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Towards Portability of Models for Predicting Students’ Final Performance in University Courses Starting from Moodle Logs
(MDPI, 2020)
Predicting students’ academic performance is one of the older challenges faced by the educational scientific community. However, most of the research carried out in this area has focused on obtaining the best accuracy ...
Assignments as Influential Factor to Improve the Prediction of Student Performance in Online Courses
(MDPI, 2021)
Studies on the prediction of student success in distance learning have explored mainly demographics factors and student interactions with the virtual learning environments. However, it is remarkable that a very limited ...
A review on data fusion in multimodal learning analytics and educational data mining
(Wiley, 2022)
The new educational models such as smart learning environments use of digital and context-aware devices to facilitate the learning process. In this new educational scenario, a huge quantity of multimodal students' data ...
Helping university students to choose elective courses by using a hybrid multi-criteria recommendation system with genetic optimization
(Elsevier, 2020)
The wide availability of specific courses together with the flexibility of academic plans in university
studies reveal the importance of Recommendation Systems (RSs) in this area. These systems appear
as tools that help ...
Multi-source and multimodal data fusion for predicting academic performance in blended learning university courses
(Elsevier, 2021)
In this paper we apply data fusion approaches for predicting the final academic performance of university students using multiple-source, multimodal data from blended learning environments. We collect and preprocess data ...
Educational data mining and learning analytics: An updated survey
(Wiley, 2020)
This survey is an updated and improved version of the previous one published
in 2013 in this journal with the title “data mining in education”. It reviews in a
comprehensible and very general way how Educational Data ...
Process mining for self-regulated learning assessment in e-learning
(Springer, 2020)
Content assessment has broadly improved in e-learning scenarios in recent decades. However, the eLearning process can give rise to a spatial and temporal gap that poses interesting challenges for assessment of not only ...
Improving prediction of students’ performance in intelligent tutoring systems using attribute selection and ensembles of different multimodal data sources
(Springer, 2021)
The aim of this study was to predict university students’ learning performance using different sources of performance and multimodal data from an Intelligent Tutoring System. We collected and preprocessed data from 40 ...
Modeling and predicting students’ engagement behaviors using mixture Markov models
(Springer, 2022)
Students’ engagements reflect their level of involvement in an ongoing learning processwhich
can be estimated through their interactions with a computer-based learning or assessment
system. A pre-requirement for stimulating ...