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ORCID11th EDM 2018: Buffalo, NY, USA
- Kristy Elizabeth Boyer, Michael Yudelson:
Proceedings of the 11th International Conference on Educational Data Mining, EDM 2018, Buffalo, NY, USA, July 15-18, 2018. International Educational Data Mining Society (IEDMS) 2018
Full papers
- Anthony F. Botelho, Ryan S. Baker, Jaclyn Ocumpaugh, Neil T. Heffernan:
Studying Affect Dynamics and Chronometry Using Sensor-Free Detectors. - Jihyun Park, Renzhe Yu, Fernando Rodriguez, Rachel Baker, Padhraic Smyth, Mark Warschauer:
Understanding Student Procrastination via Mixture Models. - Scott A. Crossley, Jaclyn Ocumpaugh, Matthew J. Labrum, Franklin Bradfield, Mihai Dascalu, Ryan S. Baker:
Modeling Math Identity and Math Success through Sentiment Analysis and Linguistic Features. - Shaghayegh Sahebi, Peter Brusilovsky:
Student Performance Prediction by Discovering Inter-Activity Relations. - Ayon Sen, Purav Patel, Martina A. Rau, Blake Mason, Robert Nowak, Timothy T. Rogers, Xiaojin Zhu:
Machine Beats Human at Sequencing Visuals for Perceptual-Fluency Practice. - Ahcène Boubekki, Shailee Jain, Ulf Brefeld:
Mining User Trajectories in Electronic Text Books. - Robert Sawyer, Jonathan P. Rowe, Roger Azevedo, James C. Lester:
Filtered Time Series Analyses of Student Problem-Solving Behaviors in Game-based Learning. - R. Wes Crues, Nigel Bosch, Carolyn J. Anderson, Michelle Perry, Suma Bhat, Najmuddin Shaik:
Who they are and what they want: Understanding the reasons for MOOC enrollment. - David Halpern, Shannon Tubridy, Hong Yu Wang, Camille Gasser, Pamela Osborn Popp, Lila Davachi, Todd M. Gureckis:
Knowledge Tracing Using the Brain. - Weiyu Chen, Carlee Joe-Wong, Christopher G. Brinton, Liang Zheng, Da Cao:
Principles for Assessing Adaptive Online Courses. - Yiqiao Xu, Collin F. Lynch, Tiffany Barnes:
How many friends can you make in a week?: evolving social relationships in MOOCs over time. - Jesus Gerardo Alvarado Mantecon, Hadi Abdi Ghavidel, Amal Zouaq, Jelena Jovanovic, Jenny McDonald:
A Comparison of Features for the Automatic Labeling of Student answers to Open-ended Questions. - Ankita Bihani, Andreas Paepcke:
QuanTyler : Apportioning Credit for Student Forum Participation. - Shivangi Chopra, Lukasz Golab:
Job Description Mining to Understand Work-Integrated Learning. - Weiyu Chen, Andrew S. Lan, Da Cao, Christopher G. Brinton, Mung Chiang:
Behavioral Analysis at Scale: Learning Course Prerequisite Structures from Learner Clickstreams. - Shivangi Chopra, Hannah Gautreau, Abeer Khan, Melicaalsadat Mirsafian, Lukasz Golab:
Gender Differences in Undergraduate Engineering Applicants: A Text Mining Approach. - Zhiqiang Cai, Art Graesser, Leah Windsor, Qinyu Cheng, David W. Shaffer, Xiangen Hu:
Impact of Corpus Size and Dimensionality of LSA Spaces from Wikipedia Articles on AutoTutor Answer Evaluation. - Connor Cook, Andrew Olney, Sean Kelly, Sidney D'Mello:
An Open Vocabulary Approach for Estimating Teacher Use of Authentic Questions in Classroom Discourse. - Harvineet Singh, Shiv Kumar Saini, Ritwick Chaudhry, Pradeep Dogga:
Modeling Hint-Taking Behavior and Knowledge State of Students with Multi-Task Learning. - Stephen Fancsali, Michael Yudelson, Susan R. Berman, Steven Ritter:
Intelligent Instructional Hand Offs. - Bita Akram, Wookhee Min, Eric N. Wiebe, Bradford W. Mott, Kristy Elizabeth Boyer, James C. Lester:
Improving Stealth Assessment in Game-based Learning with LSTM-based Analytics. - Khoi-Nguyen Tran, Jey Han Lau, Danish Contractor, Utkarsh Gupta, Bikram Sengupta, Christopher J. Butler, Mukesh K. Mohania:
Document Chunking and Learning Objective Generation for Instruction Design. - Shamya Karumbaiah, Ryan S. Baker, Valerie J. Shute:
Predicting Quitting in Students Playing a Learning Game.
