FRONTIERS OF OPEN DATA SCIENCE

RESEARCHAni Aghababyan

O P E ND A T AS C I E N C EC O N F E R E N C E_

BOSTON 2015

@opendatasci

Ani Aghababyan, Ph.D.Data ScientistMcGraw-Hill Education Analytics

Frontiers of Open Data Science ResearchData and Analytics

Saturday, May 30, 2015

Big Data

Spark

An

aly

tics

Data

S

cie

nce

Learning Science

Visualization

Learning Analytics

ReportingElastic Map Reduce

ScalaN

oS

QL

MongoDB

HadoopPrivacy

Anonymization

Open Caliper

BI

Predictive Modeling

Info

rmat

i

on

Smart Data

PostreSQL

Adaptive

Learning

Internet of Things

data lifecycle

pre

scrip

tive

descri

pti

ve

data analytics

nudge

real-time

Cassandra

EXCITING POSSIBILITIESWhat if my FitBit could if I will fail my test: ready for the test?Whether I truly have test anxiety?Should I delay taking this take home exam?

SOBERING QUESTIONSWhose data is it?

Can I even access my data—all my data?Who else can access my data?

Can the data be used against me?Is the data even accurate?How good is the science?

Research Studies

Research Studies

The 2-sigma problemGroup 2 – 1 sigma above Group 1Group 3 – 2 sigmas above Group 1The average tutored student outperformed 98% of traditional students

BENJAMIN BLOOM2𝞂

QUESTIONS + CONCLUSIONSHow do we achieve a 1- or 2-sigma improvement in outcomes?How do we encourage self-regulation in the learner?How do we provide targeted, real-time feedback (nudges)?How do we create a personalized path for the learner?

HINTLearning AnalyticsAdaptive Learning

Learning Analytics

What is the best that could happen?

What might happen?

Stages of Analytics

Analytics Maturity

Com

petit

ive

Adva

ntag

e

Raw Data

Cleaned Data

Standard Reports

Adhoc Reports &

OLAP

Generic Predictive Analytics

Predictive Modeling

PREDICTION

What happened?

What correlates to what happened??

PRESCRIPTIONDESCRIPTION

Accepted standards for learning

Aligned curricula and assessments

Measurement and reports

Course correction

Descriptive

Predictions

Prescriptive

WHAT IS LEARNING ANALYTICSThe measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs.

How could we achieve that?

HINTOpen Architecture

Open Architecture

Data Source 1

Learning Events + Context

Learning Analytics Store

Output API

Caliper Data Capture Specification

Product 1

Open Analytics Architecture

Data Source 2

Data Source 3

Data Source 4

Input APIs

Product 2

Product 3

Data Source 1

Learning Events + Context

Learning Analytics Store

Output API

Caliper Data Capture Specification

Product 1

Open Analytics Architecture

Data Source 2

Data Source 3

Data Source 4

Input APIs

Product 2

Product 3

Data Source 1

Learning Events + Context

Learning Analytics Store

Output API

Caliper Data Capture Specification

Product 1

Open Analytics Architecture

Data Source 2

Data Source 3

Data Source 4

Input APIs

Product 2

Product 3

Data Source 1

Learning Events + Context

Learning Analytics Store

Output API

Caliper Data Capture Specification

Product 1

Open Analytics Architecture

Data Source 2

Data Source 3

Data Source 4

Input APIs

Product 2

Product 3

Data Source 1

Learning Events + Context

Learning Analytics Store

Output API

Caliper Data Capture Specification

Product 1

Open Analytics Architecture

Data Source 2

Data Source 3

Data Source 4

Input APIs

Product 2

Product 3

MCGRAW-HILL EDUCATION

THANK YOU.