Purpose of the talk: Describing the use of Machine Learning and Big Data Techniques to improve the performance of elearning students. Presenting an existing case of an elearning platform (iAdLearn¡ng) and the technology used behind the scenes, to make adaptive/high performance elearning a reality. Session presented at Big Data Spain 2015 Conference 15th Oct 2015 Kinépolis Madrid http://www.bigdataspain.org Event promoted by: http://www.paradigmatecnologico.com Abstract: http://www.bigdataspain.org/program/thu/slot-17.html

2. iAdLearning
Next Generation E-Learning
Oct 2015. Version 1.0
jose.omedes@itoptraining.com

3. Copyright iTopTraining. All rights reserved.
Topics
Page  2
1. Introduction and iTopTraining
2. Where are we coming from? What are we trying
to achieve?
3. iAdLearning architecture

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1. Introduction and iTopTraining

5. Copyright iTopTraining. All rights reserved.
iTopTraining
 Privately held company
 Based in Madrid (we have presence in Guadalajara – México – )
 Founded in July 2013
 Continuation from a previous company
 Two main business lines:
 eLearning platforms on the cloud (SaaS)
 eLearning innovation
 Research and Development of innovative e-Learning software solutions
 ~50% people works on Research and Development
Page  4

6. Copyright iTopTraining. All rights reserved.
iTopTraining Technology Landscape
Page  5
Day to Day Operations
(SaaS eLearning Platforms)
Cloud Technologies
(AWS, Azure)
PHP
Javascript
Apache
MySQL (Aurora)
MemCache
Moodle
Innovative eLearning Products
(includes iAdLearning)
Cloud Technologies
(AWS, Azure)
AngularJS
NodeJS, D3js
Java, Scala
NGINX
Cassandra, MongoDB
Neo4j, Redis, ElasticSearch
Apache Spark
Machine Learning, NLP

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2. Where are we coming from and what are
we trying to achieve?

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Change of Learning Paradigms (*)
Page  7
Linear Learning
Static Training Contents
Free Learning
Content Adapts to Users
(*) We are focusing on those factors relevant for our discussion but there are
other changes such us the important irruption of mobile devices on eLearning
“Mimics” Internet Navigation
Learn “by interest”
Every user is different and has
different learning needs even
in the context of the same
course
Instructor Lead Learning eLearning
Users access to training
courses whenever they want
to and wherever they are

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Change of paradigm brings new challenges …
Page  8
e-Learning Volume
Content Transformation for eLearning
1
2
• eLearning market CAGR ~20% (depends on studies)
• +38% of company training is delivered online
• MooCs are consolidating
DELIVERY
ANALYSIS of
INFORMATION
(is this a challenge?)
• Very man intensive task
• Very time consuming task
COST
End User Learning Experience3
• Users are “left alone” …
QUALITY
INDIVIDUAL NEEDS

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Change of paradigm brings new opportunities (1) …
Page  9
Improve eLearning Experience
Using all information gathered
by eLearning platforms
MACHINE LEARNING
BIG DATA
• Improving the way contents are visualized and navigated
• Guiding users to discover the content which is relevant for them
• Providing automatic feedback to trainers about the quality of the content materials
and about the user experience when using those contents

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Change of paradigm brings new opportunities (2) …
Page  10
Facilitate migration of contents to eLearning
• Generating eLearning contents in a format that facilitates free navigation and
“learning by interest” from non-native eLearning formats (Word, PDF, Powerpoint)
• Providing a cost effective solution for content transformation
NATURAL LANGUAGE PROCESSING
MACHINE LEARNING
Processing non native
eLearning contents

12. Copyright iTopTraining. All rights reserved.Page  11
Wasn’t this
presentation
supposed to be
technical?

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Key Take-aways
 The way people learn is changing
 New formats (eLearning growth)
 New ways of using existing formats such as e-Learning (free navigation, learn by
interest, etc.)
 Growth of e-Learning provides us with an important amount of
information that properly analyzed may dramatically improve the
user’s eLearning Experience
 Requires technology
 Requires proper algorithms
 Content Transformation is key to help trainers and training
companies move into e-Learning
 Benefit from all the information analysis based on e-Learning data
 Follow the market trends (continue in the market)
Page  12

14. Copyright iTopTraining. All rights reserved.
What is iAdLearning?
Page  13
iAdLearning is a software that makes the e-Learning platforms
adapt to the individual needs of the students -adaptive e-Learning-
providing a unique personal e-learning experience throughout the
course materials while maximizing the students achievements by
making intelligent study suggestions based on previous learning
experiences

