Staff profile

Bio

Alexandra I. Cristea is Professor, Deputy Executive Dean of the Faculty of Science, Founder of the Artificial Intelligence in Human Systems research group in the Department of Computer Science at Durham University, and lead of the SCENE lab. She is Alan Turing Academic Liaison for Durham, N8 CIR Digital Humanities team lead for Durham and member of the IEEE European Public Policy on ICT, and Senior Common Room honorary member as prior Advisory Board Member at the Ustinov College. Her research includes web science, learning analytics, user modelling and personalisation, semantic web, social web, authoring, with over 350 papers on these subjects (over 7100 citations on Google Scholar, h-index 43). Especially, her work on gamification for education - over 340 citations -  and frameworks for adaptive systems has influenced many researchers and is highly cited  - over 230 citations. She was classified within the top 50 researchers in the world in the area of educational computer-based research according to  Microsoft Research (2015-02-10). Prof. Cristea has been highly active and has an influential role in international research projects. She leads and has led various projects - the JANET and JANET 2.0 (Joint Lab in Learning Analytics for Personalised Science Teaching) project series ('20-'23; '24-'25); funded by the Weizman Institute and the British Council;  the Predictive and prescriptive analytics for the media industry project series collaboration with Distinctive Publishing ('18-'19; '19-'23; '24-'25);the ATI@Durham Research Network (2022); the Epistemological Engine (2021-22);Newton funded workshop on Higher Education for All ('14-'18), Santander funded Education for disadvantaged pupils ('14-18'), Warwick-funded project APLIC ('11-;12), EU Minerva projects ALS (06-09) and EU Minerva ADAPT (’02-’05); as well as participated as university PI in several EU FP7 projects - BLOGFOREVER (’11-’13), GRAPPLE (’08- ’11), PROLEARN (’07) and as co-PI in the Warwick-funded Engaging Young People with Assistance Technologies (’13-’15) also featured by the BBC. Recently she has taken giving back to the community to a different level, leading the MESSENGER (Women inSTEM and Cultural Diversity) (2022); Empowering women in science through mentoring and exchanging experiences (2021-22) (UK-Brazil Gender Equality Partnership funded by the British Council), and co-leading the TechUP  project series  (2019-2020: training 100 women in computer science from various (BAME) backgrounds)(TechUPOnline 2020)(Bootcamp 2021)(Nominet-funded '22-'25). She has been keynote/invited speaker, chair, organiser, co-organiser, panellist and program committee member of various conferences in her research field (including, for example,  AIED, ECTEL, ITS, UMAP, ED-MEDIA, Hypertext, Adaptive Hypermedia, EDM, ICCE, ICAI). She was an Associate Editor of the ACM Computing Surveys, Associate Editor of Frontiers in Artificial Intelligence and the IEEE Transactions on Learning Technologies, co-editor of the Advanced Technologies and Learning Journal and executive peer reviewer of the IEEE LTTF Education Technology and Society Journal. She acted as UNESCO expert for adaptive web-based education at a high-level (Ministry of Education and Educational institutes) meeting of East European countries, educational invited expert for the Romanian prime minister, as well as EU expert for H2020, FP7, FP6, eContentPlus. She has interacted with various international and local media (she has given a recent live radio interview to Power 106FM in Jamaica; work from her lab has been publicised by Free Radio Coventry & Warwickshire, Birmingham Post, Birmingham Mail, phys.org, The Daily Dot, Mirror, Vice Motherboard, BBC News, Pinterest, Globenewswire, Romanian TV). She is a BCS fellow, a HEA fellow, IEEE Senior Member and IEEE CS member, EATEL (European Association of Technology Enhanced Learning) founding member, ACM member.

News

Delighted to have host a return conference in Durham, ECTEL 2025, 20th anniversary edition, organised by its gerning society EATEL, both resulting from our European project PROLEARN 20 years ago!

Happy to serve as PC Chair to AIED 2025.

... and prior to this:

Delighted to have hosted two major conferences in Durham during the Intelligence in Education Week at Durham event: AIED 2022 and EDM 2022!

Special Issues:

• Special Issue "Learner–Computer Interaction and Intelligent Tutoring Systems" in MDPI, Education Sciences
• Special Issue "Artificial Intelligence Techniques for Personalized Educational Software" in Frontiers in AI, AI for Human Learning and Behavior Change

 

Publications

• Google Scholar

 

• Adaptive, personalised web
• Applied AI
• Learner Analytics Data Analytics
• Semantic Web
• Social Web
• User Modelling
• VR, XR, CR
• Web Science

• 2022: Member of IEEE EPPC Working Group on ICT:
• 2022: External Examiner Imperial MSc in Advanced Computing:
• 2022: Associate Editor of ACM Computing Surveys:
• 2021: EPSRC College Member:
• 2021: Alan Turing Academic Liaison for Durham:
• 2020: Associate Editor of Frontiers in Artificial Intelligence:
• 2019: N8 CIR Digital Humanities team lead for Durham:
• 2019: Advisory Board Member at Ustinov College:
• 2018: Associate Editor of the IEEE Transactions on Learning Technologies:
• 2016: IEEE Senior Member:
• 2015: Fellow of the Higher Education Academy in Britain:
• 2011: Fellow of the British Computing Society:

