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The Workshop on Education and Social Science Technologies (WESST)
July 19-21, 2017 – National University of Singapore

Register for the workshop

As data and analytics technologies transform education and the social sciences, we have an unprecedented opportunity to effect positive change in both these fields. To explore this opportunity, we are pleased to host our inaugural WESST workshop on 19-21 July at the National University of Singapore (NUS).

WESST is co-hosted by the School of Computing (SoC) and the Institute for the Application of Learning Science and Educational Technology (ALSET) at NUS. Over three days, the event will include tutorials and workshops from some of the world’s leading voices in education and social science technology. It will also include a competition for students and researchers with an interest in these technologies.

In addition to highlighting case studies from around the world, we will also showcase how NUS is leading the way in education technology. For example, we will discuss how ALSET is tearing down institutional barriers and assembling one of the most comprehensive educational datasets of its kind, thereby supporting cutting-edge research on the long-term impact of learning interventions.

WESST 2017 builds upon the previous technical programme and expertise of organising the 2015 Workshop Technology for Teaching at Scale, which featured talks on educational technology from leaders in the field.

 

 

Schedule

Click here for registration.

Watch Talks Online: Many talks will be live streamed and recorded, to enable broad participation and provide an archive for later viewing. Click on the Youtube hyperlinks beside a talk to watch it live, or see the recorded talk afterwards.

tiny.cc/wesst is an easy to remember shortcut URL, to return to or share this schedule page.

Directions: Map to School of Computing, and to location of rooms. Wednesday Tutorials are at 21 Heng Mui Keng, in I3. Thursday and Friday Invited Talks are at 15 Computing Drive in Lecture Theatre 19 (LT19). 

Wed 19 July – Tutorials ( I3 )

All events are in I3, Click here for Map. Google Map directions to I3 at 21 Heng Mui KengClick here for  I3 level-03 floor plan.

Go to the URL tiny.cc/wessttutorials to access a Google Doc that will have additional resources, websites, papers to accompany the tutorials.

09:00-09:15     WESST Tutorials Introduction
Introduction to WESST, Preview of the ALSET Data Lake, by Min Yen Kan, Tuan Phan, Joseph Jay Williams (STMI ClassroomI3 03-44).

(Slides)

09:15-11:00    Tutorials Session 1
LearnSphere and Datashop, by John Stamper, Carnegie Mellon University, Human-Computer Interaction Institute (STMI ClassroomI3 03-44).

(Slides)
Basics of Deep Learning, by Animesh Prasad, NUS, Computer Science (iCube AuditoriumI3 01-Aud).
(Slides)

[Youtube live stream & recording]

11:00-11:15    Break (I3 Level 3)

11:15-13:00    Tutorials Session 2
> Leveraging Technology for Collaborative, Dynamic, Personalized Experimentation, by Joseph Jay Williams, Information Systems and Analytics (CHI Classroom, I3 03-40).

Video: https://youtu.be/I-y6S5YrakY

Slides:

Econometrics and Social Science Methods, by Tuan Q. Phan, NUS, Information Systems and Analytics (STMI Classroom, I3 03-44).

(Slides)
Sentiment Analysis on Social Media, by Wenqiang Lei, and Kishaloy Halder, NUS, Computer Science (iCube AuditoriumI3 01-Aud).

(Slides) (Slides2)

13:00-14:00    Lunch (I3 Level 3)

14:00-15:30    Tutorials Session 3
> From Data to Design of Dynamic Support for Collaborative Learningby Carolyn Rosé, Carnegie Mellon University, Language Technologies Institute and HCI Institute (STMI Classroom, I3 03-44).

Slides)
> Getting Started on the Computational Social Sciences, by Tuan Q. Phan, NUS, Information Systems and Analytics (iCube AuditoriumI3 01-Aud).

(Slides)
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).

(Slides)

15:30-16:00    Afternoon Tea (I3 Level 3)
> Visit by Mohan Kankanhalli, Dean of School of Computing (I3 Level 3).

16:00-18:00    Tutorials Session 4 & Ed Tech Challenge
AutoTutor, an Implementation of Conversation-Based Intelligent Tutoring Systems (ITS), by Xiangen Hu, University of Memphis, Psychology (CHI Classroom, 03-40).

(Slides)

2nd EdTech Challenge: Kickoff, Teams finalized by 17:30 (STMI Classroom, I3 03-44).

Thu 20 July – Invited Talks: Analytics & Data in Educational Technology (LT 19)

All talks are in Lecture Theatre LT 19, click here for directions.

All conference participants are invited to add comments and questions on the talks in the Google Doc at the URL tiny.cc/wesstnotes.

09:00-09:30    WESST Opening Session (LT 19)
Introducing ALSET & SoC, Opportunities at NUS for Data and Intervention, Data Dictionary, visit by Computer Science Department Head, Tan Kian Lee.

(Slides)

09:30-10:30    Keynote: Critical Directions for Learning Analytics Research and Practice, by Dragan Gašević, University of Edinburgh, Schools of Education and Informatics.
(Slides) (Slides and Youtube video from Wednesday talk)

10:30-10:50    TEAMMATES: A Flexible Feedback Management System for Education, by Damith Rajapakse, NUS, Computer Science.

