CategoriesJournal article

New pub: key technical features of automated feedback systems - a systematic feature analysis

New publication alert from the HyTea project titled "Enhancing presentation skills: key technical features of automated feedback systems - a systematic feature analysis", led by PhD candidate Stefan Hummel

The article presents a systematic analysis of oral presentation automated feedback systems (OPAFs), which are designed to support public speaking through automated feedback mechanisms.

Our study assessed 14 existing systems across a comprehensive set of 83 functional features and 12 additional aspects. Although there is an increased interest in these systems, we found that the overall implementation rate of key features remains low at just 16%, with notable gaps in critical areas like verbal-nonverbal congruency, adaptive feedback, and content structuring.

Moreover, evaluation methodologies tend to focus heavily on usability and user experience, while aspects such as learning outcomes and pedagogical value are often overlooked. The majority of studies are lab-based, which raises concerns about the generalisability of findings to real-world educational environments.

Our findings emphasise the importance of improved feature integration, real-world testing, and closer collaboration with educators to help transition these tools from experimental prototypes to effective educational technologies.

This is the first journal article published about the HyTea project and contributed substantially to building a solid foundation for Presentable (www.presentable.info).

This milestone was especially significant as it marks my first article published as the last author. Well done, Stefan, thanks to my co-authors and everyone who supported this research.

Paper available Open Access šŸ”“ here
https://www.inderscienceonline.com/doi/abs/10.1504/IJTEL.2025.148593

Published by Daniele Di Mitri

Daniele Di Mitri is a research group leader at the DIPF - Leibniz Institute for Research and Information in Education and a lecturer at the Goethe University of Frankfurt, Germany. Daniele received his PhD entitled "The Multimodal Tutor" at the Open University of The Netherlands (2020) in Learning Analytics and wearable sensor support. His research focuses on collecting and analysing multimodal data during physical interactions for automatic feedback and human behaviour analysis. Daniele's current research focuses on designing responsible Artificial Intelligence applications for education and human support. He is a "Johanna Quandt Young Academy" fellow and was elected "AI Newcomer 2021" at the KI Camp by the German Informatics Society. He is a member of the editorial board of Frontiers in Artificial Intelligence journal, a member of the CrossMMLA, a special interest group of the Society of Learning Analytics Research, and chair of the Learning Analytics Hackathon (LAKathon) series.

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