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zedflow
Knight-2025
Commits
e295312a
Commit
e295312a
authored
May 30, 2025
by
Traboulsi
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@@ -483,17 +483,20 @@ body {
</a>
</li>
<li>
<a
href=
" https://link.springer.com/chapter/10.1007/978-3-031-71530-3_7 "
target=
"_blank"
>
<strong>
Arfeli et al. (2024):
</strong>
Development of an AI Competence Matrix for AI Teaching at Universities
</a>
</li>
<li>
<a
href=
"https://ieeexplore.ieee.org/document/10499810"
target=
"_blank"
>
<strong>
Sharif et al. (2024):
</strong>
Multi-Modal LA in Personalized Education using Deep Reinforcement Learning Based Approach
</a>
</li>
<li>
<a
href=
"https://link.springer.com/chapter/10.1007/978-981-97-9255-9_22"
target=
"_blank"
>
<strong>
Sharif et al. (2024):
</strong>
KNIGHT: Machine Learning Methods to Enhance Individualized Learning
</a>
</li>
<li>
<a
href=
"https://link.springer.com/chapter/10.1007/978-981-97-9255-9_22"
target=
"_blank"
>
...
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@@ -512,13 +515,22 @@ Implementations, and Perspectives
<li>
<a
href=
"https://doi.org/10.1007/978-3-031-71530-3_19"
target=
"_blank"
>
<strong>
Pado et al.:
</strong>
Computer-Based Methods for Adaptive Teaching and Learning
<strong>
Pado et al.
(2024)
:
</strong>
Computer-Based Methods for Adaptive Teaching and Learning
</a>
</li>
<li>
<a
href=
"https://doi.org/10.1007/978-3-031-71530-3_19"
target=
"_blank"
>
<strong>
Pado et al.:
</strong>
Computer-Based Methods for Adaptive Teaching and Learning
<a
href=
"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10837675"
target=
"_blank"
>
<strong>
Vintila, F. (2024):
</strong>
AVERT (Authorship Verification and Evaluation Through Responsive Testing): an LLM-Based Procedure that Interactively Verifies Code Authorship and Evaluates Student Understanding
</a>
</li>
<li>
<a
href=
"https://library.iated.org/view/HOPNER2024IMP"
target=
"_blank"
>
<strong>
Höpner et al. (2024):
</strong>
Implementing Generative AI in
Academic Writing Seminars. Proceedings of the 16th annual
International Conference on Education and New Learning
</a>
</li>
...
...
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