2022
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Romero, C; W., Chango; R., Cerezo Looking for the best data fusion model in Smart Learning Environments for detecting at risk university students Inproceedings Mitrovic, Antonija; Bosch, Nigel (Ed.): Proceedings of the 15th International Conference on Educational Data Mining, pp. 725–728, International Educational Data Mining Society, Durham, United Kingdom, 2022, ISBN: 978-1-7336736-3-1. Links | BibTeX | Tags: Educational Data Mining, Predicting Student Performance @inproceedings{2022.EDM-posters.90,
title = {Looking for the best data fusion model in Smart Learning Environments for detecting at risk university students},
author = {Romero, C. and Chango W. and Cerezo R.},
editor = {Antonija Mitrovic and Nigel Bosch},
doi = {10.5281/zenodo.6853089},
isbn = {978-1-7336736-3-1},
year = {2022},
date = {2022-07-01},
booktitle = {Proceedings of the 15th International Conference on Educational Data Mining},
pages = {725--728},
publisher = {International Educational Data Mining Society},
address = {Durham, United Kingdom},
keywords = {Educational Data Mining, Predicting Student Performance},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Zafra, A; Gibaja, E; Luque, M Interactive learning and formative assessment in the classroom using quizziz Inproceedings International Handbook of Innovation and Assessment of the Quality of Higher Education and Research. Vol. 1, pp. 187, Thomson Reuters-Civitas 2022. BibTeX | Tags: Educational Data Mining, Predicting Student Performance @inproceedings{zafra2022interactive,
title = {Interactive learning and formative assessment in the classroom using quizziz},
author = {Zafra, A. and Gibaja, E. and Luque, M.},
year = {2022},
date = {2022-01-01},
booktitle = {International Handbook of Innovation and Assessment of the Quality of Higher Education and Research. Vol. 1},
pages = {187},
organization = {Thomson Reuters-Civitas},
keywords = {Educational Data Mining, Predicting Student Performance},
pubstate = {published},
tppubtype = {inproceedings}
}
|
2021
|
Esteban, A; Romero, C; Zafra, A Assignments as Influential Factor to Improve the Prediction of Student Performance in Online Courses Journal Article Applied Sciences, 11 (21), pp. 10145, 2021. Links | BibTeX | Tags: Educational Data Mining, Multi-instance Learning, Predicting Student Performance @article{esteban2021assignments,
title = {Assignments as Influential Factor to Improve the Prediction of Student Performance in Online Courses},
author = {Esteban, A. and Romero, C. and Zafra, A.},
url = {https://www.mdpi.com/2076-3417/11/21/10145},
doi = {10.3390/app112110145},
year = {2021},
date = {2021-01-01},
journal = {Applied Sciences},
volume = {11},
number = {21},
pages = {10145},
publisher = {MDPI},
keywords = {Educational Data Mining, Multi-instance Learning, Predicting Student Performance},
pubstate = {published},
tppubtype = {article}
}
|
2020
|
Romero, C; Ventura, S Educational data mining and learning analytics: An updated survey Journal Article Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, pp. e1355, 2020. Links | BibTeX | Tags: Data Science, Educational Data Mining, Educational Recommender Systems, Predicting Student Performance @article{romero2020educational,
title = {Educational data mining and learning analytics: An updated survey},
author = {Romero, C. and Ventura, S.},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/widm.1355},
doi = {10.1002/widm.1355},
year = {2020},
date = {2020-01-01},
journal = {Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery},
pages = {e1355},
keywords = {Data Science, Educational Data Mining, Educational Recommender Systems, Predicting Student Performance},
pubstate = {published},
tppubtype = {article}
}
|
López-Zambrano, J; Lara, J; Romero, C Towards Portability of Models for Predicting Students Final Performance in University Courses Starting from Moodle Logs Journal Article Applied Sciences, 10 (1), pp. 354, 2020. Links | BibTeX | Tags: Educational Data Mining, Predicting Student Performance @article{lopez2020towardsb,
