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@MISC{Gllinger:1026499,
author = {Göllinger, Robert Helmut Walter and Ahlers, Jens Daniel
Simon and Stemmler, Sebastian},
title = {{O}pen-{S}ource {I}ntelligent {T}utoring {S}ystem for
{P}rogramming {E}xercises in {E}ngineering {E}ducation;
v1.0.1},
reportid = {RWTH-2026-00924},
year = {2026},
abstract = {Implementing control and machine learning algorithms in
MATLAB and Simulink is a critical competency in advanced
control engineering. While immediate feedback is essential
for fostering intuitive understanding, it is traditionally
constrained to scheduled exercise sessions or consultation
hours. To bridge this gap, this project introduces an
open-source intelligent tutoring platform that provides
continuous, on-demand feedback. To accommodate diverse
solution strategies, the platform employs a hybrid
evaluation strategy combining result-based and code-based
metrics. This ensures that valid alternative solutions that
differ from predefined sample solutions are not
misclassified. In case of incorrect solutions, a Large
Language Model, contextualized with sample solutions and
task classification results, offers auxiliary support for
students struggling to initiate or complete tasks.
Instructional scaffolding is adaptively adjusted to guide
students toward independent problem-solving. We position
this platform as a supplementary tool designed to enhance,
rather than replace, valuable interactions between students
and human tutors. Built on open-source tools, the system is
architected for reusability, enabling lecturers across
engineering subjects to adapt the framework to their
teaching needs easily.},
cin = {416610},
cid = {$I:(DE-82)416610_20140620$},
typ = {PUB:(DE-HGF)33},
doi = {10.18154/RWTH-2026-00924},
url = {https://publications.rwth-aachen.de/record/1026499},
}
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