The document provides information about the Workshop on Education and Social Science Technologies (WESST 2017) hosted by the School of Computing at the National University of Singapore. WESST aims to develop and network faculty in educational and social science research and technologies. It also introduces ALSET, a new research institute at NUS focused on applying learning science and educational technology. The workshop schedule outlines tutorial sessions on topics ranging from deep learning and sentiment analysis to data-driven design of collaborative learning supports.

1. Welcome to the
Workshop on Education and
Social Science Technologies
(WESST 2017)
&

3. Why WESST?
The School of Computing is hosting two summer
research workshops in 2017.
WESST targets both NUS research and education
track faculty to develop and network with leading
edge pedagogical and social science knowledge.
WESST aims to introduce and highlight ALSET, a
new research institute at NUS allied in such themes.

4. SoC - NUS School of Computing
in Numbers
Faculty Strength:
105
Academic Staff
137
Research Staff
Student Population:
2,330
1,800
Undergraduate Students
530
Graduate Students

5. ALSET - The NUS Institute for
Application of Learning Science
& Educational Technology
We help learners learn.
Research
We conduct original
research on learning
science, technology,
and pedagogy.
Innovation
We promote novel and
entrepreneurial
projects that improve
learning outcomes.
Education
We work to ensure the
latest research and
learning technologies
have broad impact.

6. ALSET - The Challenge
• More research needed on how learners learn
• New technologies, pedagogies, and policies are changing
how students and teachers approach education
• Most research until now happened in the United States and
Europe → understanding of Asian contexts still limited
• Best practices don’t always make it to the classroom
• Proven technologies and pedagogies are often overlooked
• Students, teachers, and administrators lack data about their
effectiveness and how to improve

7. ALSET - Approach
ALSET uses the latest advances in data and
technology to achieve impact.
Data
We manage a “data
lake” for NUS that
includes data on
student behaviors,
performance, and
long-term outcomes.
Technology
Our team includes
experts in machine
learning, data
analytics, learning
science, and education
technology.
Impact
We help translate the
latest advances in
learning science and
technology into
solutions for students
and teachers.

8. ALSET’s Data Lake

9. ALSET’s Data Lake

10. ALSET’s Data Lake

11. ALSET’s Data Lake

12. ALSET’s Data Lake

13. ALSET’s Data Lake

14. ALSET’s Data Lake

15. ALSET’s Data Lake

16. ALSET’s Data Lake

17. ALSET’s Data Lake

18. ALSET’s Data Lake
But what’s
missing from
this picture?

20. WESST Venues - Today
I3 Auditorium (Level 1) I3 (Level 3)

21. Schedule
http://tiny.cc/wesst

22. Schedule
http://tiny.cc/wesst

23. 09:15-11:00 - Tutorials Session 2
LearnSphere and Datashop, by John Stamper, Carnegie
Mellon University, Human-Computer Interaction Institute
(STMI Classroom, I3 03-44).
Basics of Deep Learning, by Animesh Prasad and Muthu
Chandrasekaran NUS, Computer Science
(iCube Auditorium, I3 01-Aud).
http://tiny.cc/wesst

24. 11:30-13:00 - Tutorials Session 2
Leveraging Technology for Collaborative, Dynamic,
Personalized Experimentation, by Joseph Jay Williams,
Information Systems and Analytics
(CHI Classroom, I3 03-40).
Econometrics and Social Science Methods, by Tuan Q. Phan,
NUS, Information Systems and Analytics
(STMI Classroom, I3 03-44).
Sentiment Analysis on Social Media, by Wenqiang Lei, and
Kishaloy Halder, NUS, Computer Science
(iCube Auditorium, I3 01-Aud).
http://tiny.cc/wesst

25. 14:00-15:30 - Tutorials Session 3
From Data to Design of Dynamic Support for Collaborative
Learning, by Carolyn Rosé, Carnegie Mellon University,
Language Technologies Institute and HCI Institute
(STMI Classroom, I3 03-44).
Getting Started on the Computational Social Sciences, by Tuan
Q. Phan, NUS, Information Systems and Analytics
(iCube Auditorium, I3 01-Aud).
Learning Analytics Data Policy and Adoption Strategies
(Teachers to Take Interventions), by Dragan Gašević, University
of Edinburgh, Schools of Education and Informatics
(CHI Classroom, I3 03-40).
http://tiny.cc/wesst

26. 16:00-18:00 Tutorials Session 4
AutoTutor, an Implementation of Conversation-Based
Intelligent Tutoring Systems (ITS), by Xiangen Hu, University
of Memphis, Psychology
(CHI Classroom, 03-40).
2nd EdTech Challenge: Kickoff, Teams finalized by 17:30
(STMI Classroom, I3 03-44).
http://tiny.cc/wesst

27. 16:00-18:00 Tutorials Session 4
AutoTutor, an Implementation of Conversation-Based
Intelligent Tutoring Systems (ITS), by Xiangen Hu, University
of Memphis, Psychology
(CHI Classroom, 03-40).
2nd EdTech Challenge: Kickoff, Teams finalized by 17:30
(STMI Classroom, I3 03-44).
http://tiny.cc/wesst