His main research concerns Educational data mining, Data science, Artificial intelligence, Association rule learning and Machine learning. His studies deal with areas such as Anomaly detection and Data mining as well as Educational data mining. His Data science research is multidisciplinary, incorporating perspectives in Field, Concept mining, Web mining and Visualization.
His Association rule learning research includes themes of Learning Management, Collaborative filtering and Cluster analysis. Cristóbal Romero works mostly in the field of Machine learning, limiting it down to topics relating to Usage data and, in certain cases, Classifier, E-learning and Recommender system. His Genetic programming study combines topics from a wide range of disciplines, such as Evolutionary algorithm, High dimensional and Knowledge extraction.
Cristóbal Romero mainly focuses on Artificial intelligence, Machine learning, Educational data mining, Data science and Data mining. In Artificial intelligence, Cristóbal Romero works on issues like Usage data, which are connected to Classifier and Data mining algorithm. The study incorporates disciplines such as Preprocessor and Knowledge extraction in addition to Machine learning.
His biological study spans a wide range of topics, including Learning Management, Learning analytics, Web mining and Library science. His work is dedicated to discovering how Data science, Collaborative learning are connected with Educational technology and other disciplines. He has researched Association rule learning in several fields, including Class, Instructional design and Virtual learning environment, World Wide Web.
The scientist’s investigation covers issues in Artificial intelligence, Educational data mining, Machine learning, Blended learning and Data science. His research on Artificial intelligence frequently links to adjacent areas such as Natural language processing. His research integrates issues of Learning analytics and World Wide Web in his study of Educational data mining.
His work on Sensor fusion, Statistical classification, Predictive modelling and Genetic algorithm as part of general Machine learning study is frequently connected to Multi criteria, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them. His Blended learning research is multidisciplinary, relying on both Educational assessment, Game based learning, Distance education and Library science. In his works, he conducts interdisciplinary research on Data science and Process mining.
His primary areas of study are Data science, Process, World Wide Web, Learning analytics and Educational data mining. His Data science study incorporates themes from Text mining and Event. His Process research spans across into fields like Data mining and Management system.
His work in the fields of Thesaurus and Massive open online course overlaps with other areas such as Skepticism and Application areas. Cristóbal Romero has included themes like Set, Cluster analysis, Interface, Knowledge extraction and Analytics in his Learning analytics study. His Educational data mining study integrates concerns from other disciplines, such as Domain, Field, Graph and Representation.
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Educational Data Mining: A Review of the State of the Art
Cristóbal Romero;Sebastián Ventura.
systems man and cybernetics (2010)
Educational data mining: A survey from 1995 to 2005
C. Romero;S. Ventura.
Expert Systems With Applications (2007)
Data mining in course management systems: Moodle case study and tutorial
Cristóbal Romero;Sebastián Ventura;Enrique García.
Computer Education (2008)
KEEL: a software tool to assess evolutionary algorithms for data mining problems
J. Alcalá-Fdez;L. Sánchez;S. García;M. J. del Jesus.
soft computing (2008)
Data mining in education
Cristobal Romero;Sebastian Ventura.
Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery (2013)
Predicting students' final performance from participation in on-line discussion forums
Cristóbal Romero;Manuel-Ignacio López;Jose-María Luna;Sebastián Ventura.
Computer Education (2013)
Handbook of Educational Data Mining
Cristobal Romero;Sebastian Ventura;Mykola Pechenizkiy;Ryan S.J.d. Baker.
Chapman and Hall/CRC data mining and knowledge discovery series (2010)
Data Mining Algorithms to Classify Students
Cristóbal Romero;Sebastián Ventura;Pedro G. Espejo;César Hervás.
educational data mining (2008)
Web usage mining for predicting final marks of students that use Moodle courses
Cristobal Romero;Cristobal Romero;Pedro G. Espejo;Amelia Zafra;Amelia Zafra;Jose Raul Romero.
Computer Applications in Engineering Education (2013)
Knowledge Discovery with Genetic Programming for Providing Feedback to Courseware Authors
Cristóbal Romero;Sebastián Ventura;Paul De Bra.
User Modeling and User-adapted Interaction (2005)
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