Smart ePortfolio System
Experimental Prototype Testing in Living Lab and Further Artificial Intelligence
Implementation Design within ePortfolio System
Aleksandrs Gorbunovs
Distance Education Study Centre, Riga Technical University, Azenes Street 12, Riga, Latvia
Keywords: Information System, ePortfolio, Assessment, Critical Thinking, Reflection, Collaborative Learning,
Artificial Intelligence.
Abstract: This paper’s aim is to pay attention to actuality of new information system development in a form of
engaging and reflective ePortfolios. Main accent in the system is put on an encouragement of learners’
collaborative efforts in teams, activate their critical thinking and reflection, and as a result, achieve better
learning outcomes and competencies. The author introduces experimental ePortfolio system prototype and
its testing results in Living Lab environment in Riga Technical University. A notion of making ePortfolio
system more reflective, interactive and intelligent brings further proposals of development additional
artificial intelligence tools which might be embedded into the system.
1 INTRODUCTION
New technologies change our habits, work
procedures, leisure hours, communication
opportunities, and our life. These changes bring new
breath also in educational environment; educational
paradigms switch over from teacher-centric to
student-centric, from mainly individual to mainly
collaborative interaction; learners are oriented on
development of their critical thinking skills,
enhancement of creativity, wider use of technology
in knowledge acquisition process (Churches, 2010).
It allows students to be better prepared for nowadays
challenges.
Educational sphere demands for effective
managerial work, assessment and self-assessment
processes to improve learning outcomes (Goldspink,
2007). Progressive educators try to find the most
useful and suitable educational methods and tools to
satisfy lifelong learning needs. They are seeking for
new ways to make learning process more engaging,
motivating, creative, and effective. Information
technologies provide invaluable support in
introducing of new teaching and learning methods.
Occasionally scientists create new and modernize
existing educational tools and systems; and this
creativity process often is advanced by scholastic
institutions requests.
ePortfolio systems might be considered as new
effective competence enhancement instruments.
They also have changed their own nature: from
simple showcase forms (in the past) to motivating
workspace environments (nowadays). These two
different natures or faces of the ePortfolios indicate
two different senses: ePortfolio as a product in the
first case, and ePortfolio as a process in the second
case (Barett, 2009). Showcase form of ePortfolios
still has prevalence. Nevertheless, more and more
educational institutions seek for more powerful end
effective ePortfolio systems to improve learning
outcomes.
Reflection, critical thinking, ability to work in
collaborative and tied to time settings are considered
as important factors to be able to enhance learners
competencies. Excellent results might be achieved
by „involving students in doing things and thinking
about what they are doing” (Bonwell and Eisen,
1991). Stimulation of critical thinking and reflection
could be considered as a fine solution to meet the
competence enhancement demands.
This paper shows the latest ePortfolio
developments realized by Distance Education Study
Centre, Riga Technical University (DESC RTU),
examines Living Lab testing and research results
related to effectiveness of experimental ePortfolio
system prototype, as well proposes a new generation
ePortfolio system algorithmic model.
238
Gorbunovs A..
Smart ePortfolio System - Experimental Prototype Testing in Living Lab and Further Artificial Intelligence Implementation Design within ePortfolio
System.
DOI: 10.5220/0004383602380241
In Proceedings of the 5th International Conference on Computer Supported Education (CSEDU-2013), pages 238-241
ISBN: 978-989-8565-53-2
Copyright
c
2013 SCITEPRESS (Science and Technology Publications, Lda.)
2 DEVELOPMENT OF THE
E-PORTFOLIO SYSTEM
2.1 Testing of ePortfolio System
Prototype in Living Lab
Keeping in mind, that Living Labs are intended to
involve users in the innovation process, knowledge
sharing, exploration, experimentation, assessment,
and co-creation (Pallot, 2009), created engaging
scaffolding ePortfolio system was tested in RTU
DESC Living Lab in study year of 2011/2012
(Gorbunovs, Kapenieks, A., and Kudina, 2012).
Figure 1. Simplified scheme of the ePortfolio system’s
algorithmic model (Gorbunovs, et al, 2012).
Experimental ePortfolio system (the left side of
the Fig.1) embodies environment where students
after submission of their accomplished homework
(tasks) are divided in teams (groups) of four
participants each and asked to acquaint themselves
with other group members accomplished homework,
reflect, assess them both in scores and in a form of
critical thinking notes and suggestions, as well make
self-assessments about own accomplishments and
possible shortages. Students have a possibility to see
group member names against their achieved
assessment results: scores, critical thinking notes and
constructive suggestions. To clarify details, students
also can establish internal and external
communication links. These processes are monitored
by tutors who can give necessary advice and
assistance. Students are also asked to reflect on own
work and his/her group members feedback in a form
of critical thinking notes and suggestions, take a note
of tutors advice, estimate the data and put them
against own calculations, analyse information, select
appropriate conclusions, add something well-formed
or synthesize creative ideas. All this might lead to
increasing of the number of improved homework
and growing better learning outcomes.
2.2 Results and Progress Report
From 203 joined the BPOM (“Business Planning for
Open Markets”) course students only 173 learners
finished it. Drop out reasons vary but none of them
are caused by BPOM course issues. 56 learners took
part in all group-working activities (5 tasks) within
ePortfolio system, 16 students also were very active
– they participated in four group-working activities,
19 students were rather moderate – three group-
working activities, 27 students were less active –
two activities, 39 students were inactive – only one
group-work was done, and 97 did not participated in
any of ePortfolio group-working activities. As the
participation in ePortfolio activities for students was
not compulsory, shown numbers of participation
activities is rather high.
