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MiBoard: Multiplayer Interactive Board Game

Project Overview

The document explores the application of generative AI in education, highlighting the creation of MiBoard, a multiplayer serious game designed to boost student engagement through interactive gameplay. MiBoard extends the iSTART Intelligent Tutoring System, focusing on enhancing students' comprehension and reading strategies by encouraging self-explanation and peer feedback. By merging entertainment with educational elements, the game aims to motivate students, increase their time spent on learning activities, and ultimately improve their educational outcomes. The findings indicate that such innovative applications of generative AI not only make learning more enjoyable but also effectively enhance overall learning effectiveness, showing promise for broader implementation in educational settings.

Key Applications

MiBoard: Multiplayer Interactive Board Game

Context: Educational context for psychology and computer science students focusing on reading strategies and comprehension.

Implementation: Developed as an extension of the iSTART Intelligent Tutoring System, incorporating multiplayer interactions.

Outcomes: Increased student engagement, motivation, and effectiveness in applying reading strategies leading to better comprehension of texts.

Challenges: Balancing game entertainment with educational value, ensuring sustained motivation over long-term use.

Implementation Barriers

Technical

The need for an automated comprehension check within the game to assess reading strategy application.

Proposed Solutions: Encouraging player discussion and peer feedback as part of the gameplay to enhance understanding and application of strategies.

Project Team

Kyle B. Dempsey

Researcher

Justin F. Brunelle

Researcher

G. Tanner Jackson

Researcher

Chutima Boonthum

Researcher

Irwin B. Levinstein

Researcher

Danielle S. McNamara

Researcher

Contact Information

For information about the paper, please contact the authors.

Authors: Kyle B. Dempsey, Justin F. Brunelle, G. Tanner Jackson, Chutima Boonthum, Irwin B. Levinstein, Danielle S. McNamara

Source Publication: View Original PaperLink opens in a new window

Project Contact: Dr. Jianhua Yang

LLM Model Version: gpt-4o-mini-2024-07-18

Analysis Provider: Openai

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