May 2025 - EduTec Science

May302025 by Sebastian GombertNo Comments

[Workshop] Introduction to Language Technology and Language Modeling for Education

New Pub

At the recent 19th Joint Summer School on Technology-Enhanced Learning located in Rhetimno, Greece, I (Sebastian Gombert) gave an introductory workshop on language technology and language modeling and their various use cases of in education. This included use cases such as short answer scoring, essay scoring, classification of texts according to the CEFR framework, and group communication analysis in CSCL. Overall, the workshop was well-received and well-attended.

May222025 by Heather WehnerNo Comments

New Pub: Pedagogical Framework for Hybrid Intelligent Feedback

Artificial Intelligence, Feedback, Journal, Publication

[caption id="attachment_7525" align="alignright" width="300"] Principles of hybrid intelligent Feedback[/caption] ChatGPT and other Generative Artificial Intelligence (GenAI) tools have quickly become an active part of everyday academic life. Both teachers and students use them regularly to do research, summarize texts or responses, create exercises or quizzes or explain course content. But GenAI needs to be used in a sensible manner and consistent with sound teaching principles. Otherwise, it could lead to an over-reliance on technology and neglect the important roles of teachers and students. Ideally, GenAI should be used to complement rather than replace human-centered education. When pedagogical practices combine the strengths of humans and AI, this can ultimately lead to enhanced creativity, empathy and academic comprehension of students. A recently published paper explores a promising field of human-AI collaboration in…

May152025 by Heather WehnerNo Comments

ML2MT at the “AI and the Future of Society” Symposium

Artificial Intelligence, Conference, Event

At the final symposium “AI and the Future of Society” on April 23, 2025, the ML2MT project team presented key outcomes from their research on human-machine collaboration. Moving beyond traditional AI, the project explored how machines and humans can mutually benefit and learn from each other in a continuous loop. The results of this interdisciplinary project span multiple domains: In medicine, AI systems were found not only to assist diagnoses but also to promote reflection among professionals, encouraging deeper awareness of their decision-making processes. In education, adaptive AI tools were developed to analyze student feedback and help teachers identify learning gaps more effectively. In human-AI interaction, systems were designed to remember and apply user feedback, improving efficiency and reducing the need for repetitive input. Looking ahead, the project will focus…