This paper proposes a decentralized collaborative learning paradigm for Tsetlin Machines using consensus-based inference, allowing heterogeneous agents to maintain their own private models and combine…

The paper designs and evaluates a triadic LLM-Teacher collaboration system for K-12 writing, finding that strategic labor division between the LLM and teacher effectively improves writing quality but…

This paper compares two methods for assessing student teams in tabletop exercises using data from learning platforms and evaluates their validity and reliability.

This paper operationalizes knowledge-based design requirements in a generative social robot tutoring system called Teachy Mini, and evaluates its effectiveness in higher education.

This paper analyzes large-scale human-LLM conversations to identify learning behaviors and their associated factors.

The paper introduces AgentSchool, an advanced LLM-powered multi-agent simulator that models learning as state transitions to provide a robust, ethically viable testbed for educational research and ped…

This paper reports the first classroom deployment of LEA, an adaptive AI tutoring agent, with real students across three courses and evaluates its cross-course scalability.

This paper compares four requirements elicitation approaches using AI-supported collaboration and evaluates their impact on requirements artifact quality and stakeholder perceptions.

This paper investigates if team-based interaction improves LLM performance on complex reasoning tasks (ChGK), finding that structured team strategies significantly boost accuracy by acting as error-fi…

This paper proposes a multi-agent framework using LLMs to improve collaborative story generation, demonstrating that an iterative Writer-Editor process significantly enhances narrative quality for you…

This paper analyzes failure modes in collaborative visual reasoning systems, demonstrating that naive shared workspaces can amplify hallucinations and proposing diagnostics for improving communication…

This paper introduces the FedSaSync strategy for Semi-Asynchronous Federated Learning in the Flower framework, improving robustness and reducing idle time in heterogeneous environments.

The paper proposes an interpretable, AI-driven decision layer that ranks course topics needing attention using multiple student and teacher signals, successfully identifying learning gaps before forma…

This paper reports experiences and takeaways from using puzzles to teach critical testing literacy (CTL) through workshops, introducing the pedagogical framework P4TEST.

This paper proposes a modular, agentic AI chatbot architecture to assist students with exercise solving, aiming to ensure responsible and pedagogically sound AI use in education.

Robots are initialized with prior team experience in the form of knowledge-graph episodic memories to improve human-robot teamwork in the MATRX USAR environment, resulting in increased rescue success…

This paper explores the effectiveness of diverse LLM-generated explanations versus generic explanations in computer science education, finding that diverse explanations led to higher open-ended respon…

This study surveyed higher education practitioners to map their beliefs and behaviors regarding AI integration, finding that while they view AI favorably, institutional barriers and gaps in design-ori…

This paper introduces MECoBench, a multimodal embodied cooperation benchmark, and explores the benefits and limitations of collaboration in multimodal large language models through extensive experimen…