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Outputs (387)

For whom should we gamify? Insights on the users intentions and context towards gamification in education (2020)
Presentation / Conference Contribution
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

Gamification design in educational environments is not trivial and many variables need to be considered to achieve positive outcomes. Often, educators and designers do not know when the students intend on the use of gamified environments might influe... Read More about For whom should we gamify? Insights on the users intentions and context towards gamification in education.

Forum-based Prediction of Certification in Massive Open Online Courses (2021)
Presentation / Conference Contribution
Alsheri, M. A., Alamri, A., Cristea, A. I., & Stewart, C. D. (2021). Forum-based Prediction of Certification in Massive Open Online Courses.

Massive Open Online Courses (MOOCs) have been suffering a very level of low course certification (less than 1% of the total number of enrolled students on a given online course opt to purchase its certificate), although MOOC platforms have been offer... Read More about Forum-based Prediction of Certification in Massive Open Online Courses.

A Bayesian Network-based model to understand the role of soft requirements in technology acceptance: the Case of the NHS COVID-19 Test and Trace App in England and Wales (2022)
Presentation / Conference Contribution
Garcia-Paucar, L., Bencomo, N., Sutcliffe, A., & Sawyer, P. (2022). A Bayesian Network-based model to understand the role of soft requirements in technology acceptance: the Case of the NHS COVID-19 Test and Trace App in England and Wales. . https://doi.org/10.1145/3477314.3507147

Soft requirements (such as human values, motivations, and personal attitudes) can strongly influence technology acceptance. As such, we need to understand, model and predict decisions made by end users regarding the adoption and utilization of softwa... Read More about A Bayesian Network-based model to understand the role of soft requirements in technology acceptance: the Case of the NHS COVID-19 Test and Trace App in England and Wales.

A Multidimensional Deep Learner Model of Urgent Instructor Intervention Need in MOOC Forum Posts (2020)
Presentation / Conference Contribution
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

In recent years, massive open online courses (MOOCs) have become one of the most exciting innovations in e-learning environments. Thousands of learners around the world enroll on these online platforms to satisfy their learning needs (mostly) free of... Read More about A Multidimensional Deep Learner Model of Urgent Instructor Intervention Need in MOOC Forum Posts.

Semi-automatic Construction of Ontology Based on Data Mining Technique (2017)
Presentation / Conference Contribution
Wang, J., Flanagan, B., & Ogata, H. (2017). Semi-automatic Construction of Ontology Based on Data Mining Technique. . https://doi.org/10.1109/iiai-aai.2017.202

In this paper, we present a method to extract the possible relationships between knowledge points by analyzing e-book log and mining quiz data and mining Wikipedia articles. This method will be implemented in an ontology-based visualization support s... Read More about Semi-automatic Construction of Ontology Based on Data Mining Technique.

Narrative for Gamification in Education: Why Should you Care? (2019)
Presentation / Conference Contribution
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

Gamification applied to education studies are focusing to encourage students to perform specific tasks, however many of these studies are still inconclusive about how much gamification can influence engagement. Also, the frameworks used to apply gami... Read More about Narrative for Gamification in Education: Why Should you Care?.

Data-Driven Analysis of Engagement in Gamified Learning Environments: A Methodology for Real-Time Measurement of MOOCs (2020)
Presentation / Conference Contribution
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

Welfare and economic development is directly dependent on the availability of highly skilled and educated individuals in society. In the UK, higher education is accessed by a large percentage of high school graduates (50% in 2017). Still, in Brazil,... Read More about Data-Driven Analysis of Engagement in Gamified Learning Environments: A Methodology for Real-Time Measurement of MOOCs.

Single-channel EEG-based subject identification using visual stimuli (2021)
Presentation / Conference Contribution
Katsigiannis, S., Arnau-González, P., Arevalillo-Herráez, M., & Ramzan, N. (2021). Single-channel EEG-based subject identification using visual stimuli. . https://doi.org/10.1109/bhi50953.2021.9508581

Electroencephalography (EEG) signals have been recently proposed as a biometrics modality due to some inherent advantages over traditional biometric approaches. In this work, we studied the performance of individual EEG channels for the task of subje... Read More about Single-channel EEG-based subject identification using visual stimuli.

Digital Inclusion in Nothern England: Training Women from Underrepresented Communities in Tech: A Data Analytics Case Study (2020)
Presentation / Conference Contribution
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

The TechUPWomen programme takes 100 women from the Midlands and North of England, particularly from underrepresented communities, with degrees or experience in any subject area, retrains them in technology and upon graduation guarantees an interview... Read More about Digital Inclusion in Nothern England: Training Women from Underrepresented Communities in Tech: A Data Analytics Case Study.

Early Performance Prediction for CS1 Course Students using a Combination of Machine Learning and an Evolutionary Algorithm (2019)
Presentation / Conference Contribution
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

Many researchers have started extracting student behaviour by cleaning data collected from web environments and using it as features in machine learning (ML) models. Using log data collected from an online judge, we have compiled a set of successful... Read More about Early Performance Prediction for CS1 Course Students using a Combination of Machine Learning and an Evolutionary Algorithm.

Can We Use Gamification to Predict Students’ Performance? A Case Study Supported by an Online Judge (2020)
Presentation / Conference Contribution
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

The impact of gamification has been typically evaluated via self-report assessments (questionnaires, surveys, etc.). In this work, we analise the use of gamification elements as parameters, to predict whether students are going to fail or not in a pr... Read More about Can We Use Gamification to Predict Students’ Performance? A Case Study Supported by an Online Judge.

A Brief Survey of Deep Learning Approaches for Learning Analytics on MOOCs (2021)
Presentation / Conference Contribution
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

Massive Open Online Course (MOOC) systems have become prevalent in recent years and draw more attention, a.o., due to the coronavirus pandemic’s impact. However, there is a well-known higher chance of dropout from MOOCs than from conventional off-lin... Read More about A Brief Survey of Deep Learning Approaches for Learning Analytics on MOOCs.

A Multi-agent Architecture for Multi-robot Surveillance (2009)
Presentation / Conference Contribution
Vallejo, D., Remagnino, P., Monekosso, D. N., Jimenez, L., & Gonzalez, C. (2009). A Multi-agent Architecture for Multi-robot Surveillance. In N. Nguyen, R. Kowalczyk, & S. Chen (Eds.),

Exploring an Approach for Grouping through Predicting Group Performance from Analysis of Learner Characteristics (2018)
Presentation / Conference Contribution
Wang, J., & Kojima, K. (2018). Exploring an Approach for Grouping through Predicting Group Performance from Analysis of Learner Characteristics. . https://doi.org/10.1109/iiai-aai.2018.00062

In this paper, we present a mathematical model for forming heterogeneous groups of learners under different teaching strategies. This model requires a formulation which can effectively predict the learning performance of cooperative learning groups.... Read More about Exploring an Approach for Grouping through Predicting Group Performance from Analysis of Learner Characteristics.

Enhancing Personalized Feedback System by Visual Biometric Data Analysis (2016)
Presentation / Conference Contribution
Wang, J., Ho, H., & Ono, Y. (2016). Enhancing Personalized Feedback System by Visual Biometric Data Analysis. . https://doi.org/10.1109/iiai-aai.2016.231

This paper propose to develop and evaluate a learning support system which can provide personalized feedbacks for helping learners to improve their learning ability. To support the analysis of learners' cognitive processes during learning activities,... Read More about Enhancing Personalized Feedback System by Visual Biometric Data Analysis.