Research topic Archives - Page 21 of 21

Mar52021 by Prof. Dr. Hendrik DrachslerNo Comments

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

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…

Feb252021 by Prof. Dr. Hendrik DrachslerNo Comments

KI@Schule – Virtueller Expert*innen-Workshop

Artificial Intelligence, Learning Analytics, Project, School, Workshop

Prof. Dr. Hendrik Drachsler wurde von der Deutschen Telekom-Stiftung mit 15 weiteren Expert*innen zum virtuellen Workshop „KI@Schule – Zwischen Wunsch und Wahrscheinlichkeit“ am 25. Februar 2021 eingeladen, um die Befunde der Trend- und Zukunftsstudie „Künstliche Intelligenz in der schulischen Bildung“ zu diskutieren. Prof. Dr Hendrik Drachsler and 15 other experts were invited by the Deutsche Telekom Foundation to the virtual workshop "KI@Schule - Zwischen Wunsch und Wahrscheinlichkeit" on 25 February 2021 to discuss the findings of the trend and future study "Künstliche Intelligenz in der schulischen Bildung".

Feb152021 by Atezaz AhmadNo Comments

NEW Newsletter and Update on AR4STEAM

Augmented Reality, Digitalisation, Project, Publication, Report, School

AR4STE(A)M Newsletter 2 We have the pleasure to update you by this Newsletter with advance made in our project, which is designed to provide attractive means and ways to improve current technological methods, encouraging STEAM education. Joining us, you will find in our publications a lot of useful information, tips and new opportunities for modern and effective teaching.

Feb112021 by Atezaz AhmadNo Comments

Nina Seidenberg joins the team

Learning Analytics, Team

Starting January 1st 2021 Nina Seidenberg joins the EduTech team. She has a part time position at the DIPF and is also working for studiumdigitale (Goethe University). She was one of the organizing chairs of the 10th international Learning Analytics and Knowledge Conference, one of the very first conferences that was moved to the virtual space in spring 2020.Her research focuses on the management and design of virtual conferences.

Feb82021 by Atezaz AhmadNo Comments

Onur Karademir joins the team

Learning Analytics, Team

Starting February 1st 2021 Onur Karademir joins the EduTec team as a PhD candidate. During his studies in M.Sc. Computer Science at the Goethe University Frankfurt he worked at the studential think thank #DigitalChangeMaker of Hochschulreform Digitalisierung. After graduating he founded in 2020 the StartUp StudyCore which delivers EdTech Tools for Universities and Schools. In his research Onur will be working on various Learning Analytics algorithms to distinguish successful learning strategies and extract the acquired skills in a learning environment. Furthermore he will be working on didactical feedback to support the individual learning process.

Dec222020 by Prof. Dr. Hendrik DrachslerNo Comments

New Pub: A four-country cross-case analysis of academic staff expectations about learning analytics in higher education

Higher Education, Journal, Learning Analytics, Open access, Publication

The purpose of this paper is to explore the expectations of academic staff to learning analytics services from an ideal as well as a realistic perspective. This mixed-method study focused on a cross-case analysis of staff from Higher Education Institutions from four European universities (Spain, Estonia, Netherlands, UK). While there are some differences between the countries as well as between ideal and predicted expectations, the overarching results indicate that academic staff sees learning analytics as a tool to understand the learning activities and possibility to provide feedback for the students and adapt the curriculum to meet learners' needs. However, one of the findings from the study across cases is the generally consistently low expectation and desire for academic staff to be obligated to act based on data that shows students…

Dec42020 by Jan SchneiderNo Comments

New Pub: Understanding Graph Problem solving with the use of Eye-tracking and Epistemic Network Analysis

