Outputs (387)

A meaningful discovery learning environment for e-book learners (2017)
Presentation / Conference Contribution
Wang, J., Ogata, H., & Shimada, A. (2017). A meaningful discovery learning environment for e-book learners. . https://doi.org/10.1109/educon.2017.7942995

In this paper, we present a system framework making use of e-book logs for visualization learning support systems intended to provide meaningful learning environment for e-book learners. An ontology-based visualization support system, which supports... Read More about A meaningful discovery learning environment for e-book learners.

Latent Bernoulli Autoencoder (2020)
Presentation / Conference Contribution
Fajtl, J., Argyriou, V., Monekosso, D., & Remagnino, P. (2020). Latent Bernoulli Autoencoder. In H. Daume, & A. Singh (Eds.),

Detecting Fine-Grained Emotions on Social Media during Major Disease Outbreaks: Health and Well-being before and during the COVID-19 Pandemic (2021)
Presentation / Conference Contribution
Aduragba, O. T., Yu, J., Cristea, A., & Shi, L. (2021). Detecting Fine-Grained Emotions on Social Media during Major Disease Outbreaks: Health and Well-being before and during the COVID-19 Pandemic.

Exploring content game elements to support gamification design in educational systems: narrative and storytelling (2019)
Presentation / Conference Contribution
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

There are currently several studies on gamification applied to learning systems, aiming to encourage students to do certain tasks and improving their learning. According to several researches, most frameworks for gamification already developed are st... Read More about Exploring content game elements to support gamification design in educational systems: narrative and storytelling.

MOOCSent: a Sentiment Predictor for Massive Open Online Courses (2021)
Presentation / Conference Contribution
Alsheri, M. A., Alrajhi, L. M., Alamri, A., & Cristea, A. I. (2021). MOOCSent: a Sentiment Predictor for Massive Open Online Courses.

One key type of Massive Open Online Course (MOOC) data is the learners’ social interaction (forum). While several studies have analysed MOOC forums to predict learning outcomes, analysing learners’ sentiments in education and, specifically, in MOOCs,... Read More about MOOCSent: a Sentiment Predictor for Massive Open Online Courses.

COVID-19’s Impact on the Telecommunications Companies (2021)
Presentation / Conference Contribution
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

Now the world is witnessing most significant challenges due the Covid-19 crisis. Beyond health effects, it has social and economic effects. With the enormous amount of data available and the widespread use of social web globally, research can and sho... Read More about COVID-19’s Impact on the Telecommunications Companies.

Does BERT pay attention to cyberbullying? (2021)
Presentation / Conference Contribution
Elsafoury, F., Katsigiannis, S., Wilson, S., & Ramzan, N. (2021). Does BERT pay attention to cyberbullying?. . https://doi.org/10.1145/3404835.3463029

Social media have brought threats like cyberbullying, which can lead to stress, anxiety, depression and in some severe cases, suicide attempts. Detecting cyberbullying can help to warn/ block bullies and provide support to victims. However, very few... Read More about Does BERT pay attention to cyberbullying?.

Wide-Scale Automatic Analysis of 20 Years of ITS Research (2021)
Presentation / Conference Contribution
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

The analysis of literature within a research domain can provide significant value during preliminary research. While literature reviews may provide an in-depth understanding of current studies within an area, they are limited by the number of studies... Read More about Wide-Scale Automatic Analysis of 20 Years of ITS Research.

Agent-based Classroom Environment Simulation: the Effect of Disruptive Schoolchildren’s Behaviour versus Teacher Control over Neighbours (2021)
Presentation / Conference Contribution
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

Schoolchildren's academic progress is known to be affected by the classroom environment. It is important for teachers and administrators to under-stand their pupils' status and how various factors in the classroom may affect them, as it can help them... Read More about Agent-based Classroom Environment Simulation: the Effect of Disruptive Schoolchildren’s Behaviour versus Teacher Control over Neighbours.

Predicting Learners' Demographics Characteristics: Deep Learning Ensemble Architecture for Learners' Characteristics Prediction in MOOCs (2019)
Presentation / Conference Contribution
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

Author Profiling (AP), which aims to predict an author's demographics characteristics automatically by using texts written by the author, is an important mechanism for many applications, as well as highly challenging. In this research, we analyse var... Read More about Predicting Learners' Demographics Characteristics: Deep Learning Ensemble Architecture for Learners' Characteristics Prediction in MOOCs.

