POSTER PAPERS
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19 |
Sanaz Bahargam, Theodoros Lappas and Evimaria Terzi. The Guided TeamPartitioning Problem: Definition, Complexity, and Algorithm |
20 |
Chun-Kit Yeung. Deep-IRT: Make Deep Learning Based Knowledge Tracing Explainable Using Item Response Theory |
21 |
Christopher Krauss, Agathe Merceron and Stefan Arbanowski. Smart Learning Object Recommendations based on Time-Dependent Learning Need Models |
23 |
Ange Adrienne Nyamen Tato, Roger Nkambou and Aude Dufresne. Combining Deep Neural Network with Expert Knowledge for Predicting Socio-Moral Reasoning skills |
24 |
Anwar Ali Yahya and Addin Osman. A Novel Use of Educational Data Mining to Inform Effective Management of Academic Programs |
38 |
Gaurav Nanda and Kerrie Douglas. Machine Learning Based Decision Support System for Categorizing MOOC Discussion Forum Posts |
40 |
Yiqiao Xu, Niki Gitinabard, Collin Lynch and Tiffany Barnes. What You Say is Relevant to How You Make Friends: Measuring the Effect of Content on Social Connection |
53 |
Oded Vainas, Yossi Ben-David, Ran Gilad-Bachrach, Meitar Ronen, Ori Bar-Ilan, Roi Shillo and Daniel Sitton. STAYING IN THE ZONE: SEQUENCING CONTENT IN CLASSROOMS BASED ON THE ZONE OF PROXIMAL DEVELOPMENT |
54 |
Anthony F. Botelho, Ryan Baker and Neil Heffernan. Machine-Learned or Expert-Engineered Features? Exploring Feature Engineering Methods in Detectors of Disengaged Behavior and Affect |
56 |
Henry Anderson, Afshan Boodhwani and Ryan Baker. Assessing the Fairness of Graduation Predictions |
74 |
Korah Wiley, Allison Bradford, Zach Pardos and Marcia Linn. Beyond Autoscoring: Extracting Conceptual Connections from Essays for Classroom Instruction |
83 |
Anik Jacobsen and Gerasimos Spanakis. It’s a Match! Reciprocal Recommender System forGraduating Students and Jobs |
91 |
Yanjun Pu, Wenjun Wu and Tianrui Jiang. ATC Framework: A fully Automatic Cognitive Tracing Model for Student and Educational Contents |
94 |
Tianqi Wang, Fenglong Ma and Jing Gao. Deep Hierarchical Knowledge Tracing |
97 |
Juanita Hicks, Ruhan Circi and Mengyi Li. Students’ Use of Support Functions in DBAs: Analysis of NAEP Grade 8 Mathematics Process Data |
103 |
Niklas Hjuler, Stephan Lorenzen and Stephen Alstrup. Investigating Writing Style Development in High School |
104 |
Song Ju, Guojing Zhou and Min Chi. Identify Crucial Pedagogical Decisions through Adversarial Deep Reinforcement Learning |
111 |
Shivangi Chopra, Abeer Khan, Melicaalsadat Mirsafian and Lukasz Golab. Gender Differences in Work-Integrated Learning |
117 |
Mariana Oliveira and Carlos Mello. Identifying bias and underlying knowledge structures in Brazilian higher education national exam |
127 |
Rachel Dickler, Haiying Li and Janice Gobert. A Data-Driven Approach for Automated Assessment of Scientific Explanations in Science Inquiry |
129 |
Joseph Reilly and Chris Dede. Stealth Assessment via Deep Learning in an Open-Ended Virtual Environment |
135 |
Fatima Harrak, François Bouchet, Vanda Luengo and Remi Bachelet. Automatic identification of questions in MOOC forums and association with self-regulated learning |
136 |
Lucia Ramirez, William Yao, Edwin Chng, Iulian Radu and Bertrand Schneider. Toward Instrumenting Makerspaces: Using Motion Sensors to Capture Students’ Affective States and Social Interactions in Open-Ended Learning Environments |
147 |
Bruno Emond and Julio J. Valdés. Visualizing Learning Performance Data and Model Predictions as Objects in a 3D Space |
156 |
Tyler Angert and Bertrand Schneider. Augmenting Transcripts with Multimodal Data |
160 |
Lujie Chen, Eva Gjekmarkaj and Artur Dubrawski. Parent as a Companion for Solving Challenging Math Problems: Insights from Multi-modal Observational Data |
162 |
Varun Mandalapu and Jiaqi Gong. Studying Factors Influencing the Prediction of Student STEM and Non-STEM Career Choice |
