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Authors
Advisor(s)
Abstract(s)
The present paper is part of a wider study, focussed on
the development of a digital educational resource for Science
Education in primary school, integrating an Educational Data
Mining framework. The proposed conceptual framework aims to infer
the impact of the adopted learning approach for the development of
scientific competences and students’ self-regulated learning. Thus,
students’ exploration of learning sequences and students' behaviour
towards available help, formative feedback and recommendations
will be analysed. The framework derives from the proposed learning
approach, as well as from the literature review. Before introducing it,
the authors present an overview of the digital educational resource
learning approach and the adopted Educational Data Mining
methods. Finally, we present the proposed conceptual Educational
Data Mining framework for Science Education, focussing its
relevance on the development of students' scientific competences and
self-regulated learning.
Description
Keywords
Educational data mining Latent knowledge estimation Causal data mining Domain structure discovery Digital educational resources Scientific competences Selfregulated learning
Citation
Tavares, R., Vieira, R., Pedro, L. (2017) A preliminary proposal of a conceptual Educational Data Mining framework for Science Education: Scientific competences development and self-regulated learning in Ponte, C., Dodero, J. M., Silva, M. J. (2017) Atas do XIX Simpósio Internacional de Informática Educativa e VIII Encontro do CIED – III Encontro Internacional. (216-221) Lisboa: CIED – Centro Interdisciplinar de Estudos Educacionais
Publisher
CIED – Centro Interdisciplinar de Estudos Educacionais