University timetabling problems have been interested by many researchers for more than adecade. However, there is no appropriated solution or computation model available to solve these problemssuccessfully. This is because of many different version of timetabling problems. In this paper, a novalapproach of Genetic Algorithm (GA) for solving educational timetabling problem is proposed, including theconstraints statements, the definition of a hierarchical structure for the fitness function, and the generalizedgenetic operators, which can be applied to matrices representing timetables. The paper focuses on lecturingtimetables only, but not the examinational timetabling. The crossover rate and mutation rate were varied toconduct effective results and they shows that the given appropriate crossover rate of 50% and mutation rateof 50% is the best ratio to solve university timetabling problems.