Designing Knowledge Management Systems (KMSs) for higher education requires addressing complex human-technology interactions, especially where staff turnover and changing roles create ongoing challenges for reusing knowledge. While advances in process mining and Generative AI enable new ways of designing features to support knowledge management, existing KMSs often overlook the realities of educators' workflows, leading to low adoption and limited impact. This paper presents findings from a two-year human-centred design study with 108 higher education teachers, focused on the iterative co-design and evaluation of GoldMind, a KMS supporting in-the-flow knowledge management during digital teaching tasks. Through three design-evaluation cycles, we examined how teachers interacted with the system and how their feedback informed successive refinements. Insights are synthesised across three themes: (1) Technology Lessons from user interaction data, (2) Design Considerations shaped by co-design and usability testing, and (3) Human Factors, including cognitive load and knowledge behaviours, analysed using Epistemic Network Analysis.
翻译:为高等教育设计知识管理系统(KMS)需要应对复杂的人机交互问题,特别是在人员流动和角色变化持续对知识复用构成挑战的背景下。尽管过程挖掘和生成式人工智能的进步为设计支持知识管理的功能提供了新途径,但现有的KMS往往忽视教育工作者工作流的实际情况,导致采用率低且影响有限。本文呈现了一项为期两年、涉及108名高校教师的人本设计研究结果,该研究聚焦于GoldMind(一个在数字化教学任务中支持流程内知识管理的KMS)的迭代协同设计与评估。通过三个设计-评估循环,我们考察了教师如何与系统交互,以及他们的反馈如何指导后续改进。研究洞见综合为三个主题:(1)从用户交互数据中得出的技术经验,(2)由协同设计和可用性测试形成的设计考量,以及(3)使用认知网络分析探讨的人因因素,包括认知负荷与知识行为。