164 |
Meng Cao, Philip Pavlik and Gavin Bidelman. Incorporating Prior Practice Difficulty into Performance Factor Analysis to Model Mandarin Tone Learning |
167 |
David Boulanger and Vivekanandan Kumar. Shedding Light on the Automated Essay Scoring Process |
169 |
Yupei Zhang, Huan Dai, Yue Yun and Xuequn Shang. Student Knowledge Diagnosis on Response Data via the Model of Sparse Factor Learning |
173 |
Matthew Dong, Run Yu and Zachary Pardos. Design and deployment of a better university course search: Inferring latent keywords from enrollment networks |
176 |
Matthew Guthrie and Zhongzhou Chen. Adding duration-based quality labels to learning events for improved description of students’ online learning behavior |
182 |
Zichao Wang, Andrew Lan, Andrew Waters, Phillip Grimaldi and Richard Baraniuk. A Meta-Learning Approach to Automatic Short Answer Grading |
198 |
Ashvini Varatharaj, Anthony Botelho, Xiwen Lu and Neil Heffernan. Hǎo Fā Yīn: Developing Automated Audio Assessment Tools for a Chinese Language Course |
205 |
Yuta Taniguchi, Atsushi Shimada and Shin’Ichi Konomi. Investigating Error Resolution Processes in C Programming Exercise Courses |
206 |
Glenn Davis, Cindy Wang and Christina Yuan. N-gram Graphs for Topic Extraction in Educational Forums |
208 |
Praseeda, Srinath Srinivasa and Prasad Ram. Validating the Myth of Average through Evidences |
210 |
Rory Flemming, Emmanuel Schmück, Dominic Mussack, Pedro Cardoso-Leite and Paul Schrater. A generalizable performance evaluation model of driving games via risk-weighted trajectories |
213 |
Mizuho Ikeda. Learning Feature Analysis for Quality Improvement of Web-Based Teaching Materials Using Mouse Cursor Tracking |
220 |
Ahmed Zaidi, Andrew Caines, Christopher Davis, Russell Moore, Paula Buttery and Andrew Rice. Accurate modelling of language learning tasks and students using representations of grammatical proficiency |
223 |
J.D Jayaraman. Supporting Minority Student Success by using Machine Learning to Identify At-Risk Students |
245 |
Boniface Mbouzao, Michel Desmarais and Ian Shrier. A Methodology for Student Video Interaction Patterns Analysis and Classification |
252 |
Dominic Mussack, Rory Flemming, Paul Schrater and Pedro Cardoso-Leite. Discovering item similarity through deep learning: combining item features and user behavior. |
262 |
Alexander Askinadze. Predicting Student Drop-Out In Higher Education Based on Previous Exam Results |
263 |
Andrea Davis and Yun Jin Rho. Individual Differences in Student Learning Aid Usage |
264 |
Ben Levy, Arnon Hershkovitz, Odelia Tzayada, Orit Ezra, Avi Segal, Kobi Gal, Anat Cohen and Michal Tabach. Teacher vs. algorithm double-blind experiment of content sequencing in mathematics |
267 |
Jaechoon Jo, Yeongwook Yang, Gyeongmin Kim and Heuiseok Lim. A Comparative Analysis of Emotional Words for Learning Effectiveness in Online Education |
271 |
Varshita Sher. Investigating effects of considering mobile and desktop learning data on predictive power of learning management system (LMS) features on student success |
272 |
Hammad Shaikh, Arghavan Modiri, Joseph Jay Williams and Anna Rafferty. Balancing Student Success and Inferring Personalized Effects in Dynamic Experiments |
277 |
Daniel Furr. Visualization and clustering of learner pathways in an interactive online learning environment |
281 |
Giora Alexandron, Jose Ruiperez Valiente and Dave Pritchard. Towards a General Purpose Anomaly Detection Method to Identify Cheaters in Massive Open Online Courses |
283 |
Vincent Gagnon, Audrey Labrie, Michel Desmarais and Sameer Bhatnagar. Filtering non-relevant short answers in peer learning applications |
284 |
Juan Miguel Andres-Bray, Jaclyn Ocumpaugh and Ryan S. Baker. Hello? Who is posting, who is answering, and who is succeeding in Massive Open Online Courses |
290 |
Nan Jiang and Zach Pardos. Binary Q-matrix Learning with dAFM |