Staff profile

Bio

Alexandra I. Cristea is Professor, Deputy Executive Dean of the Faculty of Science, Director of Research and 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 Advisory Board Member at the Ustinov College, Alan Turing Academic Liason for Durham, N8 CIR Digital Humanities team lead for Durham and member of the IEEE European Public Policy on ICT. Her research includes web science, learning analytics, user modelling and personalisation, semantic web, social web, authoring, with over 300 papers on these subjects (over 5700 citations on Google Scholar, h-index 40). Especially, her work on frameworks for adaptive systems has influenced many researchers and is highly cited (with the top paper with over 220 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 ATI@Durham Research Network (2022); the Epistemological Engine (2021-22); Weizman Institute funded JANET (Joint Lab in Learning Analytics for Personalised Science Teaching) project (2020-2023); Predictive and prescriptive analytics for the media industry, Distinctive Publishing (2019-2023); 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 (Bootcamp 2021) (2019-2020: training 100 women in computer science from various (BAME) backgrounds). She has been keynote/invited speaker, chair, organiser, co-organizer, panellist and program committee member of various conferences in her research field (including, for example, ITS, AIED, UMAP, ED-MEDIA, Hypertext, Adaptive Hypermedia, EDM, ICCE, ICAI). She is an , Associate Editor of the ACM Computing Surveys, Associate Editor of Frontiers in Artificial Intelligence and she was Associate Editor of 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

Publications

• Google Scholar
• past paper list kept at Warwick

• 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

• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• Pereira, F. D., Junior, H. B., Rodriquez, L., Toda, A., Oliveira, E. H., Cristea, A. I., …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
• 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

