Dr Daniele Di Mitri elected AI Newcomer 2021

Dr Daniele Di Mitri elected AI Newcomer 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) 

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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Best Paper award @LAK21 – Quantum of Choice

Best Paper award @LAK21 – Quantum of Choice

Award, Conference, Empirical Study, Higher Education, Learning Analytics, Open access, Publication
Learning analytics dashboards (LADs) are designed as feedback tools for learners, but until recently, learners rarely have had a say in how LADs are designed and what information they receive through LADs. To overcome this shortcoming, we have developed a customisable LAD for Coursera MOOCs on which learners can set goals and choose indicators to monitor. Following a mixed-methods approach, we analyse 401 learners’ indicator selection behaviour in order to understand the decisions they make on the LAD and whether learner goals and self-regulated learning skills influence these decisions. We found that learners overwhelmingly chose indicators about completed activities. Goals are not associated with indicator selection behaviour, while help-seeking skills predict learners’ choice of monitoring their engagement in discussions and time management skills predict learners’ interest in procrastination indicators. The…
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Joshua Weidlich joins the team

Joshua Weidlich joins the team

Computational Psychometrics, Learning Design, Team
Starting April 2021, Joshua Weidlich joins the team as PostDoctoral researcher. He completed his PhD on social presence in online learning environments at the FernUniversität in Hagen in February 2021. He holds a Master's Degree in E-Learning and Media Education from Heidelberg University of Education as well as a Bachelor's Degree in Educational Science from Chemnitz University of Technology. See profile page for more information.
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