Authors:
Irene Urcelay-Olabarria
1
;
Ruth Lazkoz
2
;
Jon Urrestilla
2
;
Aritz Leonardo
3
and
Josu M. Igartua
3
Affiliations:
1
Euskal Herriko Unibertsitatea (UPV/EHU), Spain
;
2
University of the Basque Country (UPV-EHU), Spain
;
3
University of the Basque Country (UPV/EHU), Spain
Keyword(s):
Jupyter Notebook, Virtual Laboratory, Python
Related
Ontology
Subjects/Areas/Topics:
Computer-Supported Education
;
e-Learning
;
Information Technologies Supporting Learning
;
Ubiquitous Learning
;
Virtual Labs and Virtual Classrooms
;
Virtual Learning Environments
Abstract:
In the Physics Degree it is of fundamental importance to practice in an Experimental Laboratory. The standard
Laboratory Sessions consist of two main parts: data handling and data processing. The session should also
have a prologue, where students get to know the underlaying theory of the practical session and an epilogue,
where students present the results obtained and the difficulties encountered. The prologue and the epilogue
naturally decouple from the work in the laboratory. Data processing, in most cases, is effectively decoupled
from the work in the laboratory, as well. In this short paper we present a tool, the Jupyter Notebook, an
electronic laboratory logbook, which conveniently facilitates the decoupling of the data handling and processing,
but which merges almost completely into an electronic notebook the four parts of the laboratory practical
session: theory, data, processing and presentation. But, interestingly, the notebook goes beyond that: it allows
the stud
ents to explore the data in an interactive way (simulating variants), to acquire a deeper knowledge of
the data (by digitally altering the experiment or simulating new ones), to propose new experiments, etcetera.
We strongly believe that this tool can also motivate the students: the results are obtained interactively, immediately,
visually, and they can be shared and even improved. Moreover, the laboratory sessions get optimized:
simulations make the sessions be focused on obtaining data and in its variants.
(More)