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ORCID10th EDM 2017: Wuhan, China
- Xiangen Hu, Tiffany Barnes, Arnon Hershkovitz, Luc Paquette:
Proceedings of the 10th International Conference on Educational Data Mining, EDM 2017, Wuhan, Hubei, China, June 25-28, 2017. International Educational Data Mining Society (IEDMS) 2017
Invited Talks
- Jie Tang:
Can AI help MOOCs? - Ronald Cole:
The evolution of virtual tutors, clinician, and companions: A 20-year perspective on conversational agents in real-world applications.
JEDM Track Journal Papers
- Junchen Feng:
Identifiability of the Bayesian Knowledge Tracing Model. - Hassan Khosravi, Kendra M. L. Cooper, Kirsty Kitto:
RiPLE: Recommendation in Peer-Learning Environments Based on Knowledge Gaps and Interests. - Shimin Kai, Ma. Victoria Almeda, Ryan S. Baker, Nicole Shechtman, Cristina Heffernan, Neil T. Heffernan:
Modeling Wheel-spinning and Productive Persistence in Skill Builders. - Chase Geigle, Chengxiang Zhai:
Modeling MOOC Student Behavior With Two-Layer Hidden Markov Models. - Ran Liu, Kenneth R. Koedinger:
Closing the loop: Automated data-driven cognitive model discoveries lead to improved instruction and learning.
Full papers
- Sidney K. D'Mello, Caitlin Mills, Robert Bixler, Nigel Bosch:
Zone out no more: Mitigating mind wandering during computerized reading. - Jirí Rihák, Radek Pelánek:
Measuring Similarity of Educational Items Using Data on Learners' Performance. - Fei Mi, Boi Faltings:
Adaptive Sequential Recommendation for Discussion Forums on MOOCs using Context Trees. - Aaron Bauer, Jeff Flatten, Zoran Popovic:
Analysis of problem-solving behavior in open-ended scientific-discovery game challenges. - Zhongxiu Liu, Christa Cody, Tiffany Barnes, Collin F. Lynch, Teomara Rutherford:
The Antecedents of and Associations with Elective Replay in An Educational Game: Is Replay Worth It? - Zhiyun Ren, Xia Ning, Huzefa Rangwala:
Grade Prediction with Temporal Course-wise Influence. - S. Supraja, Kevin Hartman, Sivanagaraja Tatinati, Andy W. H. Khong:
Toward the Automatic Labeling of Course Questions for Ensuring their Alignment with Learning Outcomes. - Andrew S. Lan, Christopher G. Brinton, Tsung-Yen Yang, Mung Chiang:
Behavior-Based Latent Variable Model for Learner Engagement. - Severin Klingler, Rafael Wampfler, Tanja Käser, Barbara Solenthaler, Markus H. Gross:
Efficient Feature Embeddings for Student Classification with Variational Auto-encoders. - SungJin Nam, Gwen A. Frishkoff, Kevyn Collins-Thompson:
Predicting Short- and Long-Term Vocabulary Learning via Semantic Features of Partial Word Knowledge. - Angela Stewart, Nigel Bosch, Sidney D'Mello:
Generalizability of Face-Based Mind Wandering Detection Across Task Contexts. - Shamya Karumbaiah, Rafael Lizarralde, Danielle Allessio, Beverly P. Woolf, Ivon Arroyo:
Addressing Student Behavior and Affect with Empathy and Growth Mindset. - Zhiqiang Cai, Brendan R. Eagan, Nia Dowell, James W. Pennebaker, Arthur C. Graesser, David W. Shaffer:
Epistemic Network Analysis and Topic Modeling for Chat Data from Collaborative Learning Environment. - Guojing Zhou, Jianxun Wang, Collin F. Lynch, Min Chi:
Towards Closing the Loop: Bridging Machine-induced Pedagogical Policies to Learning Theories. - Sébastien Lallé, Cristina Conati, Roger Azevedo, Michelle Taub, Nicholas Mudrick:
On the Influence on Learning of Student Compliance with Prompts Fostering Self-Regulated Learning. - Andrew Olney, Dariush Bakhtiari, Daphne Greenberg, Arthur C. Graesser:
Assessing Computer Literacy of Adults with Low Literacy Skills. - Ran Liu, Kenneth R. Koedinger:
Towards reliable and valid measurement of individualized student parameters. - Shayan Doroudi, Emma Brunskill:
The Misidentified Identifiability Problem of Bayesian Knowledge Tracing.
