Gaming/Virtual Environments

In-Game Actions to Promote Game-Based Math Learning Engagement

Game-based learning (GBL) has increasingly been used to promote students’ learning engagement. Although prior GBL studies have highlighted the significance of learning engagement as a mediator of students’ meaningful learning, the existing accounts failed to capture specific evidence of how exactly students’ in-game actions in GBL enhance learning engagement. Hence, this mixed-method study was designed to examine whether middle school students’ in-game actions are likely to promote certain types of learning engagement (i.e., content and cognitive engagement).

Author/Presenter: 
Jewoong Moon
Fengfeng Ke
Lead Organization(s): 
Year: 
2019
Short Description: 
This mixed-method study was designed to examine whether middle school students’ in-game actions are likely to promote certain types of learning engagement (i.e., content and cognitive engagement).

The Role of Simulation-Enabled Design Learning Experiences on Middle School Students’ Self-generated Inherence Heuristics

In science and engineering education, the use of heuristics has been introduced as a way of understanding the world, and as a way to approach problem-solving and design. However, important consequences for the use of heuristics are that they do not always guarantee a correct solution. Learning by Design has been identified as a pedagogical strategy that can guide individuals to properly connect science learning via design challenges.

Author/Presenter: 
Alejandra J. Magana
Sindhura Elluri
Chandan Dasgupta
Ying Ying Seah
Aasakiran Madamanchi
Mireille Boutin
Lead Organization(s): 
Year: 
2019
Short Description: 
This article describes the effect of simulation-enabled Learning by Design learning experiences on student-generated heuristics that can lead to solutions to problems.

In Praise of Messy Data

Gould, R. R., S. Sunbury, & Dussault, M. (2014). In praise of messy data: Lessons from the search for alien worlds. The Science Teacher, 31.

Author/Presenter: 
Roy Gould
Susan Sunbury
Mary Dussault
Year: 
2014
Short Description: 
Lessons from the search for alien worlds.

Using online telescopes to explore exoplanets from the physics classroom

The search for habitable planets offers excellent opportunities to advance students’ understanding of core ideas in physics, including gravity and the laws of motion, the interaction of light and matter, and especially the nature of scientific inquiry. Thanks to the development of online telescopes, students can detect more than a dozen of the known exoplanets from the classroom, using data they gather, assess, and interpret for themselves. We present a suite of activities in which students apply basic physics concepts to their investigations of exoplanets.

Author/Presenter: 
Roy R. Gould
Susan Sunbury
Ruth Krumhansl
Year: 
2012
Short Description: 
Authors present a suite of activities in which students apply basic physics concepts to their investigations of exoplanets. The activities were developed and successfully tested with physics and earth science teachers in secondary schools in 14 states.

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.

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