D 9.2.2 Exploitation Plan

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Oct 21, 2013 (3 years and 8 months ago)

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Project Number:

257639

Project Title:

ALICE: ADAPTIVE LEARNING VIA INTUITIVE/INTERACTIVE,


COLLABORATIVE AND EMOTIONAL SYSTEMS


Instrument:

Specific Targeted Research Projects

Thematic Priority:

ICT
-
2009.4.2:Technology
-
Enhanced Learning


Project Start Date:

June 1st, 2010

Duration of Project:

24 Months



Deliverable:

D 9.2.2 Exploitation Plan

Revision:

V
2

Workpackage:

WP9 Exploitation and Dissemination

Dissemination Level:

Public


Due date:

05/31
/201
2

Submission Date:

05/31
/201
2

Responsible

MOMA

Contributors:

CRMPA,TUG,COVUNI,MOMA




PROJECT CO
-
FUNDED BY THE EUROPEAN COMMISSION WITHIN THE SEVENTH
FRAMEWORK PROGRAMME (2007
-
2013)





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Table of Content

Version History

................................
................................
................................
.................

3

1

Introduction

................................
................................
................................
............

4

1.1

Document Structure

................................
................................
................................
........

4

1.2

Alice exploitation plan purpose and strategy

................................
................................
...

4

2

Market Analysis

................................
................................
................................
.......

5

2.1

E
-
Learning Market segments and sub sector of interest (All Partners)

...............................

5

3

Exploitable Knowledge

................................
................................
............................

6

3.1

Collaborative Learning (UOC)

................................
................................
..........................

6

3.2

Simulation and Serious Game

(COVUNI)

................................
................................
..........

7

3.3

Storytelling (MOMA)

................................
................................
................................
.......

9

3.4

Affective and Emotional App
roaches (CRMPA)

................................
...............................

10

3.5

New Form of assessment (TUG)

................................
................................
.....................

11

3.6

Adaptive Technologies for e
-
Learning (CRMPA)

................................
.............................

14

4

Results/Products

................................
................................
................................
...

16

4.1

Description of the ALICE PLATFORM Product (MOMA )

................................
..................

16

4.2

Description of products/tools c
oming from WP2 (CRMPA)

................................
.............

17

4.3

Description of products/tools coming from WP3 (UOC)

................................
.................

18

4.4

Description of products/tools coming from WP4 (COVUNI)

................................
............

19

4.5

Description of products/tools coming from WP5 (TUG)

................................
..................

20

4.6

Description of products/tools comin
g from WP6 (MOMA)

................................
.............

40

4.7

Description of products / tools coming from WP7 ( CRMPA)

................................
...........

41

5

Partner’s Promotion

................................
................................
..............................

43

5.1

Promotion of initiatives and Agreements to spread the technology both at local and
national level.

................................
................................
................................
.................

44

5.2

Selection of commercial channels to promote and offer high
-
level services in each country

46

5.3

Specific actions for subjects/partners/entities wich
have already adopted IWT

......

56

5.4

Definition of a commercialization network in each country

................................
....

58

5.5

Project Target identification for each Partner
................................
.........................

60

6

Advanced Business Plan (MOMA
-
Business)

................................
............................

63




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Version History

Version

Date

Changes

Contributors
























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1

Introduction

1.1

Document Structure

1.2

Alice exploitation plan purpose
and strategy

This report describes activities and actions about the second version of ALICE WP 9 Exploitation and
Dissemination.

In the first version the scope, the project approach, partners’ role and agreements finalized to define
the exploitation ‘s intention have
been identified.

Moreover e
-
learning market analysis has been conducted in order to define the product positioning
and identified target, allowing an evaluation of the major weaknesses/opportunities on the base of the
functional aspects of the most popular

solutions point of view.

In this second version of the Exploitation plan
, which is thought as an intermediate version towards the
final Exploitation Plan,

the guidelines and the actions finalized to the promotion of the project’s results
will be defined.
Those actions will be addressed to the Educational target (already defined in the first
version) and
in particular to the
Emergency and Civil Defence training in secondary schools
; they will
be also extended
to all the other subjects
who have expressed the

need to use innovative
technologies and emotional and affective didactical approaches.

Therefore two operational phases have been planned:



In the first one each partner has to promote the enabling technology of the project : IWT e
-
learning platform.

This

action is necessary and
has

been already activated or has

to be
activated immediat
ely in order to “pave the way”

to integrate and enable the project results.



The second phase will be activated after the results’ experimentation and validation.

Each
partner will be involved in the following activities: first of all the customer /target identification
in each country, then the industrial partners selection as commercial channels and finally
specific actions to plan for customers which have already

adopted IWT platform.

Due to the short inter
v
al of time before t
he end of the project, it is necessary to start as soon as
possible with the activities among the ones listed above for which this is possible in order to be
operative immediately after the
progressive conclusion of the validation.







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2

Market A
nalysis

2.1

E
-
Learning

Market segments and
sub sector
of interest

(All
Partner
s
)

The market analysis will be accomplished, focusing on the objects and scope of ALICE
project. The mark
et trends will be investigated
about the following
e
-
learning segments
:



e
-
Learning for Education (at University and School levels)

(MOMA
-
BUSINESS
)



Learning and Training on emergency and civil defence

(MOMA BUSINESS)

In particular the following
subsector
s

will be considered
:



Collaborative Learning

: technology solutions

and

tools

to support synchronous and
asynchronous collaboration and cooperation for learning

including
Knowledge
Representation and Elicitation
(UOC)



Simulation and serious games
:
technolog
y solutions

and

tools, that manage
and
deliver
experience, simulation and intuition driven learning.

(COVUNI)



Storytelling:
technology solutions

and

tools, that manage
and deliver
storytelling
based resources
in learning experiences.

(MOMA)



Affective and Emotional Approaches:
technology solutions

and

tools

capable of
intercepting emotional and affective
states of the learner
and to
use
them with respect
to t
he educational offer. (CRMPA)



New Forms of Assess
ment
:
technology solutions

and

tools,

that

implement
advanced
automatic and collaborative assessment systems
.

(TUG)



Adaptive Technologies for e
-

learning

(CRMPA)

In
document annexes
each segment
and subsectors
is described
with respect to the demand
and the supply, the
consumer’s need,
the
standard and innovative features.







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3

Exploitable Knowledge

In this section, the exploitable kno
wledge resulting from ALICE

project are

presented. With the term
exploitable knowledge we refer here to conceptual results of the project (i.e. models and
methodologies) as opposite to software results (i.e. tools) that are presented in following se
ction

In the following sections we analyse in
dept
h

the conceptual results
of each sub sector

of the ALICE
Project.