title = {Towards Portability of Models for Predicting Students Final Performance in University Courses Starting from Moodle Logs},
author = {L\'{o}pez-Zambrano, J. and Lara, J. and Romero, C.},
url = {https://www.mdpi.com/2076-3417/10/1/354},
doi = {10.3390/app10010354},
year = {2020},
date = {2020-01-01},
journal = {Applied Sciences},
volume = {10},
number = {1},
pages = {354},
keywords = {Educational Data Mining, Predicting Student Performance},
pubstate = {published},
tppubtype = {article}
}
|
2019
|
Romero, C; Ventura, S Guest Editorial: Special Issue on Early Prediction and Supporting of Learning Performance Journal Article IEEE Transactions on Learning Technologies, 12 , pp. 145-147, 2019. Links | BibTeX | Tags: Educational Data Mining, Predicting Student Performance @article{Romero2019145,
title = {Guest Editorial: Special Issue on Early Prediction and Supporting of Learning Performance},
author = {Romero, C. and Ventura, S.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067366696&doi=10.1109%2fTLT.2019.2908106&partnerID=40&md5=4614c626c738b3d4caacf7227b39d326},
doi = {10.1109/TLT.2019.2908106},
year = {2019},
date = {2019-01-01},
journal = {IEEE Transactions on Learning Technologies},
volume = {12},
pages = {145-147},
keywords = {Educational Data Mining, Predicting Student Performance},
pubstate = {published},
tppubtype = {article}
}
|
Chango W., Cerezo R; Romero, C Predicting academic performance of university students from multi-sources data in blended learning Inproceedings Proceedings of the Second International Conference on Data Science, E-Learning and Information Systems, pp. 1–5, 2019. Links | BibTeX | Tags: Educational Data Mining, Predicting Student Performance @inproceedings{chango2019predictingb,
title = {Predicting academic performance of university students from multi-sources data in blended learning},
author = {Chango, W., Cerezo, R. and Romero, C.},
url = {https://dl.acm.org/doi/10.1145/3368691.3368694},
doi = {10.1145/3368691.3368694},
year = {2019},
date = {2019-01-01},
booktitle = {Proceedings of the Second International Conference on Data Science, E-Learning and Information Systems},
pages = {1--5},
keywords = {Educational Data Mining, Predicting Student Performance},
pubstate = {published},
tppubtype = {inproceedings}
}
|
2016
|
Márquez-Vera, C; Cano, A; Romero, C; Noaman, A Y; Mousa Fardoun, H; Ventura, S Early dropout prediction using data mining: a case study with high school students Journal Article Expert Systems, 33 (1), pp. 107–124, 2016. Links | BibTeX | Tags: Educational Data Mining, Predicting Student Performance @article{DBLP:journals/es/Marquez-Vera0RN16,
title = {Early dropout prediction using data mining: a case study with high school students},
author = {M\'{a}rquez-Vera, C. and Cano, A. and Romero, C. and Noaman, A. Y. and Mousa Fardoun, H. and Ventura, S.},
url = {http://dx.doi.org/10.1111/exsy.12135},
doi = {10.1111/exsy.12135},
year = {2016},
date = {2016-01-01},
journal = {Expert Systems},
volume = {33},
number = {1},
pages = {107--124},
keywords = {Educational Data Mining, Predicting Student Performance},
pubstate = {published},
tppubtype = {article}
}
|
Fuentes-Alventosa, J; Romero, C; García-Martínez, C; Ventura, S Predicción de la aceptación o rechazo de las calificaciones finales propuestas por el alumnado usando técnicas de Minería de Datos Inproceedings Actas de las XXII Jornadas sobre la Enseñanza Universitaria de la Informática (JENUI 2016), pp. 201–208, 2016, ISBN: 9788416642304. Links | BibTeX | Tags: Classification, Educational Data Mining, Predicting Student Performance, Supervised Learning @inproceedings{Fuentes-Alventosa2016,
title = {Predicci\'{o}n de la aceptaci\'{o}n o rechazo de las calificaciones finales propuestas por el alumnado usando t'{e}cnicas de Miner\^{i}a de Datos},
