2 citations · 5 across the 16 of their papers we have counts for
19 papers
The Role of Implicit and Explicit Demographic Signals in Large Language Model-based Student Assessment
Donya Rooein, Luca Benedetto, Dirk Hovy
Large Language Models are now common in student assessment, but we know little about how student demographics affect their use. Sometimes, considering student demographics may be n…
Symphony of Bias: Exploring Gender Associations with Musical Instruments in Multimodal LLMs
Farhan Farsi, Shayan Bali, Mohammad Heydari Rad +2
Large language models (LLMs) are increasingly embedded in everyday life and widely used for information seeking, raising concerns about their potential to perpetuate social biases…
Incentives Of EdTech: A Systematic Review Of EduNLP Research
Gabrielle Gaudeau, Aoife O'Driscoll, Jasper Degraeuwe +3
While the Natural Language Processing community has dedicated significant resources in developing educational technologies (EdTech) that support this shift, it remains unclear whos…
GeoDial: A Multimodal Conversational Tutoring Dataset for Geometry Problem-Solving with Visual Tutor Turns
Sankalan Pal Chowdhury, Junling Wang, Donya Rooein +2
Several educational domains rely heavily on diagrams and visual cues, yet most existing tutoring datasets are limited to text-only interactions. This limits the development of AI t…
Can LLMs Model Incorrect Student Reasoning? A Case Study on Distractor Generation
Yanick Zengaffinen, Andreas Opedal, Donya Rooein +3
Modeling student misconceptions in a realistic manner is critical for AI in education. In this work, we examine how large language models (LLMs) reason about misconceptions when ge…
PATS: Personality-Aware Teaching Strategies with Large Language Model Tutors
Donya Rooein, Sankalan Pal Chowdhury, Mariia Eremeeva +4
Recent advances in large language models (LLMs) demonstrate their potential as educational tutors. However, different tutoring strategies benefit different student personalities, a…
Teacher Demonstrations in a BabyLM's Zone of Proximal Development for Contingent Multi-Turn Interaction
Suchir Salhan, Hongyi Gu, Donya Rooein +5
Multi-turn dialogues between a child and a caregiver are characterized by a property called contingency - that is, prompt, direct, and meaningful exchanges between interlocutors. W…
Biased Tales: Cultural and Topic Bias in Generating Children's Stories
Donya Rooein, Vilém Zouhar, Debora Nozza +1
Stories play a pivotal role in human communication, shaping beliefs and morals, particularly in children. As parents increasingly rely on large language models (LLMs) to craft bedt…
Exploring Subjective Tasks in Farsi: A Survey Analysis and Evaluation of Language Models
Donya Rooein, Flor Miriam Plaza-del-Arco, Debora Nozza +1
Given Farsi's speaker base of over 127 million people and the growing availability of digital text, including more than 1.3 million articles on Wikipedia, it is considered a middle…
Co-DETECT: Collaborative Discovery of Edge Cases in Text Classification
Chenfei Xiong, Jingwei Ni, Yu Fan +10
We introduce Co-DETECT (Collaborative Discovery of Edge cases in TExt ClassificaTion), a novel mixed-initiative annotation framework that integrates human expertise with automatic…
Educators' Perceptions of Large Language Models as Tutors: Comparing Human and AI Tutors in a Blind Text-only Setting
Sankalan Pal Chowdhury, Terry Jingchen Zhang, Donya Rooein +3
The rapid development of Large Language Models (LLMs) opens up the possibility of using them as personal tutors. This has led to the development of several intelligent tutoring sys…
Can Reasoning Help Large Language Models Capture Human Annotator Disagreement?
Jingwei Ni, Yu Fan, Vilém Zouhar +6
Variation in human annotation (i.e., disagreements) is common in NLP, often reflecting important information like task subjectivity and sample ambiguity. Modeling this variation is…
Multilingual Performance Biases of Large Language Models in Education
Vansh Gupta, Sankalan Pal Chowdhury, Vilém Zouhar +2
Large language models (LLMs) are increasingly being adopted in educational settings. These applications expand beyond English, though current LLMs remain primarily English-centric.…
MSTS: A Multimodal Safety Test Suite for Vision-Language Models
Paul Röttger, Giuseppe Attanasio, Felix Friedrich +19
Vision-language models (VLMs), which process image and text inputs, are increasingly integrated into chat assistants and other consumer AI applications. Without proper safeguards,…
Beyond Flesch-Kincaid: Prompt-based Metrics Improve Difficulty Classification of Educational Texts
Donya Rooein, Paul Rottger, Anastassia Shaitarova +1
Using large language models (LLMs) for educational applications like dialogue-based teaching is a hot topic. Effective teaching, however, requires teachers to adapt the difficulty…
Can I introduce my boyfriend to my grandmother? Evaluating Large Language Models Capabilities on Iranian Social Norm Classification
Hamidreza Saffari, Mohammadamin Shafiei, Donya Rooein +2
Creating globally inclusive AI systems demands datasets reflecting diverse social norms. Iran, with its unique cultural blend, offers an ideal case study, with Farsi adding linguis…
Conversations as a Source for Teaching Scientific Concepts at Different Education Levels
Donya Rooein, Dirk Hovy
Open conversations are one of the most engaging forms of teaching. However, creating those conversations in educational software is a complex endeavor, especially if we want to add…
Know Your Audience: Do LLMs Adapt to Different Age and Education Levels?
Donya Rooein, Amanda Cercas Curry, Dirk Hovy
Large language models (LLMs) offer a range of new possibilities, including adapting the text to different audiences and their reading needs. But how well do they adapt? We evaluate…
Image-based Social Sensing: Combining AI and the Crowd to Mine Policy-Adherence Indicators from Twitter
Virginia Negri, Dario Scuratti, Stefano Agresti +6
Social Media provides a trove of information that, if aggregated and analysed appropriately can provide important statistical indicators to policy makers. In some situations these…