Content uploaded by Dietrich Albert
Author content
All content in this area was uploaded by Dietrich Albert on Feb 20, 2015
Content may be subject to copyright.
Conference ICL2010 September 15 -17, 2010 Hasselt, Belgium
1(7)
A Navigation Tool for Adaptive Guidance and Orientation in
Open Responsive Learning Environments
Alexander Nussbaumer
12
, Karin Fruhman
1
,Dietrich Albert
12
1
Institute for Knowledge Management, Graz University of Technology, Austria
2
Department of Psychology, University of Graz, Austria
Key words
:
navigation tool, navigational support, adaptive guidance, open
responsive learning environment, self-regulated learning
Abstract
:
This paper presents a tool which supports self-regulated learning in the context of
open responsive learning environments. The context of this tool is a technical
infrastructure which empowers learners to build their own learning environments by
choosing from existing learning resources, such as content, learning tools, and learner
networks. In order to provide support for learners in this complex environment, a tool
has been developed which supports the learner in both taking advantages from this
technical infrastructure and navigating self-regulated though the own learning
process. This tool is based on psycho-pedagogical models, such as the recently
elaborated self-regulated learning process model, competence model, and learning
activity model. The purpose of that tool is to provide adaptive guidance and
orientation in order to empower the learner to learn self-regulated and to adopt the
concept of learn self-regulated learning.
1 Introduction
One of the main goals of the ROLE research project (Open Responsive Learning
Environment, [ROLE, 2010]) is to empower the learners to build their own learning
environment and to use them for self-regulated learning. These individually compiled learning
environments should be open regarding learning content, learning tools, and learner networks.
Furthermore, they should be responsive to the learners by providing feedback on the learners'
actions and they should enable and support self-regulated learning. Therefore a technical
infrastructure is being created which allows learners to choose and select their learning
resources (content, tools, and peers) and to navigate through their self-regulated learning
processes. It is aimed that a great number of learning resources will be available which the
learner can include in the own learning environment. An example for language learning can
be seen in [Renzel, 2010].
The ROLE infrastructure is powerful and flexible and is supposed to be of great benefit for
learners who know how to use this environment in a psychological and pedagogical
meaningful way. Self-regulated learners (learners who know how learn and can control their
own learning process) in the context of ROLE should be able to set their goals and plan their
learning process, to build their own learning environment, to use the individually compiled
learning environment, and to reflect on their own learning process. Furthermore, they should
be able to use the ROLE infrastructure for these purposes or performing at least part of them
Conference ICL2010 September 15 -17, 2010 Hasselt, Belgium
2(7)
without technology (for example goal setting has not explicitly to be done technology-
supported).
However, if learners are not able to control their learning process perfectly self-regulated,
they will need some guidance and help. In order to provide effective guidance for self-
regulated learning in the context of ROLE, a tool is being developed which helps learners to
navigate through their own self-regulated learning processes. The basic approach of this tool
is to provide concrete recommendations for performing cognitive and meta-cognitive learning
activities and for using learning resources, such as content object, learning tools, and peers for
collaboration. For grounding these recommendations on a theoretical basis, a psycho-
pedagogical framework is used which defines the self-regulated learning process and how it
can be used for scaffolding strategies. This theoretical approach is described in Section 2.
For designing navigational support, a tool from a different context but with a similar purpose
has been taken as a basis for analysing the requirements and usage scenario. When driving a
car or bicycle and the route to the destination is unknown, then people often make use of a
GPS navigation tool (see Figure 1). They drive freely through a network of streets and get
recommendation in each moment dependent on their current location. They can accept
recommendations or not to accept them and deviate from the proposed route. In both cases
this navigation tool adapts its recommendations to the actual position.
Figure 1. A typical GPS navigation tool which provides adaptive guidance
and orientation for reaching a defined destination.
The approach for designing a navigation tool for self-regulated learning can benefit from the
usage design of GPS navigation tools. The reason for the expected benefit is the similarity of
the purpose and situation. Drivers getting adaptive guidance for individually driving to a
defined destination are in a similar situation as learners getting adaptive guidance for
individually navigating through the learning process. Section 3 describes the design of the
navigation tool, which takes into account the features of the GPS navigation tool.
