5 citations · 10 across the 11 of their papers we have counts for
12 papers
Prompting Against Persona Drift: Comparing Intervention Timing and Content in LLM-Simulated Conversations
Nicolas Leins, Jennifer Haase, Varvara Geronimus +2
Simulating student personas with large language models (LLMs) enables scalable evaluation of educational systems. However, behavioral drift, a progressive decline in persona consis…
LLM-Based Educational Simulation: Evaluating Temporal Student Persona Stability Across ADHD Profiles
Jana Gonnermann-Müller, Jennifer Haase, Nicolas Leins +2
Large language model (LLM)-based student simulation offers a scalable alternative for educational research, teacher training, and learner practice. However, its validity depends on…
Within-Model vs Between-Prompt Variability in Large Language Models for Creative Tasks
Jennifer Haase, Jana Gonnermann-Müller, Paul H. P. Hanel +4
How much of LLM output variance is explained by prompts versus model choice versus stochasticity through sampling? We answer this by evaluating 12 LLMs on 10 creativity prompts wit…
Stable Personas: Dual-Assessment of Temporal Stability in LLM-Based Human Simulation
Jana Gonnermann-Müller, Jennifer Haase, Nicolas Leins +2
Large Language Models (LLMs) acting as artificial agents offer the potential for scalable behavioral research, yet their validity depends on whether LLMs can maintain stable person…
FACET: Multi-Agent AI Supporting Teachers in Scaling Differentiated Learning for Diverse Students
Jana Gonnermann-Müller, Jennifer Haase, Nicolas Leins +3
Classrooms are becoming increasingly heterogeneous, comprising learners with diverse performance and motivation levels, language proficiencies, and learning differences such as dys…
FACET: Teacher-Centred LLM-Based Multi-Agent Systems-Towards Personalized Educational Worksheets
Jana Gonnermann-Müller, Jennifer Haase, Konstantin Fackeldey +1
The increasing heterogeneity of student populations poses significant challenges for teachers, particularly in mathematics education, where cognitive, motivational, and emotional d…
Beyond Static Responses: Multi-Agent LLM Systems as a New Paradigm for Social Science Research
Jennifer Haase, Sebastian Pokutta
As large language models (LLMs) transition from static tools to fully agentic systems, their potential for transforming social science research has become increasingly evident. Thi…
S-DAT: A Multilingual, GenAI-Driven Framework for Automated Divergent Thinking Assessment
Jennifer Haase, Paul H. P. Hanel, Sebastian Pokutta
This paper introduces S-DAT (Synthetic-Divergent Association Task), a scalable, multilingual framework for automated assessment of divergent thinking (DT) -a core component of huma…
Has the Creativity of Large-Language Models peaked? An analysis of inter- and intra-LLM variability
Jennifer Haase, Paul H. P. Hanel, Sebastian Pokutta
Following the widespread adoption of ChatGPT in early 2023, numerous studies reported that large language models (LLMs) can match or even surpass human performance in creative task…
Augmenting Coaching with GenAI: Insights into Use, Effectiveness, and Future Potential
Jennifer Haase
The integration of generative AI (GenAI) tools, particularly large language models (LLMs), is transforming professional coaching workflows. This study explores how coaches use GenA…
Human-AI Co-Creativity: Exploring Synergies Across Levels of Creative Collaboration
Jennifer Haase, Sebastian Pokutta
Human-AI co-creativity represents a transformative shift in how humans and generative AI tools collaborate in creative processes. This chapter explores the synergies between human…
From Influencers to Lecturers: Understanding Public Attitudes Toward Digital vs. Traditional Jobs
Paul H. P. Hanel, Gabriel Lins de Holanda Coelho, Jennifer Haase
The rapid expansion of high-speed internet has led to the emergence of new digital jobs, such as digital influencers, fitness models, and adult models who share content on subscrip…