Research for smart contract-based problem recommendation algorithm

Abstract

As a method for learners to learn independently in distance education, the need for a problem recommendation learning guide that effectively reflects a learning pattern based on learner data is increasing. In this paper, based on blockchain Ethereum smart contract technology, we analyze and present problem recommendation patterns for individual learners by filtering, collecting, and transparently managing multiple learner data that can occur in a distance education environment. In this study, various weighting factors were assigned to each learning situation. The optimal problem recommendation path is presented so that learners can solve problems based on weight-based learning factors in various learning situations. For the performance evaluation of this study, a similar learning environment was set up, and learning satisfaction, usefulness of problem recommendation guides, and learner data processing speed were analyzed. As a result of the performance evaluation, it was confirmed that the learning satisfaction improved by more than 15% compared to the existing learning environment in the proposed environment. In addition, it was confirmed that the learning data processing speed was improved by more than 17%.