Items where Author is "Al-Shabandar, R"

Article

Khan, W ORCID: 0000-0002-7511-3873, Topham, L ORCID: 0000-0002-6689-7944, Jones, N, Atherton, P ORCID: 0000-0003-3258-0436, Al-Shabandar, R, Kolivand, H ORCID: 0000-0001-5460-5679, Khan, I ORCID: 0000-0002-4206-7663, Alatrany, A and Hussain, A (2026) Auto-assessment of assessment: A human-in-the-loop AI framework addressing policy gaps in academic assessment. PLoS One, 21 (4). ISSN 1932-6203

Ahmed, Z, Hussain, A, Khan, W, Baker, T, Al-Askar, H, Lunn, J, Liatsis, P, Al-Jumeily, D and Al-Shabandar, R (2020) Lossy and Lossless Video Frame Compression: A Novel Approach for the High-Temporal Video Data Analytics. Remote Sensing, 12 (6). ISSN 2072-4292

Al-Shabandar, R, Hussain, A, Liatsis, P and Keight, R (2019) Detecting At-Risk Students with Early Interventions Using Machine Learning Techniques. IEEE Access, 7. pp. 149464-149478. ISSN 2169-3536

Al-Shabandar, R, Hussain, A, Liatsis, P and Keight, R (2018) Analyzing Learners Behavior in MOOCs: An Examination of Performance and Motivation Using a Data-Driven Approach. IEEE Access, 6. pp. 73669-73685. ISSN 2169-3536

Al-Shabandar, R, Hussain, A, Laws, A, Keight, R and Lunn, J (2017) Towards the Differentiation of Initial and Final Retention in Massive Open Online Courses. Lecture Notes in Computer Science, 10361. ISSN 0302-9743

Conference or Workshop Item

Al-Shabandar, R, Hussain, A, Laws, A, Keight, R and Lunn, J (2017) Machine Learning Approaches to Predict Learning Outcomes in Massive Open Online Courses. In: Neural Networks (IJCNN) . (2017 International Joint Conference on Neural Networks (IJCNN 2017), 14 May 2017 - 19 May 2017, Anchorage, Alaska, USA).

Thesis

Al-Shabandar, R (2019) The application of Machine Learning for Early Detection of At -Risk Learners in Massive Open Online Courses. Doctoral thesis, Liverpool John Moores University.