Targeting At-risk Students Using Engagement and Effort Predictors in an Introductory Computer Programming Course. - David Azcona; Alan F. Smeaton (EC-TEL, 2017)

Modelling Math Learning on an Open Access Intelligent Tutor. - David Azcona; I-Han Hsiao; Alan F. Smeaton (AIED (2), 2018)

An Exploratory Study on Student Engagement with Adaptive Notifications in Programming Courses. - David Azcona; I-Han Hsiao; Alan F. Smeaton (EC-TEL, 2018)

Learning by Reviewing Paper-Based Programming Assessments. - Yancy Vance M. Paredes; David Azcona; I-Han Hsiao; Alan F. Smeaton (EC-TEL, 2018)

Personalizing Computer Science Education by Leveraging Multimodal Learning Analytics. - David Azcona; I-Han Hsiao; Alan F. Smeaton (FIE, 2018)

user2code2vec: Embeddings for Profiling Students Based on Distributional Representations of Source Code. - David Azcona; Piyush Arora; I-Han Hsiao; Alan F. Smeaton (LAK, 2019)

Predicting Media Memorability Using Ensemble Models. - David Azcona; Enric Moreu; Feiyan Hu; Tomás E. Ward; Alan F. Smeaton (MediaEval, 2019)

Detecting students-at-risk in computer programming classes with learning analytics from students' digital footprints. - David Azcona; I-Han Hsiao; Alan F. Smeaton (User Model. User Adapt. Interact., 2019)

A Comparative Study of Existing and New Deep Learning Methods for Detecting Knee Injuries using the MRNet Dataset. - David Azcona; Kevin McGuinness; Alan F. Smeaton (IDSTA, 2020)

A Smart-Site-Survey System using Image-based 3D Metric Reconstruction and Interactive Panorama Visualization. - Sha Yu; Kevin McGuinness; Patricia Moore; David Azcona; Noel E. O'Connor (ACM Multimedia, 2020)

Brand Recommendations for Cold-Start Problems Using Brand Embeddings. - David Azcona; Alan F. Smeaton (IntelliSys (3), 2022)