Understanding Attitudes Towards Blockchain-Based Assessment System: A Sentiment Analysis of Form Six Teachers' Views

Abstract

Form six students are now using School Base Assessment (SBA) with paper projects to prepare for university-level learning. Although teachers are encouraged to use technology to enhance the learning process, their sentiment about using technology in educational assessment is still unknown. This study used Sentiment Analysis (SA) to analyze Form six teachers' opinions on using new technology to manage SBA. The study found that Microsoft Azure Machine Learning can effectively build SA models for data analytics based on teachers' opinions obtained from a Telegram group of form six teachers in Pahang. The results showed that most teachers have a neutral sentiment with a moderate amount of positive sentiment and some negative sentiment present. The overall sentiment is slightly positive, but "workload" is a prominent concern among Form six teachers when working with technology in their SBA process.