The automated classification of examination questions based on Bloom's Taxonomy (BT)
aims to assist the question setters so that high-quality question papers are produced. Most …

Watermarks should be introduced in the natural language outputs of AI systems in order to
maintain the distinction between human and machine-generated text. The ethical imperative …

Learning objectives, especially those well defined by applying Bloom's taxonomy for
Cognitive Objectives, have been widely recognized as important in various teaching and …

In recent years, there has been a lot of focus on Bloom's taxonomy-based classification of E-
Learning materials. Researchers employ different methods and features. In our previous …

The quality of student-generated questions in computer-supported collaborative learning
(CSCL) plays a pivotal role in determining the overall effectiveness of CSCL experiences …

Examination is one of the common ways to evaluate the students' cognitive levels in higher
education institutions. Exam questions are labeled manually by educators in accordance …

The programme outcomes are broad statements of knowledge, skills, and competencies that
the students should be able to demonstrate upon graduation from a programme, while the …

Term weighting in text classification plays a crucial role in determining the accuracy of text
classifiers based on supervised machine-learning techniques. Similarly, its importance in …

Subjective exams and tests have been a staple metric of student evaluation. These tests
require students to give brief theoretical responses to the questions. Evaluation of subjective …

Human users tend to selectively ignore information that contradicts their pre-existing beliefs
or opinions in their process of information seeking. These “self-imposed filter bubbles”(SFB) …