2014
Jerez, Alex Rayón; Guenaga, Mariluz; Núñez, Asier
vol. 8719, Springer, Cham, 2014, ISBN: 978-3-319-11199-5.
Abstract | Links | BibTeX | Tags: competency-assessment, dashboard, learning analytics, learning metrics
@conference{Jerez2014b,
title = {Heterogeneous Educational Data Integration and Knowledge Discovery to Supporting Competency Assessment in SCALA Web Tool},
author = {Alex Rayón Jerez and Mariluz Guenaga and Asier Núñez },
doi = {10.1007/978-3-319-11200-8_81},
isbn = {978-3-319-11199-5},
year = {2014},
date = {2014-09-19},
volume = {8719},
pages = {584-585},
publisher = {Springer, Cham},
abstract = {The lack of data interoperability among different educational systems imposes a challenge to data analytics. To face these problems, we have developed SCALA (Scalable Competency Assessment web platform through a Learning Analytics approach), an integrated analytics system that employs Learning Analytics techniques to visualize in a single interface enriched indicators to teachers and learners, gaining insights into their habits and the impact of their learning activities.},
keywords = {competency-assessment, dashboard, learning analytics, learning metrics},
pubstate = {published},
tppubtype = {conference}
}
The lack of data interoperability among different educational systems imposes a challenge to data analytics. To face these problems, we have developed SCALA (Scalable Competency Assessment web platform through a Learning Analytics approach), an integrated analytics system that employs Learning Analytics techniques to visualize in a single interface enriched indicators to teachers and learners, gaining insights into their habits and the impact of their learning activities.
2009
Jerez, Alex Rayón; Guenaga, Mariluz; Núñez, Asier
Integrating and visualizing learner and social data to elicit higher-order indicators in SCALA dashboard Journal Article
In: i-KNOW '14 Proceedings of the 14th International Conference on Knowledge Technologies and Data-driven Business, no. 28, 2009, ISBN: 978-1-4503-2769-5.
Abstract | Links | BibTeX | Tags: computer-assisted instruction, dashboard, data integration, information retrieval, large-scale interoperability, learning analytics, visual analytics
@article{Jerez2009,
title = {Integrating and visualizing learner and social data to elicit higher-order indicators in SCALA dashboard},
author = {Alex Rayón Jerez and Mariluz Guenaga and Asier Núñez},
editor = {ACM New York, NY, USA ©2014},
doi = {10.1145/2637748.2638435},
isbn = { 978-1-4503-2769-5},
year = {2009},
date = {2009-09-16},
journal = {i-KNOW '14 Proceedings of the 14th International Conference on Knowledge Technologies and Data-driven Business},
number = {28},
abstract = {The assessment of competencies is a difficult task; on one hand due to its subjective nature, and, on the other one, because of the difficulties to make it scalable and simple. Since ICT are becoming increasingly important learning mediating tools, data stored in learning tools could yield a wealth of information that could serve as an indicator to measure students' progress and the development of competencies. However, the lack of data interoperability among different educational applications imposes a challenge to data mining and analytics that rely on diverse and distributed data. Besides, these educational technologies do neither usually provide a statistics module in which the teacher can obtain specific reports about students' performance, nor visualization tools to summarize student usage data. In response to this weakness, and based on the limitations encountered in existing tools, we have developed an integrated and extensible web tool called SCALA (Scalable Competency Assessment through a Learning Analytics approach) that not only shows but also mines using analytics techniques for the discovery of student patterns and metric relations in web-based educational systems.},
keywords = {computer-assisted instruction, dashboard, data integration, information retrieval, large-scale interoperability, learning analytics, visual analytics},
pubstate = {published},
tppubtype = {article}
}
The assessment of competencies is a difficult task; on one hand due to its subjective nature, and, on the other one, because of the difficulties to make it scalable and simple. Since ICT are becoming increasingly important learning mediating tools, data stored in learning tools could yield a wealth of information that could serve as an indicator to measure students' progress and the development of competencies. However, the lack of data interoperability among different educational applications imposes a challenge to data mining and analytics that rely on diverse and distributed data. Besides, these educational technologies do neither usually provide a statistics module in which the teacher can obtain specific reports about students' performance, nor visualization tools to summarize student usage data. In response to this weakness, and based on the limitations encountered in existing tools, we have developed an integrated and extensible web tool called SCALA (Scalable Competency Assessment through a Learning Analytics approach) that not only shows but also mines using analytics techniques for the discovery of student patterns and metric relations in web-based educational systems.