Accepted full papers and works-in-progress (posters and demos) for Learning At Scale 2014. Papers can be found in the ACM Digital Library at http://dl.acm.org/citation.cfm?id=2556325, Proceedings of the first ACM conference on Learning@Scale.

Accepted Full Papers

Session: Student Skills and Behavior

Session: Course Materials

Session: The Role of the Instructor

Session: Assessment

Session: Forums and Chat Rooms

Accepted Works in Progress

Authors were invited to submit two page works in progress to be presented in poster or demonstration format. Below are the accepted work-in-progress submissions, grouped into topics. All but the last group will be presented as posters; the last group will be presented in a demonstration track during the poster session.

MOOC Case Studies

  1. Model Thinking: Demographics and Performance of Students Unable to Afford a Formal Education, Tawanna Dillahunt (University of Michigan, School of Information), Bingxin Chen (University of Michigan, Department of Economics), and Stephanie Teasley (University of Michigan, School of Information)
  2. Corporate learning at scale: Lessons from a large online course at Google, Arthur Asuncion, Jac de Haan, Mehryar Mohri, Kayur Patel, Afshin Rostamizadeh, Umar Syed, and Lauren Wong (Google)
  3. Evaluating Educational Interventions at Scale: A Case Study in Making, Rakesh Agrawal (Microsoft Research), M. Hanif Jhaveri (Stanford University), and Krishnaram Kenthapadi (Microsoft Research)
  4. Distance Learning, OER, and MOOCs: some UK experiences, Eileen Scanlon and Patrick McAndrew (The Open University) and Tim O'Shea (The University of Edinburgh)

MOOC Enrollment and Participation

  1. Due Dates in MOOCs: Does Stricter Mean Better?, Sergiy O Nesterko (HarvardX), Daniel Seaton (MITx), Justin Reich (HarvardX), Joseph McIntyre (Graduate School of Education, Harvard University), Qiuyi Han (Department of Statistics, Harvard University), Isaac Chuang (MITx), and Andrew Ho (Graduate School of Education, Harvard University)
  2. Social Factors that Contribute to Attrition in MOOCs, Carolyn Rose, Ryan Carlson, Diyi Yang, and Miaomiao Wen (Carnegie Mellon University) and Lauren Resnick, Pam Goldman, and Jennifer Sheerer (University of Pittsburgh)
  3. A Behavioral Biometrics based Authentication Method for MOOC's that is Robust against Imitation Attempts, Markus Krause (Leibniz University, Hannover, Germany)
  4. What does enrollment in a MOOC mean?, Eni Mustafaraj (Wellesley College)

Collaborative Learning

  1. Initial Experiences with Small Group Discussions in MOOCs, Seongtaek Lim, Derrick Coetzee, Bjoern Hartmann, Armando Fox, and Marti Hearst (UC Berkeley)
  2. Forming Beneficial Teams of Students in Massive Online Classes, Rakesh Agrawal (Microsoft Research) and Behzad Golshan and Evimaria Terzi (Boston University)
  3. Facilitating MOOCs Learning through Weekly Meet-up: A Case Study in Taiwan, Pin-Ju Chen and Yang-Hsueh Chen (National University of Tainan)
  4. Talkabout: Small group discussions in massive global classes, Julia Cambre, Chinmay Kulkarni, and Michael Bernstein (Stanford University) and Scott Klemmer (Stanford University/UC San Diego)

Instructors and TAs

  1. Community TAs Scale High-Touch Learning, Provide Student-Staff Brokering, and Build Esprit de Corps, Kathryn Papadopoulos and Lalida Sritanyaratana (Stanford University) and Scott R. Klemmer (UC San Diego)
  2. Teacher Usage Behaviors within an Online Open Educational Resource Repository, Jennifer Sabourin, Lucy Kosturko, and Scott McQuiggan (SAS Institute)

Forums

  1. ForumDash: Analyzing Online Discussion Forums, Jacquelin Speck, Eugene Gualtieri, Gaurav Naik, Thach Nguyen, Kevin Cheung, Larry Alexander, and David Fenske (Drexel University)
  2. Improving Online Class Forums by Seeding Discussions and Managing Section Size, Kelly Miller (Harvard University), Sacha Zyto and David Karger (MIT), and Eric Mazur (Harvard University)

Analyzing Student Behavior

  1. Uncovering Hidden Engagement Patterns for Predicting Learner Performance in MOOCs, Arti Ramesh, Dan Goldwasser, Bert Huang, and Hal Daume III (University of Maryland, College Park) and Lise Getoor (University of California, Santa Cruz)
  2. Tracking Progress: Predictors of Students’ Weekly Achievement During a Circuits and Electronics MOOC, Jennifer DeBoer and Lori Breslow (MIT)
  3. Visual Analytics of MOOCs at Maryland, Zhengzheng Xu, Dan Goldwasser, Benjamin B. Bederson, and Jimmy Lin (University of Maryland)

