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cs.CL2026
CogEvol: Towards Efficient and Reliable Learning Environment Generation
Shangqing Tu, Daniel Zhang-Li, Yucheng Wang +20
We present CogEvol, a family of models trained specifically for Learning Environment Generation: turning a course brief into a finished learning artifact (structured-JSON slides or…
cs.AI2026
Large-scale semantic mapping of learner agency and autonomy reveals what measurement and generative AI research overlook
Fei Qin, Xiaobo Liu, Yaowen Zhang +5
Learner agency and autonomy are foundational to personal development, yet a pervasive "jingle-jangle" fallacy (i.e. identical terms denoting different constructs, distinct terms de…
cs.CL2026
MAIC-UI: Making Interactive Courseware with Generative UI
Shangqing Tu, Yanjia Li, Keyu Chen +7
Creating interactive STEM courseware traditionally requires HTML/CSS/JavaScript expertise, leaving barriers for educators. While generative AI can produce HTML codes, existing tool…