Abstract

It is a common practice to issue a summary of a learner’s learning achievements in form of a transcript or certificate. However, detailed information on the depth of learning and how learning or teachings were conducted is not present in the transcript of scores. This work presents the first practical implementation of a new platform for keeping track of learning achievements beyond transcripts and certificates. This is achieved by maintaining digital hashes of learning activities and managing access rights through the use of smart contracts on the blockchain. The blockchain of learning logs (BOLL) is a platform that enable learners to move their learning records from one institution to another in a secure and verifiable format. This primarily solves the cold-start problem faced by learning data analytic platforms when trying to offer personalized experience to new learners. BOLL enables existing learning data analytic platforms to access the learning logs from other institutions with the permission of the learners and/or institution who originally have ownership of the logs. The main contribution of this paper is to investigate how learning records could be connected across institutions using BOLL. We present an overview of how the implementation has been carried out, discuss resource requirements, and compare the advantages BOLL has over other similar tools.

Highlights

  • Big data has revolutionized many areas of business ranging from search companies to ecommerce, where insights from data have driven personalization, targeted advertising, improved services, and overall business growth

  • We show that it is possible to achieve a privacy-preserving lifelong learning log using the blockchain with defined smart contracts, discuss resource requirements, and the benefits of our proposed system

  • System design We propose a blockchain of learning logs (BOLL): a blockchain platform that connects the learning logs of students across the different institutions they have attended on a single, (2019) 14:4

Read more

Summary

Introduction

Big data has revolutionized many areas of business ranging from search companies to ecommerce, where insights from data have driven personalization, targeted advertising, improved services, and overall business growth. Similar success has not yet been achieved in the field of education technology, and the use of data-driven education in the field is still lagging behind (Siemens and Long 2011). One of the key challenges in this area is the lack of data continuity. When students change from one institution to another, their learning data remains largely immobile, such as the usual progression from elementary, junior-high, and high school. As institutes maintain separate Learning Record Stores (LRSs) which are not connected to one another, this results in the learning data that was collected at previous institutes not being available for analysis at current or future institutes. The situation causes a typical cold-start problem, where the current institution’s learning environment does not have sufficient data for effective personalization or adaptation when the learner is first enrolled.

Methods
Findings
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call