3.1

Collaborative Learning (UOC)

Table
1
: Overview of
ALICE

Exploitable Knowledge

Id

EK


Brief Description

Related
WP

EK
1

Methodology
to foster the
VCS


This methodology defines how to interact with the
VCS
.
The
VCS

is an environment that:



fosters real interactivity
,

with

immediate feedback,
clear short
-
term goals and better “flow” in moving
through the content.
S
uch interaction directly
affects the learner’s overall experience and provides
engagement

and
motivation

to continue in the

learning process.



provides
challenging collaborative tools, which
stimulate learners, making

the collaborative
experience attractive

and en
couraging progression
.




enhances
empowerment, as
the
learner
feels
in
control of their own collaborative learning
experiences



improves
learning achieved through social
interaction and collaboration,
reducing the
feeling
of learners
isolated from th
e peers.



WP
3


3.1.1

Methodology description

3.1.2

Distinctive characteristics










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3.2

Simulation and Serious Game (COVUNI)


Table
2
: Overview of
ALICE

Exploitable Knowledge


Id

EK


Brief Description

Related
WP

EK

Methodologies
for intuitive
Guided
Learning


This methodology will provide an exploitable resource for
educators and developers of technology
-
enhanced
learning solutions. Introducing the concept of 'intuitive
guided' learning, the methodology explores the

applicability of techniques built around this paradigm, and
through ALICE prototypes, provides a demonstrable
evaluation of their efficacy. Whilst the principal
beneficiaries of this knowledge would be anticipated to
be educators and pedagogists, wider po
tential for the
exploitation of this knowledge exists in the technical and
development communities. These communities
frequently report a lack of clear demonstrable
pedagogical approaches for technology enhanced learning
solutions, and the models provided
by this exploitation
will allow the introduction of new, validated techniques.
Key highlights of this activity with potential for
exploitation include:


-

The introduction, in synergy with other WP outcomes, of
the concept of Intuitive Guided Learning (IGL
)

-

A coherent and validated methodology for implementing
IGL in practice (D4.1.2)

-

A functional example of a realised use of IGL through
prototyping

(D4.3.2)


Combined these elements will

be the base for

a platform
for the exploitation of core ALICE concepts developed in
WP4, and more widely across the project.


WP4




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Id

EK


Brief Description

Related
WP

EK

Methods and
Techniques
for Simulative
Content
Creation


Content creation for serious games is often a cost
-
intensive exercise, due to the high fidelity levels required
for content. ALICE places particular emphasis on the reuse
of existing simulative assets, providing techniques for
lessening the burden on the g
ame's creator.

Seeking to exploit synergies between games and
simulations, the explo
i
table product of this activity will be
a set of clearly defined and demonstrated principles and
practices for simulative content creation. This includes
both bespoke
creation, and creation through brick
-
based
or semiotic approaches to repurposing.


Such practices have particular potential through their
ability to offer a cost
-
effective means for producing
serious games, in particular those based around
exploratory, or
intuitive guided learning, wherein
simulation often plays a key role in establishing a

'sandbox' learning environment, so providing a
conceptual framework.


WP 4


3.2.1

Methodology description

3.2.2

Distinctive characteristics




















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3.3

Storytelling (MOMA)



Id

EK


Brief Description

Related
WP

EK

Storytelling
Design
Model


SDM aims to overcome the shortcomings of existing
researches which mainly concern the lack of a
pedagogical model that ensures the achievement of
learning objectives through an educational

process
based on the playful aspects of digital storytelling
integrated with aspects such as, for instance, the social
-
collaborative learning. The Storytelling Design Model
aims to fill the lacks of existing storytelling models by
providing ways to:



empo
wer the pedagogical drivers during the
storytelling definition phase in order to connect
storytelling situations and events to achieve specific
levels of educational objectives and emotional
status



exploit branching logic in order to design
microadaptivity

mechanisms by using indications
coming from different types of educational
strategies to define remedial paths tailored to meet
the learning progress of the learner;



enhance the character
-
based approach by defining
role playing, taking and making strategi
es in order to
support telling, re
-
telling and re
-
living;

WP6


3.3.1

Methodology description

3.3.2

Distinctive characteristics













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3.4

Affective and Emotional Approaches (CRMPA)

Overview table for Exploitable Knowledge


Id

EK


Brief Description

Related
WP

EK

Methodology
to
investigate
emotional
state



The purpose of this methodology is to investigate the
emotional state of a user. We have developed a
model to identify and quantify the
emotional/affective
state of
a learner. The model is
the same for representation of affectivity and
Emotivity.
The steps of

the model are as follows:




Step Level 1:

Stimulus
-
Response (output will tell if the
student responds positively, negatively or indifferently to
the
emotional/affective
stimulus provided through the
questionnaire)



Step Level 2:

Output Response
-

Quantity (parameters are
quantified in a values scale that ranges from 1 to 10
through 10 targeted specific questions)



Step Level 3:

Estimation of Dominance (t
uple parameters
are generalized in relation to the output of the 2 °
approach and in relation to the weight given to each of the
parameters of the learner.)



Step Level 4:

Evaluation of emotivity/affectivity (a set of
parameters are quantified: absolute emo
tion, emotional
arrange
, etc.).



Step Level 4 Bis:

Characterization of emotivity/affectivity
(based on values obtained in the previous step we say that
a user experiences a feeling more strongly than another)


WP2





3.4.1

Methodology description

3.4.2

Distinctive
characteristics





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3.5

New Form of assessment (TUG)


Id

EK


Brief Description

Related
WP

EK

Integrated
model for e
-
assessment
(IMA).



The IMA model identifies enhanced forms of e
-
assessment for (CLO) and consists of four main
components:

Didactical objectives
Learning goals, defined e.g.
using Bloom’s Taxonomy, affect the type of learning
resources and assessment activities.

Complex learning resources (CLR):
an
enriched
learning experien
ce is
made up of complex learning
resources (CLR).
Those CLR are expected to add
moments of collaboration, simulation, and storytelling
to support the learners in achieving the learning
objectives.

Assessment and Feedback:
Innovative assessment
activities are considered
based

on the Bloom’s
taxonomy of edu
cational objectives

with

various kinds
of learning.
New forms of assessment based on CLR
have been defined (self assessment and peer
assessment) considering also emotional and
motivational aspects of the learner, and different
feedback type, in order to

enhance their learning
outcome.

Evaluation and Validation

To ensure that learning and
assessment activities have a high quality standard,
it have
been identified
indicators for the quality of the enriched
learning experience in order to adapt/enhance it.



WP5


3.5.1

Methodology description

The defined Integrated Model for Assessment (IMA) in WP5 exploits the research of building Enriched
Learning Experimence

out of the integration of learning experience composed of Complex Learning
Resources (CLR) (e.g., collaboration, simulation, digital stories), with assessment forms (cognitive and
affective
-
emotional) and that is able to generate an effective kind of lear
ning (e.g., reflective learning,
experiential learning, or socio
-
cognitive learning).

