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Building a Big Data Analytics Workforce in
iSchoolsPenn State Big Data Education Project Team
Presenter: Eun-Kyeong Kim (Ph.D. Candidate)([email protected])
The GeoVISTA Center, The Department of GeographyThe Pennsylvania State University
KOCSEA 2015
Big Data Education Project Team
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Dr. Jungwoo Ryoo
Associate Professor,IST at Penn State Altoona
PI Co-PIs
Dr. Soo-yong ByunAssociate Professor
Education at Penn State University Park
Dr. Dongwon LeeAssociate ProfessorIST at Penn State University Park
Graduate Project Manager
M.S. Eun-Kyeong KimPh.D. Candidate,
Geography (GIScience) at Penn State University Park
Undergraduate Research Associates
William Aiken
Security and Risk AnalysisPenn State Altoona Penn State University Park
Whitney HernandezVictoria McIntyre
Computer Science
Ryan A. Bury
Geography (GIS)
Nate GouldWilliam Casselberry
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Table of Content• Why does Big Data Education
matter?• NSF-sponsored project: Big Data
Education– Goals & objectives– Project team & timelines– Learning module 1, 2, 3 for big data
analytics– Deliverables & workshops
• Call for Participations
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Buzzword: Big DataEveryone talks about Big Data in these days.
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Why: the Explosion of Data• Data grows exponentially fast in
volume and variety.– SDSS (the Sloan Digital Sky Survey):
about 200 GB / day.– LSST (Large Synoptic Survey Telescope):
about 140 TB / 5 days.
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Why: Big Data is useful• Many applications of big data
analytics• The U.S. government “Big Data
Research and Development Initiative” in 2012
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Why: Demand in Manpower• McKinsey, “The United States alone
faces a shortage of 140,000 to 190,000 people with analytical expertise and 1.5 million managers and analysts with the skills to understand and make decisions based on the analysis of big data.”
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The Current State of Big Data Education
Course Title Offered by
Building a Data Science Team Johns Hopkins via Coursera
Data Analysis and Statistical Inference Duke via Coursera
Mining Massive Data Sets Stanford via Coursera
Course TitleTechniques and Concepts of Big Data
Hadoop Fundamentals
Up and Running with Public Data Sets
William Aiken. (2015). Online Courses on Big Data Analytics. http://sites.psu.edu/bigdata/2015/11/18/online-courses-on-big-data-analytics/ 23 Great Schools with Master’s Programs in Data Science. http://www.mastersindatascience.org/schools/23-great-schools-with-masters-programs-in-data-science/
MS in Business Analytics & Information Management
MS in Analytics
Offline Curricular Online Courses
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The Current State of Big Data Education
Course Title Offered by
Building a Data Science Team Johns Hopkins via Coursera
Data Analysis and Statistical Inference Duke via Coursera
Mining Massive Data Sets Stanford via Coursera
Course TitleTechniques and Concepts of Big Data
Hadoop Fundamentals
Up and Running with Public Data Sets
William Aiken. (2015). Online Courses on Big Data Analytics. http://sites.psu.edu/bigdata/2015/11/18/online-courses-on-big-data-analytics/ 23 Great Schools with Master’s Programs in Data Science. http://www.mastersindatascience.org/schools/23-great-schools-with-masters-programs-in-data-science/
MS in Business Analytics & Information Management
MS in Analytics
Offline Curricular Online Courses
Not much efforts to establish a
systematic curriculum for data science
for iSchools &
evaluate teaching methods.
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Big Data Education for iSchools
• Interdisciplinary institutions addressing broad “information”-related problems
• 65 world-wide institutions
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Big Data Education for iSchools
• Interdisciplinary institutions addressing broad “information”-related problems
• 65 world-wide institutions
iSchool incoming students often are
equipped with modest computational
competencies and math
understanding, compared to the
computer science.
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Big Data Education for iSchools
• Interdisciplinary institutions addressing broad “information”-related problems
• 65 world-wide institutions
iSchool incoming students often are
equipped with modest computational
competencies and math
understanding, compared to the
computer science.
It is challenging to teach the concept of
big data analytics and closely related
technologies to iSchool students.
