Siu-Cheung Kong - Computational Thinking Education in K-12: Artificial Intelligence Literacy and Physical Computing

COMPUTATIONAL THINKING EDUCATION IN K12

ARTIFICIAL INTELLIGENCE LITERACY AND PHYSICAL COMPUTING

EDITED BY SIU-CHEUNG KONG AND HAROLD ABELSON

THE MIT PRESSCAMBRIDGE, MASSACHUSETTSLONDON, ENGLAND

2022 Massachusetts Institute of Technology

This work is subject to a Creative Commons CC-BY-ND-NC license.

Subject to such license, all rights are reserved.

The MIT Press would like to thank the anonymous peer reviewers who provided comments on drafts of this book. The generous work of academic experts is essential for establishing the authority and quality of our publications. We acknowledge with gratitude the contributions of these otherwise uncredited readers.

Library of Congress Cataloging-in-Publication Data

Names: Kong, Siu Cheung, editor. | Abelson, Harold, editor.

Title: Computational thinking education in K-12 : artificial intelligence literacy and physical computing / edited by Siu-Cheung Kong and Harold Abelson.

Description: Cambridge, Massachusetts ; London, England : The MIT Press, [2022] | Includes bibliographical references and index.

Identifiers: LCCN 2021035151 | ISBN 9780262543477 (Paperback)

Subjects: LCSH: Critical thinkingStudy and teaching. | Computer literacyStudy and teaching. | Artificial intelligenceEducational applications.

Classification: LCC LB1590.3 .C655 2022 | DDC 371.33dc23/eng/20211213

LC record available at https://lccn.loc.gov/2021035151

d_r0

1. Siu-Cheung Kong, Harold Abelson, and Wai-Ying Kwok
2. Karen Brennan
3. Mark Guzdial
4. H. Ulrich Hoppe and Sven Manske
5. Marcos Romn-Gonzlez, Jess Moreno-Len, and Gregorio Robles
6. Pasi Silander, Sini Riikonen, Pirita Seitamaa-Hakkarainen, and Kai Hakkarainen
7. Christian Dindler, Ole Sejer Iversen, Michael E. Caspersen, and Rachel Charlotte Smith
8. Fredrik Heintz
9. David S. Touretzky and Christina Gardner-McCune
10. Daniella DiPaola, Blakeley H. Payne, and Cynthia Breazeal
11. Florence R. Sullivan
12. Nardie Fanchamps, Marcus Specht, Lou Slangen, and Paul Hennissen
13. Ju-Ling Shih

1. 
   Defining an image filter as a sequence of matrix transformations.
2. 
   Defining one matrix transformation.
3. 
   ctMazeStudio with rule library.
4. 
   ctMazeStudios situated rule editor.
5. 
   Flow diagram for reactive rule-based programming (RRBP).
6. 
   Architecture of the rule-based system.
7. 
   Block-structured programming interface.
8. 
   Comparison between reactive rule-based programming (RRBP) and visual block-based programming (VBBP).
9. 
   Experimental procedure.
10. 
    Algorithmic understanding: declarative and procedural knowledge of groups A and B, measured at
11. 
    Computational concepts to solve a visuospatial problem (Romn-Gonzlez, Prez-Gonzlez, and Jimnez-Fernndez 2017).
12. 
    Computational concepts to solve a linguistic-narrative problem (Howland and Good 2015).
13. 
    Interface of Flip, which blends block-based programming-language and natural language.
14. 
    Gender differences in CT performance over visuospatial problems (left; Romn-Gonzlez, Prez-Gonzlez, and Jimnez-Fernndez 2017) and linguistic-narrative problems (right; Howland and Good 2015).
15. 
    Conditional logic embedded in a linguistic-verbal context (; Campos, Signoretti, and Rodrigues 2017), and modeling as a computational practice to support language learning (bottom; Sabitzer et al. 2018).
16. 
    Overview of ScratchMaths modules and topics (), and the Scratch program, which implements the mathematical concept of place value (bottom) (Benton et al. 2018).
17. 
    Flow control through repetition structures for composing music (Barat et al. 2017).
18. 
    Examples of embodied CT: Tangible devices (left), dancing and programming (middle), and learning about sorting networks by means of an unplugged activity (right
19. 
    Visual language for solving a visual problem (https://studio.code.org/s/express-2019/stage/19/puzzle/6).
20. 4.10
    Architectural design by means of computer programming (Bauer, Butler, and Popovi2017).
21. 4.11
    Chatbot (Benotti, Martnez, and Schapachnik 2018): K12 students learn conditionals and variables (), among other computational concepts, while programming a conversational interface (bottom
22. 4.12
    Virtual home assistant built with ML techniques and implemented in Scratch (Rodrguez-Garca et al. 2019).
23. 4.13
    Wolf-Sheep predation model in NetLogo (Dickes and Sengupta 2013, Wilensky and Reisman 2006).
24. 4.14
    A visuospatial item for the upcoming CT
25. 4.15
    A verbal-linguistic item for the upcoming CT
26. 
    Framework for learning computational thinking in K12 education, consisting of the computational system and human information processing.
27. 
    Illustrating, designing, and making a prototype of the banana light invention.
28. 
    Process model for engaging students in research, ideation, construction, and reflection upon technology.
29. 
    The DORIT model for engaging students in analyzing and reflecting on the technical construction, purpose, use, value, and impact of technology.
30. 
    Students design and construct technology for others (arrows left to right), and students analyze and critique technology that others have designed for them (arrows right to left). (Adapted from Iversen, Dindler, and Smith 2019.)
31. 
    The four competence areas in the technology comprehension curriculum.
32. 
    References to AI in the 2017 CSTA Computer Science Standards.
33. 
    The Five Big Ideas in AI graphic from AI4K12.org.
34. 
    Part of the draft grade band progression chart for Big Idea #1, perception. The rows list concepts and skills; the columns are the four grade bands.
35. 
    Edge detection is one of the first stages of computer vision. Vertical and horizontal edges are detected by convolving 33 kernels with the image.
36. 
    Real-time spectrogram of the first author saying, Every child deserves to learn about artificial intelligence. The vertical axis is frequency; the horizontal axis is time;shadingindicates the amount of energy in that frequency band. (Created with