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Dr Hassan Khosravi

Associate Professor

Institute for Teaching and Learning Innovation
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

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Supervision

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Available Projects

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Publications

Journal Article

Conference Publication

  • Learner-centred Analytics of Feedback Content in Higher Education

    Lin, Jionghao, Dai, Wei, Lim, Lisa-Angelique, Tsai, Yi-Shan, Mello, Rafael Ferreira, Khosravi, Hassan, Gasevic, Dragan and Chen, Guanliang (2023). Learner-centred Analytics of Feedback Content in Higher Education. New York, NY, USA: ACM. doi: 10.1145/3576050.3576064

  • Incorporating AI and Analytics to Derive Insights from E-exam Logs

    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

  • Incorporating Explainable Learning Analytics to Assist Educators with Identifying Students in Need of Attention

    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. New York, NY, USA: Association for Computing Machinery, Inc. doi: 10.1145/3491140.3528292

  • 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

  • Learnersourcing: Student-generated Content@Scale

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

  • Effects of technological interventions for self-regulation: a control experiment in learnersourcing

    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

  • Employing peer review to evaluate the quality of student generated content at scale: a trust propagation approach

    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

  • Charting the design and analytics agenda of learnersourcing systems

    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

  • Modelling learners in adaptive educational systems: a multivariate Glicko-based approach

    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

  • 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

  • Identifying cohorts: recommending drill-downs based on differences in behaviour for process mining

    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

  • Identifying cohorts that differ in their behaviour: tool support

    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.

  • Development of educational tools that enable large-scale ethical empirical research on evaluative judgement

    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.

  • The effect of rubrics on evaluative judgement: a randomised controlled trial

    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.

  • Automated insightful drill-down recommendations for learning analytics dashboards

    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

  • Complementing educational recommender systems with open learner models

    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

  • Development and adoption of an adaptive learning system: reflections and lessons learned

    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

  • Fostering and supporting empirical research on evaluative judgement via a crowdsourced adaptive learning system

    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

  • Modelling learners in crowdsourcing educational systems

    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

  • Recommending insightful drill-downs based on learning processes for learning analytics dashboards

    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

  • Using electronic logs to explore exam-taker behaviour during MCQ exams: is there a correlation with results?

    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.

  • 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

  • A multivariate ELO-based learner model for adaptive educational systems

    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.

  • Multilevel topic dependency models for assessment design and delivery: A hypergraph based approach

    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

  • Profiling language learners in the Big data era

    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.

  • Graph-based visual topic dependency models : supporting assessment design and delivery at scale

    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

  • Predicting Student Performance: The Case of Combining Knowledge Tracing and Collaborative Filtering

    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.

  • Reciprocal content recommendation for peer learning study sessions

    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

  • Reciprocal peer recommendation for learning purposes

    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

  • Understanding (SaP) Partnerships: evaluating what works!

    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.

  • Analysing the learning pathways of students in a large flipped engineering course

    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.

  • Riple: Recommendation in peer-learning environments based on knowledge gaps and interests

    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.

  • Using learning analytics to investigate patterns of performance and engagement in large classes

    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

  • Fast parameter learning for Markov logic networks using Bayes nets

    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

  • Transaction-based link strength prediction in a social network

    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

  • A survey on statistical relational learning

    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

  • Structure learning for Markov Logic Networks with many descriptive attributes

    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.

  • The IMAP hybrid method for learning Gaussian bayes nets

    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

  • A new hybrid method for bayesian network learning with dependency constraints

    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

  • Exploratory analysis of co-change graphs for code refactoring

    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

  • LNBC: A link-based naive bayes classifier

    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

  • TACtic- a multi behavioral agent for trading agent competition

    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

  • Design guideline & tool for learning process reconstruction and analysis

    Doctor Philosophy — Principal Advisor

    Other advisors:

  • Integrating Human and Machine Intelligence Towards the Development of an Adaptive Learning System

    Doctor Philosophy — Principal Advisor

    Other advisors:

  • The application of learning analytics and multimodal data to evaluate student engagement and learning outcomes in chemistry

    Doctor Philosophy — Associate Advisor

    Other advisors:

  • Empirical investigation of strategies for the development of students¿ evaluative judgement

    Doctor Philosophy — Associate Advisor

    Other advisors:

  • Application of machine learning and Big data techniques to mining geology

    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.

This staff member is a UQ Expert for media in the following fields:

Learning analytics, Educational data mining, Computer science education, Educational technologies, Databases, Data science

They are happy to lend their expertise to your articles or broadcasts and share their research discoveries and insights with the community via media channels.

For additional assistance with story ideas, general advice and information or help with seeking further experts, please email the UQ Media Team or telephone (07) 3365 1120.

Links

ORCID: 0000-0001-8664-6117

Scopus ID:

Google Scholar ID: 0U7jTbYAAAAJ

Personal Profile: Link

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