Gianluca Romano joins the team

Gianluca Romano joins the team

July 28, 2021
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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Fernando P. Cardenas-Hernandez joins the team

Fernando P. Cardenas-Hernandez joins the team

July 28, 2021
Multimodal Learning Analytics, Project, Team
Starting 1st July 2021, Fernando P. Cardenas-Hernandez joins the team as a doctoral researcher.  He earned his Master’s degree in Microsystems from the University of Freiburg. After his graduation, he worked as a software engineer in different companies. Some of his previous projects made use of microcontrollers, SBCs and thermal & industrial cameras. He is currently involved in the MILKI-PSY project.
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New Pub: Literature Review on Co-Located Collaboration Modeling Using Multimodal Learning Analytics—Can We Go the Whole Nine Yards?

New Pub: Literature Review on Co-Located Collaboration Modeling Using Multimodal Learning Analytics—Can We Go the Whole Nine Yards?

July 21, 2021
General education, Journal, Literature review, Multimodal Learning Analytics, Open access, Publication
Collaboration is one of the important 21st-century skills. It can take place in remote or co-located settings. Co-located collaboration (CC) is a very complex process that involves subtle human interactions that can be described with indicators like eye gaze, speaking time, pitch, and social skills from different modalities. With the advent of sensors, multimodal learning analytics has gained momentum to detect CC quality. Indicators (or low-level events) can be used to detect CC quality with the help of measurable markers (i.e., indexes composed of one or more indicators) which give the high-level collaboration process definition. However, this understanding is incomplete without considering the scenarios (such as problem solving or meetings) of CC. The scenario of CC affects the set of indicators considered: for instance, in collaborative programming, grabbing the mouse…
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SoLAR webinar on: Investigating persistent and new challenges of learning analytics

SoLAR webinar on: Investigating persistent and new challenges of learning analytics

July 6, 2021
Artificial Intelligence, Computational Psychometrics, Higher Education, Keynote, Learning Analytics, Learning Design, Multimodal Learning Analytics, School, Workshop
On 29 June 2021, Hendrik Drachsler gave an invited webinar for the SoLAR webinar channel where he reflected the process of applying learning analytics solutions within higher education settings and schools, its implications, and the critical lessons learned in the Trusted Learning Research Program. The talk focused on the experience of edutec.science research collective consisting of researchers from the Netherlands and Germany that contribute to the Trusted Learning Analytics (TLA) research program. The TLA program aims to provide actionable and supportive feedback to students and stands in the tradition of human-centred learning analytics concepts.  It, therefore, applies sensor technology to support psychomotor as well as web technology to support meta-cognitive and collaborative learning skills with high-informative feedback methods. Hendrik applies validated measurement instruments from the field of psychometric and investigates…
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Meine KI-Forschung hilft dabei, produktive Lernverläufe zu identifizieren und Kompetenzen zu verbessern

Meine KI-Forschung hilft dabei, produktive Lernverläufe zu identifizieren und Kompetenzen zu verbessern

May 29, 2021
Artificial Intelligence, Higher Education, Multimodal Learning Analytics, Press
[This article appeared on bildungsserver.de and it was written by Christine Schumann for Deutscher Bildungsserver] Wie bei digitalen Lerneinheiten entstehende Daten für personalisiertes Feedback genutzt werden können. FRAGEN AN Daniele Di Mitri, der im April 2021 in der Kategorie Geistes- und Sozialwissenschaften zum AI-Newcomer des Jahres gewählt wurde. Am DIPF | Leibniz-Institut baut er gerade eine Forschungsgruppe zum Thema Künstliche Intelligenz auf, um verantwortungsvolle KI-Systeme für die Bildung zu entwickeln. Zurzeit konzentrieren sich seine Arbeiten auf praktische Lernaufgaben – und nicht auf allgemeine Lernsituationen im Klassenzimmer. Herr Di Mitri, sind Sie stolz auf Ihre Auszeichnung als „AI Newcomer“ des Jahres 2021? Ja, ich bin begeistert, dass ich im Rahmen des KI-Camps zum „AI Newcomer of 2021“ gewählt wurde. Das KI-Camp ist das nationale Event in Deutschland zur Künstlichen Intelligenz, das das Bundesministerium für…
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Interview for Hessischer Rundfunk

