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13th EDM 2020 [virtual]
- Anna N. Rafferty, Jacob Whitehill, Cristóbal Romero, Violetta Cavalli-Sforza:
Proceedings of the 13th International Conference on Educational Data Mining, EDM 2020, Fully virtual conference, July 10-13, 2020. International Educational Data Mining Society 2020, ISBN 978-1-7336736-1-7
Full Papers
- Nil-Jana Akpinar, Aaditya Ramdas, Umut A. Acar:
Analyzing Student Strategies In Blended Courses Using Clickstream Data. - Fareedah Alsaad, Abdussalam Alawini:
Unsupervised Approach for Modeling Content Structures of MOOCs. - Lovenoor S. Aulck, Dev Nambi, Jevin West:
Increasing Enrollment by Optimizing Scholarship Allocations Using Machine Learning and Genetic Algorithms. - Nigel Bosch, R. Wes Crues, Najmuddin Shaik, Luc Paquette:
"Hello, [REDACTED]": Protecting Student Privacy in Analyses of Online Discussion Forums. - Sahan Bulathwela, María Pérez-Ortiz, Aldo Lipani, Emine Yilmaz, John Shawe-Taylor:
Predicting Engagement in Video Lectures. - Steven Dang, Kenneth R. Koedinger:
The Ebb and Flow of Student Engagement: Measuring motivation through temporal pattern of self-regulation. - Oriane Dermy, Armelle Brun:
Can we Take Advantage of Time-Interval Pattern Mining to Model Students Activity? - Samuel C. Fonseca, Filipe Dwan Pereira, Elaine H. T. Oliveira, David Fernandes, Leandro S. G. Carvalho, Alexandra I. Cristea:
Automatic Subject-based Contextualisation of Programming Assignment Lists. - Nathan L. Henderson, Vikram Kumara, Wookhee Min, Bradford W. Mott, Ziwei Wu, Danielle Boulden, Trudi Lord, Frieda Reichsman, Chad Dorsey, Eric N. Wiebe, James C. Lester:
Enhancing Student Competency Models for Game-Based Learning with a Hybrid Stealth Assessment Framework. - Paul Hur, Nigel Bosch, Luc Paquette, Emma Mercier:
Harbingers of Collaboration? The Role of Early-Class Behaviors in Predicting Collaborative Problem Solving. - Weijie Jiang, Zachary A. Pardos:
Evaluating sources of course information and models of representation on a variety of institutional prediction tasks. - Song Ju, Min Chi, Guojing Zhou:
Pick the Moment: Identifying Critical Pedagogical Decisions Using Long-Short Term Rewards. - Hang Li, Wenbiao Ding, Songfan Yang, Zitao Liu:
Identifying At-Risk K-12 Students in Multimodal Online Environments: A Machine Learning Approach. - Tiffany Wenting Li, Luc Paquette:
Erroneous Answers Categorization for Sketching Questions in Spatial Visualization Training. - Zhaobin Li, Luna Yee, Nathaniel Sauerberg, Irene Sakson, Joseph Jay Williams
, Anna N. Rafferty:
Getting too personal(ized): The importance of feature choice in online adaptive algorithms. - Ye Mao, Samiha Marwan, Thomas W. Price, Tiffany Barnes, Min Chi:
What Time is It? Student Modeling Needs to Know. - Tong Mu, Andrea Jetten, Emma Brunskill:
Towards Suggesting Actionable Interventions for Wheel Spinning Students. - Quan Nguyen, Oleksandra Poquet, Christopher Brooks, Warren Li:
Exploring homophily in demographics and academic performance using spatial-temporal student networks. - Adam Sales, John Pane:
The effect of teachers reassigning students to new Cognitive Tutor sections. - Debopam Sanyal, Nigel Bosch, Luc Paquette:
Feature Selection Metrics: Similarities, Differences, and Characteristics of the Selected Models. - Machi Shimmei, Noboru Matsuda:
Learning a Policy Primes Quality Control: Towards Evidence-Based Automation of Learning Engineering. - Khushboo Thaker, Lei Zhang, Daqing He, Peter Brusilovsky:
Recommending Remedial Readings Using Student's Knowledge state. - Rafael Wampfler, Andreas Emch, Barbara Solenthaler, Markus Gross:
Image Reconstruction of Tablet Front Camera Recordings in Educational Settings. - Mike Wu, Richard Lee Davis, Benjamin W. Domingue, Chris Piech, Noah D. Goodman:
Variational Item Response Theory: Fast, Accurate, and Expressive. - Xi Yang, Guojing Zhou, Michelle Taub, Roger Azevedo, Min Chi:
Student Subtyping via EM-Inverse Reinforcement Learning. - Mengfan Yao, Shaghayegh Sahebi, Reza Feyzi-Behnagh:
Analyzing Student Procrastination in MOOCs: A Multivariate Hawkes Approach. - Renzhe Yu, Qiujie Li, Christian Fischer, Shayan Doroudi, Di Xu:
Towards Accurate and Fair Prediction of College Success: Evaluating Different Sources of Student Data. - Fabian Zehner, Scott Harrison, Beate Eichmann, Tobias Deribo, Daniel Bengs, Nico Andersen, Carolin Hahnel
The NAEP EDM Competition: Theory-Driven Psychometrics and Machine Learning for Predictions Based on Log Data. - Siqian Zhao, Chunpai Wang, Shaghayegh Sahebi:
Modeling Knowledge Acquisition from Multiple Learning Resource Types. - Yijun Zhao, Qiangwen Xu, Ming Chen, Gary Weiss:
Predicting Student Performance in a Master's Program in Data Science using Admissions Data.