Agent-based Simulation of the Classroom Environment to Gauge the Effect of Inattentive or Disruptive Students (2021)
Presentation / Conference Contribution
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

The classroom environment is a major contributor to the learning process in schools. Young students are affected by different details in their academic progress, be it their own characteristics, their teacher’s or their peers’. The combination of the... Read More about Agent-based Simulation of the Classroom Environment to Gauge the Effect of Inattentive or Disruptive Students.

Temporal Sentiment Analysis of Learners: Public Versus Private Social Media Communication Channels in a Women-in-Tech Conversion Course (2020)
Presentation / Conference Contribution
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

Social media is ubiquitous, a continuous part of our daily lives; it offers new ways of communication. This is especially crucial in education, where various online systems make use of (perceived) public or private communication, as a means to suppor... Read More about Temporal Sentiment Analysis of Learners: Public Versus Private Social Media Communication Channels in a Women-in-Tech Conversion Course.

Design of an educational multimedia library to teach Python to non-technical university students (2020)
Presentation / Conference Contribution
Valente, A., Marchetti, E., & Wang, J. (2020). Design of an educational multimedia library to teach Python to non-technical university students.

Starting from our teaching experience and previous research on programming for non-technical university students in Japan and Denmark, we identify an unarticulated dependency of programming materials from other technical domains, which causes a knowl... Read More about Design of an educational multimedia library to teach Python to non-technical university students.

Defining gaze tracking metrics by observing a growing divide between 2D and 3D tracking (2020)
Presentation / Conference Contribution
Blakey, W. A., Katsigiannis, S., Hajimirza, N., & Ramzan, N. (2020). Defining gaze tracking metrics by observing a growing divide between 2D and 3D tracking. In IS&T International Symposium on Electronic Imaging 2020 : Human vision and electronic imaging (129.1-129.9). https://doi.org/10.2352/issn.2470-1173.2020.11.hvei-129

This work examines the different terminology used for defining gaze tracking technology and explores the different methodologies used for describing their respective accuracy. Through a comparative study of different gaze tracking technologies, such... Read More about Defining gaze tracking metrics by observing a growing divide between 2D and 3D tracking.

Image-Evoked Affect and its Impact on EEG-Based Biometrics (2019)
Presentation / Conference Contribution
Arnau-González, P., Katsigiannis, S., Arevalillo-Herráez, M., & Ramzan, N. (2019). Image-Evoked Affect and its Impact on EEG-Based Biometrics. . https://doi.org/10.1109/icip.2019.8803315

Use of Machine Learning for Rate Adaptation in MPEG-DASH for Quality of Experience Improvement (2018)
Presentation / Conference Contribution
Alzahrani, I. R., Ramzan, N., Katsigiannis, S., & Amira, A. (2018). Use of Machine Learning for Rate Adaptation in MPEG-DASH for Quality of Experience Improvement. . https://doi.org/10.1007/978-3-319-78753-4

Parallel computing techniques for performance enhancement of a cDNA microarray gridding algorithm (2013)
Presentation / Conference Contribution
Katsigiannis, S., & Maroulis, D. (2013). Parallel computing techniques for performance enhancement of a cDNA microarray gridding algorithm. . https://doi.org/10.1109/isspit.2013.6781922

Contourlet Transform for Texture Representation of Ultrasound Thyroid Images (2010)
Presentation / Conference Contribution
Katsigiannis, S., Keramidas, E. G., & Maroulis, D. (2010). Contourlet Transform for Texture Representation of Ultrasound Thyroid Images. In Artificial Intelligence Applications and Innovations. https://doi.org/10.1007/978-3-642-16239-8_20

Towards a Human-AI hybrid system for categorising programming problems (2021)
Presentation / Conference Contribution
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

As programming skills are increasingly required world-wide and across disciplines, many students use online platforms that provide automatic feedback through a Programming Online Judge (POJ) mechanism. POJs are very popular e-learning tools, boasting... Read More about Towards a Human-AI hybrid system for categorising programming problems.

Sequential Recommender via Time-aware Attentive Memory Network (2020)
Presentation / Conference Contribution
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

Recommendation systems aim to assist users to discover desirable contents from an ever-growing corpus of items. Although recommenders have been greatly improved by deep learning, they still face several challenges: (1) behaviours are much more comple... Read More about Sequential Recommender via Time-aware Attentive Memory Network.