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iAdLearning Principles
Page  14
ADAPTIVE
Each student has a complete different
experience throughout the course content
based on his/her background
Students can navigate through the entire
training materials in a non lineal fashion
based on their needs or interests
NON LINEAR
LEARNING
MAKE USE OF
EVERYBODY’s
EXPERIENCE
The system uses previous learning
experiences to recommend customized
learning paths throughout the content
EXISTING
CONTENT
IS EASY TO
IMPORT
iAdLearning allows to easily import
existing non e-learning native
training materials (Word, PDF, PPT)

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How does iAdLearning work?
Page  15
1
Importing documents, analyzing them and establishing semantic relationships
among the document individual content components creating, as a result, a user
navigable graph (knowledge network)
2
Allowing free navigation through the knowledge network not only based on the
original content structure but also on the user preferences and interests
3
Discovering successful navigation patterns that maximize user performance
through the course materials in a way those can be suggested to students during
their learning experience
IMPORT
VISUALIZE
RECOMMEND

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How does iAdLearning work?
Page  16
Set of
Documents
(Word, PPT, PDF)
Semantic
Analysis
Semantic
Analysis
ACE
1
1.2.2
2
Course Graph
Knowledge Net
1.1 1.2
1.2.1
• A set of documents belonging to an e-Learning course is imported, analyzed
and broken down into semantically relevant fragments called ACEs (Atomic
Content Elements). ACEs represent course fragments that can be individually
studied and understood
• iAdLearning creates a graph representing the relationships between the
different ACEs:
• Structural Relationships (blue lines): represent connections related to the
course structure as initially established by documents authors
• Semantic Relationships (red lines): represent connections created due to
the similarity of the contents being described by the connected ACEs
IMPORT

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How does iAdLearning work?
Page  17
IMPORT
Section 1Section 1
Section 1.1Section 1.1
Section 1.2Section 1.2
Section 2Section 2
Section 2.1Section 2.1
Section 2.2Section 2.2
Section 2.2.1Section 2.2.1
Section 2.2.2Section 2.2.2
Section 7Section 7
…
Section 7.1Section 7.1
Section 7.1.1Section 7.1.1
Section 7.1.2Section 7.1.2
ACE 1ACE 1
ACE 2ACE 2
ACE 3ACE 3
ACE 4ACE 4
ACE 5ACE 5
ACE 6ACE 6
ACE 7ACE 7
0.95
0.72
ACE 1ACE 1
ACE 2ACE 2
ACE 3ACE 3
ACE 4ACE 4
ACE 5ACE 5
ACE 6ACE 6
ACE 7ACE 7
Fragmentation
Analysis of
Relationships

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How does iAdLearning work?
Page  18
IMPORT
STRUCTURE OF THE DOCUMENT AS
DISCOVERED BY iAdLearning

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How does iAdLearning work?
Page  19
ACE
1
1.2.2
2
Course Graph
Knowledge Net
1.1 1.2
1.2.1
VISUALIZE
EXAM
{ 1, 1.1, 1.2.1, 2, 1.2.2, 1.2, EXAM}
{ 1, 1.2, 1.2.1, 1.1, 1.2.2, 2, EXAM}
USER 1
USER 2
User Navigation Patterns
• When accessing the e-Learning course contents, users navigate through the graph (*)
either following the initial course structure (blue connections) or jumping into other
related content elements according to their preferences/interests (red connections)
• User navigation patterns (visited ACEs and their sequence) are recorded together
with the user evaluation results (exam results), in a way they can be further analyzed
(*) On top of the graph navigation, iAdLearning offers other navigation views such a tree-view
(**) Contents created with iAdLearning can be visualized in Moodle through a plugin

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How does iAdLearning work?
Page  20
VISUALIZE
STRUCTURAL
RELATIONSHIPS
SEMANTIC
RELATIONSHIPS

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How does iAdLearning work?
Page  21
{ 1, 1.1, 1.2.1, 2, 1.2.2, 1.2}
{ 1, 1.2, 1.2.1, 1.1, 1.2.2, 2}
USER 1
USER n
User Navigation Patterns
… Behavioral
Analysis
Behavioral
Analysis
• Navigation patterns are analyzed using advanced machine learning techniques
• As a result of the analysis, users are grouped according to their course navigation
pattern and a set of relevant variables (age, studies, knowledge of the topics covered
by the course, etc.). iAdLearning establishes recommended navigation paths for
each group of users based on the recorded course performance.
…
Recommended Navigation
Paths
{ 1, 1.1, 1.2, 1.2.1, 1.2.2, 2}
{ 1, 1.1, 1.2.1, 2, 1.2.2, 1.2}
age, studies,
previous knowledge,
evaluation mark, etc.
RECOMMEND

