Towards an Operational Responsible AI Framework for Learning Analytics in Higher Education
Project Overview
The document examines the growing use of Artificial Intelligence (AI) in higher education, with a specific focus on Learning Analytics (LA) and Predictive Learning Analytics (PLA) to improve student success outcomes. It addresses the ethical issues linked to these technologies, including concerns about algorithmic bias and transparency. To tackle these challenges, the authors introduce a Responsible AI framework designed for LA in educational settings, which prioritizes principles such as fairness, accountability, and transparency. This framework seeks to guide educational institutions in implementing ethical AI practices effectively, thereby promoting responsible use of AI technologies while enhancing the educational experience. Through these insights, the document underscores the importance of balancing technological advancement with ethical considerations in the pursuit of improved learning outcomes.
Key Applications
Learning Analytics systems and Predictive Learning Analytics
Context: Higher Education Institutions (HEIs) targeting both educators and students.
Implementation: Adoption of data-driven strategies to identify at-risk students, personalize learning, and enhance decision-making through a Responsible AI framework.
Outcomes: Improved identification of at-risk students, personalized learning experiences, and enhanced teacher support.
Challenges: Ethical concerns related to algorithmic bias, lack of transparency in decision-making, and potential misuse of student data.
Implementation Barriers
Ethical and Operational barrier
Concerns about bias in AI systems affecting the equitable support for minority students, along with a lack of practical guidance for HEIs on how to operationalize ethical principles in AI systems.
Proposed Solutions: Development of Responsible AI frameworks that include principles of fairness, transparency, and accountability, as well as the creation of tailored frameworks that provide actionable items for HEIs to integrate ethical practices.
Project Team
Alba Morales Tirado
Researcher
Paul Mulholland
Researcher
Miriam Fernandez
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Alba Morales Tirado, Paul Mulholland, Miriam Fernandez
Source Publication: View Original PaperLink opens in a new window
Project Contact: Dr. Jianhua Yang
LLM Model Version: gpt-4o-mini-2024-07-18
Analysis Provider: Openai