Search Results for author:
Found 17 papers, 5 papers with code
Auditing Large Language Models for Enhanced Text-Based Stereotype Detection and Probing-Based Bias Evaluation
Recent advancements in Large Language Models (LLMs) have significantly increased their presence in human-facing Artificial Intelligence (AI) applications.
A Toolbox for Modelling Engagement with Educational Videos
With the advancement and utility of Artificial Intelligence (AI), personalising education to a global population could be a cornerstone of new educational systems in the future.
Towards Auditing Large Language Models: Improving Text-based Stereotype Detection
In summary, our work establishes a robust and practical framework for auditing and evaluating the stereotypic bias in LLM.
TrueLearn: A Python Library for Personalised Informational Recommendations with (Implicit) Feedback
This work describes the TrueLearn Python library, which contains a family of online learning Bayesian models for building educational (or more generally, informational) recommendation systems.
Scalable Educational Question Generation with Pre-trained Language Models
We develop \textit{EduQG}, a novel educational question generation model built by adapting a large language model.
Pre-Training With Scientific Text Improves Educational Question Generation
With the boom of digital educational materials and scalable e-learning systems, the potential for realising AI-assisted personalised learning has skyrocketed.
Towards Proactive Information Retrieval in Noisy Text with Wikipedia Concepts
Extracting useful information from the user history to clearly understand informational needs is a crucial feature of a proactive information retrieval system.
Can Population-based Engagement Improve Personalisation? A Novel Dataset and Experiments
This work explores how population-based engagement prediction can address cold-start at scale in large learning resource collections.
Watch Less and Uncover More: Could Navigation Tools Help Users Search and Explore Videos?
The user questionnaire revealed that participants found the Content Flow Bar helpful and enjoyable for finding relevant information in videos.
Semantic TrueLearn: Using Semantic Knowledge Graphs in Recommendation Systems
In informational recommenders, many challenges arise from the need to handle the semantic and hierarchical structure between knowledge areas.
Could AI Democratise Education? Socio-Technical Imaginaries of an EdTech Revolution
Artificial Intelligence (AI) in Education has been said to have the potential for building more personalised curricula, as well as democratising education worldwide and creating a Renaissance of new ways of teaching and learning.
An AI-based Learning Companion Promoting Lifelong Learning Opportunities for All
Artifical Intelligence (AI) in Education has great potential for building more personalised curricula, as well as democratising education worldwide and creating a Renaissance of new ways of teaching and learning.
PEEK: A Large Dataset of Learner Engagement with Educational Videos
One of the main challenges in advancing this research direction is the scarcity of large, publicly available datasets.
VLEngagement: A Dataset of Scientific Video Lectures for Evaluating Population-based Engagement
This paper introduces VLEngagement, a novel dataset that consists of content-based and video-specific features extracted from publicly available scientific video lectures and several metrics related to user engagement.
Predicting Engagement in Video Lectures
The explosion of Open Educational Resources (OERs) in the recent years creates the demand for scalable, automatic approaches to process and evaluate OERs, with the end goal of identifying and recommending the most suitable educational materials for learners.
Towards an Integrative Educational Recommender for Lifelong Learners
One of the most ambitious use cases of computer-assisted learning is to build a recommendation system for lifelong learning.
TrueLearn: A Family of Bayesian Algorithms to Match Lifelong Learners to Open Educational Resources
The recent advances in computer-assisted learning systems and the availability of open educational resources today promise a pathway to providing cost-efficient, high-quality education to large masses of learners.