Short papers
- Jile Zhu, Xiang Li, Zhuo Wang, Ming Zhang:
An Effective Framework for Automatically Generating and Ranking Topics in MOOC Videos. - Rakesh Agrawal, Sharad Nandanwar, Narasimha Murty Musti:
Grouping Students for Maximizing Learning from Peers. - Andrew Olney, Borhan Samei, Patrick J. Donnelly, Sidney D'Mello:
Assessing the Dialogic Properties of Classroom Discourse: Proportion Models for Imbalanced Classes. - Yuntao Li, Chengzhen Fu, Yan Zhang:
When and who at risk? Call back at these critical points. - Maureen Villamor, Ma. Mercedes T. Rodrigo:
Characterizing Collaboration in the Pair Program Tracing and Debugging Eye-Tracking Experiment: A Preliminary Analysis. - Scott A. Crossley, Tiffany Barnes, Collin F. Lynch, Danielle S. McNamara:
Linking Language to Math Success in a Blended Course. - Joshua Cook, Collin F. Lynch, Andrew Hicks, Behrooz Mostafavi:
Task and Timing: Separating Procedural and Tactical Knowledge in Student Models. - Thomas W. Price, Rui Zhi, Tiffany Barnes:
Evaluation of a Data-driven Feedback Algorithm for Open-ended Programming. - David Lang, Ben Domingue, Alex Kindel, Andreas Paepcke:
Making the Grade: How Learner Engagement Changes After Passing a Course. - Thanaporn Patikorn, Douglas Selent, Neil T. Heffernan, Joseph Beck, Jian Zou:
Using a Single Model Trained across Multiple Experiments to Improve the Detection of Treatment Effects. - Joshua J. Michalenko, Andrew S. Lan, Andrew E. Waters, Phillip Grimaldi, Richard G. Baraniuk:
Data-Mining Textual Responses to Uncover Misconception Patterns. - Haiying Li, Janice D. Gobert, Rachel Dickler:
Automated Assessment for Scientific Explanations in On-line Science Inquiry. - Truong-Sinh An, Christopher Krauss, Agathe Merceron:
Can Typical Behaviors Identified in MOOCs be Discovered in Other Courses? - Stephen Hutt, Jessica Hardey, Robert Bixler, Angela Stewart, Evan F. Risko, Sidney D'Mello:
Gaze-based Detection of Mind Wandering during Lecture Viewing. - Christian Hansen, Casper Hansen, Niklas Hjuler, Stephen Alstrup, Christina Lioma:
Sequence Modelling For Analysing Student Interaction with Educational Systems. - Oluwabukola Mayowa Ishola, Gordon McCalla:
Predicting Prospective Peer Helpers to Provide Just-In-Time Help to Users in Question and Answer Forums. - Renu Balyan, Kathryn S. McCarthy, Danielle S. McNamara:
Combining Machine Learning and Natural Language Processing Approach to Assess Literary Text Comprehension. - Shimin Kai, Juan Miguel L. Andres, Luc Paquette, Ryan S. Baker, Kati Molnar, Harriet Watkins, Michael Moore:
Predicting Student Retention from Behavior in an Online Orientation Course. - Renuka Sindhgatta, Smit Marvaniya, Tejas I. Dhamecha, Bikram Sengupta:
Inferring Frequently Asked Questions from Student Question Answering Forums. - Yingying Bao, Guanliang Chen, Claudia Hauff:
On the Prevalence of Multiple-Account Cheating in Massive Open Online Learning. - Shitian Shen, Min Chi:
Clustering Student Sequential Trajectories Using Dynamic Time Wrapping. - Ziheng Zeng, Snigdha Chaturvedi, Suma Bhat:
Learner Affect Through the Looking Glass: Characterization and Detection of Confusion in Online Courses. - Dipesh Gautam, Zachari Swiecki, David W. Shaffer, Vasile Rus, Arthur C. Graesser:
Modeling Classifiers for Virtual Internships Without Participant Data. - Ange Adrienne Nyamen Tato, Roger Nkambou, Aude Dufresne:
Convolutional Neural Network for Automatic Detection of Sociomoral Reasoning Level. - Jack Z. Wang, Andrew S. Lan, Phillip Grimaldi, Richard G. Baraniuk:
A Latent Factor Model For Instructor Content Preference Analysis. - Linting Xue, Collin F. Lynch, Min Chi:
Mining Innovative Augmented Graph Grammars for Argument Diagrams through Novelty Selection. - Yi Dong, Gautam Biswas:
An Extended Learner Modeling Method to Assess Students' Learning Behaviors. - Siyuan Zhao, Neil T. Heffernan:
Estimating Individual Treatment Effect from Educational Studies with Residual Counterfactual Networks. - Ying Fang, Benjamin Nye, Philip I. Pavlik Jr., Yonghong Xu, Arthur C. Graesser, Xiangen Hu:
Online Learning Persistence and Academic Achievement. - Michael A. Madaio, Rae Lasko, Justine Cassell, Amy Ogan:
Using Temporal Association Rule Mining to Predict Dyadic Rapport in Peer Tutoring. - Lisa Wang, Angela Sy, Larry Liu, Chris Piech:
Learning to Represent Student Knowledge on Programming Exercises Using Deep Learning. - Longwei Zheng, Rui Shi, Xiaoqing Gu, Bingcong Wu, Yuanyuan Feng:
Development of a Trajectory Model for Visualizing Teacher ICT Usage Based on Event Segmentation Data.
Posters
- Jingjing Zhang, Maxim Skryabin:
Modeling Network Dynamics of MOOC Discussion Interactions at Scale. - Juan Miguel L. Andres, Ryan S. Baker, George Siemens, Dragan Gasevic, Catherine A. Spann, Scott A. Crossley:
Studying MOOC Completion at Scale Using the MOOC Replication Framework. - Seth Adjei, Korinn Ostrow, Erik Erickson, Neil T. Heffernan:
Clustering Students in ASSISTments: Exploring System- and School-Level Traits to Advance Personalization. - Alexander Askinadze, Stefan Conrad:
Application of the Dynamic Time Warping Distance for the Student Drop-out Prediction on Time Series Data. - Elizabeth A. McBride, Jonathan M. Vitale, Marcia C. Linn:
Student Use of Scaffolded Inquiry Simulations in Middle School Science. - David D. Pokrajac, Kimberley Sudler, Diana Yankovich, Teresa Hardee:
Modeling Dormitory Occupancy Using Markov Chains. - Yong Han, Wenjun Wu, Xuan Zhou:
Improving Models of Peer Grading in SPOC. - Joshua J. Michalenko, Andrew S. Lan, Richard G. Baraniuk:
Personalized Feedback for Open-Response Mathematical Questions using Long Short-Term Memory Networks. - Lin Ma, Yuchun Ma:
Intelligent Composition of Test Papers based on MOOC Learning Data. - Josh Gardner, Christopher Brooks:
Toward Replicable Predictive Model Evaluation in MOOCs. - Irene-Angelica Chounta, Bruce M. McLaren, Patricia L. Albacete, Pamela W. Jordan, Sandra Katz:
Modeling the Zone of Proximal Development with a Computational Approach. - Won-Joon Hong, Matthew L. Bernacki:
A Prediction and Early Alert Model Using Learning Management System Data and Grounded in Learning Science Theory. - Alvaro Ortiz-Vazquez, Xiang Liu, Ching-Fu Lan, Hui Soo Chae, Gary Natriello:
Cluster Analysis of Real Time Location Data - An Application of Gaussian Mixture Models. - Xiaoting Kuang, Hui Soo Chae, Brian Hughes, Gary Natriello:
A Topic Model and Social Network Analysis of a School Blogging Platform. - Aashna Garg, Andreas Paepcke:
Supporting the Encouragement of Forum Participation. - R. Wes Crues:
Untangling The Program Name Versus The Curriculum: An Investigation of Titles and Curriculum Content. - Kejkaew Thanasuan, Warasinee Chaisangmongkon, Chanikarn Wongviriyawong:
Emerging Patterns in Student's Learning Attributes through Text Mining. - Qi Guo, Maria Cutumisu, Ying Cui:
A Neural Network Approach to Estimate Student Skill Mastery in Cognitive Diagnostic Assessments. - Nicholas Diana, Michael Eagle, John C. Stamper, Shuchi Grover, Marie A. Bienkowski, Satabdi Basu:
Automatic Peer Tutor Matching: Data-Driven Methods to Enable New Opportunities for Help. - Andrew E. Waters, Phillip Grimaldi, Andrew S. Lan, Richard G. Baraniuk:
Short-Answer Responses to STEM Exercises: Measuring Response Validity and Its Impact on Learning. - Genghu Shi, Philip I. Pavlik Jr., Arthur C. Graesser:
Using an Additive Factor Model and Performance Factor Analysis to Assess Learning Gains in a Tutoring System to Help Adults with Reading Difficulties. - Niki Gitinabard, Collin F. Lynch, Sarah Heckman, Tiffany Barnes:
Identifying student communities in blended courses. - Keiji Yasuda, Izuru Nogaito, Hiroyuki Kawashima, Hiroaki Kimura, Masayuki Hashimoto:
Automatic Scoring Method for Descriptive Test Using Recurrent Neural Network. - Beate Grawemeyer, Alex Wollenschlaeger, Sergio Gutiérrez Santos, Wayne Holmes, Manolis Mavrikis, Alexandra Poulovassilis:
Using Graph-based Modelling to explore changes in students' affective states during exploratory learning tasks. - Han Wan, Jun Ding, Xiaopeng Gao, Qiaoye Yu, Kangxu Liu:
Predicting Performance in a Small Private Online Course. - Heeryung Choi, Zijian Wang, Christopher Brooks, Kevyn Collins-Thompson, Beth Glover Reed, Dale Fitch:
Social work in the classroom? A tool to evaluate topical relevance in student writing. - Biao Yin, Anthony F. Botelho, Thanaporn Patikorn, Neil T. Heffernan, Jian Zou:
Causal Forest vs. Naive Causal Forest in Detecting Personalization: An Empirical Study in ASSISTments. - Thanaporn Patikorn, Neil T. Heffernan, Jian Zou:
An Offline Evaluation Method for Individual Treatment Rules and How to Find Heterogeneous Treatment Effect. - Jiao Guo, Xinhua Huang, Boqing Wang:
MyCOS Intelligent Teaching Assistant. - Cristóbal Romero, Pedro G. Espejo, Eva Gibaja, Alfredo Zapata Gonzalez, Víctor H. Menéndez:
Towards Automatic Classification of Learning Objects: Reducing the Number of Used Features. - Andrew Olney, Breya Walker, Raven Davis, Arthur C. Graesser:
The Reading Ability of College Freshmen. - Soo-Yun Han, Jiyoung Yoon, Yun Joo Yoo:
Discovering skill prerequisite structure through Bayesian estimation and nested model comparison. - Junyi Li, Yun Tang, Lijun Sun, Xiangen Hu:
Text analysis with LIWC and Coh-Metrix: Portraying MOOCs Instructors. - Fatima Harrak, François Bouchet, Vanda Luengo:
Identifying relationships between students' questions type and their behavior. - Kathryn S. McCarthy, Amy M. Johnson, Aaron D. Likens, Zachary Martin, Danielle S. McNamara:
Metacognitive Prompt Overdose: Positive and Negative Effects of Prompts in iSTART. - Andrew Olney, Eric Hosman, Arthur C. Graesser, Sidney D'Mello:
Tracking Online Reading of College Students. - Han Wan, Jun Ding, Xiaopeng Gao, David Pritchard:
Dropout Prediction in MOOCs using Learners' Study Habits Features. - Jingxuan Liu, Hongli Li:
Exploring the Relationship Between Student Pre-knowledge and Engagement in MOOC Class Using Polytomous IRT. - Meng Cao, Yun Tang, Xiangen Hu:
An Analysis of Students' Questions in MOOCs Forums.
