Interpret3C: Interpretable Student Clustering Through Individualized Feature Selection

I. Salles; P. Mejia; V. Swamy; J. Blackwell; T. Käser 

InterpretCC: Intrinsic User-Centric Interpretability through Global Mixture of Experts

V. Swamy; S. Montariol; J. Blackwell; J. A. Frej; M. Jaggi et al. 

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

E. G. Gado; T. Martorella; L. Zunino; P. Mejia-Domenzain; V. Swamy et al. 

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

A. Yazici; P. Meija-Domenzain; J. A. Frej; T. Käser 

Evaluating the Impact of Learner Control and Interactivity in Conversational Tutoring Systems for Persuasive Writing

T. Wambsganss; I. Benke; A. Maedche; K. Koedinger; T. Käser 

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

P. Mejia-Domenzain; J. A. Frej; S. P. Neshaei; L. Mouchel; T. Nazaretsky et al. 

Finding Paths for Explainable MOOC Recommendation: A Learner Perspective

J. A. Frej; N. Shah; M. Knezevic; T. Nazaretsky; T. Käser 

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

R. L. Davis; T. Wambsganss; W. Jiang; K. G. Kim; T. Käser et al. 

Finding Paths for Explainable MOOC Recommendation: A Learner Perspective

J. A. Frej; S. Neel; K. Marta; T. Nazaretsky; T. Käser 

Simulated Learners in Educational Technology: A Systematic Literature Review and a Turing-like Test

T. Kaser; G. Alexandron 

Consistency of Inquiry Strategies Across Subsequent Activities in Different Domains

J. M. Cock; I. Roll; T. Käser 

Fashioning the Future: Unlocking the Creative Potential of Deep Generative Models for Design Space Exploration

R. L. Davis; T. Wambsganss; W. Jiang; K. G. Kim; T. Käser et al. 

Trusting the Explainers: Teacher Validation of Explainable Artificial Intelligence for Course Design

V. Swamy; S. Du; M. Marras; T. Käser 

Understanding Revision Behavior in Adaptive Writing Support Systems for Education

L. Mouchel; T. Wambsganss; P. Mejia; T. Käser 

MultiModN- Multimodal, Multi-Task, Interpretable Modular Networks

V. Swamy; M. Satayeva; J. Frej; T. Bossy; T. Vogels et al. 

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

R. Galici; T. Kaser; G. Fenu; M. Marras 

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

V. Swamy; J. A. Frej; T. Käser 

Co-Designing a Teacher Tool for Visualizing Self-Regulated Learning Behaviors

E. Laini 

Improving Students Argumentation Learning with Adaptive Self-Evaluation Nudging

T. Wambsganss; A. Janson; T. Käser; J. M. Leimeister 

Maschinelles Lernen zur Förderung von höheren Kompetenzen

C. Giang; T. Wambsganss; T. Käser 

Evolutionary Clustering of Apprentices’ Self- Regulated Learning Behavior in Learning Journals

P. Mejia; M. Marras; C. Giang; A. Cattaneo; T. Käser 

Identifying and Comparing Multi-dimensional Student Profiles Across Flipped Classrooms

P. Mejia; M. Marras; C. Giang; T. Käser 

Generalisable Methods for Early Prediction in Interactive Simulations for Education

J. M. L. Cock; M. Marras; C. Giang; T. Käser 

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

V. Swamy; B. Radmehr; N. Krco; M. Marras; T. Käser 

Meta Transfer Learning for Early Success Prediction in MOOCs

V. Swamy; M. Marras; T. Käser 

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

J. M. Cock; M. Bilal; R. Davis; M. Marras; T. Käser 

Ripple: Concept-Based Interpretation for Raw Time Series Models in Education

M. Asadi; V. Swamy; J. Frej; J. Vignoud; M. Marras et al. 

Introducing Productive Engagement for Social Robots Supporting Learning

Bias at a Second Glance: A Deep Dive into Bias for German Educational Peer-Review Data Modeling

T. Wambsganss; V. Swamy; R. Rietsche; T. Käser 

How We Use Wikipedia: Studying Readers’ Behavior with Navigation Traces

Design and evaluation of digital tools to expand experience in vocational education

Can Feature Predictive Power Generalize? Benchmarking Early Predictors of Student Success across Flipped and Online Courses

M. Marras; T. Tu; J. Vignoud; T. Käser 

Early Prediction of Conceptual Understanding in Interactive Simulations

J. M. L. Cock; M. Marras; C. Giang; T. Käser 

Designing Intelligent Systems for Online Education: Open Challenges and Future Directions

D. Dessì; T. Käser; M. Marras; E. Popescu; H. Sack 

L2D 2021: First International Workshop on Enabling Data-Driven Decisions from Learning on the Web

D. Dessi; T. Käser; M. Marras; E. Popescu; H. Sack 

Computational Analysis and Design of Structurally Stable Assemblies with Rigid Parts

Learning Analytics for Adaptive and Self-Improving Learning Environments for Inductive Teaching

Modeling and Analyzing Inquiry Strategies in Open-Ended Learning Environments

T. Kaeser; D. L. Schwartz 

Efficacy of a Computer-Based Learning Program in Children With Developmental Dyscalculia. What Influences Individual Responsiveness?

