Outputs (92)

Scaling up and automating formative assessment in computer science (2025)
Book Chapter
Gordon, N. (2025). Scaling up and automating formative assessment in computer science. In S. Elkington, & A. Irons (Eds.), Formative Assessment and Feedback in Post-Digital Learning Environments: Disciplinary Case Studies in Higher Education (172-178). Routledge. https://doi.org/10.4324/9781003360254-22

The rise in student numbers in computer science creates a challenge for delivery. Computer science has some of the worst attainment and retention profiles across subjects. Given its technology focus, it is a subject where digital technologies have lo... Read More about Scaling up and automating formative assessment in computer science.

Comprehensive Health Tracking Through Machine Learning and Wearable Technology (2025)
Journal Article
Yusuf, A., Jaber, T. A., & Gordon, N. (online). Comprehensive Health Tracking Through Machine Learning and Wearable Technology. Journal of Data Science and Intelligent Systems, https://doi.org/10.47852/bonviewjdsis52023588

The accurate interpretation of data from wearable devices is paramount in advancing personalized healthcare and disease prevention. This study explores the application of machine learning techniques to improve the interpretation of health metrics fro... Read More about Comprehensive Health Tracking Through Machine Learning and Wearable Technology.

Evaluating and implementing machine learning models for personalised mobile health app recommendations (2025)
Journal Article
Morenigbade, H., Al Jaber, T., Gordon, N., & Eke, G. (2025). Evaluating and implementing machine learning models for personalised mobile health app recommendations. PLoS ONE, 20(3 March), Article e0319828. https://doi.org/10.1371/journal.pone.0319828

This paper focuses on the evaluation and recommendation of healthcare applications in the mHealth field. The increase in the use of health applications, supported by an expanding mHealth market, highlights the importance of this research. In this stu... Read More about Evaluating and implementing machine learning models for personalised mobile health app recommendations.

Teaching and Assessing at Scale: The Use of Objective Rubrics and Structured Feedback Teaching and Assessing at Scale: The Use of Objective Rubrics and Structured Feedback (2024)
Journal Article
Grey, S., & Gordon, N. (2024). Teaching and Assessing at Scale: The Use of Objective Rubrics and Structured Feedback Teaching and Assessing at Scale: The Use of Objective Rubrics and Structured Feedback. New Directions in the Teaching of Physical Sciences, 19(1), 1-9. https://doi.org/10.29311/ndtns.vi19.4103

It is widely recognised that feedback is an important part of learning: effective feedback should result in a meaningful change in student behaviour (Morris et al., 2021). However, individual feedback takes time to produce, and for large cohorts-typi... Read More about Teaching and Assessing at Scale: The Use of Objective Rubrics and Structured Feedback Teaching and Assessing at Scale: The Use of Objective Rubrics and Structured Feedback.

Computing for Social Good in Education (2024)
Journal Article
Ellis, H., Hislop, G. W., Goldweber, M., Rebelsky, S., Pearce, J., Ordonez, P., Pias, M., & Gordon, N. (2024). Computing for Social Good in Education. ACM Inroads, 15(4), 47-57. https://doi.org/10.1145/3699719

Computing for Social Good in Education (CSG-Ed) engages students with the positive potential of computing to benefit society. It can introduce students to aspects of professional responsibility, something computing students need more than ever given... Read More about Computing for Social Good in Education.

Artificial Intelligence in Education: An automatic Rule-Based Chatbot to generate guidance from lecture recordings (2024)
Journal Article
Hing, W., Gordon, N., & Al Jaber, T. (2024). Artificial Intelligence in Education: An automatic Rule-Based Chatbot to generate guidance from lecture recordings. Acta Scientific Computer Sciences, 6(7), 64-74

In a new era of educational and research-based chatbots, implementing personalised interactive learning resources is critical in enhancing students' academic experiences. Whilst general purpose chatbots are now available with a range of platforms, th... Read More about Artificial Intelligence in Education: An automatic Rule-Based Chatbot to generate guidance from lecture recordings.

Application of Artificial Intelligence and Data Science in Detecting the Impact of Usability from Evaluation of Mobile Health Applications (2024)
Journal Article
Kayode, O., Al Jaber, T., & Gordon, N. (2024). Application of Artificial Intelligence and Data Science in Detecting the Impact of Usability from Evaluation of Mobile Health Applications. International Journal on Engineering Technologies and Informatics, 5(1), 1-9. https://doi.org/10.51626/ijeti.2024.05.00070

Mobile health (mHealth) applications have demonstrated immense potential for facilitating preventative care and disease management through intuitive platforms. However, realizing transformational health objectives relies on creating accessible tools... Read More about Application of Artificial Intelligence and Data Science in Detecting the Impact of Usability from Evaluation of Mobile Health Applications.

Improving Rice Yield Prediction Accuracy Using Regression Models with Climate Data (2024)
Presentation / Conference Contribution
Mohamad Mohsin, M. F., Umana, M. K., Hassan, M. G., Sharif, K. I. M., Ismail, M. A., Salleh, K., Zahari, S. M., Sarmani, M. A., & Gordon, N. Improving Rice Yield Prediction Accuracy Using Regression Models with Climate Data. Presented at International Conference on Computing and Informatics 2023, Kuala Lumpur, Malaysia

Rice production is critical to food security, and accurate yield predictions are required for planning and decision-making. However, precisely predicting rice yields using machine learning models can be difficult due to the complicated interactions o... Read More about Improving Rice Yield Prediction Accuracy Using Regression Models with Climate Data.

Fairness, Bias, and Ethics in AI: Exploring the Factors Affecting Student Performance (2024)
Journal Article
Omughelli, D., Gordon, N., & Al Jaber, T. (2024). Fairness, Bias, and Ethics in AI: Exploring the Factors Affecting Student Performance. Journal of Intelligent Communication, 4(1), 100-110. https://doi.org/10.54963/jic.v4i1.306

The use of artificial intelligence (AI) as a data science tool for education has enormous potential for increasing student performance and course outcomes. However, the growing concern about fairness, bias, and ethics in AI systems requires a careful... Read More about Fairness, Bias, and Ethics in AI: Exploring the Factors Affecting Student Performance.

A Portable Multi-user Cross-Platform Virtual Reality Platform for School Teaching in Malawi (2023)
Presentation / Conference Contribution
Kambili-Mzembe, F., & Gordon, N. A. A Portable Multi-user Cross-Platform Virtual Reality Platform for School Teaching in Malawi. Presented at International Conference on Immersive Learning 2023, San Luis Obispo, USA

This paper discusses and evaluates a self-contained portable multi-user cross-platform Virtual Reality (VR) setup that was devised and configured using off the shelf technologies and devices. This paper exemplifies how some fundamental challenges lik... Read More about A Portable Multi-user Cross-Platform Virtual Reality Platform for School Teaching in Malawi.