Interlingua - Providing foreign students with on-demand access to relevant learning material in their mother tongue

1. © 2014 interlingua
Providing foreign
students with on-demand
access to relevant
learning material in their
mother tongue
Sergey Sosnovsky
DFKI
02/12/2015

2. © 2014 interlingua
Structured learning material on the Web
• High-quality, domain-oriented
• Their content has been chosen, structured and formatted
for the purpose of explaining the domain knowledge by
the experts in the domain
• The structure of the domain knowledge has been used as a
mean for organizing these resources
• If extracted, this structure represents the model of the
resource and the model of the domain as the author
understands it
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Tutorials
Textbooks
Digital LibrariesDictionaries
Encyclopedias
Table of Contents
Links between Pages
Headers of Sections
Content Formatting
Motivation 1

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Example: @Connexions

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Example: @Wikipedia

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Example: @Wolfram MathWorld

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Example: @online tutorial

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Project 1: Linking textbooks to ontologies
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Sosnovsky, S., Hsiao, I-H., & Brusilovsky, P.
(2012). Adaptation “in the wild”: Ontology-
based personalization of open-corpus learning
material. In Proceedings of EC-TEL'2012: 7th
European Conference on Technology
Enhanced Learning (pp. 425-431).
Berlin/Heidelberg, Germany: Springer.
Ontology
mapping
Open-corpus model Exercises

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Project 2: Linking textbooks to textbooks
• Latent Dirichlet
Allocation
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Guerra, J., Sosnovsky, S., & Brusilovsky, P.
(2013). When one textbook is not enough:
Linking multiple textbooks using probabilistic
topic models. In Proceedings of EC-TEL'2013:
8th European Conference on Technology
Enhanced Learning (pp. 125-138).
Berlin/Heidelberg, Germany: Springer.
Linking
Linking

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Why linking?
• Integration and Cross-reasoning
• Discovery and Retrieval
• Navigation and Recommendation
• Restructuring and Enrichment
• Connection to External LinkedData bases
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Student mobility in EU/GR
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Motivation 2
• Strongly supported on EU level:
– promotion of teacher/student mobility (Erasmus+,
”Youth on the Move” action of the Europe2020 strategy)
– Harmonization of cross-national study programs and
– Development of the the European competency
(Bologna process)
• one of the key factors for ensuring sustainable
economical and social progress in Greater Region

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Large population of “interlingual” students in GR
• 30 cross-border study programs (up to 600 students)
• Every year 200 Erasmus+ students (doubled since 2008)
• 400 UniLor/HTW students study in ISFATES/DFHI program
• German-speaking students in Wallonia universities
• University of Luxembourg students
• Students engaged in new educational opportunities
(MOOCS, Cross-border vocational training, informal
learning with OER)
+

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Problems of “interlingual” students
• Transition to a new educational context is
aggravated by the need to study in a foreign
language:
– unfamiliar teaching tradition
– prerequisite knowledge exist in a different language

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Problems of “interlingual” students (2)
Institutional
lack of understanding that this is a barrier for effective cross-border
educational mobility. The current efforts focus on building overall
capacities in GR, and not on individual students and their situation.
Pedagogical
the course material is rarely adapted to the cultural, linguistic and
background conditions of students. A “one size fits all” approach can
be the most convenient for a teacher, but not effective for a student.
Technological
existing e-Learning systems do not take advantage of modern
semantic and adaptive technologies. They remain repositories of
digital material with poor functionality and little interactivity.
Methodological
formative assessment and individual scaffolding could have been
used to help interlingual students focus on the problem, self-
estimate its source and engage in an effective remedial activity.
Motivational
If a student cannot progress, because of language problems is likely
to develop frustration and anxiety, which will inevitably transform
into poor grades and high risks of dropping out of the study program.
Organizational
insufficient level of collaboration and exchange between the GR
universities, when it comes to best teaching practices for foreign
students and best learning material in the languages of GR.

