Dr Hassan Khosravi

Associate Professor

Institute for Teaching and Learning Innovation

Affiliate Senior Lecturer

School of Business
Faculty of Business, Economics and Law
h.khosravi@uq.edu.au
+61 7 334 60774

Overview

Dr Hassan Khosravi is an Associate Professor in Data Science and Learning Analytics at The University of Queensland. As a computer scientist by training, he is passionate about the role of artificial intelligence in the future of education. In his research, he draws on theoretical insights driven from the learning sciences and exemplary techniques from the fields of human-centred AI and crowdsourcing to build technological solutions that enhance student learning and experience. His past research and publications have addressed a number of diverse topics such as learning graphical models, statistical-relational learning, social network analysis, cybersecurity and game theory.

Hassan's teaching career includes coordinating 30 different offerings with class sizes ranging from 50 to 700, in 10 distinct courses to a total of approximately 7000 students at three top-ranked institutions: Simon Fraser University (SFU) and The University of British Columbia (UBC) in Canada, and The University of Queensland (UQ) in Australia. He has taught a range of courses including introductory programming courses, data structures and algorithms, artificial intelligence, database management systems as well as graduate-level data science courses. he also leads and teaches into a variety of formal and programs that mentor and foster the next generation of great teachers. These programs cover a wide variety of topics, including student-centred learning, active learning tools and strategies, supporting assessment design and delivery at scale, and enhancing teaching with learning analytics.

Hassan holds a Senior Fellowship with the Higher Education Academy, which has been awarded in recognition of his contributions to effective approaches to teaching and learning as well as successful coordination, support, supervision, management and mentoring of others in relation to learning and teaching.

Research Interests

  • Educational Technologies and Learning Analytics
  • Human-AI Interaction and Explainable AI

Qualifications

  • Doctor of Philosophy, Simon Fraser University

Publications

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Grants

View all Grants

Supervision

  • Doctor Philosophy

  • Doctor Philosophy

  • Doctor Philosophy

View all Supervision

Available Projects

View all Available Projects

Publications

Journal Article

Conference Publication

  • Lahza, Hatim Fareed, Khosravi, Hassan and Demartini, Gianluca (2022). Incorporating AI and Analytics to Derive Insights from E-exam Logs. 23rd International Conference of Artificial Intelligence in Education AIED 2022, Durham, United Kingdom, 27–31 July 2022. Heidelberg, Germany: Springer. doi: 10.1007/978-3-031-11644-5_78

  • Shabaninejad, Shiva, Khosravi, Hassan, Abdi, Solmaz, Indulska, Marta and Sadiq, Shazia (2022). Incorporating Explainable Learning Analytics to Assist Educators with Identifying Students in Need of Attention. Association for Computing Machinery, Inc. doi: 10.1145/3491140.3528292

  • 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

  • Moore, Steven, Stamper, John, Brooks, Christopher, Denny, Paul and Khosravi, Hassan (2022). Learnersourcing: Student-generated Content@Scale. Association for Computing Machinery, Inc. doi: 10.1145/3491140.3528286

  • Lahza, Hatim, Khosravi, Hassan, Demartini, Gianluca and Gasevic, Dragan (2022). Effects of technological interventions for self-regulation: a control experiment in learnersourcing. LAK22: 12th International Learning Analytics and Knowledge Conference, Virtual, United States, 21 - 25 March 2022. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3506860.3506911

  • 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

  • Khosravi, Hassan, Demartini, Gianluca, Sadiq, Shazia and Gasevic, Dragan (2021). Charting the design and analytics agenda of learnersourcing systems. 11th International Learning Analytics and Knowledge Conference, Irvine, CA USA, April 2021. New York, NY, USA: ACM. doi: 10.1145/3448139.3448143

  • Abdi, Solmaz, Khosravi, Hassan and Sadiq, Shazia (2021). Modelling learners in adaptive educational systems: a multivariate Glicko-based approach. 11th International Learning Analytics and Knowledge Conference, Irvine, CA USA, April 2021. New York, NY, USA: ACM. doi: 10.1145/3448139.3448189

