  Contributions: Prior studies on education have mostly followed the model of
the cross sectional study, namely, examining the pretest and the posttest
scores. This paper shows that students' knowledge throughout the intervention
can be estimated by time series analysis using a hidden Markov model.
Background: Analyzing time series and the interaction between the students and
the game data can result in valuable information that cannot be gained by only
cross sectional studies of the exams. Research Questions: Can a hidden Markov
model be used to analyze the educational games? Can a hidden Markov model be
used to make a prediction of the students' performance? Methodology: The study
was conducted on (N=854) students who played the Save Patch game. Students were
divided into class 1 and class 2. Class 1 students are those who scored lower
in the test than class 2 students. The analysis is done by choosing various
features of the game as the observations. Findings: The state trajectories can
predict the students' performance accurately for both class 1 and class 2.