Short Papers
- Zhila Aghajari, Deniz Sonmez Unal, Mesut Erhan Unal, Ligia Gómez, Erin Walker:
Decomposition of Response Time to Give Better Predictions of Children's Reading Comprehension. - Noah Arthurs, A. J. Alvero:
Whose Truth is the "Ground Truth"? College Admissions Essays and Bias in Word Vector Evaluation Methods. - Sameer Bhatnagar, Michel C. Desmarais, Amal Zouaq, Elizabeth S. Charles:
A Dataset of Learnersourced Explanations from an Online Peer Instruction Environment. - Faeze Brahman, Nikhil Varghese, Suma Bhat, Snigdha Chaturvedi:
Effective Forum Curation via Multi-task Learning. - Zhaorui Chen, Carrie Demmans Epp:
CSCLRec: Personalized Recommendation of Forum Posts to Support Socio-collaborative Learning. - Benjamin Clavié, Kobi Gal:
Deep Embeddings of Contextual Assessment Data for Improving Performance Prediction. - Theodora Danciulescu, Stella Heras, Javier Palanca, Vicente Julián, Cristian Mihaescu:
More Data and Better Keywords Imply Better Educational Transcript Classification? - Aleksandr Efremov, Ahana Ghosh, Adish Singla:
Zero-shot Learning of Hint Policy via Reinforcement Learning and Program Synthesis. - Effat Farhana, Teomara Rutherford, Collin F. Lynch:
Investigating Relations between Self-Regulated Reading Behaviors and Science Question Difficulty. - Carol Forsyth, Jessica Andrews-Todd, Jonathan Steinberg:
Are You Really a Team Player?: Profiles of collaborative problem solvers in an online environment. - Niki Gitinabard, Ruth Okoilu, Yiqiao Xu, Sarah Heckman, Tiffany Barnes, Collin F. Lynch:
Student Teamwork on Programming Projects. What can GitHub logs show us? - Tao Gong, Lan Shuai, Burcu Arslan, Yang Jiang:
Using Process Data to Evaluate Scientific Inquiry Practice in Technology-Enhanced Assessment. - Cyril Goutte, Guillaume Durand:
Confident Learning Curves in Additive Factor Modeling. - Qian Hu, Huzefa Rangwala:
Towards Fair Educational Data Mining: A Case Study on Detecting At-risk Students. - Noah Hunt-Isaak, Peter Cherniavsky, Mark Snyder, Huzefa Rangwala:
Using online text books and in-class quizzes to predict in class performance. - Hamid Karimi, Tyler Derr, Jiangtao Huang, Jiliang Tang:
Online Academic Course Performance Prediction using Relational Graph Convolutional Neural Network. - Mark Klose, Vasvi Desai, Yang Song, Edward F. Gehringer:
EDM and Privacy: Ethics and Legalities of Data Collection, Usage, and Storage. - Boxuan Ma, Yuta Taniguchi, Shin'ichi Konomi:
Course Recommendation for University Environment. - Boniface Mbouzao, Michel C. Desmarais, Ian Shrier:
Methodology to measure of similarity in student video sequence of interactions. - Dezhuang Miao, Yu Dong, Xuesong Lu:
PIPE: Predicting Logical Programming Errors in Programming Exercises. - Leonardo Moreno, Matías Núñez, Cecilia Emery, Inés Méndez, Elisa Borba, Eliana Lucián:
Incidence of teacher curricular emphasis in reading achievement of Uruguayan ninth-grade students. - Huy Anh Nguyen, Xinying Hou, John C. Stamper, Bruce M. McLaren:
Moving beyond Test Scores: Analyzing the Effectiveness of a Digital Learning Game through Learning Analytics. - Chris Piech, Engin Bumbacher, Richard Lee Davis:
Measuring Ability-to-Learn Using Parametric Learning Gain Functions. - Stefan Slater, Ryan Baker, Yeyu Wang:
Iterative Feature Engineering Through Text Replays of Model Error. - Zachary Warnes, Magnus Kinder, Evgueni N. Smirnov:
Course Recommender Systems with Statistical Confidence. - Yunkai Xiao, Gabriel Zingle, Qinjin Jia, Shoaib Akbar, Song Yang, Muyao Dong, Li Qi, Edward F. Gehringer:
Problem detection in peer assessments between subjects by effective transfer learning and active learning. - Liangbei Xu, Mark A. Davenport:
Dynamic Knowledge Embedding and Tracing. - Linting Xue, Collin F. Lynch:
Incorporating Task-specific Features into Deep Models to Classify Argument Components. - Yijun Zhao, Bryan Lackaye, Jennifer G. Dy, Carla E. Brodley:
A Quantitative Machine Learning Approach to Master Students Admission for Professional Institutions.
