<p>During the Covid-19 pandemic and mass disaster, universities have had to continue their courses with distance education. Internet servers in educational institutions slowed down for some periods, and courses could not be processed. The interruptions are due to the intensity of users on the servers and the internet congestion in the country during some time periods. For these reasons, the course time scheduling problem for distance education is discussed in this study. This study aims to balance the number of users in the system to prevent internet congestion. To solve the problem, two different mathematical models are developed. The first model obtains the balanced course scheduling for any time period. The second model is provided by the course assignment, considering internet congestion that occurred during any period. The proposed models were tested in a real case study dealing with the charting of courses offered in all departments of the engineering faculty of a university in Turkey. A problem-specific heuristic model is developed to solve the problem since a solution could not be obtained from the mathematical models in polynomial time due to the large size of the actual data set. The comparative results obtained from mathematical models and problem-specific heuristics are reported, and their performance is discussed. According to the comparative results, problem-specific heuristic outperforms mathematical models in obtaining a balanced schedule and solution time.</p>