  • 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

  • Leemans, Sander J. J., Shabaninejad, Shiva, Goel, Kanika, Khosravi, Hassan, Sadiq, Shazia and Wynn, Moe Thandar (2020). Identifying cohorts: recommending drill-downs based on differences in behaviour for process mining. Conceptual Modeling 39th International Conference, ER 2020, Vienna, Austria, 3–6 November, 2020. Cham, Switzerland: Springer International Publishing. doi: 10.1007/978-3-030-62522-1_7

  • Leemans, Sander, Shabaninejad, Shiva, Goel, Kanika, Khosravi, Hassan, Sadiq, Shazia and Wynn, Moe (2020). Identifying cohorts that differ in their behaviour: tool support. 39th International Conference on Conceptual Modeling , Vienna, Austria, 3-6 November 2020. CEUR-WS.

  • Khosravi, Hassan, Gyamfi, George , Hanna, Barbara and Lodge, Jason (2020). Development of educational tools that enable large-scale ethical empirical research on evaluative judgement. University Assessment, Learning and Teaching: New Research Directions for a Postdigital World, Online, 19-20 October 2020.

  • Gyamfi, George, Hanna, Barbara and Khosravi, Hassan (2020). The effect of rubrics on evaluative judgement: a randomised controlled trial. University Assessment, Learning and Teaching: New Research Directions for a Postdigital World, Online, 19-20 October 2020.

  • Shabaninejad, Shiva, Khosravi, Hassan, Indulska, Marta, Bakharia, Aneesha and Isaias, Pedro (2020). Automated insightful drill-down recommendations for learning analytics dashboards. 10th International Conference on Learning Analytics and Knowledge, Portland, OR USA, March 2020. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3375462.3375539

  • Abdi, Solmaz, Khosravi, Hassan, Sadiq, Shazia and Gasevic, Dragan (2020). Complementing educational recommender systems with open learner models. 10th International Conference on Learning Analytics and Knowledge, Portland, OR USA, March 2020. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3375462.3375520

  • Khosravi, Hassan, Sadiq, Shazia and Gasevic, Dragan (2020). Development and adoption of an adaptive learning system: reflections and lessons learned. SIGCSE '20: The 51st ACM Technical Symposium on Computer Science Education, Portland, OR USA, March 2020. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3328778.3366900

  • Khosravi, Hassan, Gyamii, George, Hanna, Barbara E. and Lodge, Jason (2020). Fostering and supporting empirical research on evaluative judgement via a crowdsourced adaptive learning system. LAK 2020: the Tenth International Conference on Learning Analytics and Knowledge, Frankfurt, Germany, 23 - 27 March 2020. New York, United States: ACM. doi: 10.1145/3375462.3375532

  • Abdi, Solmaz, Khosravi, Hassan and Sadiq, Shazia (2020). Modelling learners in crowdsourcing educational systems. AIED: International Conference on Artificial Intelligence in Education, Ifrane, Morocco, 6-10 July 2020. Cham, Switzerland: Springer International Publishing. doi: 10.1007/978-3-030-52240-7_1

  • Shabaninejad, Shiva, Khosravi, Hassan, Leemans, Sander J. J., Sadiq, Shazia and Indulska, Marta (2020). Recommending insightful drill-downs based on learning processes for learning analytics dashboards. AIED: International Conference on Artificial Intelligence in Education, Ifrane, Morocco, 6-10 July 2020. Cham, Switzerland: Springer International Publishing. doi: 10.1007/978-3-030-52237-7_39

  • Smith, Tammy, Lahza, Hatim and Khosravi, Hassan (2020). Using electronic logs to explore exam-taker behaviour during MCQ exams: is there a correlation with results?. Ottawa 2020, Kuala Lumpur, Malaysia, 29 February - 4 March 2020.

