Publications

2024

Interpret3C: Interpretable Student Clustering Through Individualized Feature Selection

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

2024-06-14. The 25th Conference on Artificial Intelligence in Education (AIED), Recifé, Brazil, July 8-12, 2024.

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

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

2024. DOI : 10.48550/arxiv.2402.02933.

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. 

2024. 17th International Conference on Educational Data Mining (EDM 2024), Atlanta, GA, USA, July 14-17, 2024. DOI : 10.48550/arxiv.2405.20079.

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

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

2024. CHI EA ’24, Honolulu, HI, USA, May 11-16, 2024. p. 10. DOI : 10.1145/3613905.3650900.

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 

International Journal of Artificial Intelligence in Education. 2024. DOI : 10.1007/s40593-024-00409-x.

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. 

International Journal of Artificial Intelligence in Education. 2024. DOI : 10.1007/s40593-024-00405-1.

Finding Paths for Explainable MOOC Recommendation: A Learner Perspective

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

2024-01-01. 14th Annual International Conference on Learning Analytics and Knowledge (LAK) – Learning Analytics in the Age of Artificial Intelligence, Kyoto, JAPAN, MAR 18-22, 2024. p. 426-437. DOI : 10.1145/3636555.3636898.

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. 

2024. CHI 2024, Honolulu, Hawaii, USA, May 11-16, 2024.

2023

Understanding Revision Behavior in Adaptive Writing Support Systems for Education

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

2023. 16th International Conference on Educational Data Mining, Bengaluru, India, July 11-15, 2023. DOI : 10.5281/zenodo.8115765.

Finding Paths for Explainable MOOC Recommendation: A Learner Perspective

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

2023-12-23. 

Consistency of Inquiry Strategies Across Subsequent Activities in Different Domains

J. M. Cock; I. Roll; T. Käser 

24th International Conference on Artificial Intelligence in Education, AIED 2023, Tokyo, Japan, July 3-7, 2023.

MultiModN- Multimodal, Multi-Task, Interpretable Modular Networks

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

2023. 37th Conference on Neural Information Processing Systems (NeurIPS), New Orleans, US, December 10-16, 2023. DOI : 10.48550/arxiv.2309.14118.

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

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

2023-01-01. 31st ACM Conference on User Modeling, Adaptation and Personalization (ACM UMAP), Limassol, CYPRUS, Jun 26-30, 2023. p. 135-145. DOI : 10.1145/3565472.3595620.

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

T. Kaser; G. Alexandron 

International Journal Of Artificial Intelligence In Education. 2023-07-20. DOI : 10.1007/s40593-023-00337-2.

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

V. Swamy; J. A. Frej; T. Käser 

2023. DOI : 10.48550/arxiv.2307.00364.

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. 

2023-04-19. CHI 2023, Hamburg, Germany, April 3-28, 2023. p. Article No.: 136, pp 1-9. DOI : 10.1145/3544549.3585644.

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

E. Laini 

2023.

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

V. Swamy; S. Du; M. Marras; T. Käser 

2023-03-13. LAK 2023: The 13th International Learning Analytics and Knowledge Conference, Arlington, Texas, USA, March 13-17, 2023. DOI : 10.1145/3576050.3576147.

2022

Maschinelles Lernen zur Förderung von höheren Kompetenzen

C. Giang; T. Wambsganss; T. Käser 

Lernen und Lernstörungen. 2022-10-27. DOI : 10.1024/2235-0977/a000393.

Improving Students Argumentation Learning with Adaptive Self-Evaluation Nudging

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

Proceedings of the ACM on Human-Computer Interaction. 2022-11-11. Vol. 6, num. CSCW2, p. 1-31. DOI : 10.1145/3555633.

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 

2022

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

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

2022. AAAI 2023: 37th AAAI Conference on Artificial Intelligence (EAAI: AI for Education Special Track), Washington DC, USA, February 7-14, 2023. DOI : 10.48550/arxiv.2212.01133.

Introducing Productive Engagement for Social Robots Supporting Learning

J. Nasir / P. Dillenbourg; B. Bruno (Dir.)  

Lausanne, EPFL, 2022. 

Identifying and Comparing Multi-dimensional Student Profiles Across Flipped Classrooms

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

2022-07-27. 23rd International Conference on Artificial Intelligence in Education (AIED 2022), Durkham, UK, July 27-31, 2022. p. 90-102. DOI : 10.1007/978-3-031-11644-5_8.

