P356 - DELFI 2024 - Die 22. Fachtagung Bildungstechnologien
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- Conference paperBeyond Realism: Rethinking Presence in Virtual Environments for Abstract Concept Learning(Proceedings of DELFI 2024, 2024) Baberowski, David; Leonhardt, Thiemo; Lilienthal, Lanea; Bergner, NadinePresence, as the feeling of actually being in a virtual place, is an important metric for VR learning applications due to its positive impact on learning. In the literature, the level of immersion a system can provide is assumed to be the main factor influencing presence. This paper investigates this assumption for virtual environments in abstract learning contexts that are not based on reality. This is done by building a physical replica of a VR learning game and comparing both in terms of learning outcomes and presence. The study shows that subjects do not have a consistent view of what can be described as real in abstract contexts, suggesting that the distinction between reality-based virtual environments and those in abstract contexts is important in terms of presence.
- Conference paperProblem-Specific Visual Feedback in Discrete Modelling(Proceedings of DELFI 2024, 2024) Herwig, Maurice; Hundeshagen, Norbert; Hundhausen, John; Kablowski, Stefan; Lange, MartinDiscrete modelling as the basis of problem solving is an essential skill for computer scientists, but the correct use of formal languages like propositional logic for such purposes remains a big challenge for undergraduate students. The DiMo tool provides support for the acquisition of formal modelling competencies using propositional logic. We extend the tool by generic capabilities to generate problem-specific feedback to students. This allows them to visualise the result of their modelling attempts in terms of the modelled problem at hand, thus helping students to initiate corresponding learning cycles.
- Conference demoAdaptive Learning Systems in Programming Education: A Prototype for Enhanced Formative Feedback(Proceedings of DELFI 2024, 2024) Lohr, Dominic; Berges, Marc; Chugh, Abhishek; Striewe, MichaelFormative feedback is crucial in programming education, yet many learning systems fall short, concentrating mostly on pinpointing errors rather than guiding learners on how to resolve them. This is particularly unhelpful for novices who often lack advanced skills like debugging. Feedback is considered more valuable when it addresses error causes rather than just symptoms. However, this is challenging using only conventional methods like unit testing. Identifying error causes requires detailed information about both the error and the learner. Our proposed prototype introduces a new approach to integrating programming exercises into adaptive learning systems. It directly categorizes student code into so-called answer classes using a combination of static and dynamic code analysis. When integrated with data derived from a learner model, this approach enables tailored feedback that lowers the barrier to learning programming while keeping motivation high.
- Conference demoEnhancing Geographical Learning Through GeoVR: Immersive Exploration and Topographic Analysis Educational Application(Proceedings of DELFI 2024, 2024) Sabah, Sam; Tillmann, Alexander; Weiß, David; Drachsler, HendrikGeoVR, a Virtual Reality immersive educational application, facilitates pedagogical approaches in geographical education, enabling students and educators to explore and analyze landscape features. This research examines the benefits of this educational environment, enabling students to seamlessly transition between macro and micro perspectives of terrain, facilitating a comprehensive understanding of surface structures. GeoVR aims to improve learning experiences, while simultaneously enhancing the user’s understanding of topographical features and spatial relationships through scalable observation and interactive analysis tools. The application notably extends the scope of actions available to learners and educators in fields such as geography, geology, environmental studies, urban planning, and education. The precision of the representation, the interactive capabilities, the infinitely adjustable scales and the contribution to a realistic and immersive learning environment for geoinformation and processes can lead to a better understanding of the systems under investigation. Despite potential challenges, GeoVR seeks to bridge the gap between virtual and physical environments, changing how people learn and explore landscapes digitally.
- Complete VolumeDELFI 2024 - Complete Volume(Proceedings of DELFI 2024, 2024)
- Conference demo19squared - Interaktive XR-Inhalte gemeinsam selbst erstellen(Proceedings of DELFI 2024, 2024) Ehlenz, Matthias; Maquet,FredericDie hier vorgestellte Demo präsentiert ein webbasiertes Tool, welches Lehrkräften und Schüler:innen die Erstellung eigener immersiver und interaktiver Lerninhalte für den Unterricht ermöglicht. Als zentrales Medium dienen 360°-Aufnahmen (Fotos und Videos), welche mittlerweile mit relativ geringem Aufwand mit Actioncams, Smartphone-Gimbals oder Drohnen selbst erstellt werden können. Das Open Source-Werkzeug ermöglicht die Verarbeitung der Aufnahmen zu interaktiven Touren, welche im Browser, auf dem Tablet oder in Virtual Reality erkundet werden können. Zudem bietet die Software die Möglichkeit der kollaborativen Bearbeitung, die Erstellung von virtuellen Escape Rooms sowie die Beobachtung des Lernfortschritts durch Learning Analytics-Integration. Im Rahmen der Demonstration können sowohl das Erstellen interaktiver Touren mit vorbereitetem 360° Material als auch das Durchführen von Exkursionen, die bereits in der Lehre eingesetzt werden, erprobt werden. Zudem kann auch die eigenständige Erstellung von 360°-Medien auf verschiedene Arten getestet werden, sofern die Rahmenbedingungen es zulassen.
