2015
Guenaga, Mariluz; Menchaca, Iratxe; Solabarrieta, J.
Project-Based Learning: Methodology and Assessment Learning Technologies and Assessment Criteria Conference
Using Educational Analytics to Improve Test Performance, 2015, ISBN: 978-3-319-24257-6.
Abstract | Links | BibTeX | Tags: aprendizaje automático, learning analytics, machine learning, mining educational data
@conference{Guenaga2015b,
title = {Project-Based Learning: Methodology and Assessment Learning Technologies and Assessment Criteria},
author = {Mariluz Guenaga and Iratxe Menchaca and J. Solabarrieta},
url = {https://home/learninglabdeust/public_html.researchgate.net/publication/283535054_Project-Based_Learning_Methodology_and_Assessment_Learning_Technologies_and_Assessment_Criteria},
doi = {10.1007/978-3-319-24258-3_68},
isbn = {978-3-319-24257-6},
year = {2015},
date = {2015-01-01},
booktitle = {Using Educational Analytics to Improve Test Performance},
pages = {601-604},
abstract = {This paper uses a project-based learning methodology in higher education to analyse its relation to a theoretical framework of competency. Based on this analysis, we propose a set of technological tools to support the development of competency at the university level as well as a set of indicators to systematize the assessment process. Finally, indicators are related to data that can be obtained from these technological tools. This is the basis for additional work on learning analytics that is used to support the assessment of a project-based learning approach. },
keywords = {aprendizaje automático, learning analytics, machine learning, mining educational data},
pubstate = {published},
tppubtype = {conference}
}
This paper uses a project-based learning methodology in higher education to analyse its relation to a theoretical framework of competency. Based on this analysis, we propose a set of technological tools to support the development of competency at the university level as well as a set of indicators to systematize the assessment process. Finally, indicators are related to data that can be obtained from these technological tools. This is the basis for additional work on learning analytics that is used to support the assessment of a project-based learning approach.