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

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

IEEE Transactions on Learning Technologies. 2022-08-02.  p. 1-14. DOI : 10.1109/TLT.2022.3195881.

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 

2022. 29th International Conference on Computational Linguistics (COLING 2022), Gyeongju, Republic of Korea, October 12-17, 2022. DOI : 10.48550/arxiv.2209.10335.

Generalisable Methods for Early Prediction in Interactive Simulations for Education

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

2022-07-24. 5th International Conference on Educational Data Mining, Durham, UK, July 24-27. DOI : 10.5281/zenodo.6852967.

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

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

2022-07-24. 15th International Conference on Educational Data Mining (EDM 2022), Durham, UK, July 24-27, 2022. DOI : 10.5281/zenodo.6852963.

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

T. Piccardi / R. West (Dir.)  

Lausanne, EPFL, 2022. 

Meta Transfer Learning for Early Success Prediction in MOOCs

V. Swamy; M. Marras; T. Käser 

2022-05-31. 9th ACM Conference on Learning at Scale, New York, USA, June 1-3, 2022. DOI : 10.1145/3491140.3528273.

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

K. G. Kim / P. Dillenbourg (Dir.)  

Lausanne, EPFL, 2022. 

2021

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

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

2021-03-12. 1st / 14th International Workshop on Enabling Data-Driven Decisions from Learning on the Web co-located with the 14th ACM International Conference on Web Search and Data Mining (WSDM 2021), (Online) Jerusalem, Israel, March 8-12, 2021. p. 57-64.

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

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

2021-07-02. 14th International Conference on Educational Data Mining (EDM 2021), (Online from) Paris, France, June 29th – July 2nd, 2021. p. 150-160.

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 

2021-03-08. 14th ACM International Conference on Web Search and Data Mining, (Online) Jerusalem, Israel, March 8-12, 2021. p. 1165–1166. DOI : 10.1145/3437963.3441840.

Early Prediction of Conceptual Understanding in Interactive Simulations

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

2021-06-29. 14th International Conference on Educational Data Mining, (Online) Paris, France, June 29th – July 2nd, 2021. p. 161-171.

Computational Analysis and Design of Structurally Stable Assemblies with Rigid Parts

Z. Wang / M. Pauly; P. Song (Dir.)  

Lausanne, EPFL, 2021. 

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

L. P. Faucon / P. Dillenbourg (Dir.)  

Lausanne, EPFL, 2021. 

2020

Towards the alignment of educational robotics learning systems with classroom activities

C. Giang / F. Mondada; A. Piatti (Dir.)  

Lausanne, EPFL, 2020. 

Modeling and Analyzing Inquiry Strategies in Open-Ended Learning Environments

T. Kaeser; D. L. Schwartz 

International Journal Of Artificial Intelligence In Education. 2020-09-09. Vol. 30, p. 504–535. DOI : 10.1007/s40593-020-00199-y.

Analysis and Remediation of Handwriting difficulties

T. L. C. Asselborn / P. Dillenbourg (Dir.)  

Lausanne, EPFL, 2020. 

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. 

Frontiers In Psychology. 2020-07-15. Vol. 11, p. 1115. DOI : 10.3389/fpsyg.2020.01115.

2019

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

T. Käser; D. L. Schwartz 

2019. 12th International Conference on Educational Data Mining, Montreal, Canada, July 2-5, 2019. p. 109-118.

2018

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

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

2018-06-07

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

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

International Handbook of Mathematical Learning Difficulties; Cham: Springer International Publishing, 2018. p. 733-754.

2017

Dynamic Bayesian Networks for Student Modeling

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

IEEE Transactions on Learning Technologies. 2017. Vol. 4, num. 10, p. 450-462. DOI : 10.1109/TLT.2017.2689017000418421400005.

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

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

Lernen und Lernstörungen. 2017-04-01. Vol. 2, num. 6, p. 51-63. DOI : 10.1024/2235-0977/a000166.

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

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

Lernen und Lernstörungen. 2017-04-01. Vol. 2, num. 6, p. 75-86. DOI : 10.1024/2235-0977/a000168.

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

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

2017-03-13. LAK ’17: 7th International Learning Analytics and Knowledge Conference. p. 31-40. DOI : 10.1145/3027385.3027422.

Efficient Feature Embeddings for Student Classification with Variational Auto-encoders

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

2017-06-25. 10th International Conference on Educational Data Mining (EDM 2017), Wuhan, China, June 25-28, 2017. p. 72-79.