Automated Assessment

  1. Feature Engineering for Clustering Student Solutions, Elena L. Glassman, Rishabh Singh, and Robert C. Miller (MIT CSAIL)
  2. Automatic Coding Composition Evaluator, Stephanie Rogers, Steven Tang, and John Canny (University of California, Berkeley)

Conducting Surveys

  1. Reducing Non-Response Bias with Survey Reweighting: Applications for Online Learning Researchers, René F. Kizilcec (Stanford University)
  2. "Why did you enroll in this course?" Developing a Standardized Survey Question for Reasons to Enroll, Emily Schneider and René F. Kizilcec (Stanford University)

Using Video

  1. Assigning Videos to Textbooks at Appropriate Granularity, Marios Kokkodis (New York University) and Anitha Kannan and Krishnaram Kenthapadi (Microsoft Research)
  2. Open System for Video Learning Analytics, Konstantinos Chorianopoulos (Ionian University), Michail N. Giannakos (Norwegian University of Science and Technology and Old Dominion University), and Nikos Chrisochoides (Old Dominion University)

Advising, Mentoring, and Tutoring

  1. Student Explorer: A Tool for Supporting Academic Advising at Scale, Steven Lonn and Stephanie D. Teasley (University of Michigan)
  2. Modeling Programming Knowledge for Mentoring at Scale, Anvisha H. Pai (MIT CSAIL), Philip J. Guo (University of Rochester), and Robert C. Miller (MIT CSAIL)
  3. Java Tutor: Bootstrapping with Python to Learn Java, Casey O'Brien, Max Goldman, and Robert C. Miller (MIT)
  4. Towards Macro- and Micro-Adaptive Conversational Intelligent Tutoring At Scale, Vasile Rus, Dan Stefanescu, and Arthur Graesser (The University of Memphis)
  5. Improving Problem Solving Performance in Computer-Based Learning Environments through Subgoal Labels, Lauren Margulieux and Richard Catrambone (Georgia Institute of Technology)

Hybrid Courses

  1. Online Learning versus Blended Learning: An Exploratory Study, Andrew Cross, B. Ashok, Srinath Bala, Edward Cutrell, Naren Datha, and Rahul Kumar (Microsoft Research India), Viraj Kumar (PES University), Madhusudan Parthasarathy (University of Illinois at Urbana Champaign), and Siddharth Prakash, Sriram Rajamani, Satish Sangameswaran, Deepika Sharma, and William Thies (Microsoft Research India)
  2. Promoting Active Learning & Leveraging Dashboards for Curriculum Assessment in an OpenEdX Introductory CS Course for Middle School, Shuchi Grover (Stanford Graduate School of Education), Roy Pea (Stanford Graduate School of Education/H-STAR Institute), and Steve Cooper (Computer Science Department, Stanford University)

Adaptive Learning

  1. OCTAL: Online Course Tool for Adaptive Learning, Daniel Armendariz, Zachary MacHardy, and Daniel D. Garcia (University of California, Berkeley)
  2. Adaptive and Social Mechanisms for Automated Improvement of eLearning Materials, Kevin Buffardi and Stephen H. Edwards (Virginia Tech)

Teaching Programming

  1. A Multiplayer Online Game for Teaching Software Engineering Practices, David Xiao and Robert C. Miller (MIT)
  2. Educational Programming Systems for Learning at Scale, QianxiangWang and Wenxin Li (Peking University) and Tao Xie (University of Illinois at Urbana-Champaign)
  3. The Challenges of Using a MOOC to Introduce "Absolute Beginners" to Programming on Specialized Hardware, Jennifer S. Kay (Rowan University Computer Science) and Tom McKlin (SageFox Consulting Group)

Demos

  1. Runestone Interactive: Tools for Creating Interactive Course Materials, David Ranum and Brad Miller (Luther College)
  2. Work-in-Progress: Program Grading and Feedback Generation with Web-CAT, Stephen H. Edwards (Virginia Tech)
  3. Demo: Best Practices for MOOC video, Michael Ball and Dan Garcia (University of California, Berkeley)
  4. A system for sending the right hint at the right time, Matthew Elkherj and Yoav Freund (UCSD)
  5. Code Hunt: Gamifying Teaching and Learning of Computer Science at Scale, Nikolai Tillmann and Jonathan de Halleux (Microsoft Research), Tao Xie (University of Illinois at Urbana-Champaign), and Judith Bishop (Microsoft Research)