8 papers
Confirming Correct, Missing the Rest: LLM Tutoring Agents Struggle Where Feedback Matters Most
Tahreem Yasir, Wenbo Li, Sam Gilson +3
Effective tutoring requires distinguishing optimal, valid but suboptimal, and incorrect student solutions, a distinction central to intelligent tutoring systems (ITS) but untested…
Democratizing Foundations of Problem-Solving with AI: A Breadth-First Search Curriculum for Middle School Students
Griffin Pitts, Kimia Fazeli, Tirth Bhatt +5
As AI becomes more common in students' everyday experiences, a major challenge for K-12 AI education is designing learning experiences that can be meaningfully integrated into exis…
Data-Driven Hints in Intelligent Tutoring Systems
Sutapa Dey Tithi, Kimia Fazeli, Dmitri Droujkov +3
This chapter explores the evolution of data-driven hint generation for intelligent tutoring systems (ITS). The Hint Factory and Interaction Networks have enabled the generation of…
Exploring Teacher-Chatbot Interaction and Affect in Block-Based Programming
Bahare Riahi, Ally Limke, Xiaoyi Tian +8
AI-based chatbots have the potential to accelerate learning and teaching, but may also have counterproductive consequences without thoughtful design and scaffolding. To better unde…
Exploring the Design and Impact of Interactive Worked Examples for Learners with Varying Prior Knowledge
Sutapa Dey Tithi, Xiaoyi Tian, Ally Limke +2
Tutoring systems improve learning through tailored interventions, such as worked examples, but often suffer from the aptitude-treatment interaction effect where low prior knowledge…
Adaptive Scaffolding for Cognitive Engagement in an Intelligent Tutoring System
Sutapa Dey Tithi, Nazia Alam, Tahreem Yasir +4
The ICAP framework defines four cognitive engagement levels: Passive, Active, Constructive, and Interactive, where increased cognitive engagement can yield improved learning. Howev…