Interview for Hessischer Rundfunk

May 20, 2021
Artificial Intelligence, Higher Education, Multimodal Learning Analytics, Press
Dr. Draniele Di Mitri was interviewed (in German) by Hessischer Rundfunk by Alexander Schmitt. The theme of the episode was: Artificial intelligence is penetrating deeper and deeper into our lives: we talk to computers, rely on their search results and will soon be driven by robot cars. The revolution is just beginning. What are young research talents in Hesse working on? [audio mp3="https://edutec.science/wp-content/uploads/2021/05/hr-info_wirtschaft_20210512_87919984-AudioTrimmer.com_.mp3"][/audio] Listen to the entire episode  Below the answer to the questions translated into English: *** You are interested in education and in technology - is it related to your parents? Yes, I believe I inherited my two main passions from my parents. My father was a first-generation software engineer and my mother was a teacher. In my teenage years, my father showed me how to create a…
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New Pub: Towards Automatic Collaboration Analytics for Group Speech Data Using Multimodal Learning Analytics

New Pub: Towards Automatic Collaboration Analytics for Group Speech Data Using Multimodal Learning Analytics

May 3, 2021
General education, Journal, Multimodal Learning Analytics, Open access, Publication
Collaboration is an important 21st Century skill. Co-located (or face-to-face) collaboration (CC) analytics gained momentum with the advent of sensor technology. Most of these works have used the audio modality to detect the quality of CC. The CC quality can be detected from simple indicators of collaboration such as total speaking time or complex indicators like synchrony in the rise and fall of the average pitch. Most studies in the past focused on “how group members talk” (i.e., spectral, temporal features of audio like pitch) and not “what they talk”. The “what” of the conversations is more overt contrary to the “how” of the conversations. Very few studies studied “what” group members talk about, and these studies were lab based showing a representative overview of specific words as topic clusters…
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Dr Daniele Di Mitri elected AI Newcomer 2021

Dr Daniele Di Mitri elected AI Newcomer 2021

April 27, 2021
Artificial Intelligence, Award, General education, Multimodal Learning Analytics
Dr. Daniele Di Mitri is the AI Newcomer 2021 of the category Humanities and Social Sciences at the KI Camp 2021 organised by the German Informatics Society and the German Federal Ministry of Education. His research is oriented towards the question: how can we best interface artificial intelligence applications with humans to ultimately support human learning, support their goal achievement and boost human productivity? "The only function for which is AI is currently used in higher education is plagiarism check. There is a lot more that AI can do for education. I can imagine realistic application scenario both at primary school, with intelligent tutors via playful interfaces can engage students both individually and in group in learning concepts as geometry, geography, algebra, history, physics." - Daniele Di Mitri, PhD Here the name…
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Workshop on Multimodal Artificial Intelligence in Education (MAIEd’21) 

Workshop on Multimodal Artificial Intelligence in Education (MAIEd’21) 

April 18, 2021
Artificial Intelligence, Higher Education, Multimodal Learning Analytics, Workshop
1st International Workshop on Multimodal Artificial Intelligence in Education (MAIEd'21)  @ the 22nd International Conference on Artificial Intelligence in Education (AIED’2021) https://aied2021.science.uu.nl/ 14th June 2021, 9 am to 4 pm CET online workshop Website: https://maied.edutec.science/ - Proceedings to be published by CEUR (more…)
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Kickoff Meeting: MILKY-PSY – Multimodal Immersive Learning with Artificial Intelligence for Psychomotor Skills

Kickoff Meeting: MILKY-PSY – Multimodal Immersive Learning with Artificial Intelligence for Psychomotor Skills

March 5, 2021
Digitalisation, Higher Education, Multimodal Learning Analytics, Project
Those who want to learn a sport train new psychomotor skills. Until now, this has required role models such as teachers on site who explain, demonstrate and assess certain processes. A consortium around the Cologne Game Lab of the TH Köln is developing a learning environment with artificial intelligence (AI) to support the training process as part of the joint research project MILKI-PSY.   Wer eine Sportart erlernen will, trainiert neue psychomotorische Fähigkeiten. Bislang werden dafür Vorbilder wie Lehrerinnen und Lehrer vor Ort benötigt, die bestimmte Abläufe erklären, zeigen und beurteilen. Ein Konsortium um das Cologne Game Lab der TH Köln entwickelt im Rahmen des Verbundforschungsprojekts MILKI-PSY eine Lernumgebung mit künstlicher Intelligenz (KI), die den Trainingsprozess unterstützen soll. Künstlerische, sportliche und handwerkliche Tätigkeiten erfordern psychomotorische Fähigkeiten, bei denen körperliche Bewegungen mit…
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