• Aduragba, T. O., Yu, J., Cristea, A. I., & Long, Y. (in press). Improving Health Mention Classification through Emphasising Literal Meanings: a Study Towards Diversity and Generalisation for Public Health Surveillance.
• Nagai, T., Klem, S., Kayama, M., Asuke, T., Meccawy, M., Wang, J., …Shi, L. (2023). PICA-PICA: Exploring a Customisable Smart STEAM Educational Approach via a Smooth Combination of Programming, Engineering and Art. . https://doi.org/10.1109/educon54358.2023.10125184
• Dwan Pereira, F., Oliveira, E., Rodrigues, L., Cabral, L., Oliveira, D., Carvalho, L., …Ferreira Mello, R. (2023). Evaluation of a hybrid AI-human recommender for CS1 instructors in a real educational scenario. In Responsive and Sustainable Educational Futures: 18th European Conference on Technology Enhanced Learning, EC-TEL 2023, Aveiro, Portugal, September 4–8, 2023, Proceedings (308-323). https://doi.org/10.1007/978-3-031-42682-7_21
• Hodgson, R., Wang, J. W., Cristea, A., Matsuzaki, F., & Kubota, H. (2022). A Topic-Centric Crowdsourced Assisted Biomedical Literature Review Framework for Academics. In A. Mitrovic, & N. Bosch (Eds.), . https://doi.org/10.5281/zenodo.6853001
• Yu, J., Cristea, A. I., Harit, A., Sun, Z., Aduragba, O. T., Shi, L., & Al Moubayed, N. (2022). Efficient Uncertainty Quantification for Multilabel Text Classification. . https://doi.org/10.1109/ijcnn55064.2022.9892871
• Sun, Z., Harit, A., Cristea, A. I., Yu, J., Al Moubayed, N., & Shi, L. (2022). Is Unimodal Bias Always Bad for Visual Question Answering? A Medical Domain Study with Dynamic Attention. . https://doi.org/10.1109/bigdata55660.2022.10020791
• Yu, J., Cristea, A. I., Harit, A., Sun, Z., Aduragba, O. T., Shi, L., & Al Moubayed, N. (2022). INTERACTION: A Generative XAI Framework for Natural Language Inference Explanations. . https://doi.org/10.1109/ijcnn55064.2022.9892336
• Sun, Z., Harit, A., Cristea, A. I., Yu, J., Shi, L., & Al Moubayed, N. (2022). Contrastive Learning with Heterogeneous Graph Attention Networks on Short Text Classification. . https://doi.org/10.1109/ijcnn55064.2022.9892257
• Hodgson, R., Wang, J., Cristea, A. I., & Graham, J. (2022). Hybrid Weighted Retrieval of Twitter Users for Temporally Relevant Full-Text Querying in the Media Industry. . https://doi.org/10.1109/iiai-aai-winter58034.2022.00018
• Alsheri, M. A., Alrajhi, L. M., Alamri, A., & Cristea, A. I. (2021). MOOCSent: a Sentiment Predictor for Massive Open Online Courses.
• Alsheri, M. A., Alamri, A., Cristea, A. I., & Stewart, C. D. (2021). Forum-based Prediction of Certification in Massive Open Online Courses.
• Sun, Z., Harit, A., Yu, J., Cristea, A. I., & Shi, L. (2021). A Brief Survey of Deep Learning Approaches for Learning Analytics on MOOCs. In A. Cristea, & C. Troussas (Eds.), . https://doi.org/10.1007/978-3-030-80421-3_4
• Pereira, F. D., Piris, F., Cristo da Fonseca, S., Cristea, A., Oliveira, E. H., Carvalho, L., & Fernandes, D. (2021). Towards a Human-AI hybrid system for categorising programming problems. In SIGCSE '21: Proceedings of the 52nd ACM Technical Symposium on Computer Science Education (94-100). https://doi.org/10.1145/3408877.3432422
• Pereira, F. D., Oliveira, E. H. T. D., Oliveira, D. B. F. D., Carvalho, L. S. G. D., & Cristea, A. I. (2021). Interpretable AI to Understand Early Effective and Ineffective Programming Behaviours from CS1 Learners. . https://doi.org/10.5753/educomp_estendido.2021.14853
• Alharbi, K., Cristea, A. I., Shi, L., Tymms, P., & Brown, C. (2021). Agent-based Classroom Environment Simulation: the Effect of Disruptive Schoolchildren’s Behaviour versus Teacher Control over Neighbours. In I. Roll, M. Danielle, S. Sergey, L. Rose, & D. Vania (Eds.), Artificial Intelligence in Education Lecture Notes in Computer Science (48-53). https://doi.org/10.1007/978-3-030-78270-2_8
• Yu, J., Alrajhi, L., Harit, A., Sun, Z., Cristea, A. I., & Shi, L. (2021). Exploring Bayesian Deep Learning for Urgent Instructor Intervention Need in MOOC Forums. In A. I. Cristea, & C. Troussos (Eds.), Intelligent Tutoring Systems (78-90). https://doi.org/10.1007/978-3-030-80421-3_10
• Li, Z., Shi, L., Cristea, A. I., & Zhou, Y. (2021). A Survey of Collaborative Reinforcement Learning: Interactive Methods and Design Patterns. . https://doi.org/10.1145/3461778.3462135
• Alharbi, K., Cristea, A. I., Shi, L., Tymms, P., & Brown, C. (2021). Agent-based Simulation of the Classroom Environment to Gauge the Effect of Inattentive or Disruptive Students. In A. I. Cristea, & C. Troussas (Eds.), Intelligent Tutoring Systems 17th International Conference, ITS 2021, Virtual Event, June 7–11, 2021, Proceedings (211-223). https://doi.org/10.1007/978-3-030-80421-3_23
