Changes of Learning in Mobile Scenarios
Analysis and Comparison of Use and Browsing of a Virtual Campus
in Mobile Scenarios
Magí Almirall-Hill and Julià Minguillon
Universitat Oberta de Catalunya, Av Tibidabo 39, Barcelona, Spain
Keywords: Elearning, Mobile, Human Computer Interaction, System Analysis.
Abstract: Mobility and working with mobile devices is now a well-established reality in our society. Students use the
train, car or weekend away to work on their teaching materials. Likewise, technology allows for the
generation of new content formats every day – letting us write text and convert it automatically into voice,
web, PDF or DVD. This article proposes detailed monitoring of the browsing logs of a number of students
using a mobile device (iPad) in order to better understand students’ habits. The study is based on a
comparison of browsing habits on PCs and mobile devices, and includes contextual observation fieldwork.
Thus, the study combines both quantitative and qualitative data. Results obtained using this methodology
will provide us with better insight of user navigational behaviour with respect to the used devices.
1 INTRODUCTION
The growth of mobile devices looks as it will
overtake personal computers. The official data show
that we already have more mobile telephones than
any other kind of technology, apart from televisions.
This can be seen in the following Figure 1 published
by the Instituto Nacional de Estadística (Spanish
National Institute of Statistics, INE) as one the main
conclusions to its 2008 survey on ICT equipment
and use (Encuesta sobre Equipamiento y Uso de
Tecnologías de Información y Comunicación en los
Hogares. Año 2008).
Figure 1: 2008 survey on ICT equipment and use in Spain.
On the other hand, students currently enrolling
on e-learning courses are generally adults with work
commitments. The Figure 2 below from the UOC’s
portal shows the profiles of its students.
Fig 2: UOC’s students profiles in 2010.
The data show that the number of people who
need to make the most of mobile scenarios for
learning is very high. This paper studies in detail
these mobile scenarios, obtaining browsing data so
as to improve and optimise learning. We can already
see people on different forms of public transport
using devices, generally for listening to music,
reading or consulting documents. The proposal
outlined below focuses on in-depth analysis of these
scenarios and a pilot test – so as to aid and support
students in making the most of this time for learning
anytime and anywhere.
120
Almirall-Hill M. and Minguillon J..
Changes of Learning in Mobile Scenarios - Analysis and Comparison of Use and Browsing of a Virtual Campus in Mobile Scenarios.
DOI: 10.5220/0004091301200122
In Proceedings of the 14th International Conference on Enterprise Information Systems (ICEIS-2012), pages 120-122
ISBN: 978-989-8565-12-9
Copyright
c
2012 SCITEPRESS (Science and Technology Publications, Lda.)
2 RESEARCH PROPOSAL AND
AIMS
This research forms part of a larger project on
mobility and learning at the Universitat Oberta de
Catalunya (Open University of Catalonia, UOC). To
date, work has been carried out to provide
classrooms with new content formats for mobility
and additional qualitative studies have been made
into how these new content formats are used. For the
first time, a pilot test group has been brought
together in a virtual classroom and provided with
iPads with an internet connection, allowing us to
obtain data on their actual use.
Thus, our proposal is to analyse, describe and
understand how people study in mobile scenarios.
To do so, we will ask two kinds of questions; firstly,
to find out about and describe the scenarios, and,
secondly, to look at the technological solutions that
could be used to optimise students’ work. We first
intend to fully describe the scenarios; i.e., what is
happening and how it is happening. To do so, we
will ask the following research questions:
What are the new mobile scenarios for learning
like?
What tasks are undertaken by students in these
scenarios?
How do they differ from tasks undertaken on
traditional PCs?
Once this is complete, we will also look to
analyse the process by examining how interactions
take place and assessing how this scenario develops.
We also intend to ask a question about use of time
that will allow us to ascertain the travel taking place
in each scenario.
What use of time does a student make on public
transport?
Likewise, we also intend to ask questions
relating to the evolution of the learning tasks carried
out by students in these scenarios – assessing which
one of reading, writing, searching for information or
working with other classmates best adapts to each
scenario. Then we would like to obtain answers to
the following questions:
Which tasks best adapt to each scenario?
Which tasks do students tend to undertake in
each scenario?
This last question will help us to guide how the
technology, tools, content formats, voice, video,
text, interaction, annotations, etc. have to evolve in
terms of improving each student’s learning
experience in each scenario, so we can answer the
following question:
How do we need to adapt the Virtual Campus
to each scenario?
We intend to set two working objectives that
encompass the above research questions:
1. Describe the new mobile scenarios, including
both the scenario and the profile of the people
and tasks involved.
This objective not only describes the scenarios,
but also what happens therein. Thus, it is important
that this objective responds to the first three
questions. We want this objective to have clear data
on what is happening, not in terms of a single
snapshot, but as a film. Therefore, the analysis of the
use of time is essential. This data will provide us
with a browsing tree structure in terms of time and
frequency.
2. Assess how the different tasks necessary in
the learning process change in a mobile
scenario.
This second objective ensures that the results of
the project will not only involve a description, but
also a pilot test of new tools, in order to see what
changes are needed, and, thus, what is required of
mobile learning tools in terms of adaptation to users
and their environment.
3 OPERATING METHOD AND
METHODOLOGY
3.1 Justification
The combination of qualitative analysis and real
browsing has been seen in a number of cases to be
useful for describing user-system interaction (Yuni,
2005). This proposal focuses our efforts on
discovering the actual interaction with an iPad and
comparing it to the interaction with a PC.
Thus, Table 1 below shows the series of tools to
be used in this research, and the specific aim of
each.
ChangesofLearninginMobileScenarios-AnalysisandComparisonofUseandBrowsingofaVirtualCampusinMobile
Scenarios
121
Table 1: Instruments of analysis.
INSTRUMENT SOURCE AIM
Analysis of PC
logs
UOC logs
Ascertain the current
standard browsing using a
PC for subjects similar to
the pilot test.
Analysis of iPad
logs
UOC logs
Ascertain the browsing
developed by pilot test
users on their iPads, both
using the application and
the web.
Focus groups
Pilot
students
Analyse and understand the
quantitative results.
3.2 Research Phases
We envisage undertaking the research in two
consecutive phases: the first phase focuses on
preparing and carrying out the pilot test with iPads,
which will allow us for extraction of data on the
browsing record on both PCs and iPads. The second
phase analyzes on the real student behaviour using
focus groups, in order to better understand
quantitative results obtained in the first phase.
PHASE 1: Browsing analysis
Three possible groups:
PC students browsing
iPad students browsing on PCs
iPad students browsing on iPads
PHASE 2: Focus groups
Why did changes take place?
What new tools do students expect?
4 EXPECTED RESULTS
Once the information has been classified in terms of
the initial objectives, we will be able to identify the
weak points of the current system (which was not
originally designed for iPads) and adapt the design
of the technology or format to make working and
learning in these scenarios easier. We expect to
observe a different kind of browsing to that seen
when using PCs, with simultaneous use of voice and
text, and shorter browsing with less intense activity.
We also expect to identify the types of tasks that
are usually seen in mobile scenarios: skim reading,
short responses, etc.
ACKNOWLEDGEMENTS
This work has been partially supported by Project
MAVSEL (ref. TIN2010-21715-C02-02).
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