Chapter in book

• Alshehri, M., Alamri, A., & Cristea, A. I. (2022). Adopting Automatic Machine Learning for Temporal Prediction of Paid Certification in MOOCs. In M. Mercedes Rodrigo, N. Matsuda, A. I. Cristea, & V. Dimitrova (Eds.), Artificial Intelligence in Education (717-723). Springer Verlag. https://doi.org/10.1007/978-3-031-11644-5_73
• Xiao, C., Shi, L., Cristea, A., Li, Z., & Pan, Z. (2022). Fine-grained Main Ideas Extraction and Clustering of Online Course Reviews. In M. Rodrigo, N. Matsuda, A. Cristea, & V. Dimitrova (Eds.), Artificial Intelligence in Education (294-306). Springer, Cham. https://doi.org/10.1007/978-3-031-11644-5_24
• Alshehri, M., & Cristea, A. I. (2022). MOOCs Paid Certification Prediction Using Students Discussion Forums. In M. Mercedes Rodrigo, N. Matsuda, A. I. Cristea, & V. Dimitrova (Eds.), Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium (542-545). Springer Verlag. https://doi.org/10.1007/978-3-031-11647-6_111
• Alrajhi, L., Alamri, A., & Cristea, A. I. (2022). Intervention Prediction in MOOCs Based on Learners’ Comments: A Temporal Multi-input Approach Using Deep Learning and Transformer Models. In S. Crossley, & E. Popescu (Eds.), Intelligent Tutoring Systems (227-237). Springer Verlag. https://doi.org/10.1007/978-3-031-09680-8_22
• Wang, J., Hodgson, R., & Cristea, A. I. (2022). MEMORABLE: A Multi-playEr custoMisable seriOus Game fRAmework for cyBer-security LEarning. In S. Crossley, & E. Popescu (Eds.), Intelligent Tutoring Systems (313-322). Springer Verlag. https://doi.org/10.1007/978-3-031-09680-8_29
• Drousiotis, E., Pentaliotis, P., Shi, L., & Cristea, A. I. (2022). Balancing Fined-Tuned Machine Learning Models Between Continuous and Discrete Variables - A Comprehensive Analysis Using Educational Data. In Artificial Intelligence in Education (256-268). Springer, Cham. https://doi.org/10.1007/978-3-031-11644-5_21
• Li, Z., Shi, L., Cristea, A., Zhou, Y., Xiao, C., & Pan, Z. (2022). SimStu-Transformer: A Transformer-Based Approach to Simulating Student Behaviour. In Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium (348-351). Springer, Cham. https://doi.org/10.1007/978-3-031-11647-6_67
• Wynn, A. T., Wang, J., Umezawa, K., & Cristea, A. I. (2022). An AI-Based Feedback Visualisation System for Speech Training. In M. Mercedes Rodrigo, N. Matsuda, A. I. Cristea, & V. Dimitrova (Eds.), Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium (510-514). Springer Verlag. https://doi.org/10.1007/978-3-031-11647-6_104
• Aljohani, T., Cristea, A. I., & Alrajhi, L. (2022). Bi-directional Mechanism for Recursion Algorithms: A Case Study on Gender Identification in MOOCs. In M. Mercedes Rodrigo, N. Matsuda, A. I. Cristea, & V. Dimitrova (Eds.), Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium (396-399). Springer Verlag. https://doi.org/10.1007/978-3-031-11647-6_78
• Alrajhi, L., Pereira, F. D., Cristea, A. I., & Aljohani, T. (2022). A Good Classifier is Not Enough: A XAI Approach for Urgent Instructor-Intervention Models in MOOCs. In M. Mercedes Rodrigo, N. Matsuda, A. I. Cristea, & V. Dimitrova (Eds.), Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium (424-427). Springer Verlag. https://doi.org/10.1007/978-3-031-11647-6_84
• Drousiotis, E., Pentaliotis, P., Shi, L., & Cristea, A. I. (2021). Capturing Fairness and Uncertainty in Student Dropout Prediction – A Comparison Study. In I. Roll, D. McNamara, S. Sosnovsky, R. Luckin, & V. Dimitrova (Eds.), Artificial Intelligence in Education (139-144). Springer, Cham. https://doi.org/10.1007/978-3-030-78270-2_25
• Alrajhi, L., Alamri, A., Pereira, F. D., & Cristea, A. I. (2021). Urgency Analysis of Learners’ Comments: An Automated Intervention Priority Model for MOOC. In A. I. Cristea, & C. Troussas (Eds.), Intelligent Tutoring Systems: 17th International Conference, ITS 2021, Virtual Event, June 7–11, 2021, Proceedings (148-160). Springer Verlag. https://doi.org/10.1007/978-3-030-80421-3_18
• Alshehri, M., Alamri, A., & Cristea, A. I. (2021). Predicting Certification in MOOCs based on Students’ Weekly Activities. In A. I. Cristea, & C. Troussas (Eds.), Intelligent Tutoring Systems: 17th International Conference, ITS 2021, Virtual Event, June 7–11, 2021, Proceedings (173-185). Springer Verlag. https://doi.org/10.1007/978-3-030-80421-3_20
• Toda Yacobson, E., Cristea, A., & Alexandron, G. I. (2021). Encouraging Teacher-sourcing of Social Recommendations Through Participatory Gamification Design. In A. Cristea, & C. I. Troussas (Eds.), Intelligent Tutoring Systems: 17th International Conference, ITS 2021, Virtual Event, June 7–11, 2021, Proceedings (418-429). Springer Verlag. https://doi.org/10.1007/978-3-030-80421-3_46
• Aljohani, T., & Cristea, A. I. (2021). Training Temporal and NLP Features via Extremely Randomised Trees for Educational Level Classification. In A. I. Cristea, & C. Troussas (Eds.), Intelligent Tutoring Systems: 17th International Conference, ITS 2021, Virtual Event, June 7–11, 2021, Proceedings (136-147). Springer Verlag. https://doi.org/10.1007/978-3-030-80421-3_17
• Pereira, F. D., Junior, H. B., Rodriquez, L., Toda, A., Oliveira, E. H., Cristea, A. I., Oliveira, D. B., Carvalho, L. S., Fonseca, S. C., Alamri, A., & Isotani, S. (2021). A Recommender System Based on Effort: Towards Minimising Negative Affects and Maximising Achievement in CS1 Learning. In A. I. Cristea, & C. Troussas (Eds.), Intelligent Tutoring Systems: 17th International Conference, ITS 2021, Virtual Event, June 7–11, 2021, Proceedings (466-480). Springer Verlag. https://doi.org/10.1007/978-3-030-80421-3_51
• Alamri, A., Sun, Z., Cristea, A. I., Steward, C., & Pereira, F. D. (2021). MOOC next week dropout prediction: weekly assessing time and learning patterns. In A. I. Cristea, & C. Troussas (Eds.), Intelligent Tutoring Systems: 17th International Conference, ITS 2021, Virtual Event, June 7–11, 2021, Proceedings (119-130). Springer Verlag. https://doi.org/10.1007/978-3-030-80421-3_15
• Shi, L., Cristea, A. I., Toda, A. M., & Oliveira, W. (2020). Exploring Navigation Styles in a FutureLearn MOOC. In V. Kumar, & C. Troussas (Eds.), Intelligent Tutoring Systems (45-55). Springer Verlag. https://doi.org/10.1007/978-3-030-49663-0_7
• Alamri, A., Alshehri, M., Cristea, A. I., Pereira, F. D., Oliveira, E., Shi, L., & Stewart, C. (2019). Predicting MOOCs Dropout Using Only Two Easily Obtainable Features from the First Week’s Activities. In A. Coy, Y. Hayashi, & M. Chang (Eds.), Intelligent tutoring systems. ITS 2019 (163-173). Springer Verlag. https://doi.org/10.1007/978-3-030-22244-4_20
• Zhou, Y., Demidova, E., & Cristea, A. (2017). What's new? Analysing language-specific Wikipedia entity contexts to support entity-centric news retrieval. In N. Nguyen, R. Kowalczyk, A. Pinto, & J. Cardoso (Eds.), Transactions on Computational Collective Intelligence XXVI (2010-231). Springer Verlag. https://doi.org/10.1007/978-3-319-59268-8_10
• Shi, L., Cristea, A., & Hadzidedic, S. (2014). Multifaceted open social learner modelling. In P. Elvira, R. W. Lau, K. Pata, H. Leung, & L. Mart (Eds.), Advances in Web-Based Learning – ICWL 2014, 13th International Conference, Tallinn, Estonia, August 14-17, 2014, Proceedings (32-42). Springer Verlag. https://doi.org/10.1007/978-3-319-09635-3_4

