Agentic tutoring systems introduce a coordination challenge: multiple agents may propose different but reasonable interventions, yet only one response can be delivered to the learner. In this paper, we study how voting protocols shape cooperation among four role-constrained pedagogical agents responsible for scaffolding, misconception, motivation, and metacognition. We compare four voting protocols -- simple, ranked, cumulative, and approval voting -- across two simulated tutoring environments on SciQ and HumanEval benchmarks. Rather than using voting as a simple aggregation step, we use it to analyze how collective decision rules shape coordination under partial pedagogical conflict. Across 1,200 simulated interactions, we find that agent deliberation and voting protocol type frequently change which response ultimately wins, showing that both meaningfully shape the collective decision. Different voting rules also produce distinct coordination behaviors, and even brief tutoring turns show measurable learning gains in simulated students. Overall, we show that protocol choice is associated with distinct coordination patterns among role-specialized pedagogical agents.

翻译：智能辅导系统面临一项协调挑战：多个智能体可能提出不同但合理的干预措施，然而只能向学习者传递一个响应。本文研究了投票协议如何塑造四个角色约束的教学智能体（负责支架、误解、动机和元认知）之间的协作。我们比较了四种投票协议——简单投票、排名投票、累积投票和同意投票——在基于SciQ和HumanEval基准的两个模拟辅导环境中进行。我们并非将投票作为简单的聚合步骤，而是用它分析在部分教学冲突下集体决策规则如何塑造协调。在1200次模拟交互中，我们发现智能体协商和投票协议类型经常改变最终获胜的响应，这表明两者都显著影响集体决策。不同的投票规则还会产生不同的协调行为，即使是简短的辅导回合也能在模拟学生中显示出可测量的学习增益。总体而言，我们表明协议选择与角色专精教学智能体间的不同协调模式相关联。