A Study on Smart contract for efficient learner problem recommendation in distance education environment

Abstract

AbstractFor learner's self-directed distance education, the need for Problem Recommendation learning guidesreflecting accurate learning patterns based on learner data is increasing. In this paper, based onblockchain based smart contract technology, various learner data generated in the distance educationenvironment were collected and accurately managed to analyze Problem Recommendation patternsfor individual learners and gave weights for each learning situation. It is possible to present the optimalProblem Recommendation path when individual learners solve problems based on the assigned weightsfor each learning situation. To evaluate the performance of this study, the learning satisfaction with theexisting similar learning environment, the usefulness of the Problem Recommendation guide, and theprocessing speed of learner data were analyzed. As a result, compared to the existing learningenvironment, the proposed learning environment improved learning satisfaction by 19% or more, and itwas confirmed that the learning data processing speed was improved by more than 20%.