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DELFI 2021

https://dl.gi.de/handle/20.500.12116/37429
Auflistung nach:

Auflistung DELFI 2021 nach Autor:in "Bodemer, Daniel"

1 - 2 von 2
  • Konferenzbeitrag
    Development and evaluation of the peer support web application “uniMatchUp!”
    (DELFI 2021, 2021) Ollesch, Lisa; Kohlmann, Jens; Steiner, Maribell; Bodemer, Daniel
    This paper describes the conception, development, and evaluation of a peer support web application for university students. The main goal of uniMatchUp! is to help students in finding appropriate academic support and learning groups by providing Group Awareness (GA) information about various aspects of fellow students that are useful for digital learning. The study contributes to a better understanding of the use of GA tools in the university context and reveals that active engagement with the application, in the form of contributed questions and answers, led to increased student satisfaction. During the interaction with uniMatchUp!, cognitive GA information (contribution quality) was considered more relevant than behavioral (amount of participation), and emotional (well-being) GA information about other students. The findings also provide potentials for improvement, which can shape the further development of uniMatchUp! and future applications.
  • Konferenzbeitrag
    The Impact of Guidance and Feedback in Game-Based Computational Thinking Environments
    (DELFI 2021, 2021) Manske, Sven; Feier, Alexia; Frese, Philip; Hölzel, Pia; Iffländer Rodriguez, Maurice; Körner, Joshua; Lichte, Aron; Lena Otto de Mentock, Lena Otto; Kocak, Melinda; Szymczyk, Natalia; Temel,Dilan; Haefs, Mathis; Kersting, Nina; Liewald, Rebekka C.; Bodemer, Daniel
    In this paper we investigated the impact of feedback and guidance on the development of computational thinking skills. To achieve this, we extended a game-based learning environment that aims to foster computational thinking by teaching programming in self-regulated learning scenarios. The learning environment has been enriched with multiple mechanisms to guide learners and provide feedback that is directed towards the development of computational thinking skills, particularly specific abstractions in programming among algorithmic thinking. To assess the impact of guidance and feedback, we conducted an empirical study with 57 participants. The findings indicate that feedback on the logical artifacts can reduce certain code smells and increase the motivation on the part of the learners.