Fig
ure

1 shows the abstract level of a model that represents such an enriched learning experience.
The model will mainly identify possible tools, practices, guidelines fo
r providing enhanced forms of e
-
assessment for complex
-

learning objects (CLO) such as serious
-
games and simulations, virtualized
collaborative learning, storytelling, and consideration of affective or emotional aspects. The model
consists of four main com
ponents: the didactical objectives, complex learning resources, assessment
activities (including feedback), and indicators for its evaluation and validation. Such an enriched
learning experience is influenced by several components like pedagogical and psyc
hological aspects,
technical issues and existing standards and best practices (see red arrows in Fig
ure
1). Furthermore,
quality criteria have to be defined to ensure a high quality standard of all activities in this complex



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learning environment. Therefore,

quality assurance which addresses all components of the enriched
learning experience is considered in the model. The quality assurance is also relevant with respect of
indicators that are expected to result from the enriched learning experience: indicator
s for its
educational efficiency and effectiveness. Finally, in order to ensure that the learning experience allows
adaptivity, the model also interacts with three other important models: the learning model, the
knowledge model, and the didactic model, respectively.


IMA Main Componen
ts

1)

Didactical objectives

The main didactical objective is to achieve the immediate learning goals which can be defi
ned e.g.
using Bloom’s
Taxonomy
. Didactical objectives affect the type of learning resources and assessment
activities that are chosen in an enriched learning experience.

2)

Complex learning resources (CLR)

An enriched learning experience is made up of complex learning resources

(CLR). Those CLR are
expected to add moments of collaboration, simulation, and storytelling to support the learners in
achieving the learning objectives.

3)

Assessment and Feedback

Innovative assessment activities are considered to base on the Bloom’s tax
onomy of educational
objectives
eaeefccffonsfeinaevetceffe ana
g such as reflective learni
ng and experiential learning

as well
as socio
-
cognitive learning
.
New forms of assessment for CLR including self, and peer
-
assessment
have been defined considering emo
tional and motivational aspects of the learner in order to enhance
their learning outcome
e.

4)

Evaluation and Validation

Figure
1
.
Integrated model for e
-
assessment (IMA).




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To ensure that learning and assessment activities have a high quality standard, indicators for the
quality of the enriched learning exp
erience have been identified in order to adapt and enhance it.

Prepare Inputs to the enriched learning experience

An enriched learning experience is affected by several components:

1)

Psychological and pedagogical aspect

Learning theories (such as reflecti
ve learning, experiential learning, and socio
-
cognitive learning) and
learning models have to be condifered in building enriched learning experiences. Due to these
theories, not only individual learning styles can be considered but also processes that affe
ct types of
learning (e.g. collaborative learning).

2)

Motivational and emotional/affective aspects

The measurement of the emotional/affective status of a learner supports in having a suitable and
personalized manner in order to enhance his or her affecti
ve/emotional inclination and hence, to
stimulate the learners’ attention and learning.

3)

Technological aspects

Enhanced technologies not only generate CLR but also flexibly adapt the learning path with respect to
the individuals’ needs and learning progre
ss. Developed tools will not only consider the assessment of
individual and self
-
regulated learning but also peer
-
assessment and group assessment. Furthermore,
they will provide an adaptive learning path and consider emotional and motivational aspects base
d on
the outcome of the assessment activities.

4)

Standards and Specifications

Standards for e.g. learning content reusability and interoperability, learner’s information accessibility
and share ability are essential for any learning management system (in
cluding e
-
assessment) and
also for quality assurance.

5)

Efficiency and Effectiveness

Efficiency and effectiveness of an enriched learning experience are important criteria.Parameters and
validation indicators have to be considered in the process of build
ing enriched learning experiences
strating from didactical objectives, using CLR, and integrated froms of assessment and feedback.
These paprameters form as inputs for the validation and evaluation step to allign the outcomes with
the learning goals and ob
jectives.

6)

Quality assurance

Learners profit from an enriched learning experience most when the standard of the quality is high for
activities within the learning experience. Therefore, quality assurance is essential in order to
guarantee that the learni
ng experience meet the requirements.

Interaction with other models

In order to provide adaptive and personalized learning, IMA is interacting with three other models
namely learning model, knowledge model, and didactic model. In co
-
operation with the learning
model, the cognitive status of the learner in terms of knowledg
e and skills is updated, in co
-
operation
with the knowledge model, the ontology of
learning and in co
-
operation with the didactic model,
eventual alternative models are recovered.





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3.5.2

Distinctive characteristics

IMA aims to overcome the limitations of existing research regarding the lack of assessment models
that ensures the allignment between didactical objectives and the achieved learning outcomes through
integrated assessment forms (e.g. slef, peer
-
assessment)
with CLR via educational process
underpinned by learning objectives and controled by efficiency and effectiveness parameters. IMA
aims to tackle the lack of existing assessment models through:



Reflecting unlike other models the entire life cycle of e
-
asses
sment and taking into account
pedagogical as well as technological aspects.



Pedagogical
flexibility to be used in a wide range of learning settings. The model may support
the selection process finding / compiling the right set of methods and tools to appl
y
appropriate assessment according related teaching and learning objectives.



Its flexible design to form as a methodology to divide learnig goals into fine
-
grained objectives
assign them to CLR integrated with assessment forms in a way to support the educa
tional
process and acieve the desitred goals.



Consedering other important models namely learning model, knowledge model, and didactic
model in order to provide personalized and contextulaized learning by taking into
consideration the learner kowledge and s
kill state as well as the learning domain
specifications.



3.6

Adaptive Technologies for e
-
Learning

(CRMPA)

Id

EK


Brief Description

Related
WP

EK x

Knowledge Model
Contextualisation
Methodology


The purpose of this methodology is to support
context
-
aware
e
-
learning i.e. to generate learning
experiences by selecting the more relevant and
suitable learning resources for the learner in his/her
situation. This is done through the formal
representation of a learning context

and the definition
of a contextualiza
tion algorithm able to obtain a
contextualized ontology from an abstract one

based
on the context above
.

WP7

EK y

Learning Goals
Recommendation
Methodology


The purpose of this methodology is to enable course
building starting from an implicit (latent) request
rather than from an explicit one i.e. to recommend to
a learner a
personalized list of fe
asible learning goals
basing on
w
hat he currently knows and
whi
ch
additional concepts similar
learners
know
. This allows
to anticipate and spread learning needs and act as a
pedagogical advance organizer for learners, also
supporting self
-
regulated learning.

WP7




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Id

EK


Brief Description

Related
WP

EK z

Semantic
Connections
Adaptation
Methodology


Semantic connections are typed links between
learning resources purposed to aggregate them in
compound structures to be played by learners. The
purpose of this methodology is to provide dynamic
reconfiguration of semantic connections with respect
to teachi
ng preferences, learning preferences and
context information. This allows
to support adaptation
while adopting intuitive guided learning.