Conference Paper

• Alghamdi, N., & Cristea, A. I. (2024, August). Integrating Speech Input in Educational Immersive Virtual Reality Applications: A Systematic Review. Presented at 2024 IEEE 12th International Conference on Intelligent Systems (IS), Varna, Bulgaria
• Chang, H., Pan, Z., & Cristea, A. I. (2024, July). Virtual Reality (VR) in Safety Education: A Case Study of Mining Engineering. Presented at AIED 2024: Artificial Intelligence in Education, Recife, Brazil
• Pan, Z., Cristea, A. I., & Li, F. W. B. (2024, July). Reducing University Students’ Exam Anxiety via Mindfulness-Based Cognitive Therapy in VR with Real-Time EEG Neurofeedback. Presented at AIED 2024: Artificial Intelligence in Education, Recife, Brazil
• Fern, N., Cristea, A. I., Nolan, S., & Stewart, C. (2024, June). Doctoral Colloquium—How Interactivity and Presence Affect Learning in Immersive Virtual Reality: A Mixed Methods Study Design. Presented at 10th International Conference of the Immersive Learning Research Network, Glasgow, Scotland, UK
• Pan, Z., & Cristea, A. I. (2024, June). Towards Neuro-Enhanced Education: A Systematic Review of BCI-Assisted Development for Non-academic Skills and Abilities. Presented at ITS 2024: Generative Intelligence and Intelligent Tutoring Systems, Thessaloniki, Greece
• Alghamdi, N., & Cristea, A. I. (2024, July). Natural Language Processing for a Personalised Educational Experience in Virtual Reality. Presented at Artificial Intelligence in Education (AIED 2024), Recife, Brazil
• Al Saqaabi, A., Stewart, C., Akrida, E., & Cristea, A. I. (2024, June). Paraphrase Generation and Identification at Paragraph-Level. Presented at Generative Intelligence and Intelligent Tutoring Systems ITS 2024, Thessaloniki, Greece
• Alrajhi, L., Pereira, F. D., Cristea, A. I., & Alamri, A. (2023, September). Serendipitous Gains of Explaining a Classifier - Artificial versus Human Performance and Annotator Support in an Urgent Instructor-Intervention Model for MOOCs. Paper presented at HT '23: 34th ACM Conference on Hypertext and Social Media, Rome Italy
• Aduragba, T. O., Yu, J., Cristea, A. I., & Long, Y. (2023, April). Improving Health Mention Classification Through Emphasising Literal Meanings: A Study Towards Diversity and Generalisation for Public Health Surveillance. Presented at WWW '23: The ACM Web Conference 2023, Austin, Texas
• Dwan Pereira, F., Oliveira, E., Rodrigues, L., Cabral, L., Oliveira, D., Carvalho, L., Gasevic, D., Cristea, A., Dermeval, D., & Ferreira Mello, R. (2023, September). Evaluation of a hybrid AI-human recommender for CS1 instructors in a real educational scenario. Presented at Eighteenth European Conference on Technology Enhanced Learning: ECTEL 2023, Aveiro, Portugal
• Nagai, T., Klem, S., Kayama, M., Asuke, T., Meccawy, M., Wang, J., Cristea, A. I., Stewart, C. D., & Shi, L. (2023, May). PICA-PICA: Exploring a Customisable Smart STEAM Educational Approach via a Smooth Combination of Programming, Engineering and Art. Presented at 2023 IEEE Global Engineering Education Conference (EDUCON), Kuwait
• Hodgson, R., Wang, J. W., Cristea, A., Matsuzaki, F., & Kubota, H. (2022, July). A Topic-Centric Crowdsourced Assisted Biomedical Literature Review Framework for Academics. Presented at 15th International Conference on Educational Data Mining, Durham, England
• Hodgson, R., Wang, J., Cristea, A. I., & Graham, J. (2022, December). Hybrid Weighted Retrieval of Twitter Users for Temporally Relevant Full-Text Querying in the Media Industry. Presented at 2022 13th International Congress on Advanced Applied Informatics Winter (IIAI-AAI-Winter), Phuket, Thailand
• Sun, Z., Harit, A., Cristea, A. I., Yu, J., Al Moubayed, N., & Shi, L. (2022, December). Is Unimodal Bias Always Bad for Visual Question Answering? A Medical Domain Study with Dynamic Attention. Presented at IEEE Big Data, Osaka, Japan
• Yu, J., Cristea, A. I., Harit, A., Sun, Z., Aduragba, O. T., Shi, L., & Al Moubayed, N. (2022, July). Efficient Uncertainty Quantification for Multilabel Text Classification. Presented at 2022 International Joint Conference on Neural Networks (IJCNN), Padova, Italy
• Sun, Z., Harit, A., Cristea, A. I., Yu, J., Shi, L., & Al Moubayed, N. (2022, July). Contrastive Learning with Heterogeneous Graph Attention Networks on Short Text Classification. Presented at 2022 International Joint Conference on Neural Networks (IJCNN), Padova, Italy
• Yu, J., Cristea, A. I., Harit, A., Sun, Z., Aduragba, O. T., Shi, L., & Al Moubayed, N. (2022, July). INTERACTION: A Generative XAI Framework for Natural Language Inference Explanations. Presented at 2022 International Joint Conference on Neural Networks (IJCNN), Padova, Italy
