Tanja Christina Käser Jacober

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Detecting learners in need of support is a complex process for both teachers and machines. Most prior work has devised visualization tools that allow teachers to do so by analyzing educational indicators. Other recent efforts have been devoted to models th ...

Reflective writing is known as a useful method in learning sciences to improve the metacognitive skills of students. However, students struggle to structure their reflections properly, limiting the possible learning gains. Previous works in educational tec ...

Algorithms deployed in education can shape the learning experience and success of a student. It is therefore important to understand whether and how such algorithms might create inequalities or amplify existing biases. In this paper, we analyze the fairnes ...

Interactive simulations allow students to discover the underlying principles of a scientific phenomenon through their own exploration. Unfortunately, students often struggle to learn effectively in these environments. Classifying students’ interaction data ...

Clustering in education, particularly in large-scale online environments like MOOCs, is essential for understanding and adapting to diverse student needs. However, the effectiveness of clustering depends on its interpretability, which becomes challenging w ...

While large language models (LLMs) are increasingly playing a pivotal role in education by providing instantaneous, adaptive responses, their potential to promote critical thinking remains understudied. In this paper, we fill such a gap and present an inno ...

Conversational agents (CAs) provide opportunities for improving the interaction in evaluation surveys. To investigate if and how a user-centered conversational evaluation tool impacts users' response quality and their experience, we build EVA - a novel con ...

Writing high-quality procedural texts is a challenging task for many learners. While example-based learning has shown promise as a feedback approach, a limitation arises when all learners receive the same content without considering their individual input ...

As educational technology becomes increasingly integrated into curricula, more students are engaging with online learning platforms, interactive simulations, and MOOCs. These unstructured environments record students’ behaviors, providing a rich source of ...

Recent advantages from computational linguists can be leveraged to nudge students with adaptive self-evaluation based on their argumentation skill level. To investigate how individual argumentation self-evaluation will help students write more convincing t ...

Traditional example-based learning methods are often limited by static, expert-created content. Hence, they face challenges in scalability, engagement, and effectiveness, as some learners might struggle to relate to the examples or find them relevant. To a ...

This paper investigates the potential impact of deep generative models on the work of creative professionals. We argue that current generative modeling tools lack critical features that would make them useful creativity support tools, and introduce our own ...

Modeling and predicting student learning in computer-based environments often relies solely on sequences of accuracy data. Previous research suggests that it does not only matter what we learn, but also how we learn. The detection and analysis of learning ...

Neural networks are ubiquitous in applied machine learning for education. Their pervasive success in predictive performance comes alongside a severe weakness, the lack of explainability of their decisions, especially relevant in human-centric fields. We im ...

The increasing availability of Massive Open Online Courses (MOOCs) has created a necessity for personalized course recommendation systems. These systems often combine neural networks with Knowledge Graphs (KGs) to achieve richer representations of learners ...

Intelligent Tutoring Systems (ITS) enhance personalized learning by predicting student answers to provide immediate and customized instruction. However, recent research has primarily focused on the correctness of the answer rather than the student's perfor ...

In recent decades, we have witnessed the democratization of AI-powered Educational Technology (AI-EdTech). However, despite the increased accessibility and evolving technological capabilities, its adoption is accompanied by significant challenges, predomin ...

Reflective writing is known to be effective in improving students’ learning process. However, learners often encounter difficulties when reflecting, struggling to formulate their thoughts constructively. While conversational agents have been shown to be be ...

There has been a growing interest in developing simulated learners to enhance learning and teaching experiences in educational environments. However, existing works have primarily focused on structured environments relying on meticulously crafted represent ...

Explainable Artificial Intelligence (XAI) plays a crucial role in enabling human understanding and trust in deep learning systems, often defined as determining which features are most important to a model's prediction. As models get larger, more ubiquitous ...

Tanja Christina Käser Jacober

Chattez avec Graph Search

How Close are Predictive Models to Teachers in Detecting Learners at Risk?

Metacognition meets AI: Empowering reflective writing with large language models

Protected Attributes Tell Us Who, Behavior Tells Us How: A Comparison of Demographic and Behavioral Oversampling for Fair Student Success Modeling

Generalisable Methods for Early Prediction in Interactive Simulations for Education

Interpret3C: Interpretable Student Clustering Through Individualized Feature Selection

Enhancing Critical Thinking in Education by Means of a Socratic Chatbot

Designing Conversational Evaluation Tools

Enhancing Procedural Writing Through Personalized Example Retrieval: A Case Study on Cooking Recipes

An Interpretable Approach to Identify Performance Indicators Within Unstructured Learning Environments

Improving Students Argumentation Learning with Adaptive Self-Evaluation Nudging

GELEX: Generative AI-Hybrid System for Example-Based Learning

Fashioning Creative Expertise with Generative AI: Graphical Interfaces for GAN-Based Design Space Exploration Better Support Ideation Than Text Prompts for Diffusion Models

Modeling and Analyzing Inquiry Strategies in Open-Ended Learning Environments

Evaluating the Explainers: Black-Box Explainable Machine Learning for Student Success Prediction in MOOCs

Finding Paths for Explainable MOOC Recommendation: A Learner Perspective

Student Answer Forecasting: Transformer-Driven Answer Choice Prediction for Language Learning

The critical role of trust in adopting AI-powered educational technology for learning: An instrument for measuring student perceptions

MindMate: Exploring the Effect of Conversational Agents on Reflective Writing

PharmaSimText: A Text-Based Educational Playground filled with RL-LLM Agents That Work Together Even in Disagreement

The future of human-centric eXplainable Artificial Intelligence (XAI) is not post-hoc explanations