Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Bridging Pedagogy and Play: Introducing a Language Mapping Interface for Human-AI Co-Creation in Educational Game Design

Daijin Yang, Erica Kleinman, Casper Harteveld

TL;DR

A controlled natural language framework-based web tool that positions language as the primary interface for LLM-assisted educational game design and has the potential to lower design barriers for non-expert designers, preserves human agency in critical decisions, and enables alignment and reflections between pedagogy and gameplay during and after co-creation.

Abstract

Educational games can foster critical thinking, problem-solving, and motivation, yet instructors often find it difficult to design games that reliably achieve specific learning outcomes. Existing authoring environments reduce the need for programming expertise, but they do not eliminate the underlying challenges of educational game design, and they can leave non-expert designers reliant on opaque suggestions from AI systems. We designed a controlled natural language framework-based web tool that positions language as the primary interface for LLM-assisted educational game design. In the tool, users and an LLM assistant collaboratively develop a structured language that maps pedagogy to gameplay through four linked components. We argue that, by making pedagogical intent explicit and editable in the interface, the tool has the potential to lower design barriers for non-expert designers, preserves human agency in critical decisions, and enables alignment and reflections between pedagogy and gameplay during and after co-creation.

Bridging Pedagogy and Play: Introducing a Language Mapping Interface for Human-AI Co-Creation in Educational Game Design

TL;DR

A controlled natural language framework-based web tool that positions language as the primary interface for LLM-assisted educational game design and has the potential to lower design barriers for non-expert designers, preserves human agency in critical decisions, and enables alignment and reflections between pedagogy and gameplay during and after co-creation.

Abstract

Educational games can foster critical thinking, problem-solving, and motivation, yet instructors often find it difficult to design games that reliably achieve specific learning outcomes. Existing authoring environments reduce the need for programming expertise, but they do not eliminate the underlying challenges of educational game design, and they can leave non-expert designers reliant on opaque suggestions from AI systems. We designed a controlled natural language framework-based web tool that positions language as the primary interface for LLM-assisted educational game design. In the tool, users and an LLM assistant collaboratively develop a structured language that maps pedagogy to gameplay through four linked components. We argue that, by making pedagogical intent explicit and editable in the interface, the tool has the potential to lower design barriers for non-expert designers, preserves human agency in critical decisions, and enables alignment and reflections between pedagogy and gameplay during and after co-creation.
Paper Structure (9 sections, 3 figures, 1 table)

This paper contains 9 sections, 3 figures, 1 table.

Table of Contents

  1. Introduction
  2. Related Work
  3. Introducing the educational game design language mapping framework
  4. System Design
  5. Requirement Extraction
  6. Language Translation
  7. Language Development
  8. Implementations
  9. Conclusions and Future Studies

Figures (3)

  • Figure 1: The Requirement Extraction Components in the Tool. Instructors answers questions asked by AI around the defined grammatical elements on the right and co-author the requirement document on the left.
  • Figure 2: The Language Translation Components (Partially) in the Tool. Instructors explore AI-generated gameplay translations of their teaching language. They can edit, regenerate, or write their own translations during the process. The interface uses color mapping to link corresponding grammatical elements in the teaching language and the game language.
  • Figure 3: The Language Development Components (Partially) in the Tool. Instructors can further edit and refine the generated game-concept sentence with AI. They can also click the Zoom In buttons to have the AI generate a descriptive paragraph and pseudocode for the game’s procedures.