Ali, a lecturer in business analytics at UQ Business School, specialises in AI, machine learning, data science, and learning analytics. His work aims to enhance education through technology. He has published in top-tier educational technology journals, earned best paper award nominations, and received a commendation from the UQ Award for Excellence in Innovation as part of a team co-developing an online learning platform. His teaching portfolio includes a range of courses, from Introduction to Data Science and Advanced Data Analytics to Business Analytics Foundations and Machine Learning in Business. As an academic and researcher, Ali is passionately committed to advancing student learning, fostering innovation, and enriching educational experiences through the power of technology, data analytics, and AI.
Journal Article: Assessing the quality of student-generated content at scale: a comparative analysis of peer review models
Darvishi, Ali, Khosravi, Hassan, Rahimi, Afshin, Sadiq, Shazia and Gasevic, Dragan (2022). Assessing the quality of student-generated content at scale: a comparative analysis of peer review models. IEEE Transactions on Learning Technologies, 16 (1), 106-120. doi: 10.1109/tlt.2022.3229022
Journal Article: Incorporating AI and learning analytics to build trustworthy peer assessment systems
Darvishi, Ali, Khosravi, Hassan, Sadiq, Shazia and Gašević, Dragan (2022). Incorporating AI and learning analytics to build trustworthy peer assessment systems. British Journal of Educational Technology, 53 (4), 844-875. doi: 10.1111/bjet.13233
Journal Article: Neurophysiological measurements in higher education: a systematic literature review
Darvishi, Ali, Khosravi, Hassan, Sadiq, Shazia and Weber, Barbara (2021). Neurophysiological measurements in higher education: a systematic literature review. International Journal of Artificial Intelligence in Education, 32 (2), 413-453. doi: 10.1007/s40593-021-00256-0
Darvishi, Ali, Khosravi, Hassan, Rahimi, Afshin, Sadiq, Shazia and Gasevic, Dragan (2022). Assessing the quality of student-generated content at scale: a comparative analysis of peer review models. IEEE Transactions on Learning Technologies, 16 (1), 106-120. doi: 10.1109/tlt.2022.3229022
Incorporating AI and learning analytics to build trustworthy peer assessment systems
Darvishi, Ali, Khosravi, Hassan, Sadiq, Shazia and Gašević, Dragan (2022). Incorporating AI and learning analytics to build trustworthy peer assessment systems. British Journal of Educational Technology, 53 (4), 844-875. doi: 10.1111/bjet.13233
Neurophysiological measurements in higher education: a systematic literature review
Darvishi, Ali, Khosravi, Hassan, Sadiq, Shazia and Weber, Barbara (2021). Neurophysiological measurements in higher education: a systematic literature review. International Journal of Artificial Intelligence in Education, 32 (2), 413-453. doi: 10.1007/s40593-021-00256-0
Impact of AI assistance on student agency
Darvishi, Ali, Khosravi, Hassan, Sadiq, Shazia, Gašević, Dragan and Siemens, George (2023). Impact of AI assistance on student agency. Computers & Education, 210 104967, 104967. doi: 10.1016/j.compedu.2023.104967
Darvishi, Ali, Khosravi, Hassan, Rahimi, Afshin, Sadiq, Shazia and Gasevic, Dragan (2022). Assessing the quality of student-generated content at scale: a comparative analysis of peer review models. IEEE Transactions on Learning Technologies, 16 (1), 106-120. doi: 10.1109/tlt.2022.3229022
Incorporating AI and learning analytics to build trustworthy peer assessment systems
Darvishi, Ali, Khosravi, Hassan, Sadiq, Shazia and Gašević, Dragan (2022). Incorporating AI and learning analytics to build trustworthy peer assessment systems. British Journal of Educational Technology, 53 (4), 844-875. doi: 10.1111/bjet.13233
Neurophysiological measurements in higher education: a systematic literature review
Darvishi, Ali, Khosravi, Hassan, Sadiq, Shazia and Weber, Barbara (2021). Neurophysiological measurements in higher education: a systematic literature review. International Journal of Artificial Intelligence in Education, 32 (2), 413-453. doi: 10.1007/s40593-021-00256-0
A regression-based approach for measuring similarity in discrete signals
Hassanpour, Hamid, Darvishi, Ali and Khalili, Atena (2011). A regression-based approach for measuring similarity in discrete signals. International Journal of Electronics, 98 (9), 1141-1156. doi: 10.1080/00207217.2011.589740
Incorporating training, self-monitoring and AI-assistance to improve peer feedback quality
Darvishi, Ali, Khosravi, Hassan, Abdi, Solmaz, Sadiq, Shazia and Gašević, Dragan (2022). Incorporating training, self-monitoring and AI-assistance to improve peer feedback quality. L@S '22: Proceedings of the Ninth ACM Conference on Learning @ Scale, New York, NY, United States, 1 - 3 June 2022. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3491140.3528265
Darvishi, Ali, Khosravi, Hassan and Sadiq, Shazia (2021). Employing peer review to evaluate the quality of student generated content at scale: a trust propagation approach. L@S '21: Proceedings of the Eighth ACM Conference on Learning @ Scale, Virtual, 22-25 June 2021. New York, NY, USA: ACM. doi: 10.1145/3430895.3460129
Open learner models for multi-activity educational systems
Abdi, Solmaz, Khosravi, Hassan, Sadiq, Shazia and Darvishi, Ali (2021). Open learner models for multi-activity educational systems. 22nd International Conference, AIED, Utrecht, The Netherlands, 14-18 June 2021. Cham, Switzerland: Springer International Publishing. doi: 10.1007/978-3-030-78270-2_2
Utilising learnersourcing to inform design loop adaptivity
Darvishi, Ali, Khosravi, Hassan and Sadiq, Shazia (2020). Utilising learnersourcing to inform design loop adaptivity. 15th European Conference on Technology Enhanced Learning, EC-TEL 2020, Heidelberg, Germany, 14 – 18 September 2020. Heidelberg, Germany: Springer. doi: 10.1007/978-3-030-57717-9_24
AI and learning analytics to improve peer review and feedback in learnersourcing
Darvishi, Ali (2023). AI and learning analytics to improve peer review and feedback in learnersourcing. PhD Thesis, School of Information Technology and Electrical Engineering, The University of Queensland. doi: 10.14264/40d7932