Generating Game Levels to Develop Computer Science Competencies in Game-Based Learning Environments

Abstract

Game-based learning environments hold significant potential for supporting K-12 computer science (CS) education by providing CS learning experiences embedded within engaging virtual worlds. However, many game-based learning environments do not adaptively support individual students based on their specific knowledge and skills. Often, this is because creating game levels is highly labor-intensive, which limits the number of levels created to support student learning. Procedural content generation (PCG) is a promising direction for addressing this challenge by dynamically creating game levels that address specific student needs without requiring extensive development effort. In this paper, we investigate a PCG framework driven by answer set programming (ASP), a variant of logic programming that utilizes well-formed logical rules to express constraints for valid game levels. We demonstrate how variations in CS learning objectives and game-playing skills can be incorporated into ASP-based rules to generate learner-adaptive levels in a middle-grades CS game-based learning environment. Evaluations of the generated levels suggest that the ASP-based level generator not only reliably generates desired CS educational game levels but also synthesizes a large set of diverse game levels. The findings suggest that the ASP-based PCG approach has considerable promise for creating highly engaging and adaptive game-based learning experiences for K-12 CS education.