Figure 2: BPOM competence (on average of seven)
development correlations with ePortfolio activities.
ePortfolio prototype testing results in Living Lab
show (for example, Fig. 2) that activities within
0,00
2,00
4,00
6,00
8,00
10,00
12,00
Very active (5
tasks)
Active (4 tasks)
Moderate (3 tasks)
Less active (2
tasks)
Non-active ( 1 task)
Inactive (0 tasks)
SmartePortfolioSystem-ExperimentalPrototypeTestinginLivingLabandFurtherArtificialIntelligenceImplementation
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239
Figure 3: Proposed ePortfolio system’s algorithmic model.
ePortfolio system have direct correlations with
students’ exam results and increased level of their
competencies. Similarly, the number of improved
homework also has direct correlation with activities
within ePortfolio system, i.e. the number of
ePortfolio login files. More active students much
more take part in offered group work activities. It is
clearly that learners’ reflection on critical thinking
notes and constructive suggestions leads to a
creativity, synthesis and competence development.
As a result, the number of corrected, slightly
improved or crucially processed works depends on
users’ activity level within ePortfolio system. All in
all there were received 312 improved works. From
them the second homework was improved 78 times,
the third homework was improved 66 times, the
fourth homework was improved 65 times; and the
fifth homework was improved 103 times.
In the current study year of 2012/2013
experimental ePortfolio system is improved by
adding new features, such as automation of students’
homework submission to the ePortfolio system and
automatic ePortfolio group formation based on a
sequence of submitted homework accomplishments.
Nevertheless, the challenging issues regarding
development of a new generation ePortfolio system,
i.e. smart ePortfolios, still remain.
2.3 Initialization of Artificial
Intelligence Methods
New smart ePortfolio system might be created by
enrichment of existing system algorithmic model
with artificial intelligence (AI) traits. The system
will start by assembling person’s achievements data
(certificates, diplomas, self-assessments, exam
results and so on) to form a person’s competence
profile (Fig. 3) and determination whether the
person’s competence profile exists or not. If the
profile does not meet fixed requirements (there is no
competence markers within a cell), the system will
encore the procedure. If the profile exists, an
eligibility of the person’s initial competences against
learning goals will be assessed. Further the system
will analyse whether the person (i.e. person’s
competence profile) fits these requirements or not.
In a positive acknowledgement an assertion of
conformity will be issued. It means that the person
does not need any learning for particular case.
Otherwise, the person will be asked to apply for
the course. The system will issue corresponding
CSEDU2013-5thInternationalConferenceonComputerSupportedEducation
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learning objects and/or links allowing acquisition of
the course. The learner will accomplish the first
home-work and test, make self-assessment and
assess ePortfolio group members’ homework which
will include marking of required assessment criteria
and formulating an opinion in a form of constructive
recommendation. Based on these critical thinking
notes the learner will reflect and decide whether
peers’ suggestions are useful or not. This decision
may lead to further homework improvement and
creativity actions. Improved work again will be
input into the system and exposed for analysing and
assessment by ePortfolio group participants once
more. The student will be able also do not take any
homework improvement actions if he/she concludes
that ePortfolio system group members’ remarks are
not constructive and useful. In both cases after
completion of the first theme the next course module
will open.
Test results and competence assessments data
further will be assembled and analysed in order to
state the value of gained competences. Depending
on achieved competence level appropriate learning
object code will be generated; and the learner will
receive necessary learning objects with assigned
codes. Initial competence assessment is essential.
Processes, such as an assignment of the competence
correlative codes to the learning objects and the
assignment of the learning objects’ self-correction
rates, play significant role in ePortfolio system’s AI
decision making process. They allow finding the
most suitable learning path in specific case.
3 CONCLUSIONS
Created collaborative ePortfolio system prototype
verified our expectations regarding system’s positive
impact on learning outcomes. Activities within
ePortfolio system have direct correlations with
students’ exam results and increased level of their
competencies. Students are encouraged reflect and
think critically. Their creativeness grows by virtue
of active participation in collaborative activities
within ePortfolio system.
On the other hand, an analysis of students’ self-
assessments within university’s study portal
“ORTUS” displayed learners’ inability to make self-
assessments by objective considerations: many
students had a lack of confidence, and, as a result,
their initial self-assessment marks were far from real
competence levels. It took time to get some
confidence. Hardworking students enabled steady
progress, which allowed them to acquire required
competences and achieve remarkable final exam
results. Other students overleapt themselves. Starting
from the second course module they made
corrections in self-assessment questionnaires.
Activities within ePortfolio system influenced more
precise adjustment of these changes.
Proposed artificial intelligence methods and
tools to be embedded into ePortfolio system might
look promising. Both students and teachers might
gain by its use. There will be further considerations,
developments and adjustments (creation of system
modules, generating competence correlative codes to
the learning objects, etc.) needed to build up the new
generation ePortfolio system – smart ePortfolios.
ACKNOWLEDGEMENTS
The travel costs and participation fee to conference
was supported by the European Regional
Development Fund project «Development of
international cooperation projects and capacity in
science and technology Riga Technical University»,
Nr. 2DP/2.1.1.2.0/10/APIA/VIAA/003.
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