Dr Kate Han K.Han3@salford.ac.uk
Lecturer
Dr Kate Han K.Han3@salford.ac.uk
Lecturer
Dr Kate Han K.Han3@salford.ac.uk
Other
In today's evolving business landscape, professionals are required to possess a broad skill set, encompassing fundamental business knowledge and digital proficiencies. This heightened demand for diverse technical skills has raised the learning bar for current business students. Concurrently, educators in business schools must excel in multiple disciplines and effectively convey complex ideas to students in an accessible yet valuable manner. In this project, we proposed a Generative AI-assisted lifelong learning approach. Our ongoing research includes two preliminary case studies that blend Inquiry-Based Learning (IBL) with AI assistance. One case study focuses on undergraduate website development, while the other explores Python in a postgraduate module at Salford Business School. This module targets students seeking to efficiently acquire both business acumen and coding skills. The primary goal is to establish a strong coding foundation while guiding students in developing lifelong learning habits using Generative AI tools.
Han, K. (2024). Generative AI assisted Life-long Learning in Higher Education: A Case Study of Coding Learning for Business Students at Salford Business School. In Leading Global Excellence in Pedagogy: Augmenting Teaching Excellence: Embracing the future of Education with AI and Emerging Technologies. IFNTF Publishing
Online Publication Date | Apr 18, 2024 |
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Publication Date | Apr 18, 2024 |
Deposit Date | Jan 10, 2025 |
Book Title | Leading Global Excellence in Pedagogy: Augmenting Teaching Excellence: Embracing the future of Education with AI and Emerging Technologies |
Publisher URL | https://www.amazon.co.uk/Leading-Global-Excellence-Pedagogy-Technologies-ebook/dp/B0D279S8R8 |
Optimising Public Transport Through the Integration of Micro and Macro-level Simulations
(2025)
Presentation / Conference Contribution
Automating Business Process to Enhance Organisational Efficiency and Productivity: Using Academic Intervention at Salford Business School as a Case Study
(2025)
Presentation / Conference Contribution
A Novel Surrogate Model for Variable-Length Encoding and its Application in Optimising Deep Learning Architecture
(2024)
Presentation / Conference Contribution
VISTA: A Variable Length Genetic Algorithm and LSTM-Based Surrogate Assisted Ensemble Selection algorithm in Multiple Layers Ensemble System
(2024)
Presentation / Conference Contribution
About USIR
Administrator e-mail: library-research@salford.ac.uk
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