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How does iAdLearning work?
Page  22
NEW
USER
ClassificationClassification RecommendationRecommendation
1
1.2.2
2
1.1 1.2
1.2.1
1
2
3
4
• When a new user comes into the e-Learning platform, it is classified according to
the criteria established by the behavioral analysis already performed on the
navigation patterns of preceding users
• Based on the user classification, iAdLearning suggests an individual
recommended navigation path targeted to maximize the user performance on the
course
RECOMMEND

24. Copyright iTopTraining. All rights reserved.
How does iAdLearning work?
Page  23
STRUCTURAL
RELATIONSHIPS
SEMANTIC
RELATIONSHIPS
RECOMMENDED
NEXT NODE

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3. iAdLearning Architecture

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Architecture Principles
Page  25
All user actions are being logged for
further analysis (logging intensive
application)
Separate Application and
“Logging” Information Flows
Individual Functions Scalability
The different components of the
application must be individually
scalable according to the real needs
The different parts of the application
must be implemented in different
logical entities that communicate
through APIs
Function Separation via APIs
Redundancy / Resiliency All the system must be redundant
Cloud Based /
Cloud Provider Independent
The system must reside on the cloud
The system must be independent of
the cloud provider

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iAdLearning Architecture (version 1)
Page  26

28. Copyright iTopTraining. All rights reserved.
iAdLearning Architecture
Page  27
IMPORT
• Traffic coming from the Front End is redirected by NGINX into the Web Server
• The Web Server sends the documents to import to a pending jobs queue handled
by RabbitMQ.
• Whenever there is processing power available, they are analyzed, fragmented
and the “knowledge network” (graph) gets generated.
• Results of the import process are persisted into MongoDB, Neo4j, Elastic Search
and Cloud Storage.

29. Copyright iTopTraining. All rights reserved.Page  28
•Regular application flow is directed through NGINX into the Web Server
•The Web Server gets information to visualize from MongoDB / Neo4j
•When required, the front end component pulls content from the cloud storage
•Information persisted in MongoDB / Neo4j corresponds to:
• Training contents
• Recommend paths through the content materials
iAdLearning Architecture
VISUALIZE

30. Copyright iTopTraining. All rights reserved.Page  29
•User “action events” come to NGNIX which redirects the traffic to the logging server.
•The logging server persists the user action events into Cassandra.
•Logs stored in Cassandra are periodically analyzed by a batch process which runs
the analysis in Apache Spark.
•Results of the Analysis (Recommended Paths through the content) are persisted
into MongoDB.
iAdLearning Architecture
RECOMMEND

31. Copyright iTopTraining. All rights reserved.Page  30
iAdLearning Architecture - Technologies
FRONT
PROGRAMMING
LANGUAJES
DATABASES SEARCH ENGINES
ANALYTICS
CLOUD
PROVIDERS
QUEUEING

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iAdLearning Architecture – Technologies
Page  31
Members of DataStax Startup
Program
DataStax Enterprise 4.8
(DSE)
Spark 1.4
Cassandra 2.1
OpsCenter
DevCenter
Spark Cassandra Drivers

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iAdLearning Architecture – Thinking points
Page  32
We are permanent newbies …
We live in a world of complex technologies continuously evolving
Solutions need to be simplified
There is always a new technology/system that may play a role in your solution
Management of solutions and cost need to be part of the equation
We miss “relational” …
Relational databases are great !!!
Sometimes you cannot use relational databases but they are still great !!!

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iAdLearning Architecture – Thinking points
Page  33
Security is important from day 1
Don’t treat security as a marginal element in your system until you go into production
Automate your deployments
How many times are you going to install the same type of node?
We use Chef
Networking is important from day 1
Don’t treat networking as a marginal element in your system until you go into production

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iAdLearning Architecture – Thinking points
Page  34
Reuse and go to the source
There are tons of libraries out there that may be used in your development
Go to the source … minimize the library over library effect ...

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iAdLearning Architecture (version 2)
Page  35
1
Simplify the way the front end is delivered to the user by using a Content
Delivery Network
Content is static and the dynamic part (JavaScript) runs at the user browser
2 Reduce number of databases
A graph oriented database is not needed for the time being
3 Reduce the number of software components
Simplify the way importing of documents is performed (queuing part)
4 Introduce Deployment Tools and Continuous Integration
Reduce the deployment of new software cycle

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iAdLearning Architecture (version 2)
Page  36

38. Copyright iTopTraining. All rights reserved.Page  37
Thank you very much
iTopTraining
www.itoptraining.com
jose.omedes@itoptraining.com