Capturing and Sharing Know-How through Visual Process Representations: A Human-Centred Approach to Teacher Workflows

2025-08-06

AI Summary

High faculty turnover in higher education institutions leads to teaching knowledge loss, imposes heavy documentation burdens on domain experts, and creates steep learning curves for novices. Method: This study proposes a human-centered Visual Process Representation (VPR) framework that integrates Sequential Pattern Mining (SPM) with log data analysis to automatically transform instructor interaction logs into intuitive, story-like visual narratives—eliminating the need for manual process documentation. Contribution/Results: VPR innovatively unifies knowledge management with narrative visualization, supporting dual-modal (text + image) presentation. A user-perception evaluation involving 160 university instructors demonstrated that VPR significantly improves task completion efficiency, system usability, and user engagement; enhanced visual representations yielded superior outcomes. The framework provides a scalable, low-intervention, automated solution for knowledge retention and transfer in educational organizations.

Technology Category

• Data Mining & Knowledge Management: Mining of Visual, Multimedia & Multimodal Data
• Knowledge Representation and Reasoning: Knowledge Acquisition
• Computer Vision: Visual Reasoning & Symbolic Representations

Application Category

• Web Mining and Content Analysis: Web data visualization
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• User Modeling, Personalization and Recommendation: Practical large-scale studies of user experience

Abstract

Knowledge Management is crucial for capturing and transferring expertise within universities, especially in high staff turnover contexts where expertise loss disrupts teaching. Documenting teachers' workflows is time-intensive and diverts experts from core responsibilities. Sequential Pattern Mining (SPM) leverages log data to identify expert workflows, offering an automated alternative to represent workflows but requiring transformation into intuitive formats for novice educators. This paper introduces Visual Process Representations (VPR), a design approach combining SPM, Knowledge Management processes, and storytelling techniques to convert expert log data into clear visualisations. We detail the design phases and report a study evaluating visual affordances (text lists vs. pictorial-style) and teachers' perceptions of four versions of the VPR with 160 higher teachers on Prolific. Results indicate improved task performance, usability, and engagement, particularly with enriched visuals, though process memorability and task time improvements were limited. The findings highlight VPR's potential to visualise workflows and support novice educators.

Problem

• Automating teacher workflow documentation to reduce time burden
• Transforming log data into intuitive visual formats for novices
• Enhancing knowledge transfer in high turnover university settings

Innovation

• Combines SPM with Knowledge Management and storytelling
• Transforms expert log data into clear visualizations
• Evaluates visual affordances for improved usability