(Slides)

10:50-11:10    Break (LT 19 foyer)

11:10-11:35    VisuAlgo: Visualizing Data Structures and Algorithms through Animation, by Steven Halim, NUS, Computer Science.

(Slides)

11:35-12:00    Archipelago: Live Interaction Platform for Large Classes, by Soo Yuen Jien, NUS, Computer Science.

(Slides)

12:00-13:00    Keynote: Continuous Improvement of Educational Technology through Discoveries with Big Data, by John Stamper, Carnegie Mellon University, Human-Computer Interaction Institute.

https://youtu.be/8krFO9TBU_M

(Slides)

13:00-14:00    Lunch (LT 19 foyer)

14:00-14:30    Connecting Instructors with Social Behavioral Scientists and Machine Learning Researchers: Collaborative, Dynamic, Personalized Experimentation in MOOClets, by Joseph Jay Williams, NUS, Information Systems and Analytics, School of Computing.

(Slides)

14:30-15:00    Theatre Performances as Data: Implications for Research and Teaching, by Miguel Escobar, NUS, Theatre Studies & Contemporary Wayang Archive.

(Slides)

15:00-15:30    NUS’ Technology Enhanced Learning Environment, by Ravi Chandran, NUS, Centre for Instructional Technology.

(Slides)

15:30-16:00    Applied Research in Workforce Development, by Jo Fang, Institute for Adult Learning.
(Slides)

16:00-16:30    Afternoon Tea (LT 19 foyer)

16:30-17:30    Social Networks and Causal Inference, by Prasanta Bhattacharya, Institute of High Performance Computing (IHPC), Singapore (LT 19).

(Slides)

17:30-18:00    Closing Summary & Discussion- Day 1 (LT 19)

Fri 21 July – Invited Talks: Collaboration & Interventions to Support Learning (LT 19)

All talks are in LT 19, click here for directions.

All conference participants are invited to add comments and questions on the talks in the Google Doc at the URL tiny.cc/wesstnotes.

09:00-09:10    Second Day Opening

09:10-10:10    Keynote:  Technology Support for Effective Team-Based Learning in Online Education, by Carolyn Rosé, Carnegie Mellon University, Language Technologies Institute and HCI Institute.

https://youtu.be/haxCsxBe6WE

(Slides)

10:10-10:30     Leveraging learning analytics to formatively assess teamworkby Elizabeth Koh, National Institute of Education, Office of Education Research.

(Slides)

10:30-10:50    Dynamically Personalized Interventions, by Bibhas Chakraborty, Duke-NUS.

https://youtu.be/AXY4vSiREZw

(Slides)

11:25-11:45    Break

11:45-12:05    LA Visualisations to Foster Collaborative Critical Reading Skills and Deepen Learning Engagement in English Language: Students’ Perceived Benefits and Problematics, by Jennifer Tan, National Institute of Education, Office of Education Research.

(Slides)

12:05-12:50    Using Discourse Signals for Robust Instructor Intervention Prediction, by Muthu Kumar Chandrasekaran, NUS, Computer Science.

12:50-13:50    Keynote: Conversational Tutors and the Experience API, by Xiangen Hu, University of Memphis, Psychology.

(Slides)

13:50-14:45    Lunch (LT 19 foyer)

14:45-15:05    Automated  Assessment of  Argumentation in Science Classrooms, by Wenli Chen, National Institute of Education, Learning Sciences & Technologies.

15:05-16:35    Panel & Audience Discussion & Closing Remarks: Bringing Research to Bear on Learning at NUS
> Presentation of Key Questions for Panel & Audience to Discuss
> Key Insights & Closing Remarks
> Discussion of Future Directions

16:35-17:00    Afternoon Tea (LT 19 foyer)

News

Critical directions for learning analytics research and practice

Prof. Dragan Gašević will be giving the following invited talk at WESST! Critical directions for learning analytics research and practice The analysis of data collected from user interactions with educational and information technology has attracted much attention as a promising approach for advancing our understanding of the learning process. This promise motivated the emergence of …

Technology Support for Effective Team-Based Learning in Online Education

Prof. Carolyn Rosé will be giving the following invited talk at WESST! Technology Support for Effective Team-Based Learning in Online Education Computational Discourse Analysis is an active area of Learning Analytics that offers real time insights into social processes that impact learning and performance in online courses. This talk reports on research that leverages this …

Contact

Local Organizers:

  • Chris Boesch, NUS Institute of Application of Learning Sciences and Educational Technologies (ALSET)
  • Min-Yen Kan, School of Computing, Department of Computer Science and NUS Institute of Application of Learning Sciences and Educational Technologies (ALSET)
  • Tuan Q Phan, School of Computing, Department of Information Systems
  • Joseph Jay Williams, School of Computing, Department of Information Systems

Contact Min for any inquiries regarding WESST 2017.  Registration is coming soon.

Steering Committee:

  • Robert Kamei, Director, NUS ALSET
  • Kian Lee Tan, Head, Department of Computer Science