Jun232023 by Gianluca RomanoNo Comments
Building an Application to Track Psychomotor Skills with Wearable Sensors @ #JTELSS23

Building an Application to Track Psychomotor Skills with Wearable Sensors @ #JTELSS23

Summer School, Workshop
At the 17th EATEL Summer School on Technology-Enhanced Learning (JTELSS 2023) in La Manga, Spain, Gianluca Romano, Jan Schneider, and Daniele Di Mitri conducted the workshop "Building an Application to Track Psychomotor Skills with Wearable Sensors”. The workshop delved into the world of scalable mobile applications and wearable sensors, providing insights into psychomotor skill development. Let's take a moment to reflect on the key highlights from this enriching session. Participants embarked on an exploration of mobile application architecture, gaining a comprehensive understanding of how tasks are effectively distributed between the frontend and backend. Further, participants learned about software building principles to build more reliable and maintainable software such as Separation of Concerns, Single Source of Truth, and Dependency Injection. Through interactive exercises and insightful group work, attendees discovered what it…
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Sep142022 by Gianluca RomanoNo Comments
New Pub: Meaningful Feedback from Wearable Sensor Data to Train Psychomotor Skill

New Pub: Meaningful Feedback from Wearable Sensor Data to Train Psychomotor Skill

Workshop
A new workshop paper was presented at the MILeS 2022 workshop written by Gianluca Romano entitled: Meaningful Feedback from Wearable Sensor Data to Train Psychomotor Skill. The MILeS 2022 – Multimodal Immersive Learning Systems workshop took place on the 13th of September at EC-TEL 2022 conference taking place in Toulouse, France. The paper will appear in the CEUR proceedings. Abstract. Learning psycho-motor skills requires feedback for improvement and give insight on performance. However, providing feedback is not trivial. Every learner is different and the same feedback might not work for everyone. The workshop aims to make participants aware of the problematic transition from analyzed wearable sensor data to meaningful feedback. Thus, the participants will get more familiar with wearable sensor data and directly experience how learners might want to receive feedback that they deem…
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Jul282021 by Gianluca RomanoNo Comments
Gianluca Romano joins the team

Gianluca Romano joins the team

Higher Education, Multimodal Learning Analytics, Team
Starting July 2021, Gianluca Romano joins the team as a doctoral researcher. He holds a Master's as well as a Bachelor's degree in Computer Science from the Goethe University Frankfurt. He finished his study with a thesis on an Intelligent Tutoring System for dancing which was also published in an online journal. Further, he has experience as an AI Engineer and currently is also employed as a Machine Learning Engineer.
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