WP7







3.6.1

Methodology description

3.6.2

Distinctive characteristics






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4

Results/Products

This section describes the
expected re
sults/products of the ALICE

project categorized
considering the
whole product obtained by extending the reference platform IWT with results coming from all
workp
ackages as well as products/tools
coming from the
core
project workpackages
:



Affective and Emotional Approaches (WP 2)



Live and Virtualized Collaboration (WP 3)



Simulation and Serious Games (WP 4)



New Forms of Assessment (WP 5)



Storytelling (WP 6)



Adaptive Technologies for e
-
learning
(
WP 7
)

4.1

Description of
the
ALICE PLATFORM
Produc
t

(MOMA )

Focus on .....

4.1.1

Overview of competitors

describes from a “functional” viewpoint the characteristics of current product available on the market. It
is not necessary to perform an analysis per product but to provide an overview of key features
avail
able from similar products


4.1.2

Competitive advantages


explain the advantage that can be intro
duced by the specific ALICE

product
s

with respect to what is
available on the market landscape

















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4.2

Description of
products/tools

coming from
WP2

(CRMPA)


Result(s)

Product(s)


Related


WP

Brief Description

Emotive
-
Affective
Module

WP2

This prototype
creates

the representation model of
emotions and the methodology used to detect the
emotional state of a learner.

The prototype allows

to
identify

any changes in emotional states using tes
ts. When
it detects a change

of the emotional state, it passes
through
further

questionnaires to measure the level of
alteration.

The prototype is characterized by the
following
distinctive features:



The mechanism

t
hat

trigger
s

the
prototype

is
based on the learning curve that tracks the level
of concepts acquired by the user during
the
use of
the course and testing.



The flexibility of the model to explore different
emotions by changing the questionnaires which
are

placed in simple XML files
.



When the system detects an alteration in

the

emotional
state
it sends this information via email
to the teacher of the course,
who

finds the
message and can decide the action
s

to take:

o

he may start a live sessions with the
lear
ner to try to understand the problem
that caused the emotional alteration and
provide the right guidance and stimuli

o

he may suggest to the learner a new set
of alternative educational resources
with
the goal of rebalancing
his emotional
state.



Compared to
most of the systems the way we
investigate the emotional state is not invasive and
has no need for additional hardware such as
webcams
,

pressure gauges etc.




4.2.1

Overview of competitors

Describes from a functional viewpoint the

characteristics of current
product available on the market. It
is not necessary to perform an analysis per product but to provide an overview of key features
available from similar products

4.2.2

Competitive advantages

Explain the advantage that can be introduced by the specific ALICE pr
oducts with respect to what
is
available on the market land
scape





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4.3

Description of
products/tools

coming from
WP3
(UOC)



Overview table results/products

Table
3
: summary of expected
ALICE

products

Result(s)

Product(s)


Related


WP

Brief Description

Virtualized Collaborative
Sessions

WP3

Virtualized Collaborative Sessions (VCS) is a registered
collaboration session augmented by alternative flows,
additional content, etc., during an authoring phase.


This

virtualization
process is enabled by the following
steps:

-

t
he data source of a live collaborative learning session
was considered from the IWT Web
-
forums.

-

a

specific converter turned the IWT data model into
a
standardized data

format

-

Generation of

an animated
storyboard
showing how
people discuss and collaborate and how discussion
threads gro
w

From a technical viewpoint, it is
a Storyboard Learning
Objects embedded into web forums of online learning
platforms
that can be
editable and
customized via
a web
-
based
graphical
user interface.


4.3.1

Overview of competitors


describes

from a “functional” viewpoint the characteristics of current product available on the market.
It is not necessary to perform an analysis per product but to provide an overview of key features
available from similar products>


4.3.2

Competitive advantages

Explai
n the advantage that can be introduced by the specific ALICE products with respect to what is
available on the market landscape














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4.4

Description
of
products/tools
coming from
WP4
(COVUNI)

5


Result(s)

Product(s)


Related


WP

Brief Description

Integrated Serious
Games


WP4

The serious game developed in WP4 is tightly integrated with
the IWT system. However. feature
-
disabled standalone
versions will also be available for a range of platforms
including PC, Mac, PS3 and Xbox360.

The principal
exploitable technology will be the integrated
solution including the IWT system, which implements a range
of features to express and manipulate the game as a learning
object. Hence a range of feedback mechanisms can be
supplied, supporting in particular le
arners who fall outside
the 'intuitive' typology noted as a key consideration by
conceptual work.


In addition to the technology itself, underlying technologies
supporting integration between a modern game engine and
the IWT system also form an exploitable

middleware solution,
which could be generalised to include other LCM systems


5.1.1

Overview of competitors


describes

from a “functional” viewpoint the characteristics of current product available on the market.
It is not necessary to perform an analysis per product but to provide an overview of key features
available from similar products>


5.1.2

Competitive advantages

Explai
n the advantage that can be introduced by the specific Alice products with respect to what is
available
on the market land
scape














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5.2

Description of
products
/tools

coming from
WP5
(TUG)

6


Result(s)

Product(s)


Related


WP

Brief Description

Assessment

tools


WP5

The WP5 focuses on the following tools:

(a)
a tool for semi
-
automated (interactive) and fully
automated creation of various types of test items from
learning content
: this which supports various learning
scenarios, and can be used as a tool (stand
-
alone ore
integrated in a LMS) or as a service. The tool can support test
item creation (interactive mode) in self
-
directed learning
(fully automated) and supports the creat
ion of several
assessment types (multiple choice, false/true, fill in the blank
etc).

(b)
an enhanced Wiki system with integrated self and peer
assessment as well as teacher feedback:
this tools integrates
self, peer, and group
-
assessment activities with
the use of
assessment rubric designed for scientific writing. Visualization
tools
are included
to support both students and teachers to
know who did what and when.


6.1.1

Overview of competitors


describes

from a “functional” viewpoint the characteristics of current product available on the market.
It is not necessary to perform an analysis per product but to provide an overview of key features
available from similar products>

Automatic Test Item Creation

tool AQC
:

Automatic
test item creation from textual learning content has raised the interest of the community for
quite a while, but research results and products in past were quite limited and basic; for an overview of
developments in the past may be fou
nd elsewhere, such as in (
Gütl, Lankmayr, Weinhofer, & Höfler,
2011)
. The objective of this section is to give an overview of
recent work on
different approaches by
exemplarily
outlining one approach and tool each, which is finally used to compare system a
vailable
with the Automatic Question Creator tool AQC (see also D5.21).

