  We provide ongoing results from the development of a personalized learning
system integrated into a serious game. Given limited instructor resources, the
use of computerized systems to help tutor students offers a way to provide
higher quality education and to improve educational efficacy. Personalized
learning systems like the one proposed in this paper offer an accessible
solution. Furthermore, by combining such a system with a serious game, students
are further engaged in interacting with the system. The proposed learning
system combines expert-driven structure and lesson planning with computational
intelligence methods and gamification to provide students with a fun and
educational experience. As the project is ongoing from past years, numerous
design iterations have been made on the system based on feedback from students
and classroom observations. Using computational intelligence, the system
adaptively provides support to students based on data collected from both their
in-game actions and by estimating their emotional state from webcam images. For
our evaluation, we focus on student data gathered from in-classroom testing in
relevant courses, with both educational efficacy, results and student
observations. To demonstrate the effect of our proposed system, students in an
early electrical engineering course were instructed to interact with the system
in place of a standard lab assignment. The system would then measure and help
them improve their background knowledge before allowing them to complete the
lab assignment. As they played through the game, we observed their interactions
with the system to gather insights for future work. Additionally, we
demonstrate the system's educational efficacy through pre-post-test results
from students who played the game with and without the personalized learning
system.
