Raging Skies¶
Product or Programme · All products and programmes
Evidence · 3 claims (3 mixed) · 1 study (1 design),q2· 0 of 1 report an effect size · 3 claims rest on one study
Description¶
Raging Skies is a digital game-based assessment developed by Ying Cui and colleagues that measures Grade 5 students' weather knowledge through storm-chasing tasks, adaptive difficulty, and in-game and summary feedback.
Components¶
Claims¶
- Learning curves show error rates decreased for wind direction, air movement, and cloud type but stayed high for wind speed and precipitation skills [~W]
- BKT estimates show most students mastered wind direction and air movement but few mastered wind speed, precipitation type, or amount [~W]
- DBN analysis shows wind direction and air movement reached the highest posterior mastery probabilities while other skills stayed flat or declined [~W]
Related Products and Programmes¶
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Key Sources¶
- Ying Cui, Man-Wai Chu, Fu Chen. (2019). Analyzing Student Process Data in Game-Based Assessments with Bayesian Knowledge Tracing and Dynamic Bayesian Networks. Journal of Educational Data Mining, Volume 11, No 1. https://jedm.educationaldatamining.org/index.php/JEDM/article/view/397
Page metadata
| Field | Value |
|---|---|
type |
product |
id |
raging-skies |
title |
Raging Skies |
description |
Raging Skies is a digital game-based assessment developed by Ying Cui and colleagues that measures Grade 5 students' weather knowledge through storm-chasing tasks, adaptive difficulty, and in-game and summary feedback. |
status |
review |
moved_from |
element/raging-skies-game-assessment |
product_kind |
assessment |
generated |
by process:sweep-kinds on 2026-10-10 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — ying-cui-2019 |
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