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