Automation of developing adaptive e-learning using blockchain technology

Abstract

The low percentage of completion of online courses in the framework of the modern mass online education may be related to the lack of adaptation for a specific user of an online course of a learning path unifying all the stu-dents. The solution to the problem can be adaptive learning, which modifies the learning process for different students depending on their characteristics and learning conditions. The purpose of the study is to automate the process of developing adaptive e-learning by using the blockchain technology. The results of a study, in which adaptive learning was organized on the basis of the Felder-Silverman learning styles model was used as input data for the experiment. Applying the mechanism of smart contracts, the blockchain technology registered learning events, which made it possible to determine the learning style of users directly during the learning process. The chosen model of learning styles, as well as the number of categories of students, were configured exclusively in the smart contract code, which made it possible to talk about the universality and scalability of the process of organizing adaptive e-learning using the blockchain. The technology also ensured the reliability of data storage and traceability. It documents heterogeneous data in a single storage space adding a timemarker and the author's address to each recorded event. The proposed method also unifies the organization of adaptive e-learning, since it is suitable for different models of learning styles with different parameters. The automated process does not require the development of preliminary tests and is free from biased assessments from the students in the learning course