Research on Education Text Analysis and Teaching Best Practice
Text Analysis for Education
Detecting Hate Speech Online Using Machine Learning Models
The detection of offensive and hate speech online is challenging but crucial. A new study compares the challenge posed in the context of both majority and minority languages, using existing Machine Learning models.
David Griffin
Using Machine Learning for Automated Language Analysis
A recently published paper has outlined how AI automated text analysis may be used in a range of applications, from gauging public opinion to comparing subjective human experiences.
Definitions of Fairness in Machine Learning Explained Through Examples
Designating an algorithm as ‘fair’ is a challenging and complex task. A recently published paper explores the many and varied definitions of fairness used in machine learning.
Improving Functionality and Reducing Bias in Natural Language Processing Systems.
Machine learning-based language systems should be fair and unbiased. To ensure this, robust testing is needed. A recently published paper has proposed a novel test procedure and a detailed framework for its implementation.
The Best Text Analysis Software for Education
If you are considering doing manual text analysis at your institution and don't need automated labelling or sector benchmarking what is the best text analysis software for education?
Stuart Grey
Module Evaluation, Likability and The Case For Free-Text Comments
From the paper: The student evaluation of teaching and likability: what the evaluations actually measure
Halo Effects in the Student Voice: Unwanted Correlations
From the paper: Quantifying halo effects in students’ evaluation of teaching. We look at how correlated questions become less useful in student voice surveys
Gender Stereotypes in the Text of Teaching Excellence Submissions
From the paper: Gender stereotyping in student perceptions of teaching excellence: applying the shifting standards theory
Lexicon and Software Choice in Education Text Analysis
From the paper: Making sense of student feedback using text analysis – adapting and expanding a common lexicon
