DELFI 2024 Workshops

Permanent URI for this collectionhttps://dl.gi.de/handle/20.500.12116/45021

Authors with most Documents  

Cohausz, Lea
3
Libbrecht, Paul
3
Mulders, Miriam
3
Appel, Sven
2
Dieing, Thilo I.
2

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Author: search.filters.author.Libbrecht, PaulSubject: search.filters.subject.E-Portfolios

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  • Conference Paper
    Szenarien für eine automatische Analyse von E-Portfolios
    (Gesellschaft für Informatik e.V., 2024) Isking, Andreas; Libbrecht, Paul; Kiesler, Natalie; Schulz, Sandra
    Wir verwenden Scenario Based Design, um automatische Analysen von E-Portfolios in übersichtlichen Dashboards zu visualisieren. Die Ergebnisse dieser Analysen können auf unter- schiedlichste Arten dargestellt werden. In Szenarien wird versucht, die Situationen zu identifizieren, in denen es Probleme oder Verbesserungspotenzial gibt, damit Bewertungs- und Schreibprozesse verbessert werden. Wir präsentieren die angewandte Methode und ausgewählte Szenarien, die bei der Entwicklung einer Web-Applikation geholfen haben.
  • Text Document
    EPEPLA Workshop on E-Portfolios Evolution Powered by Language Analysis
    (Gesellschaft für Informatik e.V., 2024) Libbrecht, Paul; Hoeppner, Kristina; Rebholz, Sandra; Mueller, Wolfgang; Kiesler, Natalie; Schulz, Sandra
    The practice of students creating ePortfolios has been experienced as an effective means of students proving their individual knowledge and competencies by creating digital works that can be shared. This practice has been used for decades and has allowed many students to create study-relevant work and document these in E-Portfolios. Teachers, recruitment actors and fellow learners have enjoyed the possibility to perceive the learning and the relevant knowledge by reviewing E-Portfolios. Artificial intelligence empowers the reviewers of the work by providing powerful techniques that inform the many dimensions of the texts and can support the review and the creation of additional learning evidence. The Workshop ‘E-Portfolios Evolution Powered by Language Analysis’ has surfed this wave and provided a panorama of current techniques of employing machine-learning and large language model technology that support the pedagogical practice of e-portfolios to demonstrate student learning activity.
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