The Intelligent Civics can be defined as a hypothetical path towards the modernization of ideological and political education in the age of artificial intelligence. Thus, the intelligent transformation of Civics teaching in higher education institutions has become one of the key issues in the realm of educational discussion. This study claims that in the digital age when students learn using the digital education environment, traditional methods of deep knowledge tracing fail to reflect their behavioral traits. In order to compensate for the above deficiency, the improved deep knowledge tracing approach which incorporates corrections alongside behavioral features has been suggested, and referred to in English as the DKT-Correcting model. By incorporating it into the learning platform, the educators will be able to track in real time the degree to which students understand the material, help them fill any potential learning gaps, pace the lessons in accordance with their needs, and gradually develop a customized intelligent tutoring system for the intelligent upgrade of Civics instruction in colleges and universities of the digital era. The DKT-Correcting model was used in order to measure the level of mastery of knowledge points by students in the Civics and Political Science class. With regard to knowledge point M2, out of 100 participants, 20 students failed to master the topic (20%), while 65 showed partial mastery (65%), with only 15% mastering it fully. The results suggest that the introduced DKT-Correcting model positively affects the process of intelligent transformation of Civics and Political Science teaching in higher education institutions.
