Premium
A learning analytics tool for the support of the flipped classroom
Author(s) -
RubioFernández Aarón,
MuñozMerino Pedro J.,
Delgado Kloos Carlos
Publication year - 2019
Publication title -
computer applications in engineering education
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.478
H-Index - 29
eISSN - 1099-0542
pISSN - 1061-3773
DOI - 10.1002/cae.22144
Subject(s) - flipped classroom , computer science , learning analytics , set (abstract data type) , analytics , flipped learning , face (sociological concept) , data science , mathematics education , psychology , sociology , programming language , social science
Nowadays, there are quite a few experiences of the use of the flipped classroom (FC) in engineering education due to their advantages in comparison with the traditional methodology. The possibility of promoting students’ active learning under the FC can lead to improvements in the learning outcomes. Nonetheless, there are several issues that arise when using the FC (such as the students’ need of preparing the face‐to‐face lesson) that must be addressed. To take advantage of the whole potential of the FC, we propose the application of learning analytics (LA) to improve the FC. In particular, we define a methodology that proposes a set of recommended actions to be done to enhance a specific type of flipped classroom through LA. Moreover, we present a LA tool designed and implemented specifically for this methodology. This tool allows teachers to obtain relevant information needed to improve their FC experiences. The information is provided using several visualizations that are analyzed and explained in detail. We illustrate the use of the tool with students from engineering courses.