This Research to Practice Work-in-Progress Paper builds on prior developments of a gamified adaptive tutoring system that automates and personalizes a student's learning process without instructor intervention. To address the continued expansion of general education, as well as the grand challenge of personalized learning, automated learning systems are becoming common within higher education. Our personalized learning system uses an uses a structured, general-purpose game model that enables us to both track and control student progress through the sections of the game. While students play through a system-integrated game, a back-end AI component adaptively chooses both where the student is directed and what help they receive to optimize their learning. The end result is a fully integrated game system that can measure student performance using integrated tests, leveraging that information to adjust game content, address learner misconceptions, and lead to a faster and more effective learning session. As part of continued research, we present results from comparison testing of our educational game system in tandem with relevant course material.With our preliminary results, we focus on demonstrating the system's ability to provide appropriate content to players based on expert opinion. We show the educational utility of the game system, demonstrating an increase in student performance post-intervention on relevant content tests. We also show results from self-efficacy surveys administered to students to test their opinion of their own abilities. By sharing our testing and verification, we demonstrate the effectiveness of our intelligent educational game system.