author = {Fuentes-Alventosa, J. and Romero, C. and Garc\^{i}a-Mart\^{i}nez, C. and Ventura, S.},
url = {http://www.aenui.net/ojs/index.php?journal=actas_jenui&page=article&op=view&path%5B%5D=252},
isbn = {9788416642304},
year = {2016},
date = {2016-01-01},
booktitle = {Actas de las XXII Jornadas sobre la Ense\~{n}anza Universitaria de la Inform\'{a}tica (JENUI 2016)},
pages = {201--208},
keywords = {Classification, Educational Data Mining, Predicting Student Performance, Supervised Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
|
2015
|
Olmo, J L; Romero, C; Gibaja, E; Ventura, S Improving Meta-learning for Algorithm Selection by Using Multi-label Classification: A Case of Study with Educational Data Sets Journal Article Int. J. Computational Intelligence Systems, 8 (6), pp. 1144–1164, 2015. Links | BibTeX | Tags: Educational Data Mining, Predicting Student Performance @article{DBLP:journals/ijcisys/OlmoRGV15,
title = {Improving Meta-learning for Algorithm Selection by Using Multi-label Classification: A Case of Study with Educational Data Sets},
author = {Olmo, J. L. and Romero, C. and Gibaja, E. and Ventura, S.},
url = {http://dx.doi.org/10.1080/18756891.2015.1113748},
doi = {10.1080/18756891.2015.1113748},
year = {2015},
date = {2015-01-01},
journal = {Int. J. Computational Intelligence Systems},
volume = {8},
number = {6},
pages = {1144--1164},
keywords = {Educational Data Mining, Predicting Student Performance},
pubstate = {published},
tppubtype = {article}
}
|
Jiménez, M A; Luna, J M; Romero, C; Ventura, S Discovering clues to avoid middle school failure at early stages Inproceedings Proceedings of the 5th International Conference on Learning Analytics and Knowledge, pp. 300-304, 2015, ISBN: 978-1-4503-3417-4. Links | BibTeX | Tags: Educational Data Mining, Predicting Student Performance @inproceedings{Luna-2015-LAK,
title = {Discovering clues to avoid middle school failure at early stages},
author = {Jim'{e}nez, M. A. and Luna, J. M. and Romero, C. and Ventura, S.},
url = {http://dl.acm.org/citation.cfm?id=2723597&dl=ACM&coll=DL&CFID=501310898&CFTOKEN=38124969},
doi = {10.1145/2723576.2723597},
isbn = {978-1-4503-3417-4},
year = {2015},
date = {2015-01-01},
booktitle = {Proceedings of the 5th International Conference on Learning Analytics and Knowledge},
pages = {300-304},
series = {LAK '15},
keywords = {Educational Data Mining, Predicting Student Performance},
pubstate = {published},
tppubtype = {inproceedings}
}
|
2014
|
Fuentes-Alventosa, J; Romero, C; García-Martínez, C; Ventura, S Accepting or Rejecting Students' Self-grading in Their Final Marks by using Data Mining Inproceedings International Conference on Educational Data Mining (EDM'14), pp. 327–328, 2014. Links | BibTeX | Tags: Classification, Educational Data Mining, Predicting Student Performance, Supervised Learning @inproceedings{Fuentes-Alventosa2014,
title = {Accepting or Rejecting Students' Self-grading in Their Final Marks by using Data Mining},
author = {Fuentes-Alventosa, J. and Romero, C. and Garc\^{i}a-Mart\^{i}nez, C. and Ventura, S.},
url = {http://educationaldatamining.org/EDM2014/uploads/procs2014/posters/3_EDM-2014-Poster.pdf},
year = {2014},
date = {2014-01-01},
booktitle = {International Conference on Educational Data Mining (EDM'14)},
pages = {327--328},
keywords = {Classification, Educational Data Mining, Predicting Student Performance, Supervised Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
|
2013
|
Jiménez, M A; Luna, J M; Ventura, S EDM para la detección precoz del fracaso escolar en secundaria Inproceedings VI Simposio de Teoría y Aplicaciones de Minería de Datos, pp. 1353-1362, Madrid, España, 2013. BibTeX | Tags: Educational Data Mining, Predicting Student Performance @inproceedings{Luna-2013-TAMIDA,
title = {EDM para la detecci\'{o}n precoz del fracaso escolar en secundaria},
author = {Jim'{e}nez, M. A. and Luna, J. M. and Ventura, S.},
year = {2013},
date = {2013-01-01},
booktitle = {VI Simposio de Teor\^{i}a y Aplicaciones de Miner\^{i}a de Datos},