The authors in (
Papasalouros Kotis,
& Kanaris,
2008
;
Papasalouros Kotis,
& Kanaris, 2011
)

describe
an
ontology
-
based approach and prototype

to automatically create
multiple choice test

items
.
The
domain ontologies are resented in the OWL format which is a standard Web ontology language based
on description logic knowledge representation formalism.
The concrete structure of the ontologies
applied for question creations is compiled of con
cepts or classes which can have different
relationships or properties, also known as roles (see also Figure 1 and Figure 2). For creating multiple
choice questions (MCQ) distractors are automatically created
based on two strategies:
class
-
based
strategies

take advantages of so called individuals in hierarchic structures which are members of
classes (is
-
a relationships); correct distractors are created by actual is
-
a relationships and wrong one
by individuals not member of a certain class. Property
-
based str
ategies take advantages of properties



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and roles which describe relationships between individuals in a given ontology; in general a property
has a so
-
called
valid
domain

which specifies the member of individual which a certain property can be
applied, a ran
ge which describes the valid values. Both information of domain and range can be used
to create wrong or correct distractors. The prototype implementation focuses on one type of question
which is find the correct sentences (see also Figure 3).



Figure
1
-

Formal description of classes and roles

(
Papasalouros Kotis, & Kanaris, 2008
).


Figure
2
-

Eupalios Tunnel as an example of an ontology
(
Papasalouros Kotis, & Kanaris, 2008
).






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Figure
3
-

Multiple choice questions as an example of the tools output
(
Papasalouros Kotis, &
Kanaris, 2008
).


The authors in
(Sanz
-
Lobera, González Roig, & González Requena, 2011)

have proposed a
parametric approach to create variants of exercises. In this variant of parametric approach mathematic
formula and models are the b
ase for distractors of multiple choice test items; the application domain of
such created test items are engineering and physics topics. Figure 4 outlines the applied
methodology: (a)
question parameterization

defines the variable values and the ranges of
variation;
(b)
parametric resolution

executes the solution of all
parameters defined in (a); (c) alternative generation
selected different variants which may include multiple correct and/or wrong answers; (d)
questionnaires creation and maintenance created

and managed the actual test items by combining
text and computed values of variables; (e) results spreading and evaluation concerns the actual
assessment activities. Figure 5 illustrated the way how the multiple choice questions are created by
means of te
mplates, Figure 6 shows concrete examples, and Figure 7 shows the result in an LMS
manually copied by a tutor.



Figure
4
-

Methodology of parametric
-
based question creation
(Sanz
-
Lobera, González Roig,
&
González Requena, 2011)





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Figure
5
-

Example of a template to create paramtric
-
best exercise

(Sanz
-
Lobera, González
Roig,
&
González Requena, 2011)



Figure
6
-

Example of two concrete test item in the GIFT format
(Sanz
-
Lobera, González Roig,
&
González Requena, 2011)



Figure
7
-

Created example integrated (copied) into a LMS
(Sanz
-
Lobera, González Roig,
&
González Requena, 2011)


The
AEGIS system

creates automatically test items from annotated documents. This system can
create multiple choice exercises, fill
-
the
-
gap questions and
error
-
correcting questions based on tagged
learning content. The teachers can add tags in the learning content
to indicate the chunk of content to
be a potential test item. Teachers also can define one or more hidden regions which will be used to
create a
fill
-
the
-
gap exercise or can add candidate list to create multiple choice or error
-
correction
answers (see also Figure 8 and Figure 9). The AEGIS system can import such tagged learning



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content, extracts potential content, creates automatically test items,
administers online tests, and
provides results and feedback to the students

(see Figure 10)
.



Figure
8
-

Example of tagged data to create different types of test items
(Mine, Suganuma, &
Shoudai, 2000)



Figure
9
-

Overview on tags for test item creation (Mine, Suganuma, & Shoudai, 2000)



Figure
10
-

Overiew of the AEGIS system (Mine, Suganuma, & Shoudai, 2000)





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The authors in (Goto

et al., 2010) describe an approach and prototype to automatically create multiple
choice questions from English texts for native or foreign language assessment
. The
learning/assessment environment is design to receive texts from students and creates based on the
text test items accordingly (see also
Figure 11
). The approach applies mach
ine learning techniques
(preference learning) to extract potential sentences, estimates blank parts based on the discriminative
model (
conditional random field), and creates distractors based on statistical patterns of existing
questions (see also Figure 1
2). Figure 13 illustrated the flow into the system: textual input is tagged by
a part of speech tagger, followed by the tree above mentioned process steps and finally a selected
number of candidate distractors are selected and the test items are created.



Figure
1
1
-

The learning and assessment environment at a glance
(Goto et al., 2010)


Figure
12
-

Overview of the proposed approach
(Goto et al., 2010)




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Figure 13
-

data

and process flow
(Goto et al., 2010)


Figure 1
4
-

Example of an input and created test items
(Goto et al., 2010)



The authors in (
Cubric & Tosic, 2010) extent the existing approach using ontologies to automatically
create test items (such as described in
(
Papasalouros Kotis,
& Kanaris,
2008
); see also above) by the
two following interesting aspects: a meta ontology to model and creating different question types, and
a semantic interpretation on question types and respective levels
based on the Bloom’s taxonomy.
Finally, the approach applies
question template for the test item creation process (see

Figure 14).
The
described approach make use of concepts and their “is
-
a” relationships only, a proof of concept is
available as Protégé plugin.





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Figure 1
4
-

mapping between domain ontology and met
a ontology for different test item types
(Cubric & Tosic, 2010)



Figure 1
4
-

Overview of question types and level
(Cubric & Tosic, 2010)


The approach introduced by
(Heilman, 2011) focuses on the automatic creation of factual questions
based on an
unseen
input text. The goal is to create questions for assessing a reader’s or student’s
knowledge of information in the text. The approach is composed of three stages (see also Figure 15

and Figure 16
): (1) natural language processing transformations are applied

to transform a sentence
or a set of sentences into a simpler declarative statement. (2) The question transducer component
turns the simplified declarative sentences into a set of questions by executing a series of well
-
defined
syntactic transformations. (
3)
The question ranker module scores the created candidate questions
according to features of the source sentences, question type and transformation rules applied in the
creation process. The output is a list of open
-
ended factual questions.




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Figure 1
5
-

T
hree
-
stage conceptual architecture for automatic factual question creation
(Heilman, 2011)



Figure 1
6
-

Simplified illustration of the process steps and data flow from input text to factual
questions
(Heilman, 2011)





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Table
4
.

Features comparison among s
e
lected research of
automatic test item creation

System

Conten
structure
based

Seman
-
tic
based

Ontology
based

Required
domain
know
-
ledge

Interac
-
tive
Mode

Automatic
test item
creation

Multi
-
lingual
support

Web
Service
Integra
-
tion

Standard
Compliant
(QTI)

(
Papasalour
os
et al.,
2008
)













(Sanz
-
Lobera

et
al.
, 2011)












(Mine et al.
,
2000)














(Goto et al.,
2010)












(Cubric &
Tosic, 2010)













(Heilman,
2011)












AQC



















Enhanced Wiki system with integrated self and peer assessment as well as teacher
feedback:

Several researches have been conducted to investigate the validity of using wiki systems in CSCL.
The use of wikis in CSCL lacks some incentives to motivate students to contribute to the wiki such as
assessment procedures (Judd et. al., 2010).
T
his goes in

line with Macdonalds’ (2003) guidelines for
CSCL assessment as he argued that

CSCL activities should be linked to assessment procedures in
order to more attract students and
to
increase their motivation and engagement to learning activity.
Despite that
,

wiki constitutes from semiotic contributions, wiki plays an interesting double role of
medium and product of the collaborating (Reimann & Kay, 2010). However, wikis prevent users from
editing the same page simultaneously which may be a disadvantage in some

scenarios like using
wikis for co
-
writing.
T
his may be avoided in distance learning as the probability of simultaneous editing
for the same page is less than in
-
campus learning.

