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Lesson Planning of Smart Classroom Based on Genetic Algorithm

Smart classrooms with smart devices and AI applications increase the efficiency of course study. However, smart lesson planning is a time-consuming and confusing task for teachers. Thus, a lesson planning algorithm based on a genetic algorithm is proposed for promising lesson plans. Teaching activities, such as lectures, exercises, and classroom questioning are modeled as an event sequence to form a lesson plan. The mastery degree of students is selected as the fitness function of the genetic algorithm, and the estimated attention degree is calculated. Crossover and mutation genetic operators are designed for lesson planning. The algorithm is tested and optimal solutions or suboptimal solutions are found.