• Alsheri, M. A., Alrajhi, L. M., Alamri, A., & Cristea, A. I. (2021, September). MOOCSent: a Sentiment Predictor for Massive Open Online Courses. Presented at 29th International Conference on Information systems and Development (ISD2021), Valencia, Spain
• Alsheri, M. A., Alamri, A., Cristea, A. I., & Stewart, C. D. (2021, September). Forum-based Prediction of Certification in Massive Open Online Courses. Presented at 29th International Conference on Information systems and Development (ISD2021), Valencia, Spain
• Sun, Z., Harit, A., Yu, J., Cristea, A. I., & Shi, L. (2021, June). A Brief Survey of Deep Learning Approaches for Learning Analytics on MOOCs. Presented at Intelligent Tutoring Systems, Athens, Greece / Virtual
• Pereira, F. D., Piris, F., Cristo da Fonseca, S., Cristea, A., Oliveira, E. H., Carvalho, L., & Fernandes, D. (2021, March). Towards a Human-AI hybrid system for categorising programming problems. Presented at SIGCSE Technical Symposium
• Yu, J., Alrajhi, L., Harit, A., Sun, Z., Cristea, A. I., & Shi, L. (2021, June). Exploring Bayesian Deep Learning for Urgent Instructor Intervention Need in MOOC Forums. Presented at Intelligent Tutoring Systems, Athens, Greece / Virtual
• Pereira, F. D., Júnior, H. B. D. F., Oliveira, E. H. T. D., Carvalho, L. S. G. D., Oliveira, D. B. F. D., Benedict, A., Dorodchi, M., & Cristea, A. I. (2021, April). Automatic creating variation of CS1 assignments and exams. Presented at Anais Estendidos do I Simpósio Brasileiro de Educação em Computação (EDUCOMP Estendido 2021), Online
• Li, Z., Shi, L., Cristea, A. I., & Zhou, Y. (2023, June). A Survey of Collaborative Reinforcement Learning: Interactive Methods and Design Patterns. Presented at ACM Designing Interactive Systems (DIS), Virtual
• Alharbi, K., Cristea, A. I., Shi, L., Tymms, P., & Brown, C. (2021, June). Agent-based Simulation of the Classroom Environment to Gauge the Effect of Inattentive or Disruptive Students. Presented at Intelligent Tutoring Systems, Athens, Greece / Virtual
• Alharbi, K., Cristea, A. I., Shi, L., Tymms, P., & Brown, C. (2021, June). Agent-based Classroom Environment Simulation: the Effect of Disruptive Schoolchildren’s Behaviour versus Teacher Control over Neighbours. Presented at Artificial Intelligence in Education, Utrecht
• Pereira, F. D., Oliveira, E. H. T. D., Oliveira, D. B. F. D., Carvalho, L. S. G. D., & Cristea, A. I. (2021, April). Interpretable AI to Understand Early Effective and Ineffective Programming Behaviours from CS1 Learners. Presented at Anais Estendidos do I Simpósio Brasileiro de Educação em Computação (EDUCOMP Estendido 2021), Online
• Almuqren, L., & Cristea, A. I. (2021, December). COVID-19’s Impact on the Telecommunications Companies. Presented at World Conference on Information Systems and Technologies
• Hodgson, R., Cristea, A., Shi, L., & Graham, J. (2021, June). Wide-Scale Automatic Analysis of 20 Years of ITS Research. Presented at Intelligent Tutoring Systems, Athens, Greece / Virtual
• Sun, Z., Harit, A., Yu, J., Cristea, A., & Al Moubayed, N. (2021, July). A Generative Bayesian Graph Attention Network for Semi-supervised Classification on Scarce Data. Presented at IEEE International Joint Conference on Neural Network (IJCNN2021), Virtual
• Ji, W., Wang, K., Wang, X., Chen, T., & Cristea, A. I. (2020, October). Sequential Recommender via Time-aware Attentive Memory Network. Presented at 29th Conference on Information and Knowledge Management (CIKM), Virtual Event
• Aduragba, O. T., Yu, J., Cristea, A. I., Hardey, M., & Black, S. (2020, December). Digital Inclusion in Nothern England: Training Women from Underrepresented Communities in Tech: A Data Analytics Case Study. Presented at 2020 15th International Conference on Computer Science & Education (ICCSE)
• Yu, J., Aduragba, O. T., Sun, Z., Black, S., Stewart, C., Shi, L., & Cristea, A. (2020, December). Temporal Sentiment Analysis of Learners: Public Versus Private Social Media Communication Channels in a Women-in-Tech Conversion Course. Presented at 2020 15th International Conference on Computer Science & Education (ICCSE), Delft, Netherlands
• Fonseca, S. C., Pereira, F. D., Oliveira, E. H., Oliveira, D. B., Carvalho, L. S., & Cristea, A. I. (2020, December). Automatic Subject-based Contextualisation of Programming Assignment Lists. Presented at Educational Data Mining 2020 (EDM), Virtual
• Alrajhi, L., Alharbi, K., & Cristea, A. I. (2020, December). A Multidimensional Deep Learner Model of Urgent Instructor Intervention Need in MOOC Forum Posts. Presented at ITS 2020: International Conference on Intelligent Tutoring Systems
• Pereira, F. D., Toda, A., Oliveira, E. H., Cristea, A. I., Isotani, S., Laranjeira, D., Almeida, A., & Mendonça, J. (2021, June). Can We Use Gamification to Predict Students’ Performance? A Case Study Supported by an Online Judge. Presented at ITS 2020, Athens / Virtual
