Coding theory is a major component of Applied Algebra. It has many applications in the mathematics of communications and has many links with other scientific disciplines, such as electrical engineering and computer science. Coding theory arises in almost every imaginable digital communications and storage system. In UCD, it is taught at the undergraduate level in the module MATH30180 An Introduction to Coding Theory.
Initiative
AI for Fairer Learning Journeys: Bridging Pre-Learning, In-Learning, Assessment and Feedback
About this initiative
This project will design, pilot and evaluate an AI-supported approach to reducing learning inequality in finance education. It focuses on four stages of the learning journey: pre-learning, in-learning, assessment and feedback.
Stage 1. Evidence and preparation
The project will start with a student-centred evidence phase. Student partners will survey students, faculty, and academic literature to identify the main barriers in finance education. These may include weak mathematical preparation, limited finance knowledge, unclear assessment expectations, limited feedback literacy and etc. This phase will also include a focused literature review on AI and education, answering three questions (1) how to measure inequality in education, which will be used in Stages 2 and 3; (2) what are main sources of inequality in finance education; and (3) why AI has the potential to address them.
Stage 2. Four AI-supported interventions
The project will develop and test four reusable interventions. For pre-learning, it will create a finance readiness diagnostic and feedback system. This system will identify students’ starting points and recommend preparation routes, including linking them to external resources and existing UCD supports (such as UCD math support centre). For in-learning, it will develop tools to help students unpack finance concepts, worked examples and common misconceptions. For assessment, it will improve test rubric literacy and marking-calibration by providing personalized explanations of rubric. For feedback, it will test tools that help make feedback clearer, more actionable and better matched to students’ learning needs.
Stage 3. Deliverables and outcomes
The project will produce a reusable toolkit for finance and business education to address inequality. It will also produce student-tested guidance, workshops for students and faculty, evaluation evidence and open educational resources. The findings will support dissemination within UCD and may also lead to publications on AI, finance education and educational inequality.
| Project Lead | Dr Chen Yang |
|---|---|
| College | UCD College of Business |
| School | UCD Michael Smurfit Graduate Business School |
Lead organisations
Affiliated organisations
Linked open educational resources
Contributors
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