WindowDash¶
Product or Programme · All products and programmes
Evidence · 3 claims (3 for) · 1 study (1 design),q2· 0 of 1 report an effect size · 3 claims rest on one study
Description¶
WindowDash is a synthetic food-delivery teaching-case dataset and accompanying instructional materials developed by Bang An et al. for undergraduate business analytics and visualization instruction.
Components¶
Claims¶
- The Olist and WindowDash simulation inputs are matched in scale and analytical scope, with overlapping distributions but differing duration-rating associations [+W]
- Designed patterns can rest on very small supporting subgroups: only three orders meet the Price-Rating Sensitivity conditions, with a mean rating of 2.0 [+W]
- AI agents recover a smaller share of reference patterns from the synthetic WindowDash dataset than from the real-world Olist dataset [+W]
Related Products and Programmes¶
Key Sources¶
- Bang An, Maria Hamdani, Joseph Fox. (2026). DataCanvas-EDU: An Agentic Framework for Instructor-Guided Synthetic Data Generation in Business Analytics Education. https://arxiv.org/abs/2609.19617
Page metadata
| Field | Value |
|---|---|
type |
product |
id |
windowdash |
title |
WindowDash |
description |
WindowDash is a synthetic food-delivery teaching-case dataset and accompanying instructional materials developed by Bang An et al. |
status |
review |
product_kind |
dataset |
generated |
by process:settle-candidates on 2026-10-10 |
trust |
unverified — no one has confirmed this page's content |
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