Task Complexity Classifier using Transformer-based NLP model based on Bloom's Taxonomy

Bloom's Taxonomy Question Classifier: A versatile tool for educators to categorize questions by cognitive complexity, aiding in assessment design and fostering diverse thinking skills in students.

The Dynamic Test Paper Generator using Bloom's Taxonomy is a Streamlit-based application that helps educators create customized test papers. By inputting subject details, syllabus, and example questions, users can generate multiple-choice, short answer, and long answer questions.

Developing a feedback theory-informed natural language processing (NLP) model to enable large-scale evaluation of written feedback, and analysing a large set of feedback extracted from Moodle using this model to understand the presence of student-centred feedback elements, the commonality and differences in feedback provision across disciplines.