pages = {1353-1362},
address = {Madrid, Espa\~{n}a},
series = {TAMIDA 2013},
keywords = {Educational Data Mining, Predicting Student Performance},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Márquez-Vera, C; Cano, A; Romero, C; Ventura, S Predicting student failure at school using genetic programming and different data mining approaches with high dimensional and imbalanced data Journal Article Applied Intelligence, 38 (3), pp. 315-330, 2013. Links | BibTeX | Tags: Educational Data Mining, Predicting Student Performance @article{Marquez-Vera-2013-APIN,
title = {Predicting student failure at school using genetic programming and different data mining approaches with high dimensional and imbalanced data},
author = {M\'{a}rquez-Vera, C. and Cano, A. and Romero, C. and Ventura, S.},
url = {http://dx.doi.org/10.1007/s10489-012-0374-8},
doi = {10.1007/s10489-012-0374-8},
year = {2013},
date = {2013-01-01},
journal = {Applied Intelligence},
volume = {38},
number = {3},
pages = {315-330},
keywords = {Educational Data Mining, Predicting Student Performance},
pubstate = {published},
tppubtype = {article}
}
|
Márquez-Vera, C; Romero, C; Ventura, S Predicting school failure and dropout by using data mining techniques Journal Article Revista Iberoamericana de Tecnologias del Aprendizaje, 8 (1), pp. 7-14, 2013. Links | BibTeX | Tags: Educational Data Mining, Predicting Student Performance @article{Marquez-Vera-2013-RITA,
title = {Predicting school failure and dropout by using data mining techniques},
author = {M\'{a}rquez-Vera, C. and Romero, C. and Ventura, S.},
url = {http://dx.doi.org/10.1109/RITA.2013.2244695},
doi = {10.1109/RITA.2013.2244695},
year = {2013},
date = {2013-01-01},
journal = {Revista Iberoamericana de Tecnologias del Aprendizaje},
volume = {8},
number = {1},
pages = {7-14},
keywords = {Educational Data Mining, Predicting Student Performance},
pubstate = {published},
tppubtype = {article}
}
|
Romero, C; López, M I; Luna, J M; Ventura, S Predicting students' final performance from participation in on-line discussion forums Journal Article Computers and Education, 68 , pp. 458-472, 2013. Links | BibTeX | Tags: Educational Data Mining, Predicting Student Performance @article{Romero-2013-CAE,
title = {Predicting students' final performance from participation in on-line discussion forums},
author = {Romero, C. and L\'{o}pez, M. I. and Luna, J. M. and Ventura, S.},
url = {http://dx.doi.org/10.1016/j.compedu.2013.06.009},
doi = {10.1016/j.compedu.2013.06.009},
year = {2013},
date = {2013-01-01},
journal = {Computers and Education},
volume = {68},
pages = {458-472},
keywords = {Educational Data Mining, Predicting Student Performance},
pubstate = {published},
tppubtype = {article}
}
|
Romero, C; Espejo, P G; Zafra, A; Romero, J R; Ventura, S Web usage mining for predicting final marks of students that use Moodle courses Journal Article Computer Applications in Engineering Education, 21 (1), pp. 135-146, 2013. Links | BibTeX | Tags: Educational Data Mining, Predicting Student Performance @article{Romero-2013-CAEE,
title = {Web usage mining for predicting final marks of students that use Moodle courses},
author = {Romero, C. and Espejo, P. G. and Zafra, A. and Romero, J. R. and Ventura, S.},
url = {http://dx.doi.org/10.1002/cae.20456},
doi = {10.1002/cae.20456},
year = {2013},
date = {2013-01-01},
journal = {Computer Applications in Engineering Education},
volume = {21},
number = {1},
pages = {135-146},
keywords = {Educational Data Mining, Predicting Student Performance},
pubstate = {published},
tppubtype = {article}
}
|
2012
|
López, M I; Luna, J M; Romero, C; Ventura, S Classification via clustering for predicting final marks based on student participation in forums Inproceedings Proceedings of the 5th International Conference on Educational Data Mining, pp. 148-151, Chania, Greece, 2012. Links | BibTeX | Tags: Educational Data Mining, Predicting Student Performance @inproceedings{Romero-2012-EDM-A,
