Date
Publisher
arXiv
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.
Study at a glance
- Question: How can a knowledge management system be designed with teachers to support their daily digital teaching tasks?
- Setting and data: 108 higher education teachers over two years.
- Method: Iterative co-design and usability testing across three design-evaluation cycles (human-centred design study).
Why it matters
Staff turnover and changing roles make reusing knowledge challenging, yet existing knowledge management systems often overlook the realities of educators' workflows. This leads to low adoption and limited impact, despite advances in Generative AI.
Key findings
- In a two-year study with 108 higher education teachers, educator feedback guided the refinement of a knowledge management system for digital teaching tasks.
- Existing knowledge management systems often overlook teachers' actual workflows, leading to low educator adoption and limited impact.
- Teachers' interactions with the knowledge system highlighted critical human factors, including educator cognitive load and knowledge-sharing behaviors during digital tasks.
Summary drafted with AI from the paper’s abstract and may contain errors. See the full paper for details.
What is the application?
Who is the user?
Who age?
Why use AI?
