About this paper

Appears in:
Pages: 5173-5178
Publication year: 2019
ISBN: 978-84-09-12031-4
ISSN: 2340-1117
doi: 10.21125/edulearn.2019.1279

Conference name: 11th International Conference on Education and New Learning Technologies
Dates: 1-3 July, 2019
Location: Palma, Spain

TOOLBOX.ACADEMY: CODING & ARTIFICIAL INTELLIGENCE MADE EASY FOR KIDS, BIG DATA FOR EDUCATORS

F. Vico1, J. Masa2, R. García2

1University of Malaga, Departamento de Lenguajes y Ciencias de la Computación (SPAIN)
2ToolboX Academy (SPAIN)
The world has reached the point where there is considerable awareness about the need of teaching coding skills at the schools. Both, political leaders and educational systems start taking positions in this strategic new arena, but lack from much of the expertise and necessary tools about how to teach this complex (but also intuitive to children and youngsters) field of knowledge. In this context, ToolboX Academy is a programming platform which subscribes a slightly new approach to attack the problem, for at least four differential aspects: 1) While most attention focuses on block-based approaches (Scratch and Code.org being the most popular initiatives), ToolboX embraces coding as it works for developers: text-based programming; 2) ToolboX embeds mainstream programming languages, which are widely used, are supported by big communities, are weakly typed, and closer to human natural language, like it is GNU Octave in engineering and scientific research, and Javascript in web applications; 3) provides user-oriented problem-based learning designed upon educational research results, and 4) integrates curricular subjects in learning to code. In this paper, we review the design constraints taken into account to develop ToolboX Academy, and how it has been tested in the classroom. Some features are particularly stressed, like the use of open formats for content representation (definition of tasks or problems); the design of a simplified environment to represent most CS concepts, from basic loops to complex graph traversal strategies; and the use of learning analytics based on big data algorithms that can help educators and managers to learn from the interaction of their students with this environment.
@InProceedings{VICO2019TOO,
author = {Vico, F. and Masa, J. and Garc{\'{i}}a, R.},
title = {TOOLBOX.ACADEMY: CODING & ARTIFICIAL INTELLIGENCE MADE EASY FOR KIDS, BIG DATA FOR EDUCATORS},
series = {11th International Conference on Education and New Learning Technologies},
booktitle = {EDULEARN19 Proceedings},
isbn = {978-84-09-12031-4},
issn = {2340-1117},
doi = {10.21125/edulearn.2019.1279},
url = {http://dx.doi.org/10.21125/edulearn.2019.1279},
publisher = {IATED},
location = {Palma, Spain},
month = {1-3 July, 2019},
year = {2019},
pages = {5173-5178}}
TY - CONF
AU - F. Vico AU - J. Masa AU - R. García
TI - TOOLBOX.ACADEMY: CODING & ARTIFICIAL INTELLIGENCE MADE EASY FOR KIDS, BIG DATA FOR EDUCATORS
SN - 978-84-09-12031-4/2340-1117
DO - 10.21125/edulearn.2019.1279
PY - 2019
Y1 - 1-3 July, 2019
CI - Palma, Spain
JO - 11th International Conference on Education and New Learning Technologies
JA - EDULEARN19 Proceedings
SP - 5173
EP - 5178
ER -
F. Vico, J. Masa, R. García (2019) TOOLBOX.ACADEMY: CODING & ARTIFICIAL INTELLIGENCE MADE EASY FOR KIDS, BIG DATA FOR EDUCATORS, EDULEARN19 Proceedings, pp. 5173-5178.
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