© 2013 IBM Corporation IBM Confidential

IBM Research - India

Big Data in Education

Presenter NameTitle

Mukesh Mohania, Ph.D.IBM Distinguished Engineer

Chief Architect, Education Research

Hi-Ed GER >30% (2020)>30% (2020)

20.2% (2012)20.2% (2012)12.4%

(2009)12.4% (2009)

45M more 10th graders

Will need 50K more colleges; 800 more universities (now: 350+)

India

Supply, Demand

Digitization Content

Content

Digitization

Online Blended Learning eLearning CAGR (GSV Advisors)

Global 23% ; US 15%

eBook Accounts for 23% of US Publisher Sales, $6B 2012 - $16B 2016

An Industry Transitioning to Digital

3

Today education data is siloed. Integrating those data silos provides transparency, meaning and security.

Consolidated data foundation

Institutions

Parents

Learners

Faculty

Institutional insights and

personalization

Data-driven learning

pathways

Individualized learning

pathways

Data silos and fragmentation

Lack of institutional

insights

Overwhelming volume of data

Class level learning services

Current Future

Mobile Social

Cloud

Analytics

Data is rapidly becoming the foundation for the transformation of Education

Analytics driven personalized learning pathways

-- improves outcomes in learning and in talent management

Data Sources

Predictive Analytics1. Learner stratification2. Deviation from suggested

path3. Identify at-risk learners

Prescriptive Analytics

1. Personalized learning pathway

2. Identify optimal delivery strategy

3. Track corrective processApplication Analytics1.Analyze content usage 2.Extract learning patterns3.Visualize interactions

Timely graduation Increased employability Reduced training costs Efficient student population

management Efficient targeting for recruiting

or training Learning efficacy Trends in skills produced and

those required

6

Education Big Data Services

Assessment

Professional Learning

Learning Resources

Curriculum

Mobility

SocialLearning

AcademicPlanning

Post-secondaryPathways

Financial Aid

Tools

ePortfolioand

Resume

CareerPlanning

CareerPlacement

Post-secondaryReadiness

InstructionalEffectiveness

InstitutionalEffectiveness

CareerReadiness

Identity and Security

Data and Analytics

Access

Students andCitizens

Collaboration

Adaptive Learning

7

These students will receive personalized content

Good in biology,

likes to read detailed contents

Weak in biology,

learn quick by examples

and graphics CARBON--Carbon is the chemical element with symbol C and atomic number 6.

-Learning Object

Repository

----------------------------------------------------Carbon and energy requirements of the autotrophic organism are -----------------------------------------------

Receives Receives

JoinsJoins

Collaborative and Social Learning Platform

Learning Management

System

Neha Ramu

Which student appears – disengaged, bored, puzzled, attentive?

Which parts of the content - most viewed, Boring, Difficult? Any positive/negative feedback on the content? Content compatibility with Learner’s learning style?

Usage HeatMap

Instrumented Learning Platform Instrumented Learning Platform

Smart Online/Offline SynchronizationLow cost, delay tolerant delivery

Smart Online/Offline SynchronizationLow cost, delay tolerant delivery

Disconnected UseDisconnected Use

Student @ HomeStudent @ Home

Teacher @ ClassTeacher @ Class

Flipping the Classroom

Content Providers

Working with two Universities in IndiaWorking with two Universities in India

Watson Enabled Cognitive Assistants for Education

Student Advisor

Cognitive Tutor(w/ CLC student version)

Teacher Advisor(Commercial: PLP/CLC)

Career Advisor

Oth

er ideas

Piazza(Concept Map)

WEA(DeepQA)

Dialog LCH(Content Analytics)

Short AnswerScoring

Learner Models

Gamification

PETALS

Reasoning Engines

Devops

Blu

em

ix

So

ftla

ye

r H

yb

rid

E

xte

ns

ion

s

Adaptive Learning Engines (3rd party)

Student Information Systems (IBM or 3rd

party)

Content: Publisher and Open Education Resources

KnowledgeGraph

IBM.Next & Bluemix

Cognitive Assistants for Education

10

IBM’s Personalized Learning on Cloud Solution Uses Big Data and Analytics to Deliver Higher Engagement and Improved Outcomes

Student Information Hub: comprehensive and secure data store for all student data and learning telemetry

Learning Content Hub: intelligent content system to identify, tag and align learning resources

Career Pathways

Lamar High School

Personalized Learning Pathways

Cognitive Learning Environments (using Watson)