| Automatic analysis of cognitive presence in online discussions: An approach using deep learning and explainable artificial intelligence Y Hu, RF Mello, D Gašević Computers and Education: Artificial Intelligence 2, 100037, 2021 | 32 | 2021 |
| Towards automated analysis of cognitive presence in MOOC discussions: a manual classification study Y Hu, C Donald, N Giacaman, Z Zhu Proceedings of the tenth international conference on learning analytics …, 2020 | 23 | 2020 |
| Cross validating a rubric for automatic classification of cognitive presence in MOOC discussions Y Hu, C Donald, N Giacaman International Review of Research in Open and Distance Learning 23 (2), 242-260, 2022 | 11 | 2022 |
| A revised application of cognitive presence automatic classifiers for MOOCs: a new set of indicators revealed? Y Hu, C Donald, N Giacaman International journal of educational technology in higher education 19 (1), 48, 2022 | 10 | 2022 |
| Can multi-label classifiers help identify subjectivity? A deep learning approach to classifying cognitive presence in MOOCs Y Hu, C Donald, N Giacaman International Journal of Artificial Intelligence in Education 33 (4), 781-816, 2023 | 4 | 2023 |
| Enhancing Trust in Generative AI: Investigating Explainability of LLMs to Analyse Confusion in MOOC Discussions Y Hu, N Giacaman, C Donald Joint Proceedings of LAK 2024 Workshops, co-located with 14th International …, 2024 | 1 | 2024 |
| Applying Machine Learning Methods to Analyse Cognitive Presence in MOOC Discussions Y Hu PhD Thesis-University of Auckland, 2024 | | 2024 |
| A Self-assessed Study Skills Inventory for First-year Engineering Students to Improve Preparedness for University Y Hu, C Donald, E del Rey Castillo | | |
Claire DonaldUniversity of AucklandVerified email at auckland.ac.nz
