Lea Cohausz

According to our database, Lea Cohausz authored at least 16 papers between 2022 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

What Fairness Metrics Can Really Tell You: A Case Study in the Educational Domain.

Lea Cohausz, Jakob Kappenberger, Heiner Stuckenschmidt

Proceedings of the 14th Learning Analytics and Knowledge Conference, 2024

Preface.

Juan Pinto, Luc Paquette, Vinitra Swamy, Tanja Käser, Qianhui Liu, Lea Cohausz

Proceedings of the Joint Proceedings of the Human-Centric eXplainable AI in Education and the Leveraging Large Language Models for Next Generation Educational Technologies Workshops (HEXED-L3MNGET 2024) co-located with 17th International Conference on Educational Data Mining (EDM 2024), 2024

Human-Centric eXplainable AI in Education (HEXED) Workshop.

Juan Pinto, Luc Paquette, Vinitra Swamy, Tanja Käser, Qianhui Liu, Lea Cohausz

Proceedings of the 17th International Conference on Educational Data Mining, 2024

Thinking Causally in EDM: A Hands-On Tutorial for Causal Modeling Using DAGs.

Lea Cohausz

Proceedings of the 17th International Conference on Educational Data Mining, 2024

Fact Probability Vector Based Goal Recognition.

Nils Wilken, Lea Cohausz, Christian Bartelt, Heiner Stuckenschmidt

Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

Developing a Personalized Study Program Recommender.

Marc Scheffler, Thilo I. Dieing, Lea Cohausz

Proceedings of DELFI Workshops 2024, Fulda, Germany, September 9-11, 2024, 2024

Enhancing Chatbot-Assisted Study Program Orientation.

Thilo I. Dieing, Marc Scheffler, Lea Cohausz

Proceedings of DELFI Workshops 2024, Fulda, Germany, September 9-11, 2024, 2024

Workshop Learning Analytics: Study Path and Curriculum Analytics.

Lea Cohausz, Frederik Baucks, Niels Seidel

Proceedings of DELFI Workshops 2024, Fulda, Germany, September 9-11, 2024, 2024

Combining Fairness and Causal Graphs to Advance Both.

Lea Cohausz, Jakob Kappenberger, Heiner Stuckenschmidt

Proceedings of the 2nd Workshop on Fairness and Bias in AI co-located with 27th European Conference on Artificial Intelligence (ECAI 2024), 2024

2023

Leveraging Planning Landmarks for Hybrid Online Goal Recognition.

Nils Wilken, Lea Cohausz, Johannes Schaum, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt

CoRR, 2023

Investigating the Combination of Planning-Based and Data-Driven Methods for Goal Recognition.

Nils Wilken, Lea Cohausz, Johannes Schaum, Stefan Lüdtke, Heiner Stuckenschmidt

CoRR, 2023

Planning Landmark Based Goal Recognition Revisited: Does Using Initial State Landmarks Make Sense?

Nils Wilken, Lea Cohausz, Christian Bartelt, Heiner Stuckenschmidt

Proceedings of the KI 2023: Advances in Artificial Intelligence, 2023

Investigating the Importance of Demographic Features for EDM-Predictions.

Lea Cohausz, Andrej Tschalzev, Christian Bartelt, Heiner Stuckenschmidt

Proceedings of the 16th International Conference on Educational Data Mining, 2023

2022

Predicting Master's students' academic performance: an empirical study in Germany.

Sarah Alturki, Lea Cohausz, Heiner Stuckenschmidt

Smart Learn. Environ., 2022

Plan-Similarity Based Heuristics for Goal Recognition.

Lea Cohausz, Nils Wilken, Heiner Stuckenschmidt

Proceedings of the 2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, 2022

Towards Real Interpretability of Student Success Prediction Combining Methods of XAI and Social Science.

Lea Cohausz

Proceedings of the 15th International Conference on Educational Data Mining, 2022