Despite the variety in research examples of using wikis for education and lea
rning, there is
little

research for integrated self, and peer
-
assessment within wikis. Available research mainly focuses on
knowledge extraction from wiki user’s log files and visualization tools for extracted information.
Moreover, the use of integrated s
elf, peer
-
assessment activities as well as assessment rubrics in order
to: enhance task/social awareness, maintain group production function, and provide valuable feedback
for both students and teachers is not highly investigated.

In the work of Trentin (
2009), the author tested an approach for co
-
writing using wiki where the
students used online discussion forum for co
-
planning and structuring the content for the co
-
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phase. Moreover, they used online discussion forum for peer
-
review where they were

required to
peer
-
review their peers contributions and writings. 3D graphic projections had been used to visualize
both the interaction among participants and among the links between the hypertext pages. Figure 2
demonstrates the distribution of forum cont
ributions during collaborative planning of the document’s
structure. Figure 3 demonstrates a 3D graphic projection for group member’s contribution to the peer
review. Figure 4 shows the group member’s contribution to the reticularity of the final hypertext
. In this
figure, the numbered points correspond to the page clusters developed by each individual student
where the lines refer to the connection between any page of cluster “A” and any other page of cluster
“B”. The bold lines correspond to a reciprocal
link (outward

inward). Moreover, network analysis
techniques had been used to represent the reticular relationships among those interactions. According
to Trentin (2009) the use of 3D projections and the network analysis for the visualizing the reticular
r
elationships among interactions has facilitated the evaluation of the level of group collaboration.



Figure
2
-

Projection of the forum interactions (Trentin, 2009).


Figure
3
-

3D graphic projection for group member’s contribution to the peer review (
Trentin,
2009).




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Figure
4
-

Network of connections between the wiki pages clusters of the hypertext (Trentin,
2009).


Another example can be found in (Khandaker & Soh, 2010). In this work the authors implemented
what they called ClassroomWiki


an intellig
ent agent
-
based Wiki tool to assess the students’
contributions toward their groups
-

and used it to assess students’ contributions in group
-
based work
for a wiki
-
writing assignment. As part of this wiki they implemented a tracking and modeling module
(TAM)

by which they track all the interactions and activities within the CalssroomWiki. Moreover, they
provided a visualization of student activity counts over time by which teachers can assess group
-
members contributions and detect free
-
riding, scaffold group
coordination and p
roduction function, see
figure
5
.


Figure
5
-

Detailed student’s activity plan on ClassroomWiki (Khandaker & Soh, 2010).


Another example that shows how visualizations aspects can be used to facilitate the assessment of
wiki
-
based collabo
rative writing is the work of (Biuk
-
Aghai, Kelen, & Venkatesan, 2008). In this
research the authors customized the “MediaWiki” to what they named “TransWiki” in order to be used
in translation courses. Moreover, they developed visualizations in order to su
pport the teacher
answering the following research questions: How much has each student contributed to the final
product? What is the process of collaboration? What is the depth of collaboration? Nevertheless, they
used
color
-
coded textual visualization

to

show individuals contribution to a wiki
-
page, the differences
between two versions, as well as the depth of collaboration, see
F
igure 6. They used the
analysis
graph

(single/all users) to demonstrate the evolution of an article with all users or the evolu
tion of a



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single user interaction per page, see
F
igure 7. They also used
Contribution summary graph

to
demonstrate the amount of contribution per user, see
F
igure 8.




Figure
6
-

Analysis of text authors (Biuk
-
Aghai, Kelen, & Venkatesan, 2008).


Figure
7
-

User participation graphs for users Alice (top) and Graffarn (bottom) (Biuk
-
Aghai,
Kelen, & Venkatesan, 2008).





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Figure
8
-

Contribution summary graph for students involved in the wiki
-
based article (Biuk
-
Aghai, Kelen, & Venkatesan, 2008).



The work of

(Larusson & Alterman, 2009) to visualize students’ activities in a wiki
-
mediated co
-
blogging exercise is another example. Students as part of their participation may take three kinds of
actions: blogging, commenting, and reading. In this research the aut
hors developed visualizations to
demonstrate student activity as: level and balance of participation; conversation locator, as well as
interactions in a form of networked graph. Figure 9, demonstrates the students level of participation
based on the main a
ctions (blogging, commenting, and reading). “By default all actions weigh the
same. Students (circles) are placed on the axis from left (high level of participation) to right (lowest
level of participation). Each circle has a blue color indicative of the a
verage length (word count) of
his/her blog posts. The darker the color the longer the blog posts. The circle size represents the
attention that the particular student attracts. The larger the circle the more frequently are his/her blog
posts read”. Figure
10 shows the balance of students’ interactions as “Each corner on the triangle
represents an action. The top corner represents reading actions and the bottom left and right corners
represent writing blogposts and comments actions (respectively). Students (
circles) are placed within
or around the triangle depending on the balance of their execution of the three actions. If a student
performs any particular action more than others his/her circle is pulled towards the corner representing
that action. An equal
balance of the actions places the student at the center of the triangle. Having
done only a single action places a student outside the triangle but close to the relevant corner”. Figure
11 demonstrates the conversation locator by which students and teacher
s can locate conversations
within the blog
-
o
-
sphere. “On our blog
-
wiki each student is required to assign predefined tags to their
blogposts that match the lecture topics each week. Each circle represents a conversation that is taking
place between two or
more students on a particular topic. The circle gets larger as more participants
join the conversation. The number of contributions (comments) in the conversation is shown inside the
circle. The length of the conversation (word count) determines the blue c
olor of the circle


longer
conversations (more words) have a darker color. Clicking on a circle takes one to the location of the
particular conversation on the wiki”. Figure 12 shows how students interactions based on the main
actions are visualized as a
networked graph that explains the interaction (arrow) between students
(circles). “Green arrows indicate what blogs the selected student has read or commented on. Red
arrows point toward the selected student and reveal what students have read or commented
on
his/her blog. The arrow “weight” can correlate with the degree of interaction”.


Figure
9
-

students’ level of participation (Larusson & Alterman, 2009).




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Figure
10
-

students’ balance of executing the three main actions: reading (top corner),
blogging

(bottom left) and commenting (bottom right). A perfect balance of the actions places
a student at the center (Larusson & Alterman, 2009).