title = {Classification via clustering for predicting final marks based on student participation in forums},
author = {L\'{o}pez, M. I. and Luna, J. M. and Romero, C. and Ventura, S.},
url = {http://educationaldatamining.org/EDM2012/uploads/procs/Short_Papers/edm2012_short_3.pdf},
year = {2012},
date = {2012-01-01},
booktitle = {Proceedings of the 5th International Conference on Educational Data Mining},
pages = {148-151},
address = {Chania, Greece},
series = {EDM 2012},
keywords = {Educational Data Mining, Predicting Student Performance},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Zafra, A; Ventura, S Multi-instance genetic programming for predicting student performance in web based educational environments Journal Article Applied Soft Computing Journal, 12 (8), pp. 2693-2706, 2012. Links | BibTeX | Tags: Grammar-Based Genetic Programming, Multi-instance Learning, Predicting Student Performance @article{Zafra-2012-ASOC,
title = {Multi-instance genetic programming for predicting student performance in web based educational environments},
author = {Zafra, A. and Ventura, S.},
url = {http://dx.doi.org/10.1016/j.asoc.2012.03.054},
doi = {10.1016/j.asoc.2012.03.054},
year = {2012},
date = {2012-01-01},
journal = {Applied Soft Computing Journal},
volume = {12},
number = {8},
pages = {2693-2706},
keywords = {Grammar-Based Genetic Programming, Multi-instance Learning, Predicting Student Performance},
pubstate = {published},
tppubtype = {article}
}
|
2011
|
García-Martínez, C; Lozano, M Evaluating the application of timesheet management systems to quantify the students' workload in higher education centres Inproceedings International Technology, Education and Development Conference (INTED'11), pp. 1454–1463, 2011. Links | BibTeX | Tags: Predicting Student Performance @inproceedings{Garcia-Martinez2011b,
title = {Evaluating the application of timesheet management systems to quantify the students' workload in higher education centres},
author = {Garc\^{i}a-Mart\^{i}nez, C. and Lozano, M.},
url = {https://library.iated.org/view/GARCIAMARTINEZ2011EVA},
year = {2011},
date = {2011-01-01},
booktitle = {International Technology, Education and Development Conference (INTED'11)},
pages = {1454--1463},
keywords = {Predicting Student Performance},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Pedraza-Perez, R; Romero, C; Ventura, S A java desktop tool for mining moodle data Inproceedings Proceedings of the 4th International Conference on Educational Data Mining, EDM'11, pp. 319-320, 2011. Links | BibTeX | Tags: Educational Data Mining, Predicting Student Performance @inproceedings{Pedraza-Perez-2011-EDM,
title = {A java desktop tool for mining moodle data},
author = {Pedraza-Perez, R. and Romero, C. and Ventura, S.},
url = {http://educationaldatamining.org/EDM2011/wp-content/uploads/proc/edm2011_poster3_Pedraza-Perez.pdf},
year = {2011},
date = {2011-01-01},
booktitle = {Proceedings of the 4th International Conference on Educational Data Mining, EDM'11},
pages = {319-320},
keywords = {Educational Data Mining, Predicting Student Performance},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Zafra, A; Romero, C; Ventura, S Multiple instance learning for classifying students in learning management systems Journal Article Expert Systems with Applications, 38 (12), pp. 15020-15031, 2011. Links | BibTeX | Tags: Multi-instance Learning, Predicting Student Performance @article{Zafra-2011-ESWA,
title = {Multiple instance learning for classifying students in learning management systems},
author = {Zafra, A. and Romero, C. and Ventura, S.},
url = {http://dx.doi.org/10.1016/j.eswa.2011.05.044},
doi = {10.1016/j.eswa.2011.05.044},
year = {2011},
date = {2011-01-01},
journal = {Expert Systems with Applications},
volume = {38},
number = {12},
pages = {15020-15031},
keywords = {Multi-instance Learning, Predicting Student Performance},
pubstate = {published},
tppubtype = {article}
}
|
2010
|