• Hodgson, R., Cristea, A., Shi, L., & Graham, J. (2021). Wide-Scale Automatic Analysis of 20 Years of ITS Research. In A. I. Cristea, & C. Troussas (Eds.), Intelligent Tutoring Systems 17th International Conference, ITS 2021, Virtual Event, June 7–11, 2021, Proceedings (8-21). https://doi.org/10.1007/978-3-030-80421-3_2
• Sun, Z., Harit, A., Yu, J., Cristea, A., & Al Moubayed, N. (2021). A Generative Bayesian Graph Attention Network for Semi-supervised Classification on Scarce Data. . https://doi.org/10.1109/ijcnn52387.2021.9533981
• Almuqren, L., & Cristea, A. I. (2021). COVID-19’s Impact on the Telecommunications Companies. In Á. Rocha, H. Adeli, G. Dzemyda, F. Moreira, & A. M. R. Correia (Eds.), WorldCIST 2021: Trends and Applications in Information Systems and Technologies (318-327). https://doi.org/10.1007/978-3-030-72654-6_31
• 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., …Cristea, A. I. (2021). Automatic creating variation of CS1 assignments and exams. . https://doi.org/10.5753/educomp_estendido.2021.14856
• Ji, W., Wang, K., Wang, X., Chen, T., & Cristea, A. I. (2020). Sequential Recommender via Time-aware Attentive Memory Network. In Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM ’20), October 19–23, 2020, Virtual Event, Ireland (565-574). https://doi.org/10.1145/3340531.3411869
• Yu, J., Aduragba, O. T., Sun, Z., Black, S., Stewart, C., Shi, L., & Cristea, A. (2020). Temporal Sentiment Analysis of Learners: Public Versus Private Social Media Communication Channels in a Women-in-Tech Conversion Course. In International Conference on Computer Science & Education (ICCSE) (182-187). https://doi.org/10.1109/iccse49874.2020.9201631
• Alharbi, K., Alrajhi, L., Cristea, A. I., Bittencourt, I. I., Isotani, S., & James, A. (2020). Data-Driven Analysis of Engagement in Gamified Learning Environments: A Methodology for Real-Time Measurement of MOOCs. In V. Kumar, & C. Troussas (Eds.), Intelligent Tutoring Systems (142-151). https://doi.org/10.1007/978-3-030-49663-0_18
• Alrajhi, L., Alharbi, K., & Cristea, A. I. (2020). A Multidimensional Deep Learner Model of Urgent Instructor Intervention Need in MOOC Forum Posts. In C. Troussas, & V. Kumar (Eds.), ITS 2020: Intelligent Tutoring Systems (226-236). https://doi.org/10.1007/978-3-030-49663-0_27
• Fonseca, S. C., Pereira, F. D., Oliveira, E. H., Oliveira, D. B., Carvalho, L. S., & Cristea, A. I. (2020). Automatic Subject-based Contextualisation of Programming Assignment Lists. In A. N. Rafferty, J. Whitehill, C. Romero, & V. Cavalli-Sforza (Eds.), Proceedings of the 13th International Conference on Educational Data Mining (81-91)
• Aduragba, O. T., Yu, J., Cristea, A. I., Hardey, M., & Black, S. (2020). Digital Inclusion in Nothern England: Training Women from Underrepresented Communities in Tech: A Data Analytics Case Study. In 2020 15th International Conference on Computer Science & Education (ICCSE) (162-168). https://doi.org/10.1109/iccse49874.2020.9201693
• Toda, A., Klock, A. C. T., Palomino, P. T., Rodrigues, L., Oliveira, W., Stewart, C., …Isotani, S. (2020). GamiCSM: relating education, culture and gamification - a link between worlds. . https://doi.org/10.1145/3424953.3426490
• Toda, A., Pereira, F. D., Klock, A. C. T., Rodrigues, L., Palomino, P., Oliveira, W., …Isotani, S. (2020). For whom should we gamify? Insights on the users intentions and context towards gamification in education. . https://doi.org/10.5753/cbie.sbie.2020.471
• Pereira, F. D., Toda, A., Oliveira, E. H., Cristea, A. I., Isotani, S., Laranjeira, D., …Mendonça, J. (2020). Can We Use Gamification to Predict Students’ Performance? A Case Study Supported by an Online Judge. . https://doi.org/10.1007/978-3-030-49663-0_30
• Toda, A., Oliveira, W., Klock, A., Shi, L., Bittencourt, I. I., Gasparini, I., …Palomino, P. (2019). A Taxonomy of Game Elements for Gamification in Educational Contexts: Proposal and Evaluation. . https://doi.org/10.1109/icalt.2019.00028
• Toda, A., Oliveira, W., Shi, L., Bittencourt, I. I., Isotani, S., & Cristea, A. I. (2019). Planning Gamification Strategies based on User Characteristics and DM: A Gender-based Case Study. In M. Desmarais, C. F. Lynch, A. Merceron, & R. Nkambou (Eds.), Proceedings of the 12th International Conference on Educational Data Mining (438-443)
• Tsakalidis, A., Liakata, M., Damoulas, T., & Cristea, A. I. (2019). Can We Assess Mental Health through Social Media and Smart Devices? Addressing Bias in Methodology and Evaluation. In U. Brefeld, E. Curry, E. Daly, B. MacNamee, A. Marascu, F. Pinelli, …N. Hurley (Eds.), Machine Learning and Knowledge Discovery in Databases. European Conference, ECML PKDD 2018, Dublin, Ireland, September 10–14, 2018, Proceedings, Part III (407-423). https://doi.org/10.1007/978-3-030-10997-4_25
