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Seasoning Data Modeling Education with GARLIC: A Participatory Co-Design Framework

Viktoriia Makovska, Ihor Michurin, Mariia Tokhtamysh, George Fletcher, Julia Stoyanovich

TL;DR

GARLIC lowers the barrier to participatory ER modeling and equips students with practical skills for collaborative, inclusive data model design and is designed to develop both technical modeling skills and critical awareness of the social and ethical dimensions of data representation.

Abstract

Entity-Relationship (ER) modeling is commonly taught as a primarily technical activity, despite its central role in shaping how data systems represent people, processes, and institutions. Prior research in participatory design demonstrates that involving diverse stakeholders in modeling can surface tacit knowledge, challenge implicit assumptions, and produce more inclusive data representations. However, database education currently lacks structured pedagogical approaches for teaching participatory ER modeling in practice. We introduce the GARLIC methodology for teaching and learning participatory ER modeling. GARLIC adapts and extends the ONION participatory ER modeling framework of Makovska et al.(HILDA 2025) into a workshop-based learning format that combines role-playing, collaborative synthesis, guided critique, and iterative refinement. GARLIC is designed to develop both technical modeling skills and critical awareness of the social and ethical dimensions of data representation. GARLIC lowers the barrier to participatory ER modeling and equips students with practical skills for collaborative, inclusive data model design.

Seasoning Data Modeling Education with GARLIC: A Participatory Co-Design Framework

TL;DR

GARLIC lowers the barrier to participatory ER modeling and equips students with practical skills for collaborative, inclusive data model design and is designed to develop both technical modeling skills and critical awareness of the social and ethical dimensions of data representation.

Abstract

Entity-Relationship (ER) modeling is commonly taught as a primarily technical activity, despite its central role in shaping how data systems represent people, processes, and institutions. Prior research in participatory design demonstrates that involving diverse stakeholders in modeling can surface tacit knowledge, challenge implicit assumptions, and produce more inclusive data representations. However, database education currently lacks structured pedagogical approaches for teaching participatory ER modeling in practice. We introduce the GARLIC methodology for teaching and learning participatory ER modeling. GARLIC adapts and extends the ONION participatory ER modeling framework of Makovska et al.(HILDA 2025) into a workshop-based learning format that combines role-playing, collaborative synthesis, guided critique, and iterative refinement. GARLIC is designed to develop both technical modeling skills and critical awareness of the social and ethical dimensions of data representation. GARLIC lowers the barrier to participatory ER modeling and equips students with practical skills for collaborative, inclusive data model design.
Paper Structure (11 sections, 5 figures)

This paper contains 11 sections, 5 figures.

Table of Contents

  1. Introduction
  2. Prior Work
  3. A Workshop-Based Approach to Participatory Modeling
  4. Pedagogical Principles
  5. Workshop Components and Materials
  6. The Workshop Process: From Individual Voices to a Shared Model
  7. Preliminary Studies and Formative Refinements
  8. Summary and Future Work
  9. Acknowledgments
  10. Preliminary Case Study: Library System Tool
  11. Preliminary Case Study: Course Enrollment Scenario

Figures (5)

  • Figure 1: GARLIC workshop structure and validation artifacts. Individual Role Cards (right) articulate participant voices within a shared scenario, while the GARLIC framework (left) structures how these voices are integrated and validated during participatory ER modeling.
  • Figure 2: Library case study artifacts from the Observe and Nurture stages. Left: stage card goals/prompts and expected outputs. Center: participant-generated domain concepts and early clusters. Right: an initial sketch linking candidate entities/relationships prior to formalization. Students were allowed to use any visual vocabulary they considered convinient and useful.
  • Figure 3: Library case study artifacts from Integrate, Optimize, and Normalize. Left: stage card prompts focusing on unresolved tensions and voice traceability. Right: consolidated ER draft used for role-based validation (mapping each selected voice to entities, relationships, attributes, or constraints).
  • Figure 4: Course Enrollment scenario artifacts from Observe and Nurture. The team recorded a compact set of domain concepts and stakeholder concerns and moved early toward structural representation, illustrating a compressed early-stage workflow in a small-group classroom setting.
  • Figure 5: Course Enrollment scenario artifacts from Integrate/Optimize/Normalize. The team produced a draft ER model and refined it through technical validation (external validation). After voice validation (internal validation) it was decided that the ER model needs refinment and returning to previous stages needed.