1.1k citations · 1.8k across the 11 of their papers we have counts for
11 papers
Improving essay peer grading accuracy in MOOCs using personalized weights from student's engagement and performance
Carlos García-Martínez, Rebeca Cerezo, Manuel Bermúdez +1
Most MOOC platforms either use simple schemes for aggregating peer grades, e.g., taking the mean or the median, or apply methodologies that increase students' workload considerably…
Improving the portability of predicting students performance models by using ontologies
Javier Lopez Zambrano, Juan A. Lara, Cristobal Romero
One of the main current challenges in Educational Data Mining and Learning Analytics is the portability or transferability of predictive models obtained for a particular course so…
Helping university students to choose elective courses by using a hybrid multi-criteria recommendation system with genetic optimization
A. Esteban, A. Zafra, C. Romero
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.…
A holographic mobile-based application for practicing pronunciation of basic English vocabulary for Spanish speaking children
R. Cerezo, V. Calderon, C. Romero
This paper describes a holographic mobile-based application designed to help Spanish-speaking children to practice the pronunciation of basic English vocabulary words. The mastery…
Process mining for self-regulated learning assessment in e-learning
R. Cerezo, A. Bogarin, M. Esteban +1
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…
Text mining in education
R. Ferreira-Mello, M. Andre, A. Pinheiro +2
The explosive growth of online education environments is generating a massive volume of data, specially in text format from forums, chats, social networks, assessments, essays, amo…
Improving prediction of students' performance in intelligent tutoring systems using attribute selection and ensembles of different multimodal data sources
W. Chango, R. Cerezo, M. Sanchez-Santillan +2
The aim of this study was to predict university students' learning performance using different sources of data from an Intelligent Tutoring System. We collected and preprocessed da…
Modeling and predicting students' engagement behaviors using mixture Markov models
R. Maqsood, P. Ceravolo, C. Romero +1
Students' engagements reflect their level of involvement in an ongoing learning process which can be estimated through their interactions with a computer-based learning or assessme…
Subgroup Discovery in MOOCs: A Big Data Application for Describing Different Types of Learners
J. M. Luna, H. M. Fardoun, F. Padillo +2
The aim of this paper is to categorize and describe different types of learners in massive open online courses (MOOCs) by means of a subgroup discovery approach based on MapReduce.…
Educational data mining and learning analytics: An updated survey
C. Romero, S. Ventura
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 ver…
Multi-source and multimodal data fusion for predicting academic performance in blended learning university courses
W. Chango, R. Cerezo, C. Romero
In this paper we applied data fusion approaches for predicting the final academic performance of university students using multiple-source, multimodal data from blended learning en…