Tutorials
- Zhenghao Chen, Andy Nguyen, Amory Schlender, Jiquan Ngiam:
Real-time programming exercise feedback in MOOCs. - Xiangen Hu, Robby Robson, Avron Barr:
Why data standards are critical for EDM and AIED. - Adam Sales:
Tutorial: Principal Stratification for EDM Experiments. - Daisuke Yukita:
Whitebox: A Device To Assist Group Work Evaluation. - Yancy Vance M. Paredes, Po-Kai Huang, Sharon I-Han Hsiao:
Understanding Student's Reviewing and Reflection Behaviors Using Web-based Programming Grading Assistant.
Doctoral Consortium
- Ella Albrecht:
A Framework for the Estimation of Students' Programming Abilities. - Elizabeth A. McBride:
Student Use of Inquiry Simulations in Middle School Science. - Yu-Ju Lu, Bor-Chen Kuo, Kai-Chih Pai:
Developing Chinese Automated Essay Scoring Model to Assess College Students' Essay Quality. - Nicholas Diana, John C. Stamper, Kenneth R. Koedinger:
Teaching Informal Logical Fallacy Identification with a Cognitive Tutor. - R. Wes Crues:
Automated Extraction of Results from Full Text Journal Articles. - Linting Xue:
Intelligent Argument Grading System forStudent-produced Argument Diagrams.
Industry Track
- Wenjun Zeng, Si-Chi Chin, Brenda Zeimet, Rui Kuang, Chih-Lin Chi:
Dropout Prediction in Home Care Training. - Amar Lalwani, Sweety Agrawal:
Few hundred parameters outperform few hundred thousand? - Vijay Ekambaram, Ruhi Sharma Mittal, Prasenjit Dey, Ravindranath Kokku, Aditya K. Sinha, Satya V. Nitta:
Tell Me More: Digital Eyes to the Physical World for Early Childhood Learning. - Jun Xie, Shirin Mojarad, Keith T. Shubeck, Alfred Essa, Ryan S. Baker, Xiangen Hu:
Student Learning Strategies to Predict Success in an Online Adaptive Mathematics Tutoring System. - Ilia Rushkin, Yigal Rosen, Andrew M. Ang, Colin Fredericks, Dustin Tingley, Mary Jean Blink, Glenn Lopez:
Adaptive Assessment Experiment in a HarvardX MOOC.
Workshops
- Collin F. Lynch, Tiffany Barnes, Linting Xue, Niki Gitinabard:
Graph-based Educational Data Mining. - Joseph Beck, Min Chi, Ryan S. Baker:
Workshop proposal: deep learning for educational data mining. - Ran Liu, Kenneth R. Koedinger, John C. Stamper, Philip I. Pavlik Jr.:
Sharing and Reusing Data and Analytic Methods with LearnSphere.
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