- Conference paperEvaluating Task-Level Struggle Detection Methods in Intelligent Tutoring Systems for Programming(Proceedings of DELFI 2024, 2024) Dannath, Jesper; Deriyeva, Alina; Paaßen, BenjaminIntelligent Tutoring Systems require student modeling in order to make pedagogical decisions, such as individualized feedback or task selection. Typically, student modeling is based on the eventual correctness of tasks. However, for multi-step or iterative learning tasks, like in programming, the intermediate states towards a correct solution also carry crucial information about learner skill. We investigate how to detect learners who struggle on their path towards a correct solution of a task. Prior work addressed struggle detection in programming environments on different granularity levels, but has mostly focused on preventing course dropout. We conducted a pilot study of our programming learning environment and evaluated different approaches for struggle detection at the task level. For the evaluation of measures, we use downstream Item Response Theory competency models. We find that detecting struggle based on large language model text embeddings outperforms chosen baselines with regard to correlation with a programming competency proxy.
- Conference demoProduktionstechnisches Vorgehen und Demonstration der Erstellung einer Selbstlernakademie für IT-Sicherheit(Proceedings of DELFI 2024, 2024) Dobbrunz, Tabea; Naß, Miriam; Warmer, Sina; Pohlmann, Norbert; Harrer, AndreasIm Rahmen des vom Ministerium für Kultur und Wissenschaft des Landes NRW und von der Digitalen Hochschule NRW (DH.NRW) geförderten Projekts SecAware.nrw wurde eine Selbstlernakademie zum Thema IT-Sicherheit entwickelt. Mit dem Ziel, Bewusstsein zu schaffen, stellt dieses Lernangebot eine Präventionsmaßnahme für die vermehrt stattfindenden Cyber-Angriffe auf Hochschulen dar. Das Angebot setzt dabei auf ein multimediales didaktisches Konzept, bestehend aus informativ aufbereiteten und zur Exploration anregenden Elementen. In diesem Beitrag wird die produktionstechnische Vorgehensweise bei der Konzeption und Realisierung des Lernangebots beschrieben und das Resultat vorgestellt.
- Conference paperInformiertes Zustimmungsmanagement für Learning Analytics in Lernmanagementsystemen(Proceedings of DELFI 2024, 2024) Judel, Sven; Zeise, Christopher; Schroeder, UlrikDieser Beitrag präsentiert ein Konzept um Lernende angemessen über Learning Analytics zu informieren und ihnen das Management von Zustimmungen zu Datensammlungen und -verarbeitungen einfach aber vollständig zu ermöglichen. Drei Komponenten übernehmen die Aufklärung, die Zustimmungsabfrage beim ersten Aufruf des Lernmanagementsystems sowie jedes Lernraums und die Anpassung der Zustimmungen zu jeder Zeit. Die Komponenten zum Management wurden beispielhaft für Moodle umgesetzt und mit Studierenden evaluiert. Die Ergebnisse deuten auf eine gute und sichere Nutzbarkeit hin, welche den Lernenden mehr Kontrolle über ihre Daten gibt.
- Conference posterRelation between struggle and learning personality in programming exercises(Proceedings of DELFI 2024, 2024) Deriyeva, Alina; Dannath, Jesper; Paaßen, BenjaminPersonality-related characteristics can have an impact on learning experiences and learning outcomes. Moreover, understanding learning approaches of students can help to make personalized pedagogical decisions. Particularly, this has a potential to improve learning outcomes and mitigate user attrition in digital learning environments (DLEs). We hypothesize that persistent individual characteristics may influence a learners’ tendency to struggle during programming exercises. In a study within a digital learning environment for Python programming (N=55), we evaluated the relation between learners’ self-reported personality characteristics and their tendency to struggle during the exercises. We find that, in our sample, some problem solving approaches and all learning preferences are related to struggle indicators. These results indicate that it may be helpful to include personality-related features, like problem solving strategies, as context information for pedagogical modeling in DLEs.