Rasch Model Assessment for Bloom Digital Taxonomy Applications

Abstract

Assessment using Bloom’s taxonomy levels has evolved in a variety of contexts and uses. In the era of the COVID-19 pandemic, which necessitates use of online assessment, the need for teachers to use digital-based taxonomy skills or Bloom’s Digital Taxonomy (BDT) has increased even more. However, the existing studies on validity and reliability of BDT items are limited. To overcome this limitation, this study aims to test whether BDT has good psychometric characteristics as a teacher’s self-assessment tool using the Rasch model analysis and to investigate the pattern of BDT usage in teaching and learning. By using a quantitative online survey design, this study involves six levels of BDT, namely, Remembering, Understanding, Applying, Analyzing, Evaluating, and Creating. The questionnaire was developed and validated by two experts prior to administration. A stratified random sampling technique was conducted on 774 secondary teachers from five geographical zones in Malaysia, and the Rasch model was analyzed using WINSTEPS 3.71 software. The performances of items improved by Rasch psychometric assessment including the application of BDT among teachers. The hierarchy level was also assessed through graphical analysis, including the Wright map and bubble chart, to demonstrate the powerful performance of the Rasch model analysis in investigating item quality and reliability. Overall, these empirically validated items using the Rasch model could advance the academic knowledge of BDT for future assessment and promote the Rasch calibration in an educational setting.