14. © 2014 interlingua
Not the project approach
• What we have not been doing:
– Teach students foreign language
• There are enough projects doing that
• Most students can speak the language of study, but have problems with
particular terminology
– Implement another multilingual program
• There are enough programs
• We focused on helping students enrolled such programs
– Translate educational content
• This is a too challenging, impractical and unnecessary task
Instead, we propose an approach complementing
the above
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“Interlingua” Approach (1)
σ: Standardabweichung σ: Écart type
• There is enough learning material available online
(textbooks/tutorials) in most of the languages
• Most of this material is written and structured by
experts/teachers
• Our task is to link relevant pieces (chapters, sub-
chapters) of these textbooks and make the link available
to students

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“Interlingua” Approach (2)
development of an online intelligent educational
solution to provide interlingual students with
on-demand access to relevant learning material
in their mother tongue
Standardab-
weichung
Écart type

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INTERLINGUA: SUPPORTING STUDENTS OF GREATER
REGION WITH INTERLINGUAL EDUCATIONAL RESOURCES
• Project partners:
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• Project sponsors:
• Associated partners:
• Target domain: Basic Statistics
• Target language: English, French, German

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The Domain of Statistics
• The Interlingua technologies are domain
independent; however to pilot then we have
focused on Statistics
• Basic Statistics courses are a part of many curricula
and fields of studies (from natural, to engineering,
to social)
– Interlingua will be applied in the framework of COURLIS -
the MOOC on basic statistics, offered by Université de
Lorraine starting 2013
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We have asked the user
• ~1000 students filled a questionnaire
• ~ 20 professors teaching “interlingual” students were
interviewed
• Main findings:
– Foreign language terminology is one of the main
educational problems for such students
– Using Web for finding additional resources is a common
practice
– Professors recognize the problem but do not have time
for individual attention
– There is need for an Interlingua-like service
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Ontology of Statistics
• Source of concepts names:
– Le glossaire ISI / ISI Glossar
(http://isi.cbs.nl/glossary/)
– ~3500 terms in ~25 languages
– Synonyms in all languages
• Source of relations and explanations:
– dbPedia (http://dbpedia.org )
– „related“ concepts
– concept definitions
– links to Wikipedia pages
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standard score
z-score
note réduite
résultat type
note typique
ponctuation standard
score centré réduit
z-Score
standardisierter Score
Standardpunktwertung
In statistics, the standard
score is the (signed) number
of standard deviations an
observation or…
standard
score
En probabilités et statistiques,
une variable centrée réduite
est une variable aléatoire…
Unter Standardisierung oder
z-Transformation versteht
man in der mathematischen
Statistik eine …
Statistical
Ratios
http://en.wikipedia.org/wiki/Standard_score
Type
FR
DE
EN
t-statistics Type
……

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Textbook processing: Table of Contents
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Table of Contents
<Chapter>
<Subchapter>
<Subchapter>
<Subchapter>
<Subtitle>
<Subtitle>
<Subtitle>
<Subtitle>
<Subtitle>
<Subchapter>
Machine
Readable
Structure

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Textbook processing: the Content itself
Even When We Don’t Know the Language
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Human Reader VisionMachine Reader Vision Content
Chapter Title
Sub-Title of
prior Chapter
Title
Text body of
prior sub-title
Sub-Title of
prior Chapter
Title
Footer notes, may
or may not signify
importance
Text
Some more
text
Even more of the
same text
Different text
body
This is also text
Page numberYet another text

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Textbook processing: the keywords
• Recognize the ISI Glossary keywords
• Process the Index at the end of the book to
understand, where the keyword are introduced
first time
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Textbook processing: representation
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• Layers of information:
1. Formatting layer (font attributes: size,
family, boldness, indentations, etc.)
2. Structural layer (structural elements:
ToC, index, breadcrumbs, important
text, regular pages, links between
pages etc.)
3. Semantic layer (topic-based hierarchy,
keyword-based links to external
models, semantic links between pages,
types of learning objects within a book)

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Interlingua Technology (1)
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Step 1:
Textbook structure
extraction
Chapter1
Section1.1
Subsection1.1.1
Subsection1.1.2
…
Section1.2
Subsection1.2.2
…

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Interlingua Technology (2)
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Chapter1
Section1.1
Subsection1.1.1
Subsection1.1.2
…
Section1.2
Subsection1.2.2
…
Step2:
Textbook index
extraction
term -> page#
term -> page#
term -> page#
term -> page#
term -> page#
….

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Interlingua Technology (3)
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Chapter1
Section1.1
Subsection1.1.1
Subsection1.1.2
…
Section1.2
Subsection1.2.2
…
term -> page#
term -> page#
term -> page#
term -> page#
term -> page#
….
Statistics
ontology
Step 3:
Semantic
Annotation
....
....
....

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Interlingua Technology (4)
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Statistics
ontology
Other
textbooks
TAO (Self-
assessment)
....
....
....
Semantic
model of the
textbook

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All together
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....
....
....
....
....
....
....
....
....
DE

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Relevant reading in one’s mother tongue
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Relevant reading in one’s mother tongue
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Help with terminology
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