Short papers
- Paulo F. Carvalho, Min Gao, Benjamin A. Motz, Ken Koedinger:
Analyzing the relative learning benefits of completing required activities and optional readings in online courses. - Ramkumar Rajendran, Anurag Kumar, Kelly E. Carter, Daniel T. Levin, Gautam Biswas:
Predicting Learning by Analyzing Eye-Gaze Data of Reading Behavior. - Jessica Andrews-Todd, Carol Forsyth, Jonathan Steinberg, André Rupp:
Identifying Profiles of Collaborative Problem Solvers in an Online Electronics Environment. - Ben Naismith, Na-Rae Han, Alan Juffs, Brianna Hill, Daniel Zheng:
Accurate Measurement of Lexical Sophistication in ESL with Reference to Learner Data. - Ian Pytlarz, Shi Pu, Monal Patel, Rajini Prabhu:
What can we learn from college students' network transactions? Constructing useful features for student success prediction. - Guillaume Durand, Cyril Goutte, Serge Léger:
Standard error considerations on AFM parameters. - Peng Xu, Michel C. Desmarais:
An Empirical Research on Identifiability and Q-matrix Design for DINA model. - Arkar Min Aung, Anand Ramakrishnan, Jacob Whitehill:
Who are they looking at? Automatic Eye Gaze Following for Classroom Observation Video Analysis. - Huy Nguyen, Chun Wai Liew:
Using Student Logs to Build Bayesian Models of Student Knowledge and Skills. - Zheng Wang, Xinning Zhu, Junfei Huang, Xiang Li, Yang Ji:
Prediction of Academic Achievement Based on Digital Campus. - Gaurav Nanda, Nathan M. Hicks, David R. Waller, Kerrie Anna Douglas, Dan Goldwasser:
Understanding Learners' Opinion about Participation Certificates in Online Courses using Topic Modeling. - Benjamin A. Motz, Thomas A. Busey, Martin E. Rickert, David Landy:
Finding Topics in Enrollment Data. - Shirly Montero, Akshit Arora, Sean Kelly, Brent Milne, Michael Mozer:
Does Deep Knowledge Tracing Model Interactions Among Skills? - Aurora Esteban, Amelia Zafra, Cristóbal Romero:
A Hybrid Multi-Criteria approach using a Genetic Algorithm for Recommending Courses to University Students. - Niki Gitinabard, Farzaneh Khoshnevisan, Collin F. Lynch, Elle Yuan Wang:
Your Actions or Your Associates? Predicting Certification and Dropout in MOOCs with Behavioral and Social Features. - Xin Du, Wouter Duivesteijn, Mykola Pechenizkiy:
ELBA: Exceptional Learning Behavior Analysis. - Seung Yeon Lee, Hui Soo Chae, Gary Natriello:
Identifying User Engagement Patterns in an Online Video Discussion Platform. - Michael Backenköhler, Felix Scherzinger, Adish Singla, Verena Wolf:
Data-Driven Approach Towards a Personalized Curriculum. - Binglin Chen, Matthew West, Craig B. Zilles:
Towards a Model-Free Estimate of the Limits to Student Modeling Accuracy. - Nicholas Hoernle, Ya'akov Gal, Barbara J. Grosz, Pavlos Protopapas, Andee Rubin:
Modeling the Effects of Students' Interactions with Immersive Simulations using Markov Switching Systems. - Adam Winchell, Michael Mozer, Andrew S. Lan, Phillip Grimaldi, Harold Pashler:
Textbook annotations as an early predictor of student learning. - Dipesh Gautam, Nabin Maharjan, Art Graesser, Vasile Rus:
Automated Speech Act Categorization of Chat Utterances in Virtual Internships. - Adithya Sheshadri, Niki Gitinabard, Collin F. Lynch, Tiffany Barnes, Sarah Heckman:
