GoldMind: A Teacher-Centered Knowledge Management System for Higher Education -- Lessons from Iterative Design
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arXiv
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| Main Authors: | , , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866909940875001856 |
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| author | Fernández-Nieto, Gloria Sha, Lele Li, Yuheng Tsai, Yi-Shan Chen, Guanliang Wei, Yinwei Wang, Weiqing Wen, Jinchun Singh, Shaveen Silva, Ivan Li, Yuanfang Gasěvić, Dragan Swiecki, Zachari |
| author_facet | Fernández-Nieto, Gloria Sha, Lele Li, Yuheng Tsai, Yi-Shan Chen, Guanliang Wei, Yinwei Wang, Weiqing Wen, Jinchun Singh, Shaveen Silva, Ivan Li, Yuanfang Gasěvić, Dragan Swiecki, Zachari |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_04377 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | GoldMind: A Teacher-Centered Knowledge Management System for Higher Education -- Lessons from Iterative Design Fernández-Nieto, Gloria Sha, Lele Li, Yuheng Tsai, Yi-Shan Chen, Guanliang Wei, Yinwei Wang, Weiqing Wen, Jinchun Singh, Shaveen Silva, Ivan Li, Yuanfang Gasěvić, Dragan Swiecki, Zachari Human-Computer Interaction 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. |
| title | GoldMind: A Teacher-Centered Knowledge Management System for Higher Education -- Lessons from Iterative Design |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2508.04377 |