As the world faces the impact of big data, calligraphy education in colleges and universities also faces opportunities and challenges. This paper proposes the intelligent evaluation technology of calligraphic works and the intelligent interaction technology of calligraphic works as the cultural inheritance strategy in calligraphy education. The tracking algorithm combining Faster R-CNN and KCF is used to get the calligraphic writing trajectory, calculate the difference characteristics between the movement trajectory of the brush and the model, and make regression predictions on the copying scores through the regression model to get the intelligent scores of the calligraphic works. The model of rice paper, brush, ink, and particle diffusion is established to realize GPU-accelerated real-time drawing process for calligraphy works, and the interaction system is built based on the Cocos2DX framework. Taking 120 first-year students majoring in Chinese language and culture at the University of Q as research subjects, we conducted a study on the cultural inheritance of calligraphy education. The mean value of comprehensive ability in calligraphy learning of students in the experimental class was about 4.48, which was higher than that of the control class by 1.035. Among the positive psychological qualities in calligraphy learning, the mean values of psychological dimensions of the experimental class were generally higher than those of the control class, which showed a significant difference (P<0.05). For the evaluation of intuition and interest in calligraphy teaching methods, the experimental class evaluated the mean values of 4.17 and 4.28, which were higher than those of the control class of 1.1 and 1.82.