Conference ICL2010 September 15 -17, 2010 Hasselt, Belgium
3(7)
2 Self-regulated Learning Process Model
The Self-regulated Learning Process Model (SRL process model) describes how self-
regulated learning should take place in a ROLE context and how learners can be supported to
learn in a self-regulated way and. moreover, how learners improve self-regulated learning
abilities [Fruhmann et al, 2010]. It is also connected to a model of cognitive and meta-
cognitive learning activities which typically are performed in these situations. Furthermore, it
relies on a competence model which also takes into account abilities for learning with specific
tools and for the abilities of self-regulated learning.
The SRL process model consists of four learning phases which basically are the predominant
activity groups that are supposed to be performed by learners in the context of the technical
infrastructure of ROLE (see Figure 2). In short, these phases are (a) profile setting (including
goal setting), (b) compiling the own learning environment, (c) using and learning with the
individually compiled learning environment, and (d) performing self-reflective activities. This
model is built upon the approach for self-regulated learning by Zimmerman [Zimmermann,
2002] which is based on three meta-cognitive phases (forethought phase (e.g. goal setting and
planning), the performance phase (e.g. self-observation processes), and the self-reflection
phase (e.g. self-reflection processes). In order to align these meta-cognitive phases with the
ROLE infrastructure, learning activities have been defined which reflect both dimensions self-
regulated activities on a meta-cognitive level as well as more concrete activities on a
cognitive level which partly can be related to the technical infrastructure of ROLE. SRL
activities are classified using SRL processes described in [Dabbagh, 2004] and more concrete
activities are classified using the 8LEM model described in [Leclercq, 2009].
Figure 2. SRL Process Model. The diagram shows the four phases and indicates
that each phase is made up of cognitive and meta-cognitive learning activities.
Furthermore, a competence model has been defined which includes self-regulatory
competences and tool competences, besides the widely used competence definition regarding
knowledge domains. A tool competence is regarded as the ability to perform a learning
activity with a certain tool meaning the domain knowledge and domain competences can be
obtained using this tool. Self-regulatory competences describe the abilities to perform certain
Conference ICL2010 September 15 -17, 2010 Hasselt, Belgium
4(7)
meta-cognitive learning activities associated with self-regulated learning. Both types of
competences are important since they are prerequisite for certain recommendations. For
example, goal setting activity should not be recommended to a person who is not able to
perform goal setting.
The learner model contains the competences which a learner actually has available, where the
three types of competences are taken into account. Furthermore, the learning goals are part of
the learner model, whereby goals are structured hierarchically and can be assigned with
competences (to be achieved). Goals can also be assigned with learning activities which
should be performed to achieve the goal and with learning resources which should be used to
reach the respective goal. The question how this user model is filled up with data is not focus
of this paper. In short it can be stated that user model data can be set by learners themselves,
by teachers or tutors, or created automatically by tracking and analysing learner behaviour.
Learning resources (especially tools) are associated with learning activities. For example, if a
specific concept mapping tool is associated with the 'goal setting learning activity', then this
tool can be recommended to be used if goal setting is suggested earlier. To achieve a more
structured assignment, tools are analysed regarding their inherent functionalities and the
functionalities are associated with learning activities. All these associates lead to a chain of
relations which can be exploited for recommendation: SRL process phase - cognitive or meta-
cognitive key activity - concrete activity - tool functionality - tool.
