Learning Computational Thinking Efficiently

被引：3

作者：

Bender, Jeff ^{[1
]}

Zhao, Bingpu ^{[1
]}

Dziena, Alex ^{[1
]}

Kaiser, Gail ^{[1
]}

机构：

[1] Columbia Univ, Comp Sci, New York, NY 10027 USA

来源：

PROCEEDINGS OF THE 24TH AUSTRALASIAN COMPUTING EDUCATION CONFERENCE, ACE 2022 | 2022年

关键词：

Computational Thinking; Parsons Programming Puzzles; Scratch; Motivation; Cognitive Load; Learning Efficiency;

D O I：

10.1145/3511861.3511869

中图分类号：

G40 [教育学];

学科分类号：

040101 ; 120403 ;

摘要：

Using a design thinking approach, we surveyed and interviewed grade 6-9 teachers on their experience with Scratch and Parsons Programming Puzzles (PPP). The results lead us to extend Scratch with gameful PPP functionality focused on individual computational thinking (CT) concepts. In this paper, we vary elements of PPPs presented to 624 adult learners to identify those yielding manageable cognitive load (CL), and maximum CT motivation and learning efficiency, for a general populace. Findings indicate PPPs with feedback and without distractors limit CL, those with feedback produce highest CT motivation, and those with an isolated block palette and without distractors produce highest CT learning efficiency. We analyze study data across nine conditions to offer insight to those developing PPP systems with the aim to advance equitable CT education for all.

引用

收藏

页码：66 / 75

页数：10

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