Figure
11
-

Identifying conversations on the wiki focused on each lecture topic (Larusson &
Alterman, 2009).





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Figure
12
-

Visualizing (reading or commenting) interactions by drawing arrows between pairs
of students (Larusson & Alterman, 2009).


Another good example could be the research of (Reimann & Kay, 2010) in which they have
investigated possible visualization
s aspects of team performance and their ability to help in group
production as well as team coordination i.e. to develop team skills. The research discusses the
collaborative wiki writing and possible feedback strategies in order to scaffold group producti
on
function and well
-
being. According to their research they explain the challenges of collaborative wiki
witting as wiki pages constitutes from semiotic perspectives of group members. This leads to two main
challenges of group coordination on shared meani
ng of what is collaboratively written as well as wiki
content coherence on both levels of text (sentences and paragraphs) and concepts (ideas and
arguments). Therefore, in order to improve coordination of team members’ activities and increase
document cohe
rence, their research is supporting using following forms: (a) by monitoring and
visualizing group members’ interactions and contributions, (b) by visualizing wiki site structure, and (c)
by providing information on wiki page content based on a text
-
stati
stical analysis. However, the
following visualizations are discussed in this research:

Wattle Trees (Wattle tree is an Australian native plant with fluffy golden yellow round flowers) where
each member of the team is a single wattle tree, with its vertical

green stem that grows up the page.
Wiki
-
related activity is represented by yellow “flowers,” the circles on the left of the trees. The size of
the flower indicates the size of the contribution. After first experiences the Wattle Trees was replaced
by more

interactive visualization of a set of “swim lanes” one for each group member as in
F
igure 13,
area A, with three students S1, S2, S3, and one tutor, T; time is in days, running from bottom to top).
Color is used to represent the type of contribution (wiki
, ticket, svn), per day (or other time units) and
aggregated over the visualized time period (B). When the user clicks a point in one of the swim lanes
that has an activity indicated (i.e., is colored), the underlying log data for that cell will be rendere
d on
the screen (C).


Figure
13
-

interactive form of interaction visualization based on CSCL environment (Reimann &
Kay, 2010).

Social networks diagrams have been developed to visualize information regarding who contributes to
the wiki
-
page. The authors
used what they call Interaction Network (based on Social Network
Analysis) to show the relationships and flows between entities. “The network is modeled as a graph,
with each node representing a team member, always shown in the same, fixed position. Lines
between these nodes indicate interaction between these team members. We define interaction to



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occur when two people modify the same wiki page. The width of the edge is proportional to the
number of interactions between them. For a given resource, the numbe
r of interactions is calculated
as
n = min(n1, n2)

where
n1

and
n2

are the number of times user1 and user2 modified the resource.”
As depicted in Figure
14

the Interaction Network based on for the wiki shows that every member of the
team interacts with every other one, including the tutor.


Figure
14
-

Interaction network based on wiki entries (Reimann & Kay, 2010).


Visualizing wiki site structure: while st
udents are working on a wiki collaborative writing task they may
need to know which parts have been changed since their last visit to the site. Or maybe which parts of
the wiki have been changed by student “A”. Therefore, the authors utilized WikiNavMap (U
llman &
Kay, 2007)
-

a tool that enables the user to customize the view of the wiki in terms of time and in
relation to the authorship of activity on the pages
-

to support answering the following questions: Which
are the pages that I have made contributions

to? Which are the pages that another nominated person
has made contributions to? Which are the pages associated with a certain task? Which are the pages
with the most activity? Which pages changed in the last week? Which changed in a particular period of
time, such as a particular month? What is the extent of the wiki? As demonstrated in figure 1
5
,
WikiNavMap shows a navigational role, and also increases member and task awareness (hence,
affecting coordination), and helps to monitor coherence.





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Figure
2
-

WikiNavMap creates a dynamic visualization of a whole wiki site (Reimann & Kay,
2010).


Visualizing the Conceptual Structure of Wiki Page Content: providing information regarding concepts
contained in the wiki
-
page content and the
ir semantic relations may help group member’s
collaborative writing. The authors presents an automatic concept analysis method based on “Carley’s
map analysis technique” and utilizes software called Glosser. Glosser uses text
-
mining techniques
(based on La
tent Semantic Analysis technique) to provide student writers with information about their
text on a number of dimensions, including conceptual coherence. Glosser is capable to define
concepts with hierarchical representation on multiple levels of generaliz
ation and abstraction.
Moreover, it visualizes the concept map extracted from the wiki
-
page, figure
16

demonstrates
concepts map visualization based on wiki
-
page content.


Figure
16
-

A network view of the concepts identified in a jointly authored wiki p
age (Reimann &
Kay, 2010).


Table 1 lists the comparison on the level of features provided to the enhanced wikis in the research of
using enhanced wikis fo
r

collaborative writing.



Table
5
. Features comparison among s
e
lected research of using enhanced
wiki for collaborative
writing

System

Self
-
assess
ment

Peer
-
assess
ment

Group
-
assess
ment

Color
-
coded
contrib
ution

Motivat
ional
graphs

Task
aware
ness

Social
awaren
esss

Wiki
sturc
ture

Activi
ty
progr
ess

Contrib
ution
graps

Discu
ssion
Forum
s

(Biuk
-
Aghai,
Kelen,
&
Venkat
esan,
2008)


















(Trenti
n,
2009)





















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(Laruss
on &
Alterm
an,
2009)
















(Khand
aker &
Soh,
2010)
















(Reima
nn &
Kay,
2010)


















Co
-
writ
i
ng
Wiki


































6.1.2

Competitive advantages

Explain the advantage that can be

introduced by the specific Alice products with respect to what is
available on the market landscape


Automatic Test Item Creation

tool AQC
:

As depicted in Table 4 and referring to D5.2.1 and
Gütl, Lankmayr, Weinhofer, & Höfler, M. (2011)
,
competitive adva
ntages include:



Advanced tool supporting the
creation of four different test item types
: multiple
choice questions, false
-
true exercises, fill
-
in
-
the
-
blank exercises, and open ended
questions.



Learning setting dependent operating modes

supports fully
-
autom
atic test item
creation and interactive process types taking into account student or teacher input.



Domain knowledge independent methods

allow test item creation of unseen
textual content by applying statistical, semantic and structural analyses.



Language dependent data flow and process chain design provide
multilingual test
item creation
,

currently Englis
h and German,

and support the easy extension to
other languages.



Flexible design

supports an easy integration or exchange of modules in the syste
m
to offer improved processing tasks or even new features.



Easy integration into other systems
and

service provision

by a standard
-
conform
web service interface.



Standard compliance

enables an easy export and reuse of test items created by the
tool.






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Enhanced Wiki system with integrated self and peer assessment as well as teacher
feedback

As presented in Table
5
, c
ompetitive advantages include:



Enhanced tools to maintain
task and social awareness

and to support group well
-
being and production function

during a collaborative writing assignment.



