Computer Science

Toward Ontological Alignment: Coordinating Student Ideas with the Representational System of a Computational Modeling Unit for Science Learning

Computational modeling tools present unique opportunities and challenges for student learning. Each tool has a representational system that impacts the kinds of explorations students engage in. Inquiry aligned with a tool’s representational system can support more productive engagement toward target learning goals. However, little research has examined how teachers can make visible the ways students’ ideas about a phenomenon can be expressed and explored within a tool’s representational system.

Author/Presenter

Aditi Wagh

Leah F. Rosenbaum

Tamar Fuhrmann

Adelmo Eloy

Paulo Blikstein

Michelle Wilkerson

Year
2024
Short Description

Computational modeling tools present unique opportunities and challenges for student learning. Each tool has a representational system that impacts the kinds of explorations students engage in. Inquiry aligned with a tool’s representational system can support more productive engagement toward target learning goals. However, little research has examined how teachers can make visible the ways students’ ideas about a phenomenon can be expressed and explored within a tool’s representational system. In this paper, we elaborate on the construct of ontological alignment—that is, identifying and leveraging points of resonance between students’ existing ideas and the representational system of a tool.

Getting Unstuck Together: Creating Personally Authentic Programming Projects in a 4th Grade Classroom

Background and Context
Learning to create self-directed and personally authentic programming projects involves encountering challenges and learning to get unstuck.

Author/Presenter

Paulina Haduong

Karen Brennan

Lead Organization(s)
Year
2024
Short Description

Teachers play a central role in designing structures which encourage the development of students’ individual creative capacity and the classroom’s sense of community. We offer considerations for designing engaging and collaborative experiences in elementary and intermediate computing education.

Struggling to Detect Struggle in Students Playing a Science Exploration Game

The real-time detection of when a player is struggling presents an opportunity for game designers to design timely and meaningful interventions, as well as to provide targeted support that improves student learning and engagement. In this paper, we present a struggle detector in the context of students playing the learning game, Wake: Tales from the Aqualab.

Author/Presenter

Xiner Liu

Stefan Slater

Juliana Ma. Alexandra L. Andres

Luke Swanson

Jennifer Scianna

David Gagnon

Ryan S. Baker

Year
2023
Short Description

The real-time detection of when a player is struggling presents an opportunity for game designers to design timely and meaningful interventions, as well as to provide targeted support that improves student learning and engagement. In this paper, we present a struggle detector in the context of students playing the learning game, Wake: Tales from the Aqualab.

Struggling to Detect Struggle in Students Playing a Science Exploration Game

The real-time detection of when a player is struggling presents an opportunity for game designers to design timely and meaningful interventions, as well as to provide targeted support that improves student learning and engagement. In this paper, we present a struggle detector in the context of students playing the learning game, Wake: Tales from the Aqualab.

Author/Presenter

Xiner Liu

Stefan Slater

Juliana Ma. Alexandra L. Andres

Luke Swanson

Jennifer Scianna

David Gagnon

Ryan S. Baker

Year
2023
Short Description

The real-time detection of when a player is struggling presents an opportunity for game designers to design timely and meaningful interventions, as well as to provide targeted support that improves student learning and engagement. In this paper, we present a struggle detector in the context of students playing the learning game, Wake: Tales from the Aqualab.

Struggling to Detect Struggle in Students Playing a Science Exploration Game

The real-time detection of when a player is struggling presents an opportunity for game designers to design timely and meaningful interventions, as well as to provide targeted support that improves student learning and engagement. In this paper, we present a struggle detector in the context of students playing the learning game, Wake: Tales from the Aqualab.

Author/Presenter

Xiner Liu

Stefan Slater

Juliana Ma. Alexandra L. Andres

Luke Swanson

Jennifer Scianna

David Gagnon

Ryan S. Baker

Year
2023
Short Description

The real-time detection of when a player is struggling presents an opportunity for game designers to design timely and meaningful interventions, as well as to provide targeted support that improves student learning and engagement. In this paper, we present a struggle detector in the context of students playing the learning game, Wake: Tales from the Aqualab.

Open Game Data: A Technical Infrastructure for Open Science with Educational Games

In this paper we describe a technical infrastructure, entitled Open Game Data, for conducting educational game research using open science, educational data mining and learning engineering approaches. We describe a modular data pipeline which begins with telemetry events from gameplay and ends with real time APIs and automated archival exports that support research. We demonstrate the usefulness of this infrastructure by summarizing several game research projects that have utilized and contributed back to Open Game Data.

Author/Presenter

David J. Gagnon

Luke Swanson 

Year
2023
Short Description

In this paper we describe a technical infrastructure, entitled Open Game Data, for conducting educational game research using open science, educational data mining and learning engineering approaches.

Open Game Data: A Technical Infrastructure for Open Science with Educational Games

In this paper we describe a technical infrastructure, entitled Open Game Data, for conducting educational game research using open science, educational data mining and learning engineering approaches. We describe a modular data pipeline which begins with telemetry events from gameplay and ends with real time APIs and automated archival exports that support research. We demonstrate the usefulness of this infrastructure by summarizing several game research projects that have utilized and contributed back to Open Game Data.

Author/Presenter

David J. Gagnon

Luke Swanson 

Year
2023
Short Description

In this paper we describe a technical infrastructure, entitled Open Game Data, for conducting educational game research using open science, educational data mining and learning engineering approaches.