2017
Olivares-Rodriguez, Cristian; Guenaga, Mariluz; Garaizar, Pablo
Automatic Assessment of Creativity in Heuristic Problem-solving Based on Query Diversity Journal Article
In: DYNA, vol. 92, no. 4, pp. 449-455, 2017.
Abstract | Links | BibTeX | Tags: aprendizaje automático, Búsqueda de información, information search, machine learning, patrón de consultas, problem solving, query pattern, resolución de problemas
@article{Olivares-Rodriguez2017,
title = {Automatic Assessment of Creativity in Heuristic Problem-solving Based on Query Diversity},
author = {Cristian Olivares-Rodriguez and Mariluz Guenaga and Pablo Garaizar},
url = {http://home/learninglabdeust/public_html.revistadyna.com/Articulos/Ficha.aspx?IdMenu=a5c9d895-28e0-4f92-b0c2-c0f86f2a940b&Cod=8243&Codigo=b25ba3bd-bef9-4391-8317-6a8209d9309e},
doi = {10.6036/8243},
year = {2017},
date = {2017-07-03},
journal = {DYNA},
volume = {92},
number = {4},
pages = {449-455},
abstract = {Creative problem-solving emerges as one of the most relevant skill of the 21st century knowledge society. Fortunately, there are many creativity training programmes that have proven effective. However, most of these programmes require a previous measurement of creativity, which involves time-consuming tasks conducted by experienced reviewers, i.e. far from primary school classroom dynamics. In this study, we propose a model to predict the creative quality of students’ solutions based on the analysis of query patterns and the use of Wikipedia. This model has been able to predict the creative quality of solutions produced by 226 school students, aged 10 to 12 years old, reaching a sensitivity of 78.43%. The agreement among reviewers regarding students’ creative characteristics has also been evaluated using two rubrics. We hope this model can be used to foster prompt detection of non-creative solutions in order to enable intervention and improve the final result in terms of creativity.},
keywords = {aprendizaje automático, Búsqueda de información, information search, machine learning, patrón de consultas, problem solving, query pattern, resolución de problemas},
pubstate = {published},
tppubtype = {article}
}
Creative problem-solving emerges as one of the most relevant skill of the 21st century knowledge society. Fortunately, there are many creativity training programmes that have proven effective. However, most of these programmes require a previous measurement of creativity, which involves time-consuming tasks conducted by experienced reviewers, i.e. far from primary school classroom dynamics. In this study, we propose a model to predict the creative quality of students’ solutions based on the analysis of query patterns and the use of Wikipedia. This model has been able to predict the creative quality of solutions produced by 226 school students, aged 10 to 12 years old, reaching a sensitivity of 78.43%. The agreement among reviewers regarding students’ creative characteristics has also been evaluated using two rubrics. We hope this model can be used to foster prompt detection of non-creative solutions in order to enable intervention and improve the final result in terms of creativity.
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.