Integrated self, peer, and group
-
assessment

activities with the use of assessment
rubric designed for scientific writing.



Continuous
Feedback provision

for learner scaffolding as well as for teachers to
follow c
ollaboration progress.



Visualization tools

to support both students and teachers to know who did what and
when.



Motivational Charts
in order to motivate peers to contribute and work in comparison
with others in the same group as well as to motivate groups

to contribute in
comparison with other groups.


References:

[1]

Biuk
-
Aghai, R.P., Kelen, C. & Venkatesan, H. (2008).
Visualization of interactions in
collaborative writing. In Proceedings of the 2008 Second IEEE International Conference on
Digital Ecosystems and Technologies (pp. 97
-
102), Phitsanulok, Thailand.

[2]

Judd, T., Kennedy, G., & Cropper S., (2010). Using wikis for

collaborative learning: Assessing
collaboration through contribution.
Australasian Journal of Educational Technology
,
26
(3),
341
-
354.

[3]

Khandaker, N.; Leen
-
Kiat Soh (2010).
Assessing individual contributions to groupwork by a
summary of tracked computer
-
s
upported collaborative activities. In Proceedings of the
Frontiers in Education Conference (FIE), 27
-
30 Oct. 2010, (pp. S1E
-
1
-

S1E
-
6), IEEE CS
Press.

[4]

Larusson, J.A. & Alterman, R. (2009). Visualizing Student Activity in a Wiki
-
mediated Co
-
blogging Exercis
e. In CHI EA '09: Proceedings of the 27th international conference extended
abstracts on Human factors in computing systems (pp. 4093
-
4098). New York, NY: ACM.

[5]

Macdonald, J. (2003). Assessing Online Collaborative Learning: Process and Product.
Computers &
Education, 40

(4), 377
-
391.

[6]

Reimann, P., & Kay, J. (2010). Learning to learn and work in net
-
based teams: Supporting
emergent collaboration with visualization tools. In M. J. Jacobson & P. Reimann (Eds.),
Designs for learning environments of the future. (p
p. 143
-
188) New York: Springer.

[7]

Trentin, G. (2009). Using a wiki to evaluate individual contribution to a collaborative learning
project.
Journal of Computer Assisted Learning,
25
, 43
-
55.

[8]

Ullman, A. & Kay, J. (2007).
WikiNavMap: A visualisation to suppleme
nt team based wikis
Conference on Human Factors in Computing Systems, CHI ‘07 extended abstracts on Human
factors in computing systems
(pp. 2711

2716). San Jose, CA: ACM Press.

[9]

Papasalouros A., Kotis K., Kanaris K. (2008).
Automatic generation of multiple
-
choice
questions from domain ontologies. IADIS e
-
Learning 2008 conference, Amsterdam.

[10]

Papasalouros A., Kotis K., Kanaris K. (2011).
Automatic generation of tests from domain and
multimedia ontologies
Interactive Learning Environments, Volume 19, Issue 1, 20
11, 5
-
23.

[11]

Sanz
-
Lobera, A.; González Roig, A.; González Requena, I. (2011). Methodology for
automated generation of multiple choice questions in self assessment.
REES 2011
.




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[12]

T. Mine, A. Suganuma, T. Shoudai

(2000).
The Design and Implementation of Automatic
Exercise Generator with Tagged Documents based on the Intelligence of
Students:AEGIS,Proceedings of the ICCE/ICCAI 2000,pp.651
-
658
.

[13]

Goto, T.; Kojiri, T.; Watanabe, T.; Iwata, T.; & Yamada, T. (2010).
Automatic Gen
eration
System of Multiple
-
Choice Cloze Questions and its Evaluation
.
Knowledge Management & E
-
Learning: An International Journal, Vol.2, No.3.
, 210
-
224.

[14]

Heilman, M. (2011). Automatic Factual Question Generation from Text. PhD thesis,
Carnegie
Mellon Unive
rsity
.

[15]

Cubric , M.; & Tosic , M. (2010). Towards automatic generation of e
-
assessment using
semantic web technologies. In: Proceedings of the 2010 International Computer Assisted
Assessment Conference, Jul , vol 2010 .

[16]

Gütl, C.; Lankmayr, K.; Weinhofer, J.
; & Höfler, M. (2011).
Enhanced Approach of Automatic
Creation of Test Items to foster Modern Learning Setting. Electronic Journal of e
-
Learning, 9,
1, ECEL 2010 special issue Apr 2011, 23

38.



6.2

Description of
products/tools

coming from
WP6
(MOMA)

WP6
-

Overview table results/products


Result(s)

Product(s)


Related


WP

Brief Description

Storytelling Complex
learning Object

WP6

We developed a software tool that expresses storytelling
as didactic complex learning resource with the following
distinctive features:



Non linearity gained from Educational Template
:
We have developed an approach to template
-
based storytelling in order t
o help the
instructional designer to
design
well
-
structured
educational stories composed of various block
that can be executed in different manners
.



Storytelling tool
: In order to realize

this
pedagogical templates

to generate the SCLO, we
developed a STORYTELLING TOOL. The tool gives
instruments to organize and structure stories, to
define storytelling complex object behaviors and
to

execute Educational Template
.

The SCLOs can be exported in SCORM 1.3 in order to b
e
executable with other system and can be annotated with
IEEE LOM metadata schema in order to be stored in
standard digital repositories for learning objects.




6.2.1

Overview of competitors




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describes from a “functional” viewpoint the characteristics of curre
nt product available on the market.
It is not necessary to perform an analysis per product but to provide an overview of key features
available from similar products>


6.2.2

Competitive advantages


explain the advantage that can be intro
duced by the specific
ALICE

product
s

with respect to what is
available on the market landscape>



6.3

Description of products / tools coming from WP7 ( CRMPA)

Overview table results/products

The following list includes main products
coming from WP7.
All these components are
strictly
integrated in IWT and are based on other features provided by IWT so they can’t be seen
, at the
moment,

as stand
-
alone components to be exploited separately.

Result(s)

Product(s)

Related

WP

Brief Description

Abstract Knowledge
Model Editor

WP7

It is a software tool enabling to
visually build instances of
an

abstract
knowledge

m
odel by letting teachers define
a context
model
for representing
several aspects of a learning context

and
a context
profile able to link didactical

properties to a contex
t
model. The tool also allows to design an abstract ontology by
connecting

context
-
aware information

to concepts and includes
a
contextualization algorithm able to generate a
contextualized
ontology starting from an abstract
one by selecting a specific
con
text among those supported.

Learning Goals
Recommender System

WP7

It is a software too that applies a concept mapping algorithm able
to identify, for a learner, known domain concepts and concepts
currently under learning; a concept utility estimation
algorithm
able to estimate, for a learner, the utility of each unknown
concept by looking at concepts known and under learning by
similar users; a learning goals utility estimation algorithm able to
calculate the utility of each available learning goal for

a learner by
aggregating utilities of composing concepts.




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