This demo presents automatic scoring of descriptive answers written on electronic paper for Japanese, English, and math drills. We used DNN-based online and offline handwriting recognizers for each subject and took simple perfect matching of recognized candidates with correct answers. The experiment on primary school students shows that the False Negative rate is reduced by combining the online and offline recognizers and the False Positive rate is reduced by rejecting low recognition scores. Even with the current system, human scorers only need to manually score less than 30% of the answers, with false positive (risky) scores of about 2% or less for the three subjects.