A comparison of the quality of data-driven programming hint generation algorithms

TW Price, Y Dong, R Zhi, B Paaßen, N Lytle… - International Journal of …, 2019‏ - Springer
In the domain of programming, a growing number of algorithms automatically generate data-
driven, next-step hints that suggest how students should edit their code to resolve errors and …

Bibliometric analysis and systematic literature review of the intelligent tutoring systems

OA Cuéllar-Rojas, M Hincapié-Montoya… - Frontiers in …, 2022‏ - frontiersin.org
This study is a literature review with educational evaluation mediated by intelligent tutoring
systems (ITS) as its central axis seeking to establish state of the art on implementations …

The continuous hint factory-providing hints in vast and sparsely populated edit distance spaces

B Paaßen, B Hammer, TW Price, T Barnes… - ar** python programs to vectors using recursive neural encodings
B Paassen, J McBroom… - Journal of …, 2021‏ - jedm.educationaldatamining.org
Educational data mining involves the application of data mining techniques to student
activity. However, in the context of computer programming, many data mining techniques …

Temporal graph algorithms

L Oettershagen - 2022‏ - bonndoc.ulb.uni-bonn.de
Temporal graphs are often good models for real-life scenarios due to the inherently dynamic
nature of most real-world activities and processes. A significant difference between …

Manifold structured prediction

A Rudi, C Ciliberto, GM Marconi… - Advances in Neural …, 2018‏ - proceedings.neurips.cc
Structured prediction provides a general framework to deal with supervised problems where
the outputs have semantically rich structure. While classical approaches consider finite …

Bayesian tracking of video graphs using joint kalman smoothing and registration

AB Bal, R Mounir, S Aakur, S Sarkar… - European Conference on …, 2022‏ - Springer
Graph-based representations are becoming increasingly popular for representing and
analyzing video data, especially in object tracking and scene understanding applications …

[HTML][HTML] Data-distribution-informed Nyström approximation for structured data using vector quantization-based landmark determination

M Münch, KS Bohnsack, FM Schleif, T Villmann - Neurocomputing, 2024‏ - Elsevier
We present an effective method for supervised landmark selection in sparse Nyström
approximations of kernel matrices for structured data. Our approach transforms structured …

A temporal graphlet kernel for classifying dissemination in evolving networks

L Oettershagen, NM Kriege, C Jordan, P Mutze - Proceedings of the 2023 …, 2023‏ - SIAM
We introduce the temporal graphlet kernel for classifying dissemination processes in labeled
temporal graphs. Such processes can be the spreading of (fake) news, infectious diseases …