  • 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

  • Abdi, Solmaz, Khosravi, Hassan, Sadiq, Shazia and Gasevic, Dragan (2019). A multivariate ELO-based learner model for adaptive educational systems. 12th International Conference on Educational Data Mining, Montreal, Canada, July 2-5, 2019. International Educational Data Mining Society.

  • Cooper, Kendra and Khosravi, Hassan (2019). Multilevel topic dependency models for assessment design and delivery: A hypergraph based approach. The 25th International DMS Conference on Visualization and Visual Languages, Lisbon, Portugal, 8 - 9 July 2019. Knowledge Systems Institute Graduate School, KSI Research. doi: 10.18293/DMSVIVA2019-018

  • Ocana, Mauro, Khosravi, Hassan and Bakharia, Aneesha (2019). Profiling language learners in the Big data era. 36th International Conference on Innovation, Practice and Research in the Use of Educational Technologies in Tertiary Education, Singapore, 2-5 December 2019. Singapore: Singapore University of Social Sciences.

  • Cooper, Kendra and Khosravi, Hassan (2018). Graph-based visual topic dependency models : supporting assessment design and delivery at scale. 8th International Conference on Learning Analytics and Knowledge, LAK 2018, Sydney, Australia, 7-9 March 2018 . New York, United States: ACM Press. doi: 10.1145/3170358.3170418

  • Abdi, Solmaz, Khosravi, Hassan and Sadiq, Shazia (2018). Predicting Student Performance: The Case of Combining Knowledge Tracing and Collaborative Filtering. International Conference on Educational Data Mining, Buffalo, NY, United States, 15-18 July 2018. Educational Data Mining.

  • Potts, Boyd A., Khosravi, Hassan and Reidsema, Carl (2018). Reciprocal content recommendation for peer learning study sessions. International Conference on Artificial Intelligence in Education, London, United Kingdom, 27-30 June 2018. Heidelberg, Germany: Springer. doi: 10.1007/978-3-319-93843-1_34

  • Potts, Boyd A., Khosravi, Hassan, Reidsema, Carl, Bakharia, Aneesha, Belonogoff, Mark and Fleming, Melanie (2018). Reciprocal peer recommendation for learning purposes. 8th International Conference on Learning Analytics and Knowledge, Sydney, New South Wales, Australia, 7 - 9 March 2018. New York, NY, United States: ACM Digital Library. doi: 10.1145/3170358.3170400

  • Coombe, Leanne, Huang, Jasmine, Khosravi, Hassan, Russell, Stuart and Sheppard, Karen (2018). Understanding (SaP) Partnerships: evaluating what works!. Higher Education Research and Development Society of Australasia (HERDSA 2018), Adelaide, SA, Australia, 2-5 July 2018.

  • Reidsema, Carl, Kavanagh, Lydia, Fink, Esther M., Khosravi, Hassan, Fleming, Melanie and Achilles, Nicholas (2017). Analysing the learning pathways of students in a large flipped engineering course. ASCILITE2017: 34th International Conference on Innovation, Practice and Research in the Use of Educational Technologies in Tertiary Education., Toowoomba, QLD, Australia, 4 - 6 December 2017. Darling Heights, QLD, Australia: University of Southern Queensland.

  • Khosravi, Hassan, Cooper, Kendra and Kitto, Kirsty (2017). Riple: Recommendation in peer-learning environments based on knowledge gaps and interests. 10th International Conference on Educational Data Mining, EDM 2017, Wuhan, China, 25-28 June 2017. Memphis, TN, United States: International Working Group on Educational Data Mining.