Based on the SRL process model, the learner model, and the assignments of learning activities
to tools, a recommendation strategy has been elaborated, which is the underlying basis for the
navigation tool. Basically adaptive guidance is provided by offering adapted
recommendations to the learner. The recommendation strategy is built upon three important
questions: First, what can or should be recommended, second, what are the conditions and
required information in order to provide recommendations, and third, what are the parameters
that control the degree of recommendations. Regarding the first question, learning activities
and/or learning resources (learning content, tools, and peers) can be recommended. Basically,
learning activities are recommended based on the learning process model, so that activities
regarding self-regulated learning or activities regarding the 8LEM model can be
recommended. Learning tools can be recommended based on the relation of possible activities
with tools. Content can be recommended based on the personal goals of learners. The second
question is mainly related to skills and preferences of learners. If special skills needed to
perform self-regulated learning activities or to use specific tools, then possible
recommendations can be restricted if learners do not have these skills. Furthermore,
preferences may restrict recommendations if learners have preferences for or against certain
activities or resources. Regarding the third questions learners may also control the degree of
recommendations. For example, they can control if they would like to get recommendations
only for learning activities, but not for resources.
3 Design and Implementation of the SRL Navigation Tool
In the introduction section above the usage of a GPS navigation tool is shortly explained.
In order to benefit from this approach, the key features of a typical GPS navigation tool are
listed from the perspective of user requirements:
(1) Users know their destinations and indicate them before their journeys by either choosing
it textually from a structured address list or by picking it visually on a street map.
Conference ICL2010 September 15 -17, 2010 Hasselt, Belgium
5(7)
(2) The tool calculates a route and provides textual and visual support for achieving the
aimed destination. Route and support is mainly provided by giving recommendation of
concrete driving actions ('turn left')
(3) The current location is either determined automatically or the user enters it manually.
(4) The support depends on the current location and is adapted to the actual position in
terms of recommending streets which are available in each moment. This does not
require that the user followed the originally planned route.
(5) The tool provides orientation because it displays the current location with the respective
local context. The user can create individual plans based on this orientation information.
Combining the features of typical GPS navigation tools and the theoretical basis described in
the last section helps to outline the design of the SRL navigation tool. By mapping the
concepts of the GPS navigation tool to the SRL navigation tool, the key features of the GPS
navigation tool can be taken over and modified by mapping the respective concepts. The
geographic destination can be mapped to the learning goal, the route is mapped to a learning
plan consisting of learning activities and resources, the current geographic position is mapped
to he currently performed learning activities and used learning resources, the street map is
mapped to a network of related and sequenced learning activities and resources, and the
recommended actions are mapped to learning activities. Following this mapping, features of
the SRL navigation can be defined as follows:
(1) It should be possible to define learning goals (as outlined in Section 2) which are taken
into account by the recommendation engine
(2) The recommender engine creates a plan to achieve a goal by sequencing learning
activities and adding learning resources to them. Recommendations are given in terms
of learning activities and learning resources.
(3) The current learning activities and used learning resources are either entered manually
by the learner or tracked automatically by the system.
(4) The learning activities currently performed and the learning resources currently used are
taken into account and the plan is adapted to them.
(5) The tool provides orientation by displaying the current learning activities and resources
in their local context
By putting these features into a time sequence the guidelines for the usage design of the SRL
navigation tool can be derived. First the learner or teacher sets a goal and probably assigns it
with competences necessary to reach this goal. Then the learner requests a learning plan
which is graphically listed as a structure. The plan may contain learning activities of different
granularity levels and learning resources. Furthermore, the elements of this plan depend on
the preferences and competences of the user. For each element, the learner gets more
information if needed. This is especially important for meta-cognitive activities which are
more difficult to adopt and to perform for some learners. Then the learner takes up certain
activities or resources and performs or uses them. As far as possible this is automatically
tracked and stored. For example, it can be tracked which tool a learner has used. Other
elements, such as cognitive or meta-cognitive activities are hard to track, so it is expected,
that the learner marks these activities on the plan. At each step the learner can request a new
full plan or only a sub-plan. For the new request the history (performed learning activities and
used resources) are taken into account. Furthermore the history is visually represented in the
context of the actual plan, which should provide orientation to the learner.
Development of the tool has been performed along this scenario which is reflected in the user
interface (see screenshot in Figure3). It is split into an orientation and a recommendation area.
Conference ICL2010 September 15 -17, 2010 Hasselt, Belgium
6(7)
In the orientation area, the current state is given in terms of the SRL process phase and
explanation is given for each phase. In the recommendation area the current learning plan is
displayed and the learner can choose an element of the plan. Furthermore, goal setting can be
done in an extra area. Adaptive guidance is realised by providing recommendations based on
the current location in the learning plan. The strategy for recommendation is done as
described in Section 2.