Zafra, A; Ventura, S Web usage mining for improving students performance in learning management systems Inproceedings Proceedings of the 23rd International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA-AIE'10, pp. 439-449, 2010. Links | BibTeX | Tags: Multi-instance Learning, Predicting Student Performance @inproceedings{Zafra-2010-IEAAIE,
title = {Web usage mining for improving students performance in learning management systems},
author = {Zafra, A. and Ventura, S.},
url = {http://dx.doi.org/10.1007/978-3-642-13033-5_45},
doi = {10.1007/978-3-642-13033-5_45},
year = {2010},
date = {2010-01-01},
booktitle = {Proceedings of the 23rd International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA-AIE'10},
volume = {6098 LNAI},
number = {PART 3},
pages = {439-449},
keywords = {Multi-instance Learning, Predicting Student Performance},
pubstate = {published},
tppubtype = {inproceedings}
}
|
2009
|
Zafra, A; Ventura, S Predicting Student Grades in Learning Management Systems with Multiple Instance Learning Genetic Programming Inproceedings Barnes, T; Desmarais, M C; Romero, C; Ventura, S (Ed.): Educational Data Mining - EDM 2009, Cordoba, Spain, July 1-3, 2009. Proceedings of the 2nd International Conference on Educational Data Mining., pp. 309–318, www.educationaldatamining.org, 2009, ISBN: 978-84-613-2308-1. Links | BibTeX | Tags: Multi-instance Learning, Predicting Student Performance @inproceedings{ZafraP09,
title = {Predicting Student Grades in Learning Management Systems with Multiple Instance Learning Genetic Programming},
author = {Zafra, A. and Ventura, S.},
editor = {Barnes, T. and Desmarais, M. C. and Romero, C. and Ventura, S.},
url = {http://www.educationaldatamining.org/EDM2009/uploads/proceedings/zafra.pdf},
isbn = {978-84-613-2308-1},
year = {2009},
date = {2009-01-01},
booktitle = {Educational Data Mining - EDM 2009, Cordoba, Spain, July 1-3, 2009. Proceedings of the 2nd International Conference on Educational Data Mining.},
pages = {309--318},
publisher = {www.educationaldatamining.org},
keywords = {Multi-instance Learning, Predicting Student Performance},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Zafra, A; Romero, C; Ventura, S Predicting Academic Achievement Using Multiple Instance Genetic Programming Inproceedings Ninth International Conference on Intelligent Systems Design and Applications, ISDA 2009, Pisa, Italy , November 30-December 2, 2009, pp. 1120–1125, IEEE Computer Society, 2009, ISBN: 978-0-7695-3872-3. Links | BibTeX | Tags: Grammar-Based Genetic Programming, Multi-instance Learning, Predicting Student Performance @inproceedings{ZafraRV09,
title = {Predicting Academic Achievement Using Multiple Instance Genetic Programming},
author = {Zafra, A. and Romero, C. and Ventura, S.},
url = {http://dx.doi.org/10.1109/ISDA.2009.108},
doi = {10.1109/ISDA.2009.108},
isbn = {978-0-7695-3872-3},
year = {2009},
date = {2009-01-01},
booktitle = {Ninth International Conference on Intelligent Systems Design and Applications, ISDA 2009, Pisa, Italy , November 30-December 2, 2009},
pages = {1120--1125},
publisher = {IEEE Computer Society},
keywords = {Grammar-Based Genetic Programming, Multi-instance Learning, Predicting Student Performance},
pubstate = {published},
tppubtype = {inproceedings}
}
|
0000
|
García-Martínez, C; Cerezo, R; Bermúdez, M; Romero, C Improving essay peer grading accuracy in MOOCs using personalized weights Journal Article Journal of Computer Assisted Learning, In press , 0000. Links | BibTeX | Tags: Educational Data Mining, Predicting Student Performance @article{cgarcia2018peerReview,
title = {Improving essay peer grading accuracy in MOOCs using personalized weights},
author = {Garc\^{i}a-Mart\^{i}nez, C. and Cerezo, R. and Berm\'{u}dez, M. and Romero, C.},
doi = {10.1111/jcal.12316},
journal = {Journal of Computer Assisted Learning},
volume = {In press},
keywords = {Educational Data Mining, Predicting Student Performance},
pubstate = {published},
tppubtype = {article}
}
|