• Pereira, F. D., Oliveira, E. H., Fernandes, D., & Cristea, A. (2019). Early Performance Prediction for CS1 Course Students using a Combination of Machine Learning and an Evolutionary Algorithm. . https://doi.org/10.1109/icalt.2019.00066
• Aljohani, T., & Cristea, A. I. (2019). Predicting Learners' Demographics Characteristics: Deep Learning Ensemble Architecture for Learners' Characteristics Prediction in MOOCs. In Proceedings of the 2019 4th International Conference on Information and Education Innovations - ICIEI 2019 (23-27). https://doi.org/10.1145/3345094.3345119
• Aduragba, O. T., & Cristea, A. I. (2019). Research on Prediction of Infectious Diseases, their spread via Social Media and their link to Education. In Proceedings of the 2019 4th International Conference on Information and Education Innovations (ICIEI 2019) (38-42). https://doi.org/10.1145/3345094.3345118
• (2019). Proceedings of the 3rd Conference on Computing Education Practice. In S. Bradley, & A. Cristea (Eds.), Proceedings of the 3rd Conference on Computing Education Practice
• Pereira, F. D., Oliveira, E., Cristea, A., Fernandes, D., Silva, L., Aguiar, G., …Alshehri, M. (2019). Early Dropout Prediction for Programming Courses Supported by Online Judges. In S. Isotani, E. Millán, A. Ogan, P. Hastings, B. McLaren, & R. Luckin (Eds.), . https://doi.org/10.1007/978-3-030-23207-8_13
• Pereira, F. D., Oliveira, E., Cristea, A. I., Fernandes, D., Silva, L., Aguiar, G., …Alshehri, M. (2019). Early Dropout Prediction for Programming Courses supported by Online Judges. In S. Isotani, E. Millán, A. Ogan, P. Hastings, B. McLaren, & R. Luckin (Eds.), 20th International Conference, AIED 2019, Chicago, IL, USA, June 25-29, 2019, Proceedings, Part II. https://doi.org/10.1007/978-3-030-23207-8_13
• Toledo Palomino, P., Toda, A. M., Oliveira, W., Cristea, A. I., & Isotani, S. (2019). Narrative for Gamification in Education: Why Should you Care?. . https://doi.org/10.1109/icalt.2019.00035
• Palomino, P., Toda, A., Oliveira, W., Rodrigues, L., Cristea, A. I., & Isotani, S. (2019). Exploring content game elements to support gamification design in educational systems: narrative and storytelling. . https://doi.org/10.5753/cbie.sbie.2019.773
• Cristea, A., Alamri, A., Kayama, M., Stewart, C., Alsheri, M., & Shi, L. (2018). Earliest Predictor of Dropout in MOOCs: A Longitudinal Study of FutureLearn Courses. In B. Andersson, B. Johansson, S. Carlsson, C. Barry, M. Lang, H. Linger, & C. Schneider (Eds.), Information Systems Development: Designing Digitalization (ISD2018 Proceedings). Lund, Sweden: Lund University
• Cristea, A., Alshehri, M., Alamri, A., Kayama, M., Stewart, C., & Shi, L. (2018). How is learning fluctuating? FutureLearn MOOCs fine-grained temporal Analysis and Feedback to Teachers. In B. Andersson, B. Johansson, S. Carlsson, C. Barry, M. Lang, H. Linger, & C. Schneider (Eds.), Proceedings of the 27th International Conference on Information Systems Development (ISD2018), Education Track, Lund, Sweden, August 22-24, 2018
• Shi, L., & Cristea, A. (2018). Demographic Indicators Influencing Learning Activities in MOOCs: Learning Analytics of FutureLearn Courses. In B. Andersson, B. Johansson, S. Carlsson, C. Barry, M. Lang, H. Linger, & C. Schneider (Eds.), Information Systems Development: Designing Digitalization (ISD2018 Proceedings). Lund, Sweden: Lund University
• Lei, S., & Cristea, A. (2018). In-depth Exploration of Engagement Patterns in MOOCs. In H. Hacid, W. Cellary, H. Wang, H. Paik, & R. Zhou (Eds.), Web information systems engineering - WISE 2018 : 19th International Conference, Dubai, United Arab Emirates, November 12-15, 2018. Proceedings. Part II (395-409). https://doi.org/10.1007/978-3-030-02925-8_28
• Tsakalidis, A., Aletras, N., Cristea, A., & Liakata, M. (2018). Nowcasting the Stance of Social Media Users in a Sudden Vote: The Case of the Greek Referendum. In Proceedings of the 27th ACM International Conference on Information and Knowledge Management (367-376). https://doi.org/10.1145/3269206.3271783
• Cristea, A. I., Alamri, A., Kayama, M., Stewart, C., Alshehri, M., & Shi, L. (2018). Earliest Predictor of Dropout in MOOCs: A Longitudinal Study of FutureLearn Courses. In B. Andersson, B. Johansson, S. Carlsson, C. Barry, M. Lang, H. Linger, & C. Schneider (Eds.), Designing Digitalization (ISD2018 Proceedings)
• Cristea, A. I., Alamri, A., Kayama, M., Stewart, C., Alshehri, M., & Shi, L. (2018). How is Learning Fluctuating? FutureLearn MOOCs Fine-grained Temporal Analysis and Feedback to Teachers and Designers. In B. Andersson, B. Johansson, S. Carlsson, C. Barry, M. Lang, H. Linger, & C. Schneider (Eds.), Information Systems Development: Designing Digitalization (ISD2018 Proceedings)
