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This content will become publicly available on June 10, 2026

Title: Opening the Black Box: Student Motivations in an Unpackable-Block-Based Computational Modeling Environment
Not AvailableEngaging with computational models is central to both scientific and computational learning. A promising approach to “lower the floor” and make computational modeling more accessible is the development of domain-specific and block-based environments, which reduce programming complexity while leveraging students’ intuitions about scientific ideas. To balance usability and expressiveness in these environments, we develop the feature of “unpacking” blocks, allowing users to open and modify high-level blocks into the simpler constituent elements that define them. In this study, we analyze high school students’ models, screen recordings, and artifact-based interviews to investigate their motivation for modifying domain-specific blocks for eutrophication in aquatic ecosystems. We found that unpacking and modifying blocks supported students in both exploring scientific ideas and addressing specific goals of computational modeling, providing insights on how unpacking domain-specific blocks can support both computing and science learning.  more » « less
Award ID(s):
2010413
PAR ID:
10643977
Author(s) / Creator(s):
; ; ; ;
Editor(s):
Rajala, A; Cortez, A; Hofmann, R; Jornet, A; Lotz-Sisitka, H; Markauskaite, L
Publisher / Repository:
International Society of the Learning Sciences
Date Published:
Page Range / eLocation ID:
3082 to 3084
Subject(s) / Keyword(s):
education learning sciences computer modeling computer science education science education
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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