WIP: Enhancing Game-Based Learning with AI-Driven Peer Agents
Chengzhang Zhu, Cecile H. Sam, Yanlai Wu, Ying Tang

TL;DR
This paper introduces SPARC, a gamified STEM learning platform for K-12 students that uses AI peer agents to promote engagement and understanding through interactive dialogue and inquiry, showing promising early results.
Contribution
It presents a novel integration of large language model-based AI peer agents within a game-based learning platform for K-12 STEM education, grounded in educational theory.
Findings
Increased student engagement reported in classroom pilots
Moderate gains in conceptual understanding observed
Positive qualitative feedback from students and teachers
Abstract
This work-in-progress paper presents SPARC (Systematic Problem Solving and Algorithmic Reasoning for Children), a gamified learning platform designed to enhance engagement and knowledge retention in K-12 STEM education. Traditional approaches often struggle to motivate students or facilitate deep understanding, especially for complex scientific concepts. SPARC addresses these challenges by integrating interactive, narrative-driven gameplay with an artificial intelligence peer agent built on large language models. Rather than simply providing answers, the agent engages students in dialogue and inquiry, prompting them to explain concepts and solve problems collaboratively. The platform's design is grounded in educational theory and closely aligned with state learning standards. Initial classroom pilots utilized a multi-method assessment framework combining pre- and post-tests, in-game…
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Taxonomy
TopicsEducational Games and Gamification · Intelligent Tutoring Systems and Adaptive Learning · Teaching and Learning Programming