J. Kohn; L. Rauscher; K. Kucian; T. Kaeser; A. Wyschkon et al. 

Towards the alignment of educational robotics learning systems with classroom activities

Analysis and Remediation of Handwriting difficulties

Exploring Neural Network Models for the Classification of Students in Highly Interactive Environments

T. Käser; D. L. Schwartz 

Ten Years of Research on Intelligent Educational Games for Learning Spelling and Mathematics

B. Solenthaler; S. Klingler; T. Käser; M. Gross 

Perspectives to Technology-Enhanced Learning and Teaching in Mathematical Learning Difficulties

P. Räsänen; D. Laurillard; T. Käser; M. von Aster 

Efficient Feature Embeddings for Student Classification with Variational Auto-encoders

S. Klingler; R. Wampfler; T. Käser; B. Solenthaler; M. Gross 

Effekte des Calcularis-Trainings: Teil 1: Domänen-spezifische Veränderungen

J. Kohn; L. Rauscher; T. Käser; K. Kucian; U. McCaskey et al. 

Effekte des Calcularis-Trainings: Teil 2: Veränderungen psychosozialer Merkmale

L. Rauscher; J. Kohn; T. Käser; K. Kucian; U. McCaskey et al. 

Modeling exploration strategies to predict student performance within a learning environment and beyond

T. Käser; N. R. Hallinen; D. L. Schwartz 

Dynamic Bayesian Networks for Student Modeling

T. Käser; S. Klingler; A. G. Schwing; M. Gross 

Evaluation of a Computer-Based Training Program for Enhancing Arithmetic Skills and Spatial Number Representation in Primary School Children

L. Rauscher; J. Kohn; T. Käser; V. Mayer; K. Kucian et al. 

Stealth Assessment in ITS – A Study for Developmental Dyscalculia

S. Klingler; T. Käser; A-G. Busetto; B. Solenthaler; J. Kohn et al. 

When to stop? – Towards universal instructional policies

T. Käser; S. Klingler; M. Gross 

Temporally Coherent Clustering of Student Data

S. Klingler; T. Käser; B. Solenthaler; M. Gross 

Rechenleistung und Fingergnosie: Besteht ein Zusammenhang?: Eine Studie bei Grundschulkindern mit und ohne Rechenschwäche

J. Kohn; K. Kucian; E. Wuithschick; V. Mayer; L. Rauscher et al. 

On the Performance Characteristics of Latent-Factor and Knowledge Tracing Models

S. Klingler; T. Käser; B. Solenthaler; M. Gross 

Assistive technology for supporting learning numeracy

P. Räsänen; T. Käser; A. Wilson; M. v. Aster; O. Maslov et al. 

Different parameters – same prediction. An analysis of learning curves

T. Käser; K. R. Koedinger; M. Gross 

Beyond Knowledge Tracing. Modeling Skill Topologies with Bayesian Networks

T. Käser; S. Klingler; A. G. Schwing; M. Gross 

Computational Education using Latent Structured Prediction

T. Käser; A. G. Schwing; T. Hazan; M. Gross 

Modelling and Optimizing Mathematics Learning in Children

T. Käser; A. G. Busetto; B. Solenthaler; G-M. Baschera; J. Kohn et al. 

Design and evaluation of the computer-based training program Calcularis for enhancing numerical cognition

T. Käser; G-M. Baschera; J. Kohn; K. Kucian; V. Richtmann et al. 

Modeling and Optimizing Computer-Assisted Mathematics Learning in Children

Das Mathematikangstinterview (MAI). Erste psychometrische Gütekriterien

J. Kohn; V. Richtmann; L. Rauscher; K. Kucian; T. Käser et al. 

Cluster-based prediction of mathematical learning patterns

T. Käser; A. G. Busetto; B. Solenthaler; J. Kohn; M. v. Aster et al. 

Computerbasierte Lernprogramme für Kinder mit Rechenschwäche

T. Käser; M. von Aster 

Towards a Framework for Modelling Engagement Dynamics in Multiple Learning Domains

T. Käser; G-M. Baschera; A. G. Busetto; S. Klingler; B. Solenthaler et al. 

Kinder mit Dyskalkulie fokussieren spontan weniger auf Anzahligkeit

K. Kucian; J. Kohn; M. M. Hannula-Sormunen; V. Richtmann; U. Grond et al. 

Modelling and Optimizing the Process of Learning Mathematics

T. Käser; A. G. Busetto; G. M. Baschera; J. Kohn; K. Kucian et al. 

Therapy software for enhancing numerical cognition

T. Käser; K. Kucian; M. Ringwald; G. M. Baschera; M. Von Aster et al.