The learner can use this tool to navigate through the learning process in the ROLE
environment by choosing learning resources available in ROLE. It is aimed that this tool helps
learners to get an understanding of the self-regulated learning process model, so that they can
apply it by their own without the help of personalised recommendations. In this sense they
should become perfect self-regulated learners who are able to control all parts of their
learning process.
Figure 3: Screenshot of the Navigation Tool
4 Conclusion and Outlook
This paper presented the initial development of a navigation tool which supports learners to
navigate through their own self-regulated learning process in a complex environment
consisting of a great amount of learning resources. For providing guidance this tool takes into
account preferences and competences of the learner as well as the current state in the learning
process. Guidance is realised by providing personalised recommendation of learning activities
and resources and by providing orientation regarding the current state.
Further work will focus on two important but missing features. First, a strategy for
recommendation of content will be elaborated and developed. Since goals are mostly related
to attaining competences regarding certain subject domains, this must also be reflected in the
Conference ICL2010 September 15 -17, 2010 Hasselt, Belgium
7(7)
recommendation strategy. Second, the integration of the SRL navigation tool in the ROLE
infrastructure will be necessary to include the tool in the distributed environment of ROLE.
This requires of having available the recommender service, the user profile service, and
resource repository services on the Web. Furthermore, the navigation tool has to be adapted as
widget which can be used in the widget container together with the other widgets of the
personal learning environment.
References
:
[1] Dabbagh, N.; Kitsantas, A. (2004): Supporting Self-Regulation in Student-Centered Web-Based
Learning Environments. In: International Journal on E-Learning, 3 (1), 2004; pp. 40-47.
[2] Fruhmann, K.; Nussbaumer, A.; Albert, D (2010): A Psycho-Pedagogical Framework for Self-
Regulated Learning in a Responsive Open Learning Environment. In Proceedings of the
International Conference eLearning Baltics Science (eLBa Science 2010), 1-2 July 2010, Rostock,
Germany.
[3] Leclercq, D.; Poumay, M. (2009): The 8 Learning Events Model and its Principles. Release 2005.1
LabSET. University of Liège, available at http://www.labset.net/media/prod/8LEM.pdf [March,
2009].
[4] Renzel, D.; Höbelt, C.; Dahrendorf, D.; Friedrich, M.; Mödritscher, F.; Verbert, K.; Goevaerts, S.;
Palmer, M.; Bogdanov, E..(2010). Collaborative Development of a PLE for Language Learning.
International Journal of Emerging Technologies in Learning (iJET). 2010,5(S1):pp31-40. Available
at: http://online-journals.org/i-jet/article/view/1196.
[5] ROLE (2010). Responsive Open Learning Environments, http://www.role-projects.eu, retrieved on
May 20, 2010
[6] Zimmerman, B. J (2002).: Becoming a Self-Regulated Learner: An Overview. In: Theory into
Practice, 41 (2), 2002; pp. 64-70
Acknowledgement
The research leading to these results has received funding from the European Community's Seventh
Framework Programme (FP7/2007-2013) under grant agreement no 231396 (ROLE project)
Authors
:
Alexander Nussbaumer, Dipl.-Ing.
Cognitive Science Section, Department of Psychology, University of Graz, Austria
Knowledge Management Institute, Graz University of Technology, Austria
Brueckkopfgasse 1, A-8010 Graz, Austria
alexander.nussbaumer@tugraz.at
Karin Fruhmann, Mag.
Knowledge Management Institute, Graz University of Technology, Austria
Brueckkopfgasse 1, A-8010 Graz, Austria
karin.fruhmann@tugraz.at
Dietrich Albert, Prof. Dr.
Cognitive Science Section, Department of Psychology, University of Graz, Austria
Knowledge Management Institute, Graz University of Technology, Austria
Brueckkopfgasse 1, A-8010 Graz, Austria
dietrich.albert@tugraz.at
