CT4ALL: Towards Putting Teachers in the Loop to Advance Automated Computational Thinking Metric Assessments in Game-Based Learning

要旨

Computational thinking (CT) is essential for the 21st century learner. Yet, assessing CT remains challenging. This is particularly challenging in constructionist learning, where individual idiosyncrasies may clash with one-size-fits-all assessments. Tools like Dr. Scratch offer CT metrics that show promise for effective and scalable CT assessments, particularly in constructionist game-based learning (GBL). Prior work has advanced the design of automated CT metrics but hardly included teachers in the process. We extend Dr. Scratch to improve automated CT assessments for GBL and put teachers in the loop to assess its novel features. Specifically, we interviewed seven middle school teachers employing GBL in STEM curricula and asked them to provide feedback on the newly designed CT metrics. Teachers view the new CT metrics positively, underscoring their potential for adaptive CT assessments despite hindrances. We advance automated CT assessments via teacher evaluation toward design-sensitive CT metrics and CT for all.

受賞
Honorable Mention
著者
Giovanni M. Troiano
Northeastern University, Somerville, Massachusetts, United States
Michael Cassidy
TERC, Cambridge, Massachusetts, United States
Daniel Escobar Morales
Universidad Rey Juan Carlos, Madrid, Spain
Guillermo Pons
Universidad Rey Juan Carlos, Madrid, Spain
Amir Abdollahi
Northeastern University, Boston, Massachusetts, United States
Gregorio Robles
Universidad Rey Juan Carlos, Madrid, Spain
Gillian Puttick
TERC, Cambridge, Massachusetts, United States
Casper Harteveld
Northeastern University, Boston, Massachusetts, United States
DOI

10.1145/3706598.3713368

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713368

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: CS Education and Security

G303
6 件の発表
2025-04-28 20:10:00
2025-04-28 21:40:00
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