2016

Stealth Assessment in ITS – A Study for Developmental Dyscalculia

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

2016-06-06. 13th International Conference on Intelligent Tutoring Systems – ITS 2016, Zagreb, Croatia, June 6-10, 2016. p. 79-89. DOI : 10.1007/978-3-319-39583-8_8.

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. 

Frontiers in Psychology. 2016-06-27. Vol. 7, p. 913. DOI : 10.3389/fpsyg.2016.00913.

When to stop? – Towards universal instructional policies

T. Käser; S. Klingler; M. Gross 

2016. 6th International Conference on Learning Analytics & Knowledge (LAK ’16), Edinburgh, Scotland, UK, April 25-29, 2016. p. 289-298. DOI : 10.1145/2883851.2883961000390844700037.

Temporally Coherent Clustering of Student Data

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

2016. International Conference on Educational Data Mining (EDM), Raleigh, NC, USA, June 29 – July 2, 2016. p. 102-109.

2015

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. 

Lernen und Lernstörungen. 2015-08-01. Vol. 3, num. 4, p. 209-223. DOI : 10.1024/2235-0977/a000106.

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

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

2015. 8th International Conference on Educational Data Mining, EDM 2015, Madrid, Spain, June 26-29,2015. p. 37-44.

2014

Different parameters – same prediction. An analysis of learning curves

T. Käser; K. R. Koedinger; M. Gross 

2014. Educational Data Mining 2014, London, UK, July 4-7, 2014. p. 52-59.

Beyond Knowledge Tracing. Modeling Skill Topologies with Bayesian Networks

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

2014. 12th International Conference, ITS 2014, Honolulu, HI, USA, June 5-9, 2014. p. 188-198. DOI : 10.1007/978-3-319-07221-0_23000343081600023.

Computational Education using Latent Structured Prediction

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

2014. 17th International Conference on Artificial Intelligence and Statistics, AISTATS 2014, Reykjavik, Iceland, April 22-25, 2014. p. 540-548.

Assistive technology for supporting learning numeracy

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

Assistive Technology for Cognition; Psychology Press, 2014-12-22. p. 112-128.

2013

Modeling and Optimizing Computer-Assisted Mathematics Learning in Children

T. Käser Jacober / M. Gross (Dir.)  

ETH-Zürich, 2013. 

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. 

Frontiers in Psychology. 2013-08-05. num. 4, p. 489. DOI : 10.3389/fpsyg.2013.00489.

Modelling and Optimizing Mathematics Learning in Children

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

International Journal of Artificial Intelligence in Education. 2013-11-01. Vol. 1-4, num. 23, p. 135. DOI : 10.1007/s40593-013-0003-7.

Das Mathematikangstinterview (MAI). Erste psychometrische Gütekriterien

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

Lernen und Lernstörungen. 2013. Vol. 3, num. 2, p. 177-189. DOI : 10.1024/2235-0977/a000040.

Cluster-based prediction of mathematical learning patterns

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

2013. 16th international conference on Artificial intelligence in education (AIED 2013), Memphis, TN, USA, July 9-13, 2013. p. 389-399. DOI : 10.1007/978-3-642-39112-5_40.

Computerbasierte Lernprogramme für Kinder mit Rechenschwäche

T. Käser; M. von Aster 

Rechenstörungen bei Kindern. Neurowissenschaft, Psychologie, Pädagogik; Vandenhoeck & Ruprecht, 2013. p. 259-276.

2012

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. 

International Journal of Artificial Intelligence in Education. 2012. Vol. 1-2, num. 22, p. 59-83. DOI : 10.3233/JAI-130026.

Kinder mit Dyskalkulie fokussieren spontan weniger auf Anzahligkeit

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

Lernen und Lernstörungen. 2012. Vol. 4, num. 1, p. 241-253. DOI : 10.1024/2235-0977/a000024.

Modelling and Optimizing the Process of Learning Mathematics

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

2012. 11th international conference on Intelligent Tutoring Systems (ITS 2012), Chania, Greece, June 14-18, 2012. p. 389-398. DOI : 10.1007/978-3-642-30950-2_50.

2011

Therapy software for enhancing numerical cognition

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

Interdisciplinary perspectives on cognition, education and the brain. 2011. num. 7, p. 219-228. DOI : 10.5167/UZH-64859.