Computer Science

What They Learn When They Learn Coding: Investigating Cognitive Domains and Computer Programming Knowledge in Young Children

Computer programming for young children has grown in popularity among both educators and product developers, but still relatively little is known about what skills children are developing when they code. This study investigated N = 57 Kindergarten through second grade children’s performance on a programming assessment after engaging in a 6-week curricular intervention. Children used the ScratchJr programming tool to create animated stories, collages, and games.

Author/Presenter: 
Amanda Strawhacker
Marina Umaschi Bers
Lead Organization(s): 
Year: 
2018
Short Description: 
This study investigated N = 57 Kindergarten through second grade children’s performance on a programming assessment after engaging in a 6-week curricular intervention called ScratchJr.

The Computational Algorithmic Thinking (CAT) Capability Flow: An Approach to Articulating CAT Capabilities over Time in African-American Middle-school Girls

Computational algorithmic thinking (CAT) is the ability to design, implement, and assess the implementation of algorithms to solve a range of problems. It involves identifying and understanding a problem, articulating an algorithm or set of algorithms in the form of a solution to the problem, implementing that solution in such a way that the solution solves the problem, and evaluating the solution based on some set of criteria.

Author/Presenter: 
Jakita Thomas
Lead Organization(s): 
Year: 
2018
Short Description: 
This paper explores the CAT Capability Flow, which begins to describe the processes and sub-skills and capabilities involve in computational algorithmic thinking (CAT). To do this, authors engage in an approach which results in an initial flowchart that depicts the processes students are engaging in as an iteratively-refined articulation of the steps involved in computational algorithmic thinking.

Exploring African American Middle-School Girls' Perceptions of Themselves as Game Designers

Computational algorithmic thinking (CAT) is the ability to design, implement, and assess the implementation of algorithms to solve a range of problems. Supporting Computational Algorithmic Thinking (SCAT) is a longitudinal project that explores the development of CAT capabilities by guiding African American middle-school girls through the iterative game design cycle, resulting in a set of complex games around broad themes.

Author/Presenter: 
Jakita O. Thomas
Rachelle Minor
O. Carlette Odemwingie
Lead Organization(s): 
Year: 
2017
Short Description: 
This paper explores African American middle-school girls' perspectives of their experience with the Supporting Computational Algorithmic Thinking (SCAT) project and perceptions of themselves as game designers.

Exploring the Difficulties African-American Middle School Girls Face Enacting Computational Algorithmic Thinking over three Years while Designing Games for Social Change

Computational algorithmic thinking (CAT) is the ability to design, implement, and assess the implementation of algorithms to solve a range of problems. It involves identifying and understanding a problem, articulating an algorithm or set of algorithms in the form of a solution to the problem, implementing that solution in such a way that the solution solves the problem, and evaluating the solution based on some set of criteria.

Author/Presenter: 
Jakita O. Thomas
Yolanda Rankin
Rachelle Minor
Li Sun
Lead Organization(s): 
Year: 
2017
Short Description: 
This article explores middle school girls' reflections about the difficulties they faced while using computational algorithmic thinking capabilities as they engaged in collaborative game design for social change. Authors focus on how these difficulties changed over the course of three years as well as new difficulties that emerged from year to year as girls become more expert game designers and computational algorithmic thinkers.

Understanding the Difficulties African-American Middle School Girls Face While Enacting Computational Algorithmic Thinking in the Context of Game Design

Computational algorithmic thinking (CAT) is the ability to design, implement, and assess the implementation of algorithms to solve a range of problems. It involves identifying and understanding a problem, articulating an algorithm or set of algorithms in the form of a solution to the problem, implementing that solution in such a way that it solves the problem, and evaluating the solution based on some set of criteria. CAT has roots in Mathematics, through problem solving and algorithmic thinking. CAT lies at the heart of Computer Science, which is defined as the study of algorithms.

Author/Presenter: 
Jakita O. Thomas
O. Carlette Odemwingie
Quimeka Saunders
Malika Watlerd
Lead Organization(s): 
Year: 
2015
Short Description: 
This article introduces CAT as explored through the Supporting Computational Algorithmic Thinking (SCAT) project, an ongoing longitudinal between-subjects research project and enrichment program that guides African-American middle school girls (SCAT Scholars) through the iterative game design cycle resulting in a set of complex games around broad themes.

2019 International Conference on Computer-Supported Collaborative Learning; Lyon, France

Event Date: 
Mon, 06/17/2019 (All day) to Fri, 06/21/2019 (All day)
Associated Dates and Deadlines: 

To learn more, visit https://www.cscl2019.com/en/-home/4.

DRK-12 Presenters:

  • Camillia Matuk*, New York University
  • Nadav Ehrenfeld and Ilana Horn, Vanderbilt University

*Denotes CADRE Fellow or Fellows alumnus

Event Type: 
Discipline / Topic: 

STEAM-Based Interventions in Computer Science: Understanding Feedback Loops in the Classroom

Many organizations are seeking to address the need for greater numbers of computer scientists in the US, and in particular, more women and underrepresented minorities. It is not uncommon to develop curriculum that relies heavily on cutting edge technology and computing tools designed to make computing more compelling. Many curriculum developers are seeking to promote creativity as a part of computing, and often do so using STEAM (science, technology, engineering, arts, and mathematics) based interventions where the arts play a prominent role in the classroom.

Author/Presenter: 
Roxanne Moore
Michael Helms
Michael Helms
Year: 
2017
Short Description: 
In this paper, authors present the causal loop diagrams developed to explain the relationships between the actors and attributes involved in implementing EarSketch in a particular school setting. The diagram allows us to better make decisions that ensure both an engaging but also effective STEAM-based computing curriculum.

Turn-Taking and Chatting in Collaborative Music Live Coding

Co-located collaborative live coding is a potential approach to network music and to the music improvisation practice known as live coding. A common strategy to support communication between live coders and the audience is the use of a chat window. However, paying attention to simultaneous multi-user actions, such as chat texts and code, can be too demanding to follow. In this paper, we explore collaborative music live coding (CMLC) using the live coding environment and pedagogical tool EarSketch.

Author/Presenter: 
Anna Xambó
Pratik Shah
Gerard Roma
Jason Freeman
Brian Magerko
Year: 
2017
Short Description: 
In this paper, authors explore collaborative music live coding (CMLC) using the live coding environment and pedagogical tool EarSketch. In particular, we examine the use of turn-taking and a customized chat window inspired by the practice of pair programming, a team-based strategy to efficiently solving computational problems.

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