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NSF-funded Research Project:Building a Big Data Analytics
Workforce in iSchools
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Building a Big Data Analytics Workforce in iSchools• In this project, our team …1) Develop three types of learning
modules to teach big data analytics to undergraduates in iSchools;
2) Develop faculty expertise for teaching the developed materials;
3) Implement the learning modules and evaluate students’ learning.
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ObjectivesMore concretely, we …(1)Develop, assess, and disseminate three
innovative learning modules;(2)Prepare faculty with pedagogical guidelines
and lesson plans;(3)Institutionalize the learning modules and
teaching strategies among a community of 17 iSchool campuses at Penn State & beyond;
(4)Disseminate the developed materials and practices into wider audience.
Big Data Education Project Team (1/3)
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Dr. Jungwoo Ryoo
Associate Professor,IST at Penn State Altoona
PI Co-PIs
Dr. Soo-yong ByunAssociate Professor
Education at Penn State University Park
Dr. Dongwon Lee
Associate ProfessorIST at Penn State University ParkGraduate Project Manager
M.S. Eun-Kyeong KimPh.D. Candidate,
Geography (GIScience) at Penn State University Park
Undergraduate Research Associates
William Aiken
Security and Risk AnalysisPenn State Altoona Penn State University Park
Whitney HernandezVictoria McIntyre
Computer Science
Ryan A. Bury
Geography (GIS)
Nate GouldWilliam Casselberry
Big Data Education Project Team (2/3)
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Advisory Board Members
Alan MacEachren, Ph.D.The Director, The GeoVISTA CenterProfessor, The Dept. of Geographyat Penn State University Park
David Fusco, Ph.D.Lecturer, ISTat Penn State University Park
David Fusco, Ph.D.Professor, ISTat Penn State University Park
Jeongkyu Lee, Ph.D.Associate Professor, The Dept. of CSEat University of Bridgeport
Jongwook Woo, Ph.D.Professor, The Dept. of Computer Information Systemsat California State University, Los Angeles
Marlies Temper, M.A.Senior Researcher, The Dept. of Computer Science and SecurityInstitute of IT Security Research
Simon Tjoa, M.A.FH lecturer & International Coordinator, The Dept. of Computer Science and SecurityInstitute for IT Security Research
William Cantor, Ph.D.Senior Instructor, ISTat Penn State York
Big Data Education Project Team (3/3)
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Collaborating Institutions
Internal Collaborator
Penn State Berks
External CollaboratorGeorge Mason University
iSchool CollaboratorsDrexel UniversityThe University of Pittsburgh
2-yr-college CollaboratorsYTI Career Institute South Hills
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Task 1: Learning Modules• Learning modules used for 2-3 weeks in
one semester• Module 1: Digital Storytelling about
Big Data– Using “storytelling” as an education
tool to building awareness about big data, big data analytics techniques, and big data-related career opportunity
• Module 2: Security Analysis in the Cloud• Module 3: Big Data Mining
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Task 1: Learning Modules• Module 2: Security Analysis in the
Cloud– About how big data analytics can be used to
address challenges in various IT domains (e.g. network security, sensor networks, and human/device-generated signals).
• Module 3: Big Data Mining– About how big data analytics is used to solve
real-life problems in data mining applications (e.g. online dating site, climate change, and infectious disease research using social media).
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Task 2 & 3• Task 2: Implementing Learning
modules and Developing Faculty Expertise
• Task 3: Evaluating Educational Innovations– Using pre-tests and posttests– Control groups (traditional methods)
vs. Target groups (innovative methods)
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Timeline (2015.09 – 2018.08)Year 1
Year 2
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Year 3Timeline (2015.09 – 2018.08)
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Deliverables (1/2) – Big Data E-Textbook
• Co-Authors: Jungwoo Ryoo, Eun-Kyeong Kim
• Authors are not limited to the project team.
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Deliverables (1/2) – Big Data E-Textbook
• Co-Authors: Jungwoo Ryoo, Eun-Kyeong Kim
• Authors are not limited to the project team.
Teaching materials & guidelines for faculty & students
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Deliverables (2/2) –Blog Entries & Publications
• Blog Entries
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Deliverables (2/2) –Blog Entries & Publications
• Blog Entries
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Deliverables (2/2) –Blog Entries & Publications
• Blog Entries
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Call for Participations• Join our research project as a
community member!• http://sites.psu.edu/bigdata/
community/
@[email protected]://sites.psu.edu/BigData