  • Khosravi, Hassan and Cooper, Kendra (2017). Using learning analytics to investigate patterns of performance and engagement in large classes. SIGCSE '17, Seattle, WA, United States, 8-11 March 2017. New York, NY, United States: ACM. doi: 10.1145/3017680.3017711

  • Khosravi, Hassan (2013). Fast parameter learning for Markov logic networks using Bayes nets. 22nd International Conference on Inductive Logic Programming, ILP 2012, Dubrovnik, Croatia, 17-19 September 2012. Berlin, Germany: Springer. doi: 10.1007/978-3-642-38812-5_8

  • Khosravi, Hassan, Bozorgkhan, Ali and Schulte, Oliver (2013). Transaction-based link strength prediction in a social network. 2013 IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013, Singapore, 16-19 April 2013. Piscataway, NJ, United States: IEEE. doi: 10.1109/CIDM.2013.6597236

  • Khosravi, Hassan and Bina, Bahareh (2010). A survey on statistical relational learning. 23rd Canadian Conference on Artificial Intelligence, Canadian AI 2010, Ottawa, ON, Canada, 31 May - 2 June 2010. Berlin, Germany: Springer. doi: 10.1007/978-3-642-13059-5_25

  • Khosravi, Hassan, Schulte, Oliver, Man, Tong, Xu, Xiaoyuan and Bina, Bahareh (2010). Structure learning for Markov Logic Networks with many descriptive attributes. 24th AAAI Conference on Artificial Intelligence and the 22nd Innovative Applications of Artificial Intelligence Conference, AAAI-10 / IAAI-10, Atlanta, GA, United States, 11-15 July 2010. Palo Alto, CA, United States: Association for the Advancement of Artificial Intelligence.

  • Schulte, Oliver, Frigo, Gustavo, Greiner, Russell and Khosravi, Hassan (2010). The IMAP hybrid method for learning Gaussian bayes nets. 23rd Canadian Conference on Artificial Intelligence, Canadian AI 2010, Ottawa, ON, Canada, 31 May - 2 June 2010. Berlin, Germany: Springer. doi: 10.1007/978-3-642-13059-5_14

  • Schulte, Oliver, Frigo, Gustavo, Greiner, Russell, Luo, Wei and Khosravi, Hassan (2009). A new hybrid method for bayesian network learning with dependency constraints. 2009 IEEE Symposium on Computational Intelligence and Data Mining (Cidm), Nashville, TN, 30 March - 2 April 2009. Piscatawa, NJ, U.S.A.: IEEE. doi: 10.1109/CIDM.2009.4938629

  • Khosravi, Hassan and Colak, Recep (2009). Exploratory analysis of co-change graphs for code refactoring. 22nd Canadian Conference on Artificial Intelligence, Kelowna, Canada, 25-27 May 2009. Berlin, Heidelberg: Springer Berlin Heidelberg. doi: 10.1007/978-3-642-01818-3_28

  • Bina, Bahareh, Schulte, Oliver and Khosravi, Hassan (2009). LNBC: A link-based naive bayes classifier. 2009 IEEE International Conference on Data Mining Workshops, ICDMW 2009, Miami, FL, December 6, 2009-December 6, 2009. IEEE. doi: 10.1109/ICDMW.2009.116

  • Khosravi H., Shiri M.E., Khosravi H., Iranmanesh E. and Davoodi A. (2008). TACtic- a multi behavioral agent for trading agent competition. 13th International Computer Society of Iran Computer Conference on Advances in Computer Science and Engineering, CSICC 2008, Kish Island, March 9, 2008-March 11, 2008. doi: 10.1007/978-3-540-89985-3_109

Other Outputs

Grants (Administered at UQ)

PhD and MPhil Supervision

Current Supervision

  • Doctor Philosophy — Principal Advisor

  • Doctor Philosophy — Principal Advisor

  • Doctor Philosophy — Principal Advisor

    Other advisors:

  • Doctor Philosophy — Associate Advisor

  • Doctor Philosophy — Associate Advisor

    Other advisors:

  • Doctor Philosophy — Associate Advisor

    Other advisors:

Completed Supervision

Possible Research Projects

Note for students: The possible research projects listed on this page may not be comprehensive or up to date. Always feel free to contact the staff for more information, and also with your own research ideas.