Research on recommendation mechanism based on metabolism computing for online learning

In view of the characteristics of online learning during the epidemic, this paper researches the recommendation mechanism about online learning content. According to the operation mechanism of each metabolic operator in artificial metabolic algorithm, the recommended content can be adjusted. Under the action of metabolic operators, the integrity, appropriateness and sustainability of recommended content can be guaranteed. By analyzing the learners’ work state and learning result, the recommendation mechanism can be improved by information feedback. So that learners can obtain customized learning experience and obtain learning effect not less than offline learning. The example analysis shows the effectiveness of the recommendation mechanism.