Hugging Face Trending Papers

Making AI-Generated Feedback Matter: From Provision to Student Enactment

Feedback processes strongly influence student learning, yet their educational value depends on addressing two distinct challenges: providing high-quality, timely, and individualised feedback at scale, and supporting students to interpret, evaluate, and act on that feedback productively. Generative AI offers a credible means of addressing the provision challenge, but students' uptake of AI-generated feedback remains limited.

arXiv AI
6d ago

Making AI-Generated Feedback Matter: From Provision to Student Enactment

arXiv:2608. 11625v1 Announce Type: new Abstract: Feedback processes strongly influence student learning, yet their educational value depends on addressing two distinct challenges: providing high-quality, timely, and individualised feedback at scale, and supporting students to interpret, evaluate, and act on that feedback productively.

By Omar Alsaiari, Nilufar Baghaei, Jason M. Lodge, Dragan Ga\v{s}evi'c, Naomi Winstone, Hassan Khosravi
arXiv AI
2d ago

Making AI-Generated Feedback Matter: A Large-Scale Study of Feedback Workflows and Student Enactment

arXiv:2608. 11625v2 Announce Type: replace Abstract: Feedback processes strongly influence student learning, yet their educational value depends on addressing two distinct challenges: providing high-quality, timely, and individualised feedback at scale, and supporting students to interpret, evaluate, and act on that feedback productively.

By Omar Alsaiari, Nilufar Baghaei, Jason M. Lodge, Dragan Ga\v{s}evi'c, Naomi Winstone, Hassan Khosravi
arXiv AI
5d ago

Assessment Design in the GenAI Era: The X1-X2-X3 Assessment Pattern for Testing Students' AI Literacy, Learning Outcomes, and Reflection

arXiv:2608. 12351v1 Announce Type: cross Abstract: Generative artificial intelligence (GenAI) has challenged the validity of unsupervised online assessment, especially in technical subjects where plausible answers can be produced with little effort.

By Riasat Islam (School of Electronic Engineering and Computer Science, Queen Mary University of London, London, United Kingdom), Thomas Roelleke (School of Electronic Engineering and Computer Science, Queen Mary University of London, London, United Kingdom)
arXiv AI
Jul 1

What Drives Interactive Improvement from Feedback?

arXiv:2606. 30774v1 Announce Type: new Abstract: We study when natural-language feedback produces improvement beyond the gains obtainable from repeated attempts alone.

By Bart{\l}omiej Cupia{\l}, Jan {\L}ojek, Miko{\l}aj Garstecki, Szymon Pob{\l}ocki, Alicja Ziarko, Piotr Mi{\l}o\'s
arXiv AI
Jun 11

IntElicit: Eliciting and Assessing Contextualized Creativity via Dialogue Policy Optimization

arXiv:2606. 12086v1 Announce Type: new Abstract: Contextualized assessment offers high ecological validity for evaluating creativity but introduces a critical challenge: observed performance may be confounded with cognitive proficiency (domain knowledge) and agency (willingness to engage).

By Mingjia Li, Jin Wu, Hong Qian, Wenhao Huang, Yiyang Huang, Yiwen Zhang, Chanjin Zheng, Xiangfeng Wang, Aimin Zhou, Jiajun Guo