Journal, Multimodal Learning Analytics, Open access, Publication, School

Epistemic Network Analyses of Economics Students’ Graph Understanding: An Eye-Tracking Study Learning to solve graph tasks is one of the key prerequisites of acquiring domain-specific knowledge in most study domains. Analyses of graph understanding often use eye-tracking and focus on analyzing how much time students spend gazing at particular areas of a graph—Areas of Interest (AOIs). To gain a deeper insight into students’ task-solving process, we argue that the gaze shifts between students’ fixations on different AOIs (so-termed transitions) also need to be included in holistic analyses of graph understanding that consider the importance of transitions for the task-solving process. Thus, we introduced Epistemic Network Analysis (ENA) as a novel approach to analyze eye-tracking data of 23 university students who solved eight multiple-choice graph tasks in physics and economics. ENA…

Nov132020 by Prof. Dr. Hendrik DrachslerNo Comments

KickOff – AFLEK Projekt

Learning Analytics, Project

Learning Progression Analytics - Analyse und Förderung von Lernverläufen zur Entwicklung von Kompetenzen (AFLEK) Basierend auf ersten Forschungsergebnissen rund um die Trusted Learning Analytics Infrastructure der EduTec Gruppe, haben wir zusammen mit Prof. Dr. Knut Neumann from Leibniz-Institut für die Pädagogik der Naturwissenschaften und Mathematik (IPN) in Kiel und Prof. Dr. Nikol Rummel von der Ruhr-Universität Bochum ein Projekt zur Analyse und Förderung von Lernverläufen zur Entwicklung von Kompetenzen (AFLEK) einwerben können. Das AFLEK Projekt wird durch das BMBF Programm Digitalisierung II - Forschung zur Gestaltung von Bildungsprozessen unter den Bedingungen des digitalen Wandels gefördert. Digitalen Technologien wird ein hohes Potential für die Optimierung von Bildungsprozessen zugesprochen. Sie erlauben ein stärker personalisiertes Lernen, das es allen Schülerinnen und Schülern ermöglicht, die für eine gesellschaftliche und insbesondere berufliche Teilhabe erforderlichen Kompetenzen…

Nov52020 by Jan SchneiderNo Comments

New Pub: Beitrag zu Buch: Digitale Bildung und Künstliche Intelligenz in Deutschland

Artificial Intelligence, Multimodal Learning Analytics, Publication

Das Buch "Digitale Bildung und Künstliche Intelligenz in Deutschland" mit unserem Kapitel "Der multimodale Lern-Hub: Ein Werkzeug zur Sammlung individualisierbarer und sensorgestützter multimodaler Lernerfahrungen" wurde veröffentlicht. In diesem Kapitel wird ein Tool vorgestellt, mit dem Forscher anpassbare Prototypen erstellen können, um Lernaufgaben mithilfe multimodaler Daten zu untersuchen. References: Schneider, J., Di Mitri, D., Limbu, B., & Drachsler, H. (2020). Der multimodale Lern-Hub: Ein Werkzeug zur Erfassung individualisierbarer und sensorgestützter multimodaler Lernerfahrungen. In Digitale Bildung und Künstliche Intelligenz in Deutschland (pp. 537-557). Springer, Wiesbaden.

Aug12020 by Prof. Dr. Hendrik DrachslerNo Comments

New Pub: Learning Analytics Cookbook – How to Support Learning Processes Through Data Analytics and Visualization

General education, Learning Analytics, Publication

This book offers an introduction and hands-on examples that demonstrate how Learning Analytics (LA) can be used to enhance digital learning, teaching and training at various levels. While the majority of existing literature on the subject focuses on its application at large corporations, this book develops and showcases approaches that bring LA closer to smaller organizations, and to educational institutions that lack sufficient resources to implement a full-fledged LA infrastructure. In closing, the book introduces a set of software tools for data analytics and visualization, and explains how they can be employed in several LA scenarios. Reference: Jaakonmäki, R., vom Brocke, J., Dietze, S., Drachsler, H., Fortenbacher, A., Helbig, R., Kickmeier-Rust, M., Marenzi, I., Fernández, Á.S., Yun, H. (2020). Learning Analytics Cookbook - How to Support Learning Processes Through Data Analytics and Visualization. SpringerBriefs in Business Process Management, XI, 93, DOI: 10.1007/978-3-030-43377-2,…