Predicting Student Performance Based on Online Study Habits: A Study of Blended Courses. - Joseph M. Reilly, Milan Ravenell, Bertrand Schneider:
Exploring Collaboration Using Motion Sensors and Multi-Modal Learning Analytics. - Kenneth R. Koedinger, Richard Scheines, Peter Schaldenbrand:
Is the Doer Effect Robust Across Multiple Data Sets? - Ahmad Slim, Don R. Hush, Tushar Ojha, Terry Babbitt:
Predicting Student Enrollment based on Student and College Characteristics. - Michael Eagle, Albert T. Corbett, John C. Stamper, Bruce M. McLaren:
Predicting Individualized Learner Models Across Tutor Lessons. - Zhongzhou Chen, Sunbok Lee, Geoffrey Garrido:
Re-designing the Structure of Online Courses to Empower Educational Data Mining. - Fareedah Alsaad, Assma Boughoula, Chase Geigle, Hari Sundaram, Chengxiang Zhai:
Mining MOOC Lecture Transcripts to Construct Concept Dependency Graphs. - Ruhi Sharma Mittal, Seema Nagar, Mourvi Sharma, Utkarsh Dwivedi, Prasenjit Dey, Ravi Kokku:
Using a Common Sense Knowledge Base to Auto Generate Multi-Dimensional Vocabulary Assessments. - Agoritsa Polyzou, George Karypis:
Feature extraction for classifying students based on their academic performance. - Stephan Lorenzen, Niklas Hjuler, Stephen Alstrup:
Tracking Behavioral Patterns among Students in an Online Educational System. - Ying Fang, Keith T. Shubeck, Anne Lippert, Qinyu Cheng, Genghu Shi, Shi Feng, Jessica Gatewood, Su Chen, Zhiqiang Cai, Philip I. Pavlik, Jan C. Frijters, Daphne Greenberg, Arthur C. Graesser:
Clustering the Learning Patterns of Adults with Low Literacy Skills Interacting with an Intelligent Tutoring System. - Ángel Pérez-Lemonche, Byron Drury, David E. Pritchard:
Mining Student Misconceptions from Pre- and Post-Testing Data. - Adam Sales, Anthony Botelho, Thanaporn Patikorn, Neil T. Heffernan:
Using Big Data to Sharpen Design-Based Inference in A/B Tests. - Yugo Hayashi, Yugo Takeuchi:
The influence of task activity and the learner's personal characteristics on self-confidence during an online explanation activity with a conversational agent. - Cecilia Aguerrebere, Cristobal Cobo, Jacob Whitehill:
Estimating the Treatment Effect of New Device Deployment on Uruguayan Students' Online Learning Activity.
Industry track papers
- Jeffrey Matayoshi, Umberto Granziol, Christopher Doble, Hasan Uzun, Eric Cosyn:
Forgetting curves and testing effect in an adaptive learning and assessment system. - Byung-Hak Kim, Ethan Vizitei, Varun Ganapathi:
GritNet: Student Performance Prediction with Deep Learning. - Deepak Agarwal, Nishant Babel, Ryan S. Baker:
Contextual Derivation of Stable BKT Parameters for Analysing Content Efficacy. - Kumar Abhinav, Venkatesh Subramanian, Alpana Dubey, Padmaraj Bhat, Aditya Divakaruni Venkat:
LeCoRe: A Framework for Modeling Learner's preference. - Rebecca Kantar, Keith McNulty, Erica L. Snow, Matthew A. Emery, Richard Wainess, Sonia Doshi:
Constructing Cognitive Profiles for Simulation-Based Hiring Assessments. - Michael Eagle, Ted Carmichael, Jessica Stokes, Mary Jean Blink, John C. Stamper, Jason Levin:
Predictive Student Modeling for Interventions in Online Classes.
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