• Toda, A., Pereira, F. D., Klock, A. C. T., Rodrigues, L., Palomino, P., Oliveira, W., Oliveira, E. H. T., Gasparini, I., Cristea, A. I., & Isotani, S. (2020, December). For whom should we gamify? Insights on the users intentions and context towards gamification in education. Presented at Simpósio Brasileiro de Informática na Educação (SBIE 2020), Porto Alegre, Brazil
• Toda, A., Klock, A. C. T., Palomino, P. T., Rodrigues, L., Oliveira, W., Stewart, C., Cristea, A. I., Gasparini, I., & Isotani, S. (2020, October). GamiCSM: relating education, culture and gamification - a link between worlds. Presented at 19th Brazilian Symposium on Human Factors in Computing Systems, Diamantina, Brazil
• Alharbi, K., Alrajhi, L., Cristea, A. I., Bittencourt, I. I., Isotani, S., & James, A. (2020, December). Data-Driven Analysis of Engagement in Gamified Learning Environments: A Methodology for Real-Time Measurement of MOOCs. Presented at 16th International Conference, ITS 2020
• Toda, A., Oliveira, W., Shi, L., Bittencourt, I. I., Isotani, S., & Cristea, A. I. (2019, July). Planning Gamification Strategies based on User Characteristics and DM: A Gender-based Case Study. Presented at International Conference on Educational Data Mining, Montréal, Canada
• Toda, A., Oliveira, W., Klock, A., Shi, L., Bittencourt, I. I., Gasparini, I., Isotani, S., Cristea, A. I., & Palomino, P. (2019, July). A Taxonomy of Game Elements for Gamification in Educational Contexts: Proposal and Evaluation. Presented at International Conference on Advanced Learning Technologies and Technology-enhanced Learning, Maceió, Brazil
• Tsakalidis, A., Liakata, M., Damoulas, T., & Cristea, A. I. (2018, September). Can We Assess Mental Health through Social Media and Smart Devices? Addressing Bias in Methodology and Evaluation. Presented at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2018 Applied Data Science Track), Dublin
• Toledo Palomino, P., Toda, A. M., Oliveira, W., Cristea, A. I., & Isotani, S. (2019, July). Narrative for Gamification in Education: Why Should you Care?. Presented at 2019 IEEE 19th International Conference on Advanced Learning Technologies (ICALT), Maceio, Brazil
• Palomino, P., Toda, A., Oliveira, W., Rodrigues, L., Cristea, A. I., & Isotani, S. (2019, December). Exploring content game elements to support gamification design in educational systems: narrative and storytelling. Presented at Anais do XXX Simpósio Brasileiro de Informática na Educação (SBIE 2019)
• Aduragba, O. T., & Cristea, A. I. (2019, December). Research on Prediction of Infectious Diseases, their spread via Social Media and their link to Education. Presented at 4th International Conference on Information and Education Innovations - ICIEI 2019, Durham
• Pereira, F. D., Oliveira, E. H., Fernandes, D., & Cristea, A. (2019, July). Early Performance Prediction for CS1 Course Students using a Combination of Machine Learning and an Evolutionary Algorithm. Presented at 2019 IEEE 19th International Conference on Advanced Learning Technologies (ICALT), Maceio, Brazil
• (2019, December). Proceedings of the 3rd Conference on Computing Education Practice. Presented at Computing Education Practice, Durham, UK
• Aljohani, T., & Cristea, A. I. (2019, December). Predicting Learners' Demographics Characteristics: Deep Learning Ensemble Architecture for Learners' Characteristics Prediction in MOOCs. Presented at ICIEI 2019: 2019 The 4th International Conference on Information and Education Innovations
• Pereira, F. D., Oliveira, E., Cristea, A., Fernandes, D., Silva, L., Aguiar, G., Alamri, A., & Alshehri, M. (2019, June). Early Dropout Prediction for Programming Courses Supported by Online Judges. Presented at AIED 2019, Chicago, IL
• Shi, L., & Cristea, A. (2018, October). Demographic Indicators Influencing Learning Activities in MOOCs: Learning Analytics of FutureLearn Courses. Presented at 27th International Conference on Information Systems Development (ISD2018)., Lund
• Cristea, A., Alshehri, M., Alamri, A., Kayama, M., Stewart, C., & Shi, L. (2018, October). How is learning fluctuating? FutureLearn MOOCs fine-grained temporal Analysis and Feedback to Teachers. Presented at 27th International Conference on Information Systems Development (ISD2018)., Lund
• Cristea, A., Alamri, A., Kayama, M., Stewart, C., Alsheri, M., & Shi, L. (2018, October). Earliest Predictor of Dropout in MOOCs: A Longitudinal Study of FutureLearn Courses. Presented at 27th International Conference on Information Systems Development (ISD2018)., Lund, Sweden
• Lei, S., & Cristea, A. (2018, December). In-depth Exploration of Engagement Patterns in MOOCs. Presented at Web Information Systems Engineering (WISE 2018), Dubai
