2 citations · 4 across the 10 of their papers we have counts for
10 papers
AI-Integrated Scientific Inquiry: A Practice-Centered Vision for Science Education
Arne Bewersdorff, Matias Rojas, Xiaoming Zhai
Artificial intelligence (AI) has become part of scientific inquiry. Scientists use AI to observe and measure phenomena, to identify patterns in data, and to build models. As AI mov…
ArguAgent: AI-Supported Real-Time Grouping for Productive Argumentation in STEM Classrooms
Jennifer Kleiman, Yizhu Gao, Xin Xia +4
Argumentation is a core practice in STEM education, but its productivity depends on who participates and how they interact. Higher-achieving students often dominate the talk and de…
The Landscape of AI in Science Education: What is Changing and How to Respond
Xiaoming Zhai, Kent Crippen
This introductory chapter explores the transformative role of artificial intelligence (AI) in reshaping the landscape of science education. Positioned at the intersection of tradit…
Science Literacy: Generative AI as Enabler of Coherence in the Teaching, Learning, and Assessment of Scientific Knowledge and Reasoning
Xiaoming Zhai, James W. Pellegrino, Matias Rojas +4
This chapter examines the potential of generative AI in enhancing science literacy across the K-16+ grade span, including its benefits as well as the conceptual and practical chall…
Roots Beneath the Cut: Uncovering the Risk of Concept Revival in Pruning-Based Unlearning for Diffusion Models
Ci Zhang, Zhaojun Ding, Chence Yang +7
Pruning-based unlearning has recently emerged as a fast, training-free, and data-independent approach to remove undesired concepts from diffusion models. It promises high efficienc…
Transforming Science Learning Materials in the Era of Artificial Intelligence
Xiaoming Zhai, Kent Crippen
The integration of artificial intelligence (AI) into science education is transforming the design and function of learning materials, offering new affordances for personalization,…
Charting the Future of AI-supported Science Education: A Human-Centered Vision
Xiaoming Zhai, Kent Crippen
This concluding chapter explores how artificial intelligence (AI) is reshaping the purposes, practices, and outcomes of science education, and proposes a human-centered framework f…
Developing a Multi-Agent System to Generate Next Generation Science Assessments with Evidence-Centered Design
Yaxuan Yang, Jongchan Park, Yifan Zhou +1
Contemporary science education reforms such as the Next Generation Science Standards (NGSS) demand assessments to understand students' ability to use science knowledge to solve pro…
Generative Large Language Models for Knowledge Representation: A Systematic Review of Concept Map Generation
Xiaoming Zhai
The rise of generative large language models (LLMs) has opened new opportunities for automating knowledge representation through concept maps, a long-standing pedagogical tool valu…
Exploring Communication Strategies for Collaborative LLM Agents in Mathematical Problem-Solving
Liang Zhang, Xiaoming Zhai, Jionghao Lin +6
Large Language Model (LLM) agents are increasingly utilized in AI-aided education to support tutoring and learning. Effective communication strategies among LLM agents improve coll…