγγίσεις μέσω τεχνητής νοημοσύνης και εξόρυξης εκπαιδευτικών δεδομένων ; E-learning and e-assesment in engineering education: innovative approaches through artificial intelligence and educational data mining
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              Y: 2025
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