发表机构
Nakamura Gakuen University; Hiroshima University（中村学园大学; 广岛大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对新兴分析方法缺乏解释规范的问题，提出TopoLA仪表盘系统，通过三阶段流水线和三条设计原则支持拓扑数据分析结果的解释，贡献初步设计知识。
AI 中文摘要
拓扑数据分析（TDA）为理解复杂系统中的时间动态提供了新颖方法，然而其在信息系统设计中的应用面临一个根本性挑战：当解释框架仍在发展之中时，系统应如何呈现分析输出？本文报告了TopoLA的开发，这是一个将Zigzag持续同调应用于学习管理系统数据的仪表盘系统，并提出了新兴分析中解释支持的三个早期设计原则：（1）客观测量与情境解释的分离，（2）从指标到模式再到反思性提示的渐进式披露，（3）对方法论不确定性的明确承认。该系统实现了一个模块化的三阶段流水线——特征提取、拓扑计算和解释支持——使其能够扩展到其他分析方法。本研究通过阐述系统必须传达来自缺乏既定解释规范的方法的分析见解的初步设计知识，为信息系统研究做出贡献——随着新颖计算技术进入应用领域，这一挑战日益普遍。
英文摘要
Topological Data Analysis (TDA) offers novel methods for understanding temporal dynamics in complex systems, yet its application in information systems design faces a fundamental challenge: how should systems present analytical outputs when interpretation frameworks are still developing? This paper reports on the development of TopoLA, a dashboard system applying Zigzag Persistent Homology to learning management system data, and proposes three early design principles for interpretation support in emerging analytics: (1) separation of objective measurement from contextual interpretation, (2) graduated disclosure from metrics through patterns to reflective prompts, and (3) explicit acknowledgment of methodological uncertainty. The system implements a modular three-stage pipeline--feature extraction, topological computation, and interpretation support--enabling extension to additional analytical methods. This work contributes to information systems research by articulating preliminary design knowledge for systems that must communicate analytical insights from methods lacking established interpretation norms--a challenge increasingly common as novel computational techniques enter applied domains.
CommentsAuthor's version, posted under the preprint/reprint distribution rights retained in the IADIS copyright transfer agreement
Journal refProceedings of the IADIS International Conference Information Systems 2026, pp. 506-510, IADIS, 2026