• Alshehri, M., Foss, J., Cristea, A. I., Kayama, M., Shi, L., Alamri, A., & Tsakalidis, A. (2018). On the need for fine-grained analysis of Gender versus Commenting Behaviour in MOOCs. In Proceedings of the 2018 the 3rd International Conference on Information and Education Innovations (ICIEI'18) : London, United Kingdom, June 30 - July 02, 2018 (73-77). https://doi.org/10.1145/3234825.3234833
• Khan, J., Cristea, A., & Alamri, A. (2018). A large-scale category-based evaluation of a visual language for adaptive hypermedia. In Proceedings of the 2018 the 3rd International Conference on Information and Education Innovations (ICIEI'18) : London, United Kingdom, June 30 - July 02, 2018 (94-98). https://doi.org/10.1145/3234825.3234834
• Alamri, A., Rusby, H., Cristea, A. I., Khan, J., Shi, L., & Stewart, C. (2018). An intuitive Authoring System for a Personalised, Social, Gamified, Visualisation-supporting e-learning System. In Proceedings of the 2018 the 3rd International Conference on Information and Education Innovations (ICIEI'18) : London, United Kingdom, June 30 - July 02, 2018 (57-61). https://doi.org/10.1145/3234825.3234835
• Zhou, Y., Cristea, A. I., & Shi, L. (2017). Connecting Targets to Tweets: Semantic Attention-based Model for Target-Specific stance Detection. In A. Bouguettaya, Y. Gao, A. Klimenko, L. Chen, X. Zhang, F. Dzerzhinskiy, …Q. Li (Eds.), Web Information Systems Engineering -- WISE 2017 (18-32). https://doi.org/10.1007/978-3-319-68783-4_2
• Alessandrini, A., Cristea, A., Hartikainen, M., Isomäki, H., & Tuhkala, A. (2017). Identifying Objectives for a Learning Space Management System with Value-focused Thinking. In P. Escudeiro, G. Costagliola, S. Zvacek, J. Uhomoibhi, & B. M. McLaren (Eds.), Proceedings of the 9th International Conference on Computer Supported Education (CSEDU) (25-34). https://doi.org/10.5220/0006230300250034
• Tsakalidis, A., Liakata, M., Damoulas, T., Jellinek, B., Guo, W., & Cristea, A. (2016). Combining heterogeneous user generated data to sense well-being. In Y. Matsumoto, & R. Prasad (Eds.), Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics : Technical Papers (3007-3018)
• Zhou, Y., Kanhabua, N., & Cristea, A. (2016). Real-time timeline summarisation for high-impact events in Twitter. In G. A. Kaminka, M. Fox, P. Bouquet, E. Hüllermeier, V. Dignum, F. Dignum, & F. van Harmelen (Eds.), Proceedings of the 22nd European Conference on Artificial Intelligence, 29 August–2 September 2016, The Hague, The Netherlands (1158-1166). https://doi.org/10.3233/978-1-61499-672-9-1158
• Cristea, A., & Shi, L. (2016). Motivational gamification strategies rooted in self-determination theory for social adaptive E-Learning. In A. Micarelli, J. Stamper, & K. Panourgia (Eds.), Intelligent Tutoring Systems, 13th International Conference, ITS 2016, Zagreb, Croatia, June 7-10, 2016, Proceedings (294-300). https://doi.org/10.1007/978-3-319-39583-8_32
• Zhou, Y., Demidova, E., & Cristea, A. (2016). Who likes me more? Analysing entity-centric language-specific bias in multilingual Wikipedia. In Proceedings of the 2016 ACM Symposium on Applied Computing : Artificial Intelligence and Agents, Distributed Systems, and Information Systems (750-757). https://doi.org/10.1145/2851613.2851858
• Zhou, Y., & Cristea, A. (2016). Towards detection of influential sentences affecting reputation in Wikipedia. In W. Nejdl (Ed.), WebSci '16 : Proceedings of the 8th ACM Conference on Web Science (244-248). https://doi.org/10.1145/2908131.2908177
• Townsend, R., Tsakalidis, A., Zhou, Y., Wang, B., Liakata, M., Zubiaga, A., …Procter, R. (2015). WarwickDCS : from phrase-based to target-specific sentiment recognition. In Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015) (657-663). https://doi.org/10.18653/v1/s15-2110
• Al Qudah, D. A., Cristea, A. I., Hadzidedic Bazdarevic, S., Al-Saqqa, S., & Al-Sayyad, R. M. (2015). A Taxonomy-Based Evaluation of Personalized E-Advertisement. . https://doi.org/10.1109/CIT/IUCC/DASC/PICOM.2015.56
• Hadzidedic Bazdarevic, S., & Cristea, A. I. (2015). What do people affected by cancer talk about online? Text analysis of online cancer community usage in Bosnia and Herzegovina.
• Shi, L., Cristea, A. I., & Hadzidedic, S. (2014). The Critical Role of Profiles in Social E-Learning Design. . https://doi.org/10.1145/2656450.2656458
• Shi, L., Cristea, A., Awan, M., Stewart, C., & Hendrix, M. (2013). Towards understanding learning behavior patterns in social adaptive personalized e-learning systems. In Hyperconnected World: Anything, Anywhere, Anytime; Proceedings of the 19th Americas Conference on Information Systems (AMCIS 2013) (1-10)
• Gkotsis, G., Stepanyan, K., Cristea, A., & Joy, M. (2013). Zero-cost labelling with web feeds for weblog data extraction. In WWW '13 Companion : Proceedings of the 22nd international conference on World Wide Web companion (73-74)

