Accessibility Skip to Global Navigation Skip to Local Navigation Skip to Content Skip to Search Skip to Site Map Menu

Ifeanyi G Ndukwe

Ifeanyi Glory Ndukwe imageAssistant Research Fellow

Room 2.15 (temporary office), Otago Business School
Email glory.ndukwe@otago.ac.nz

Background and interests

Ifeanyi G Ndukwe is an Assistant Research Fellow at the Science for Technological Innovation (SfTI) National Science Challenge group, working with Dr Sherlock Licorish. He obtained his PhD in Educational Technology and Artificial Intelligence in Education (AIED) from the University of Otago in New Zealand.

His current research focuses on developing code quality models for code snippets and using machine learning to predict code snippet quality. He is interested in machine learning, deep learning, data mining, natural language processing, and big data analytics. He has also used data science methods in his research, including qualitative forms of content analysis, social network analysis, sentiment analysis, data visualisation, and structural equation modelling.

^ Top of page

Publications

Shephard, K., Kalsoom, Q., Gupta, R., Probst, L., Gannon, P., Santhakumar, V., Ndukwe, I. G., & Jowett, T. (2021). Exploring the relationship between dispositions to think critically and sustainability concern in HESD. International Journal of Sustainability in Higher Education. Advance online publication. doi: 10.1108/IJSHE-07-2020-0251

Ndukwe, I. G. (2021). Teaching analytics and teacher dashboards to visualise SET data: Implications to theory and practice (PhD). University of Otago, Dunedin, New Zealand. Retrieved from http://hdl.handle.net/10523/10659

Nkomo, L. M., Ndukwe, I. G., & Daniel, B. K. (2020). Social network and sentiment analysis: Investigation of students' perspectives on lecture recording. IEEE Access, 8, 228693-228701. doi: 10.1109/ACCESS.2020.3044064

Ndukwe, I. G., Amadi, C. E., Nkomo, L. M., & Daniel, B. K. (2020). Automatic grading system using Sentence-BERT network. In I. I. Bittencourt, M. Cukurova, K. Muldner, R. Luckin & E. Millán (Eds.), Artificial Intelligence in Education (AIED): Lecture notes in artificial intelligence (Vol. 12164). (pp. 224-227). Cham, Switzerland: Springer. doi: 10.1007/978-3-030-52240-7_41

Ndukwe, I. G., & Daniel, B. K. (2020). Teaching analytics, value and tools for teacher data literacy: A systematic and tripartite approach. International Journal of Educational Technology in Higher Education, 17(1), 1-31. doi: 10.1186/s41239-020-00201-6

Ndukwe, I. G. & Daniel, B. (2018, August). Data science approach in education: Simulating student teaching evaluating data. Higher Education Development Centre, University of Otago, Dunedin, New Zealand. [Department Seminar].

Other Research Output

Shephard, K., Kalsoom, Q., Gupta, R., Probst, L., Gannon, P., Santhakumar, V., Ndukwe, I. G., & Jowett, T. (2021). Exploring the relationship between dispositions to think critically and sustainability concern in HESD. International Journal of Sustainability in Higher Education. Advance online publication. doi: 10.1108/IJSHE-07-2020-0251

Journal - Research Article

Ndukwe, I. G., & Daniel, B. K. (2020). Teaching analytics, value and tools for teacher data literacy: A systematic and tripartite approach. International Journal of Educational Technology in Higher Education, 17(1), 1-31. doi: 10.1186/s41239-020-00201-6

Journal - Research Article

Nkomo, L. M., Ndukwe, I. G., & Daniel, B. K. (2020). Social network and sentiment analysis: Investigation of students' perspectives on lecture recording. IEEE Access, 8, 228693-228701. doi: 10.1109/ACCESS.2020.3044064

Journal - Research Article

Ndukwe, I. G., Daniel, B. K., & Butson, R. J. (2018). Data science approach for simulating educational data: Towards the development of teaching outcome model (TOM). Big Data & Cognitive Computing, 2(3), 24. doi: 10.3390/bdcc2030024

Journal - Research Article

Ndukwe, I. G., Amadi, C. E., Nkomo, L. M., & Daniel, B. K. (2020). Automatic grading system using Sentence-BERT network. In I. I. Bittencourt, M. Cukurova, K. Muldner, R. Luckin & E. Millán (Eds.), Artificial Intelligence in Education (AIED): Lecture notes in artificial intelligence (Vol. 12164). (pp. 224-227). Cham, Switzerland: Springer. doi: 10.1007/978-3-030-52240-7_41

Conference Contribution - Published proceedings: Full paper

Ndukwe, I. G., Daniel, B. K., & Amadi, C. E. (2019). A machine learning grading system using chatbots. In S. Isotani, E. Millán, A. Ogan, P. Hastings, B. McLaren & R. Luckin (Eds.), Artificial Intelligence in Education (AIED): Lecture notes in computer science (Vol. 11626). (pp. 365-368). Cham, Switzerland: Springer. doi: 10.1007/978-3-030-23207-8_67

Conference Contribution - Published proceedings: Full paper

Ndukwe, I. G. (2021). Teaching analytics and teacher dashboards to visualise SET data: Implications to theory and practice (PhD). University of Otago, Dunedin, New Zealand. Retrieved from http://hdl.handle.net/10523/10659

Awarded Doctoral Degree

More publications...