Role
Dr. Elaine Chen is a Senior Lecturer in Business Analytics and Course Leader for the MSc Business Analytics and Artificial Intelligence. Elaine teaches across business analytics and artificial intelligence, covering both the technical foundations and the practical applications of these subjects. Their teaching emphasises how data and AI technologies can be applied to support decision-making and strategy in real-world contexts. Elaine also has a strong interest in pedagogy projects, particularly in designing and delivering modules in business analytics and AI that are accessible and engaging for students from diverse backgrounds.
Elaine’s research focuses on the ways individuals and organisations engage with data and digital technologies in both education and business. In higher education, this includes investigating student use of generative AI and the ways educators are incorporating these tools into teaching and learning. In the business domain, Elaine examines how small and medium-sized enterprises (SMEs) can leverage AI to enhance efficiency, support decision-making, and improve competitiveness. Elaine also supervises PhD students in related areas, including AI in higher education, human–AI collaboration, and workforce analytics.
Career overview
Elaine started her career as an automation engineer in the industrial sector for Intel Corporation before joining the academic sector as a lecturer. Before joining NTU, Elaine worked as a lecturer in the School of Computing Science and Digital Media at Robert Gordon University.
Elaine holds a PhD in Computing Science, an MSc in Business Information Technology, a Postgraduate Certificate in Academic Practice, and a BTech (Hons) in Business Information Systems. Elaine is also a Senior Fellow of the Higher Education Academy (HEA), a recognition of sustained impact on teaching and learning and leadership in higher education practice.
Research areas
- Innovative pedagogies for data and AI in business education
- Human–AI collaboration in higher education
- Generative AI and the future of business education
- AI-Driven talent management and workforce analytics
- AI in small and medium-sized enterprise (SMEs)
- Natural language processing for decision support
- Sentiment-aware recommender systems
Publications
Selected Publications
- Buglear, J., & Chen, E. (2025). Stats Means Business: Statistics and Business Analytics for Business, Hospitality and Tourism (4th ed.). Routledge.
- He, Y., Chen, E. and Fletcher, R., 2025. Exploring generative AI in learning: neurodivergent and disabled students' voices in higher education. AIED 2025.
- Clos, J. and Chen, Y.Y., 2024. Investigating the impact of generative AI on students and educators: Evidence and insights from the literature. In Proceedings of the Second International Symposium on Trustworthy Autonomous Systems (pp.1-6).
- Chen, Elaine and Qin, Zhenxin, "Developing AI Literacy of Management Students using Problem and Project based Learning" (2023). AMCIS 2023 Proceedings. 13
- Chen, Y. Y., Wiratunga, N. and Lothian, R. (2017). Effective Dependency Rule-based Aspect Extraction for Social Recommender Systems. In Pacific Asia Conference on Information Systems. Association for Information Systems (AIS).
- Chen, Y.Y., Ferrer, X., Wiratunga, N. and Plaza, E., 2015. ’Aspect Selection for Social Recommender Systems’, In International Conference on Case-Based Reasoning (pp. 60-72). Springer International Publishing.
- Chen, Y.Y., Ferrer, X., Wiratunga, N. and Plaza, E., 2014. ’Sentiment and preference guided social recommendation’, In International Conference on Case-Based Reasoning (pp. 79-94). Springer International Publishing.
- Ferrer, X., Chen, Y.Y., Wiratunga, N. and Plaza, E., 2014. ’Preference and Sentiment Guided Social Recommendations with Temporal Dynamics’, In Re-search and Development in Intelligent Systems XXXI (pp. 101-116). Springer International Publishing.
- Chen, Y. Y., Yong, S. P., and Ishak, A., 2014. ’Email Hoax Detection System Using Levenshtein Distance Method’, Journal of Computers, 9(2), pp.441-446