In order to evaluate students’ concentration in offline education, an algorithm based on fuzzy comprehensive evaluation is proposed. The algorithm evaluates students’ concentration by measuring their head attitude angle, which consists of three modules: face key points detection, head attitude angle measurement and concentration decision, and outputs the curve of students’ overall concentration score over time. Compared with other concentration evaluation methods, the proposed algorithm achieves the evaluation of overall students’ concentration under low pixel video and is suitable for most offline classrooms with monitoring devices. The overall functional effectiveness of the algorithm was tested with a classroom video dataset of 35 students. The algorithm outputs students’ concentration scores at 30 FPS, meeting the requirement of a real-time classroom. The algorithm’s scores were compared to the artificial scores of 15 experts, resulting in an average accuracy of 88.3% and a Pearson’s correlation coefficient of 0.936 between the two, thus validating the effectiveness of the algorithm. The proposed algorithm can provide educators with a reference for educational effectiveness and help to realize the automatic assessment of educational quality in the future.