Benjamin Paassen
Cited by
Cited by
What is a true gamer? The male gamer stereotype and the marginalization of women in video game culture
B Paaßen, T Morgenroth, M Stratemeyer
Sex Roles 76, 421-435, 2017
The continuous hint factory-providing hints in vast and sparsely populated edit distance spaces
B Paaßen, B Hammer, TW Price, T Barnes, S Gross, N Pinkwart
arXiv preprint arXiv:1708.06564, 2017
A comparison of the quality of data-driven programming hint generation algorithms
TW Price, Y Dong, R Zhi, B Paaßen, N Lytle, V Cateté, T Barnes
International Journal of Artificial Intelligence in Education 29, 368-395, 2019
Counteracting electrode shifts in upper-limb prosthesis control via transfer learning
C Prahm, A Schulz, B Paaßen, J Schoisswohl, E Kaniusas, G Dorffner, ...
IEEE Transactions on Neural Systems and Rehabilitation Engineering 27 (5 …, 2019
Transfer learning for rapid re-calibration of a myoelectric prosthesis after electrode shift
C Prahm, B Paassen, A Schulz, B Hammer, O Aszmann
Converging Clinical and Engineering Research on Neurorehabilitation II …, 2016
Example-based feedback provision using structured solution spaces
S Gross, B Mokbel, B Paaßen, B Hammer, N Pinkwart
International Journal of Learning Technology 10 9 (3), 248-280, 2014
Metric learning for sequences in relational LVQ
B Mokbel, B Paassen, FM Schleif, B Hammer
Neurocomputing 169, 306-322, 2015
Domain-independent proximity measures in intelligent tutoring systems
B Mokbel, S Gross, B Paassen, N Pinkwart, B Hammer
Educational Data Mining 2013, 2013
Expectation maximization transfer learning and its application for bionic hand prostheses
B Paaßen, A Schulz, J Hahne, B Hammer
Neurocomputing 298, 122-133, 2018
Adaptive structure metrics for automated feedback provision in intelligent tutoring systems
B Paassen, B Mokbel, B Hammer
Neurocomputing 192, 3-13, 2016
Tree edit distance learning via adaptive symbol embeddings
B Paaßen, C Gallicchio, A Micheli, B Hammer
International Conference on Machine Learning, 3976-3985, 2018
Revisiting the tree edit distance and its backtracing: A tutorial
B Paaßen
arXiv preprint arXiv:1805.06869, 2018
Learning interpretable kernelized prototype-based models
D Hofmann, FM Schleif, B Paaßen, B Hammer
Neurocomputing 141, 84-96, 2014
Time series prediction for graphs in kernel and dissimilarity spaces
B Paaßen, C Göpfert, B Hammer
Neural Processing Letters 48 (2), 669-689, 2018
Graph edit networks
B Paassen, D Grattarola, D Zambon, C Alippi, BE Hammer
International Conference on Learning Representations, 2020
Execution Traces as a Powerful Data Representation for Intelligent Tutoring Systems for Programming.
B Paaßen, J Jensen, B Hammer
International Educational Data Mining Society, 2016
Mapping python programs to vectors using recursive neural encodings
B Paassen, J McBroom, B Jeffries, I Koprinska, K Yacef
Journal of Educational Data Mining 13 (3), 1-35, 2021
Progress networks as a tool for analysing student programming difficulties
J McBroom, B Paassen, B Jeffries, I Koprinska, K Yacef
Proceedings of the 23rd Australasian Computing Education Conference, 158-167, 2021
The gendered nature and malleability of gamer stereotypes
T Morgenroth, M Stratemeyer, B Paaßen
Cyberpsychology, Behavior, and Social Networking 23 (8), 557-561, 2020
Dynamic fairness-Breaking vicious cycles in automatic decision making
B Paaßen, A Bunge, C Hainke, L Sindelar, M Vogelsang
arXiv preprint arXiv:1902.00375, 2019
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