• Tsakalidis, A., Aletras, N., Cristea, A., & Liakata, M. (2018, December). Nowcasting the Stance of Social Media Users in a Sudden Vote: The Case of the Greek Referendum. Presented at 2018 ACM Conference on Information and Knowledge Management (CIKM’18), Torino
• Cristea, A. I., Alamri, A., Kayama, M., Stewart, C., Alshehri, M., & Shi, L. (2018, August). Earliest Predictor of Dropout in MOOCs: A Longitudinal Study of FutureLearn Courses. Presented at 27th International Conference on Information Systems Development (ISD2018)., Lund, Sweden
• Cristea, A. I., Alamri, A., Kayama, M., Stewart, C., Alshehri, M., & Shi, L. (2018, December). How is Learning Fluctuating? FutureLearn MOOCs Fine-grained Temporal Analysis and Feedback to Teachers and Designers. Presented at 27th International Conference on Information Systems Development (ISD2018), Lund, Sweden
• Khan, J., Cristea, A., & Alamri, A. (2018, June). A large-scale category-based evaluation of a visual language for adaptive hypermedia. Presented at 3rd International Conference on Information and Education Innovations (ICIEI'18), London
• Alshehri, M., Foss, J., Cristea, A. I., Kayama, M., Shi, L., Alamri, A., & Tsakalidis, A. (2018, June). On the need for fine-grained analysis of Gender versus Commenting Behaviour in MOOCs. Presented at 3rd International Conference on Information and Education Innovations (ICIEI'18), London
• Alamri, A., Rusby, H., Cristea, A. I., Khan, J., Shi, L., & Stewart, C. (2018, June). An intuitive Authoring System for a Personalised, Social, Gamified, Visualisation-supporting e-learning System. Presented at 3rd International Conference on Information and Education Innovations (ICIEI'18), London
• Zhou, Y., Cristea, A. I., & Shi, L. (2017, October). Connecting Targets to Tweets: Semantic Attention-based Model for Target-Specific stance Detection. Presented at Web Information Systems Engineering – WISE 2017, 18th International Conference, Moscow
• Alessandrini, A., Cristea, A., Hartikainen, M., Isomäki, H., & Tuhkala, A. (2017, December). Identifying Objectives for a Learning Space Management System with Value-focused Thinking. Presented at Proceedings of the 9th International Conference on Computer Supported Education, Porto, Portugal
• Tsakalidis, A., Liakata, M., Damoulas, T., Jellinek, B., Guo, W., & Cristea, A. (2016, December). Combining heterogeneous user generated data to sense well-being. Presented at COLING 2016, Osaka
• Zhou, Y., Kanhabua, N., & Cristea, A. (2016, August). Real-time timeline summarisation for high-impact events in Twitter. Presented at ECAI 2016, The Hague
• Cristea, A., & Shi, L. (2016, December). Motivational gamification strategies rooted in self-determination theory for social adaptive E-Learning. Presented at Intelligent Tutoring Systems, 13th International Conference, ITS 2016, Zagreb
• Zhou, Y., Demidova, E., & Cristea, A. (2016, April). Who likes me more? Analysing entity-centric language-specific bias in multilingual Wikipedia. Presented at SAC 2016, 31st ACM Symposium on Applied Computing, Pisa
• Zhou, Y., & Cristea, A. (2016, December). Towards detection of influential sentences affecting reputation in Wikipedia. Presented at ACM Web Science Conference 2016, Hannover
• Townsend, R., Tsakalidis, A., Zhou, Y., Wang, B., Liakata, M., Zubiaga, A., Cristea, A., & Procter, R. (2015, June). WarwickDCS : from phrase-based to target-specific sentiment recognition. Presented at 9th International Workshop on Semantic Evaluation (SemEval 2015), Denver
• Hadzidedic Bazdarevic, S., & Cristea, A. I. (2015, November). What do people affected by cancer talk about online? Text analysis of online cancer community usage in Bosnia and Herzegovina. Presented at Fifth International Conference on Social Medial Technologies, Communication and Informatics (SOTICS), Barcelona, Spain
• Al Qudah, D. A., Cristea, A. I., Hadzidedic Bazdarevic, S., Al-Saqqa, S., & Al-Sayyad, R. M. (2015, October). A Taxonomy-Based Evaluation of Personalized E-Advertisement. Presented at IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing, Liverpool, UK
• Shi, L., Cristea, A. I., & Hadzidedic, S. (2014, October). The Critical Role of Profiles in Social E-Learning Design. Presented at 15th Annual Conference on Information Technology Education (SIGITE), Atlanta, Georgia, US
• Shi, L., Cristea, A., Awan, M., Stewart, C., & Hendrix, M. (2013, May). Towards understanding learning behavior patterns in social adaptive personalized e-learning systems. Presented at 19th Americas Conference on Information Systems, Chicago
• Gkotsis, G., Stepanyan, K., Cristea, A., & Joy, M. (2013, May). Zero-cost labelling with web feeds for weblog data extraction. Presented at 23rd International World Wide Web Conference (WWW 2013)

