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4. L@S 2017: Cambridge, MA, USA
- Claudia Urrea, Justin Reich, Candace Thille:
Proceedings of the Fourth ACM Conference on Learning @ Scale, L@S 2017, Cambridge, MA, USA, April 20-21, 2017. ACM 2017, ISBN 978-1-4503-4450-0
Keynote Address
- Bror Saxberg:
Learning Engineering: The Art of Applying Learning Science at Scale. 1
Engineering Learning Environments
- Shayan Doroudi
, Vincent Aleven, Emma Brunskill:
Robust Evaluation Matrix: Towards a More Principled Offline Exploration of Instructional Policies. 3-12 - Lauren Fratamico, Sarah Perez, Ido Roll
A Visual Approach towards Knowledge Engineering and Understanding How Students Learn in Complex Environments. 13-22 - Zachary A. Pardos, Steven Tang, Daniel Davis, Christopher Vu Le:
Enabling Real-Time Adaptivity in MOOCs with a Personalized Next-Step Recommendation Framework. 23-32
Learn to Code
- Sayamindu Dasgupta
Learning to Code in Localized Programming Languages. 33-39 - Eliane Stampfer Wiese, Michael Yen, Antares Chen
Teaching Students to Recognize and Implement Good Coding Style. 41-50
Predicting and Explaining Learning
- Steven Dang, Michael Yudelson, Kenneth R. Koedinger:
Detecting Diligence with Online Behaviors on Intelligent Tutoring Systems. 51-59 - Petr Johanes:
Epistemic Cognition: A Promising and Necessary Construct for Enriching Large-scale Online Learning Analysis. 61-69
Feedback for Improving Learning
- David A. Joyner:
Scaling Expert Feedback: Two Case Studies. 71-80 - Arjun Singh, Sergey Karayev, Kevin Gutowski, Pieter Abbeel:
Gradescope: A Fast, Flexible, and Fair System for Scalable Assessment of Handwritten Work. 81-88 - Andrew Head
Writing Reusable Code Feedback at Scale with Mixed-Initiative Program Synthesis. 89-98
Plenary Panel
- Mitchel Resnick, Karen Brennan, Cristóbal Cobo
Creative Learning @ Scale. 99-100
Integrity of Courses and Learners
- Juho Leinonen
Preventing Keystroke Based Identification in Open Data Sets. 101-109 - Binglin Chen, Matthew West
Do Performance Trends Suggest Wide-spread Collaborative Cheating on Asynchronous Exams? 111-120
Experimentation
- René F. Kizilcec, Glenn M. Davis, Geoffrey L. Cohen:
Towards Equal Opportunities in MOOCs: Affirmation Reduces Gender & Social-Class Achievement Gaps in China. 121-130 - Frans van der Sluis, Tim Van der Zee
Learning about Learning at Scale: Methodological Challenges and Recommendations. 131-140
Demonstrations
- Alexander Kindel, Michael Yeomans, Justin Reich, Brandon M. Stewart, Dustin Tingley:
Discourse: MOOC Discussion Forum Analysis at Scale. 141-142 - Louis Faucon, Stian Håklev
Demo of Orchestration Graph Engine: Enabling Rich Social Pedagogical Scenarios in MOOCs. 143-144 - Rocael Hernández Rizzardini, Hector R. Amado-Salvatierra
Full Engagement Educational Framework: A Practical Experience for a MicroMaster. 145-146 - Rémi Sharrock
CODECAST: An Innovative Technology to Facilitate Teaching and Learning Computer Programming in a C Language Online Course. 147-148
Work in Progress
- Ralf Teusner
Taking Informed Action on Student Activity in MOOCs. 149-152 - Qian Zhao, Sashank Varma, Joseph A. Konstan
In-Video Reuse of Discussion Threads in MOOCs. 153-156 - Jacob Whitehill, Margo I. Seltzer:
A Crowdsourcing Approach to Collecting Tutorial Videos - Toward Personalized Learning-at-Scale. 157-160 - Jacob Whitehill, Kiran Mohan, Daniel T. Seaton, Yigal Rosen, Dustin Tingley:
MOOC Dropout Prediction: How to Measure Accuracy? 161-164 - Thomas Staubitz
Collaboration and Teamwork on a MOOC Platform: A Toolset. 165-168 - Liang Zhang, Xiaolu Xiong, Siyuan Zhao, Anthony Botelho, Neil T. Heffernan:
Incorporating Rich Features into Deep Knowledge Tracing. 169-172 - Nickolas J. G. Falkner, Claudia Szabo, Katrina Falkner
Formal Forum Triage: Towards the Strategic Selection of Responses to Student Discussion Forums. 173-176 - Jeff Offutt, Paul Ammann, Kinga Dobolyi, Chris Kauffmann, Jaime Lester, Upsorn Praphamontripong, Huzefa Rangwala, Sanjeev Setia, Pearl Y. Wang, Liz White:
A Novel Self-Paced Model for Teaching Programming. 177-180 - Glenn Lopez, Daniel T. Seaton, Andrew M. Ang, Dustin Tingley, Isaac L. Chuang:
Google BigQuery for Education: Framework for Parsing and Analyzing edX MOOC Data. 181-184 - Judith Uchidiuno, Jessica Hammer, Evelyn Yarzebinski
Characterizing ELL Students' Behavior During MOOC Videos Using Content Type. 185-188 - Siyuan Zhao, Yaqiong Zhang, Xiaolu Xiong, Anthony Botelho, Neil T. Heffernan:
A Memory-Augmented Neural Model for Automated Grading. 189-192 - Hao Wan, Joseph E. Beck:
One Decision Tree is Enough to Make Customization. 193-196 - Sunbok Lee, Zhongzhou Chen, David E. Pritchard, Alex Kimn, Andrew Paul:
Factor Analysis Reveals Student Thinking using the Mechanics Reasoning Inventory. 197-200 - Lisa Wang, Angela Sy, Larry Liu, Chris Piech:
Deep Knowledge Tracing On Programming Exercises. 201-204 - Chase Geigle, ChengXiang Zhai:
Modeling MOOC Student Behavior With Two-Layer Hidden Markov Models. 205-208 - Selen Türkay
Getting to Know English Language Learners in MOOCs: Their Motivations, Behaviors, and Outcomes. 209-212 - Jill Burstein, Nitin Madnani, John Sabatini
Generating Language Activities in Real-Time for English Learners using Language Muse. 213-215 - Yi Cui, Wan Qi Jin, Alyssa Friend Wise:
Humans and Machines Together: Improving Characterization of Large Scale Online Discussions through Dynamic Interrelated Post and Thread Categorization (DIPTiC). 217-219 - Alireza Farasat, Alexander G. Nikolaev, Suzanne Miller
CROWDLEARNING: Towards Collaborative Problem-Posing at Scale. 221-224 - Francisco Iniesto
What are the Expectations of Disabled Learners when Participating in a MOOC? 225-228 - Vijaya Dommeti, Douglas Selent:
Applying and Exploring Bayesian Hypothesis Testing for Large Scale Experimentation in Online Tutoring Systems. 229-232 - Yigal Rosen, Ilia Rushkin, Andrew M. Ang, Colin Fredericks, Dustin Tingley, Mary Jean Blink:
Designing Adaptive Assessments in MOOCs. 233-236 - Zahid Hossain, Engin Bumbacher, Paulo Blikstein, Ingmar H. Riedel-Kruse
Authentic Science Inquiry Learning at Scale Enabled by an Interactive Biology Cloud Experimentation Lab. 237-240 - Monika Gupta, Neelamadhav Gantayat, Renuka Sindhgatta
Intelligent Math Tutor: Problem-Based Approach to Create Cognizance. 241-244 - Joshua J. Michalenko, Andrew S. Lan, Richard G. Baraniuk:
D.TRUMP: Data-mining Textual Responses to Uncover Misconception Patterns. 245-248 - An Ju, Elena L. Glassman, Armando Fox:
Teamscope: Scalable Team Evaluation via Automated Metric Mining for Communication, Organization, Execution, and Evolution. 249-252 - Hao Fei Cheng, Bowen Yu, Yeong Hoon Park, Haiyi Zhu:
ProjectLens: Supporting Project-based Collaborative Learning on MOOCs. 253-256 - Ke Wang, Benjamin Lin, Bjorn Rettig, Paul Pardi, Rishabh Singh:
Data-Driven Feedback Generator for Online Programing Courses. 257-260 - Stian Håklev, Louis Faucon, Thanasis Hadzilacos, Pierre Dillenbourg:
Orchestration Graphs: Enabling Rich Social Pedagogical Scenarios in MOOCs. 261-264 - Robert A. Sottilare, Rodney A. Long, Benjamin S. Goldberg:
Enhancing the Experience Application Program Interface (xAPI) to Improve Domain Competency Modeling for Adaptive Instruction. 265-268 - Josh Gardner, Christopher Brooks:
A Statistical Framework for Predictive Model Evaluation in MOOCs. 269-272 - Lilach Gal, Arnon Hershkovitz
Suggesting a Log-Based Creativity Measurement for Online Programming Learning Environment. 273-277 - Yasmine Kotturi, Andrew Du, Scott R. Klemmer, Chinmay Kulkarni:
Long-Term Peer Reviewing Effort is Anti-Reciprocal. 279-282 - Nia M. Dowell, Christopher A. Brooks, Vitomir Kovanovic
The Changing Patterns of MOOC Discourse. 283-286 - Joseph Jay Williams, Anna N. Rafferty
MOOClets: A Framework for Dynamic Experimentation and Personalization. 287-290 - Sera Thornton
Criteria for Video Engagement in a Biology MOOC. 291-294 - Stacey L. Houston II, Katherine A. Brady, Gayathri Narasimham, Douglas H. Fisher:
Pass the Idea Please: The Relationship between Network Position, Direct Engagement, and Course Performance in MOOCs. 295-298 - Biao Yin, Thanaporn Patikorn
Observing Personalizations in Learning: Identifying Heterogeneous Treatment Effects Using Causal Trees. 299-302 - Assma Boughoula, Chase Geigle, ChengXiang Zhai:
A Probabilistic Approach for Discovering Difficult Course Topics Using Clickstream Data. 303-306 - David A. Joyner:
Congruency, Adaptivity, Modularity, and Personalization: Four Experiments in Teaching Introduction to Computing. 307-310 - Rajan Vaish, Sharad Goel, Amin Saberi:
Mobilizing the Crowd to Create an Open Repository of Research Talks. 311-314 - Dilrukshi Gamage
Improving Assessment on MOOCs Through Peer Identification and Aligned Incentives. 315-318 - Amy X. Zhang, Michele Igo, Marc T. Facciotti, David R. Karger
Using Student Annotated Hashtags and Emojis to Collect Nuanced Affective States. 319-322 - Jill-Jênn Vie
A Heuristic Method for Large-Scale Cognitive-Diagnostic Computerized Adaptive Testing. 323-326 - Curtis G. Northcutt, Kimberly A. Leon, Naichun Chen:
Comment Ranking Diversification in Forum Discussions. 327-330 - Wissam Halimi, Christophe Salzmann, Denis Gillet:
Access to Massive Open Online Labs through a MOOC. 331-334 - Xiwen Lu
Experimenting Choices of Video and Text Feedback in Authentic Foreign Language Assignments at Scale. 335-338
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