Systematic Literature Reviews (SLRs) are fundamental to scientific progress, yet the process is hindered by a fragmented tool ecosystem that imposes a high cognitive load. This friction suppresses the iterative, exploratory nature of scholarly work. To investigate these challenges, we conducted an exploratory design study with 20 experienced researchers. This study identified key friction points: 1) the high cognitive load of managing iterative query refinement across multiple databases, 2) the overwhelming scale and pace of publication of modern literature, and 3) the tension between automation and scholarly agency. Informed by these findings, we developed ARC, a design probe that operationalizes solutions for multi-database integration, transparent iterative search, and verifiable AI-assisted screening. A comparative user study with 8 researchers suggests that an integrated environment facilitates a transition in scholarly work, moving researchers from managing administrative overhead to engaging in strategic exploration. By utilizing external representations to scaffold strategic exploration and transparent AI reasoning, our system supports verifiable judgment, aiming to augment expert contributions from initial creation through long-term maintenance of knowledge synthesis.

翻译：系统性文献综述（SLR）是科学进步的基础，然而该过程因工具生态系统碎片化而受到阻碍，这给研究者带来了高认知负荷。这种摩擦抑制了学术工作固有的迭代与探索性质。为探究这些挑战，我们与20位经验丰富的研究者开展了一项探索性设计研究。该研究识别出三个关键摩擦点：1）跨多个数据库管理迭代查询优化所带来的高认知负荷；2）现代文献出版规模与速度带来的信息过载；3）自动化与学术自主性之间的张力。基于这些发现，我们开发了ARC——一个实现多数据库集成、透明化迭代搜索及可验证AI辅助筛选解决方案的设计探针。一项涉及8位研究者的对比用户研究表明，集成化环境能够促进学术工作模式的转变，使研究者从管理行政性事务转向投入战略探索。通过利用外部表征来支撑战略探索并实现透明化AI推理，我们的系统支持可验证的学术判断，旨在增强专家从知识综合的初始创建到长期维护全过程的贡献。