Presentation slides

Here is the list of all slides collected from Learning@Scale presenters. If you presented at learnig@scale and want to have your slides listed here, send an email to v.kovanovic@ed.ac.uk.

Keynotes

  1. The Future of Learning by Professor Sugata Mitra, Newcastle University
  2. Effective Pedagogy at Scale: Social Learning and Citizen Inquiry by Professor Mike Sharples, The Open University
  3. Practical Learning Research at Scale by Professor Ken Koedinger, Carnegie Mellon University, USA.

Presentations

Monday

  1. 1A: The Civic Mission of MOOCs: Measuring Engagement across Political Differences in Forums by Justin Reich, Brandon Stewart, Kimia Mavon, Dustin Tingley
  2. 1C: Online Urbanism: Interest-based Subcultures as Drivers of Informal Learning in an Online Community by Ben U Gelman, Chris Beckley, Aditya Johri, Carlotta Domeniconi, Seungwon Yang
  3. 2A: Effects of In-Video Quizzes on MOOC Lecture Viewing by Geza Kovacs
  4. 2B: Brain Points: A Deeper Look at a Growth Mindset Incentive Structure for an Educational Game by Eleanor O'Rourke, Erin Peach, Carol S. Dweck, Zoran Popovic
  5. 2C: Explaining Student Behavior at Scale The Influence of Video Complexity on Student Dwelling Time by Frans Van der Sluis, Jasper Ginn, Tim Van der Zee
  6. 3A: Using Multiple Accounts for Harvesting Solutions in MOOCs by Jose A. Ruiperez-Valiente, Giora Alexandron, Zhongzhou Chen, David E. Pritchard
  7. 3B: How Mastery Learning Works at Scale by Steve Ritter, Michael Yudelson, Stephen E Fancsali, Susan R Berman

Tuesday

  1. 4A: A Data-Driven Approach for Inferring Student Proficiency from Game Activity Logs by Mohammad H. Falakmasir, Jose P. Gonzalez-Brenes, Geoffrey J. Gordon, Kristen E. DiCerbo
  2. 4B: An Exploration of Automated Grading of Complex Assignments by Chase Geigle, ChengXiang Zhai, Duncan C. Ferguson
  3. 4C: Fuzz Testing Projects in Massive Courses by Sumukh Sridhara, Brian Hou, Jeffrey Lu, John DeNero
  4. 4D: Peer Grading in a Course on Algorithms and Data Structures: Machine Learning Algorithms do not Improve over Simple Baselines by Mehdi S. M. Sajjadi, Morteza Alamgir, Ulrike von Luxburg
  5. 5A: AXIS: Generating Explanations at Scale with Learnersourcing and Machine Learning by Joseph Jay Williams, Juho Kim, Anna Rafferty, Samuel Maldonado, Krzysztof Z. Gajos, Walter S. Lasecki, Neil Heffernan
  6. 5B: Improving the Peer Assessment Experience on MOOC Platforms by Thomas Staubitz, Dominic Petrick, Matthias Bauer, Jan Renz, Christoph Meinel
  7. 6A: Learning Transfer: Does It Take Place in MOOCs? An Investigation into the Uptake of Functional Programming in Practice by Guanliang Chen, Dan Davis, Claudia Hauff, Geert-Jan Houben