Journal Article

• 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
• Alrajhi, L., Alamri, A., Pereira, F. D., Cristea, A. I., & Oliveira, E. H. T. (2023). Solving the imbalanced data issue: automatic urgency detection for instructor assistance in MOOC discussion forums. User Modeling and User-Adapted Interaction, https://doi.org/10.1007/s11257-023-09381-y
• 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
• Rodrigues, L., Palomino, P. T., Toda, A. M., Klock, A. C., Pessoa, M., Pereira, F. D., …Isotani, S. (2023). How Personalization Affects Motivation in Gamified Review Assessments. International Journal of Artificial Intelligence in Education, https://doi.org/10.1007/s40593-022-00326-x
• 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., …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
• Cristea, A. I., Alamri, A., Alshehri, M., Dwan Pereira, F., Toda, A. M., Harada T. de Oliveira, E., & Stewart, C. (2023). The engage taxonomy: SDT-based measurable engagement indicators for MOOCs and their evaluation. User Modeling and User-Adapted Interaction, https://doi.org/10.1007/s11257-023-09374-x
• Rodrigues, L., Pereira, F. D., Toda, A. M., Palomino, P. T., Pessoa, M., Carvalho, L. S. G., …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
• 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
• Pereira, F. D., Fonseca, S. C., Oliveira, E. H., Cristea, A. I., Bellhauser, H., Rodrigues, L., …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., 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
• 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
• Pereira, F. D., Oliveira, E. H., Oliveira, D., Cristea, A. I., Carvalho, L. S., Fonseca, S., …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., …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., …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., …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. (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. (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

Presentation

• 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

Working Paper

• Hadzidedic, S., Cristea, A., & Watson, D. (2023). Effect of emotions and personalisation on cancer website reuse intentions