Journal Article

• Chang, H., Wang, X., Cristea, A. I., Meng, X., Hu, Z., & Pan, Z. (2025). Explainable artificial intelligence and advanced feature selection methods for predicting gas concentration in longwall mining. Information Fusion, 118, Article 102976. https://doi.org/10.1016/j.inffus.2025.102976
• Al-Qudah, D. A., Al-Zoubi, A. M., Cristea, A. I., Merelo-Guervós, J. J., Castillo, P. A., & Faris, H. (2025). Prediction of sentiment polarity in restaurant reviews using an ordinal regression approach based on evolutionary XGBoost. PeerJ Computer Science, 11, Article e2370. https://doi.org/10.7717/peerj-cs.2370
• Alrajhi, L., Alamri, A., Pereira, F. D., Cristea, A. I., & Oliveira, E. H. T. (2024). Solving the imbalanced data issue: automatic urgency detection for instructor assistance in MOOC discussion forums. User Modeling and User-Adapted Interaction, 34(3), 797-852. https://doi.org/10.1007/s11257-023-09381-y
• Rodrigues, L., Palomino, P. T., Toda, A. M., Klock, A. C., Pessoa, M., Pereira, F. D., Oliveira, E. H., Oliveira, D. F., Cristea, A. I., Gasparini, I., & Isotani, S. (2024). How Personalization Affects Motivation in Gamified Review Assessments. International Journal of Artificial Intelligence in Education, 34(2), 147-184. https://doi.org/10.1007/s40593-022-00326-x
• Hodgson, R., Wang, J., Cristea, A. I., & Graham, J. (2024). Partially-Supervised Metric Learning via Dimensionality Reduction of Text Embeddings using Transformer Encoders and Attention Mechanisms. IEEE Access, 12, 77536-77554. https://doi.org/10.1109/access.2024.3403991
• Cristea, A. I., Alamri, A., Alshehri, M., Dwan Pereira, F., Toda, A. M., Harada T. de Oliveira, E., & Stewart, C. (2024). The engage taxonomy: SDT-based measurable engagement indicators for MOOCs and their evaluation. User Modeling and User-Adapted Interaction, 34(2), 323-374. https://doi.org/10.1007/s11257-023-09374-x
• Frantzidis, C. A., Peristeri, E., Andreou, M., & Cristea, A. I. (2024). Editorial: New challenges and future perspectives in cognitive neuroscience. Frontiers in Human Neuroscience, 18, Article 1390788. https://doi.org/10.3389/fnhum.2024.1390788
• Yacobson, E., Toda, A. M., Cristea, A. I., & Alexandron, G. (2024). Recommender systems for teachers: The relation between social ties and the effectiveness of socially-based features. Computers & Education, 210, Article 104960. https://doi.org/10.1016/j.compedu.2023.104960
• Li, Z., Shi, L., Wang, J., Cristea, A. I., & Zhou, Y. (2023). Sim-GAIL: A generative adversarial imitation learning approach of student modelling for intelligent tutoring systems. Neural Computing and Applications, 35(34), 24369-24388. https://doi.org/10.1007/s00521-023-08989-w
• Almeqren, M. A., Almegren, M., Alhayan, F., Cristea, A. I., & Pennington, D. R. (2023). Using deep learning to analyze the psychological effects of COVID-19. Frontiers in Psychology, 14, Article 962854. https://doi.org/10.3389/fpsyg.2023.962854
• Almuqren, L., & Cristea, A. I. (2023). Predicting STC Customers' Satisfaction Using Twitter. IEEE Transactions on Computational Social Systems, 10(1), 204-210. https://doi.org/10.1109/tcss.2021.3135719
• Yu, J., Cristea, A. I., Harit, A., Sun, Z., Aduragba, O. T., Shi, L., & Al Moubayed, N. (2023). Language as a latent sequence: Deep latent variable models for semi-supervised paraphrase generation. AI open, 4, 19-32. https://doi.org/10.1016/j.aiopen.2023.05.001
• Pereira, F. D., Fonseca, S. C., Wiktor, S., Oliveira, D. B., Cristea, A. I., Benedict, A., Fallahian, M., Dorodchi, M., Carvalho, L. S., Mello, R. F., & Oliveira, E. H. (2023). Toward Supporting CS1 Instructors and Learners With Fine-Grained Topic Detection in Online Judges. IEEE Access, 11, https://doi.org/10.1109/access.2023.3247189
• Rodrigues, L., Pereira, F. D., Toda, A. M., Palomino, P. T., Pessoa, M., Carvalho, L. S. G., Fernandes, D., Oliveira, E. H., Cristea, A. I., & Isotani, S. (2022). Gamification suffers from the novelty effect but benefits from the familiarization effect: Findings from a longitudinal study. International Journal of Educational Technology in Higher Education, 19(1), https://doi.org/10.1186/s41239-021-00314-6
• Alshehri, M., Alamri, A., Cristea, A. I., & Stewart, C. D. (2021). Towards Designing Profitable Courses: Predicting Student Purchasing Behaviour in MOOCs. International Journal of Artificial Intelligence in Education, 31(2), 215-233. https://doi.org/10.1007/s40593-021-00246-2
• Pereira, F. D., Fonseca, S. C., Oliveira, E. H., Cristea, A. I., Bellhauser, H., Rodrigues, L., Oliveira, D. B., Isotani, S., & Carvalho, L. S. (2021). Explaining Individual and Collective Programming Students’ Behavior by Interpreting a Black-Box Predictive Model. IEEE Access, 9, 117097-117119. https://doi.org/10.1109/access.2021.3105956
