256 citations · 1.5k across the 113 of their papers we have counts for
9 papers · 1 filter
Sycophancy is an Educational Safety Risk: Why LLM Tutors Need Sycophancy Benchmarks
Enkelejda Kasneci, Gjergji Kasneci
This position paper argues that effective tutoring requires corrective friction: surfacing misconceptions and challenging them supportively to drive conceptual change. Yet preferen…
Towards Adaptive Feedback with AI: Comparing the Feedback Quality of LLMs and Teachers on Experimentation Protocols
Kathrin Seßler, Arne Bewersdorff, Claudia Nerdel +1
Effective feedback is essential for fostering students' success in scientific inquiry. With advancements in artificial intelligence, large language models (LLMs) offer new possibil…
From Passive Watching to Active Learning: Empowering Proactive Participation in Digital Classrooms with AI Video Assistant
Anna Bodonhelyi, Enkeleda Thaqi, Süleyman Özdel +2
In online education, innovative tools are crucial for enhancing learning outcomes. SAM (Study with AI Mentor) is an advanced platform that integrates educational videos with a cont…
Stepwise Self-Consistent Mathematical Reasoning with Large Language Models
Zilong Zhao, Yao Rong, Dongyang Guo +3
Using Large Language Models for complex mathematical reasoning is difficult, primarily due to the complexity of multi-step reasoning. The main challenges of this process include (1…
Taking the Next Step with Generative Artificial Intelligence: The Transformative Role of Multimodal Large Language Models in Science Education
Arne Bewersdorff, Christian Hartmann, Marie Hornberger +6
The integration of Artificial Intelligence (AI), particularly Large Language Model (LLM)-based systems, in education has shown promise in enhancing teaching and learning experience…
I-CEE: Tailoring Explanations of Image Classification Models to User Expertise
Yao Rong, Peizhu Qian, Vaibhav Unhelkar +1
Effectively explaining decisions of black-box machine learning models is critical to responsible deployment of AI systems that rely on them. Recognizing their importance, the field…
Assessing Student Errors in Experimentation Using Artificial Intelligence and Large Language Models: A Comparative Study with Human Raters
Arne Bewersdorff, Kathrin Seßler, Armin Baur +2
Identifying logical errors in complex, incomplete or even contradictory and overall heterogeneous data like students' experimentation protocols is challenging. Recognizing the limi…
Towards Human-centered Explainable AI: A Survey of User Studies for Model Explanations
Yao Rong, Tobias Leemann, Thai-trang Nguyen +6
Explainable AI (XAI) is widely viewed as a sine qua non for ever-expanding AI research. A better understanding of the needs of XAI users, as well as human-centered evaluations of e…
Artificial Intelligence Methods in In-Cabin Use Cases: A Survey
Yao Rong, Chao Han, Christian Hellert +2
As interest in autonomous driving increases, efforts are being made to meet requirements for the high-level automation of vehicles. In this context, the functionality inside the ve…