WSEAS Transactions on Information Science and Applications
Print ISSN: 1790-0832, E-ISSN: 2224-3402
Volume 22, 2025
Revolutionizing Educational Assessment Using Bloom’s Taxonomy Bot
Authors: , , , ,
Abstract: The authors provide a transformative solution to address prevalent challenges in educational assessment
in this research work. These challenges include aligning examination papers with syllabi, framing question papers
to cover all Bloom’s Levels, and upgrading Bloom’s Levels by re-framing questions. Bloom’s Taxonomy (BT) is
a cognitive level-based framework for understanding students’ educational progress through the assessment. The
educational assessment method is the foundation for our chatbot, Bloomify. It is designed to revolutionize the
assessment and help the keen educationists in three key scenarios. In the first scenario, mostly the educationists are
not able to reflect the all the course outcomes of the subject. Bloomify will help them to design the question paper
to cover all the course outcomes mapped with Bloom’s levels (BL). Second, often in a hurry, juggling between
students’ assessment and institution’s accreditation tasks, the educationists fail to balance the question papers
with all BLs covered. Bloomify will overcome the human fatigue and exhaustion associated with the manual
creation of balanced question papers. In the third scenario, it is observed that many of the universities use of
taxonomies and hence fail to design the assessment for the cognitive development of the students. Bloomify helps
the universities that lack taxonomy or use alternative taxonomies, and offers a Bloom’s approach for assessing
student development. Further, authors define a Bloom’s Score (BS) to find the average cognitive level of a question
paper. BS will help to focus on specific cognitive level of an assessment. For example, the assessment for
the graduate students can be defined with BS of 5 or 6 indicating higher Bloom’s levels: evaluate and create.
Bloomify automates the calculation of Bloom’s scores ensuring coverage of all the cognitive levels. This will help
the educationists in question paper creation process, saving time and effort. Bloomify includes three features:
1. Question classification 2. Suggestion of BL, and 3. Generation of entire question paper based on specific
criteria like the syllabus, marking scheme, and desired average Bloom’s score. Bloomify provides a user-friendly
interface, ensuring seamless integration with the assessment creation process. Bloomify enhances educational
assessment by addressing all cognitive levels, ensuring critical thinking in students. It supports the educationists’
efforts to design an assessment focusing on knowledge application, analysis, evaluation, and creation, aligning
with the real-world demands. The effectiveness of Bloomify is gauged by allowing different educationists to
use this chatbot and calculating the Mean Opinion Score (MoS). Bloomify received scores of 9, 9.5, and 8 for
classification, suggestion, and generation features, respectively from the educators of the authors’ institute.
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Keywords: Educational Assessment, Cognitive Skills, Large Language Models (LLMs), Bloom’s Taxonomy,
Chatbots, Cognitive Assessment
Pages: 593-603
DOI: 10.37394/23209.2025.22.49