28 citations · 37 across the 11 of their papers we have counts for
12 papers
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…
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…
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…
The Social Blindspot in Human-AI Collaboration: How Undetected AI Personas Reshape Team Dynamics
Lixiang Yan, Xibin Han, Yu Zhang +8
As generative AI systems become increasingly embedded in collaborative work, they are evolving from visible tools into human-like communicative actors that participate socially rat…
Student Development Agent: Risk-free Simulation for Evaluating AIED Innovations
Jianxiao Jiang, Yu Zhang
In the age of AI-powered educational (AIED) innovation, evaluating the developmental consequences of novel designs before they are exposed to students has become both essential and…
Mapping Student-AI Interaction Dynamics in Multi-Agent Learning Environments: Supporting Personalised Learning and Reducing Performance Gaps
Zhanxin Hao, Jie Cao, Ruimiao Li +3
Multi-agent AI systems, which simulate diverse instructional roles such as teachers and peers, offer new possibilities for personalized and interactive learning. Yet, student-AI in…
Unpacking Graduate Students' Learning Experience with Generative AI Teaching Assistant in A Quantitative Methodology Course
Zhanxin Hao, Haifeng Luo, Yongyi Chen +1
The study was conducted in an Advanced Quantitative Research Methods course involving 20 graduate students. During the course, student inquiries made to the AI were recorded and co…
AI instructional agent improves student's perceived learner control and learning outcome: empirical evidence from a randomized controlled trial
Fei Qin, Zhanxin Hao, Jifan Yu +2
This study examines the impact of an AI instructional agent on students' perceived learner control and academic performance in a medium demanding course with lecturing as the main…
How Students Use AI Feedback Matters: Experimental Evidence on Physics Achievement and Autonomy
Xusheng Dai, Zhaochun Wen, Jianxiao Jiang +2
Despite the precision and adaptiveness of generative AI (GAI)-powered feedback provided to students, existing practice and literature might ignore how usage patterns impact student…
Intelligent Interaction Strategies for Context-Aware Cognitive Augmentation
Xiangrong, Zhu, Yuan Xu +4
Human cognition is constrained by processing limitations, leading to cognitive overload and inefficiencies in knowledge synthesis and decision-making. Large Language Models (LLMs)…
Student-AI Interaction in an LLM-Empowered Learning Environment: A Cluster Analysis of Engagement Profiles
Zhanxin Hao, Jianxiao Jiang, Jifan Yu +2
Integrating Large Language Models (LLMs) into educational practice enables personalized learning by accommodating diverse learner behaviors. This study explored diverse learner pro…
From MOOC to MAIC: Reshaping Online Teaching and Learning through LLM-driven Agents
Jifan Yu, Zheyuan Zhang, Daniel Zhang-li +30
Since the first instances of online education, where courses were uploaded to accessible and shared online platforms, this form of scaling the dissemination of human knowledge to r…