• Almuqren, L., & Cristea, A. (2021). AraCust: a Saudi Telecom Tweets corpus for sentiment analysis. PeerJ Computer Science, 7, Article e510. https://doi.org/10.7717/peerj-cs.510
• Aljohani, T., & Cristea, A. I. (2021). Learners Demographics Classification on MOOCs During the COVID-19: Author Profiling via Deep Learning Based on Semantic and Syntactic Representations. Frontiers in Research Metrics and Analytics, 6, Article 673928. https://doi.org/10.3389/frma.2021.673928
• Almuqren, L., Alrayes, F. S., & Cristea, A. I. (2021). An Empirical Study on Customer Churn Behaviours Prediction Using Arabic Twitter Mining Approach. Future Internet, 13(7), Article 175. https://doi.org/10.3390/fi13070175
• Pereira, F. D., Oliveira, E. H., Oliveira, D., Cristea, A. I., Carvalho, L. S., Fonseca, S., Toda, A., & Isotani, S. (2020). Using learning analytics in the Amazonas: understanding students’ behaviour in introductory programming. British Journal of Educational Technology, 51(4), 955-972. https://doi.org/10.1111/bjet.12953
• Al Qudah, D. A., Al-Shboul, B., Al-Zoubi, A., Al-Sayyed, R., & Cristea, A. I. (2020). Investigating users’ experience on social media ads: perceptions of young users. Heliyon, 6(7), Article e04378. https://doi.org/10.1016/j.heliyon.2020.e04378
• Pereira, F. D., Fonseca, S. C., Oliveira, E. H., Oliveira, D. B., Cristea, A. I., & Carvalho, L. S. (2020). Deep learning for early performance prediction of introductory programming students: a comparative and explanatory study. Revista Brasileira de Informática na Educação, 28, 723-749. https://doi.org/10.5753/rbie.2020.28.0.723
• Toda, A. M., Palomino, P. T., Oliveira, W., Rodrigues, L., Klock, A. C., Gasparini, I., Cristea, A. I., & Isotani, S. (2019). How to Gamify learning Systems? An Experience Report using the Design Sprint Method and a Taxonomy for Gamification Elements in Education. Journal of Educational Technology & Society, 22(3), 47-60
• Toda, A. M., Klock, A. C., Oliveira, W., Palomino, P. T., Rodrigues, L., Shi, L., Bittencourt, I., Gasparini, I., Isotani, S., & Cristea, A. I. (2019). Analysing Gamification Elements in Educational Environments Using an Existing Gamification Taxonomy. Smart Learning Environments, 6(1), https://doi.org/10.1186/s40561-019-0106-1
• Tsakalidis, A., Papadopoulos, S., Voskaki, R., Ioannidou, K., Boididou, C., Cristea, A., Liakata, M., & Kompatsiaris, Y. (2018). Building and evaluating resources for sentiment analysis in the Greek language. Language Resources and Evaluation, 52(4), 1021-1044. https://doi.org/10.1007/s10579-018-9420-4
• Qaffas, A. A., Cristea, A., & Mead, M. A. (2018). Lightweight adaptive E-Advertising Model. Journal of Universal Computer Science, 24(7), 935-974
• Gkiokas, A., & Cristea, A. (2018). Cognitive agents and machine learning by example : representation with conceptual graphs. Computational Intelligence, 34(2), 603-634. https://doi.org/10.1111/coin.12167
• Hadzidedic Bazdarevic, S., & Cristea, A. I. (2017). Do personalisation and emotions affect the use of cancer-related websites?. Online Information Review, 41(1), 102-118. https://doi.org/10.1108/oir-09-2015-0305
• Hadzidedic Bazdarevic, S., & Cristea, A. I. (2015). How emotions stimulate people affected by cancer to use personalised health websites. Knowledge management & e-learning: an international journal, 7(4), 658-676
• Shi, L., & Cristea, A. I. (2015). Learners Thrive When Using Multifaceted Open Social Learner Models. IEEE MultiMedia, 23(1), 36-47. https://doi.org/10.1109/mmul.2015.93
• Tsakalidis, A., Papadopoulos, S., Cristea, A., & Kompatsiaris, Y. (2015). Predicting elections for multiple countries using Twitter and polls. IEEE Intelligent Systems, 30(2), 10-17. https://doi.org/10.1109/mis.2015.17
• Ashman, H., Brailsford, T., Cristea, A., Sheng, Q. Z., Stewart, C., Toms, E. G., & Wade, V. (2014). The ethical and social implications of personalization technologies for e-learning. Information and Management, 51(6), 819-832. https://doi.org/10.1016/j.im.2014.04.003
• Cristea, A., Katsaros, D., & Manolopoulos, Y. (2014). Introduction to the special issue of the journal World Wide Web: Social media preservation and applications. World Wide Web, 17(4), 691-693. https://doi.org/10.1007/s11280-014-0282-4
• Gkotsis, G., Stepanyan, K., Cristea, A., & Joy, M. (2013). Entropy-based automated wrapper generation for weblog data extraction. World Wide Web, 17(4), 827-846. https://doi.org/10.1007/s11280-013-0269-6

Working Paper

• Hadzidedic, S., Cristea, A., & Watson, D. Effect of emotions and personalisation on cancer website reuse intentions