frontiers of open data science research
TRANSCRIPT
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.