Poster Papers
- Paulo J. L. Adeodato, Rogerio Luiz C. S. Filho:
Where to aim? Factors that influence the performance of Brazilian secondary schools. - Lalitha Agnihotri, Ryan Baker, Steve Stalzer:
A Procrastination Index for Online Learning Based on Assignment Start Time. - Bita Akram, Hamoon Azizsoltani, Wookhee Min, Eric N. Wiebe, Bradford W. Mott, Anam Navied, Kristy Elizabeth Boyer, James C. Lester:
Automated Assessment of Computer Science Competencies from Student Programs with Gaussian Process Regression. - Farook Al-Shamali, Hongxin Yan, Sabine Graf, Fuhua Lin:
Educational Data Mining and Personalized Support in Online Introductory Physics Courses. - Moriah Ariely, Tanya Nazaretsky, Giora Alexandron:
First Steps Towards NLP-based Formative Feedback to Improve Scientific Writing in Hebrew. - Mehmet Cem Aytekin, Stefan Räbiger, Yücel Saygin:
Discovering the Prerequisite Relationships Among Instructional Videos From Subtitles. - Francisco Cervera, Juan Alfonso Lara
A method for generating features representing the students' degree of anticipation/delay to complete assignments. - Wilson Chango, Miguel Sánchez-Santillán, Rebeca Cerezo, Cristóbal Romero:
Predicting students' performance using emotion detection from face-recording video when interacting with an ITS. - Clarence Chen, Zachary A. Pardos:
Applying Recent Innovations from NLP to MOOC Student Course Trajectory Modeling. - Maximillian Chen, René F. Kizilcec:
Return of the Student: Predicting Re-Engagement in Mobile Learning. - Christa Cody, Mehak Maniktala, David Warren, Min Chi, Tiffany Barnes:
Does autonomy help Help? The impact of unsolicited hints and choice on help avoidance and learning. - Ibtissem Daoudi, Erwan Tranvouez, Raoudha Chebil, Bernard Espinasse, Wided Lejouad Chaari:
An EDM-based Multimodal Method for Assessing Learners' Affective States in Collaborative Crisis Management Serious Games. - Philipp Dumbach, Alexander Aly, Markus Zrenner, Björn M. Eskofier:
Exploration of Process Mining Opportunities In Educational Software Engineering - The GitLab Analyser. - Edward F. Gehringer, Xiaohan Liu, Abhirav Kariya, Guoyi Wang:
Comparing and combining tests for plagiarism detection in online exams. - Aleksandr Gromov, Andrei Maslennikov, Nikolas Dawson, Katarzyna Musial, Kirsty Kitto:
Curriculum profile: modelling the gaps between curriculum and the job market. - Tianyu Hu, Guangzhong Sun, Zhongtian Xu:
Assessing Student Contributions in Wiki-based Collaborative Writing System. - Tao Huang, Zhi Li, Hao Zhang, Huali Yang, Hekun Xie:
EAnalyst: Toward Understanding Large-scale Educational Data. - Rachel Jansen, Ruthe Foushee:
How we talk about math: Leveraging naturalistic datasets to define the discourse of math in contrast to other domains. - J. D. Jayaraman:
Predicting Student Dropout by Mining Advisor Notes. - Hyunbin Loh, Piljae Chae, Chanyou Hwang:
Data Efficient Educational Assessment via Multi-Dimensional Pairwise Comparisons. - Salil Maharjan, Amruth Kumar:
Using Edit Distance Trails to Analyze Path Solutions of Parsons Puzzles. - Jessica McBroom, Irena Koprinska, Kalina Yacef:
How Does Student Behaviour Change Approaching Dropout? A Study of Gender and School Year Differences. - Maciej Pankiewicz:
Measuring task difficulty for online learning environments where multiple attempts are allowed - the Elo rating algorithm approach. - Mohammad S. Parsa, Lukasz Golab:
Social Media Mining to Understand the Impact of Co-operative Education on Mental Health. - Thomas Sergent, François Bouchet, Thibault Carron:
Towards Temporality-Sensitive Recurrent Neural Networks through Enriched Traces. - Lauren Singelmann, Enrique Alvarez Vazquez, Ellen Swartz, Ryan Striker, Mary Pearson, Dan Ewert:
Predicting and Understanding Success in an Innovation-Based Learning Course. - Lavendini Sivaneasharajah, Katrina Falkner, Thushari Atapattu:
Linguistic Changes across Different User Roles in MOOCs: What do they tell us? - Komi Sodoké, Roger Nkambou, Aude Dufresne, Issam Tanoubi:
Toward a deep convolutional LSTM for eye gaze spatiotemporal data sequence classification. - Shashank Sonkar, Andrew S. Lan, Andrew E. Waters, Phillip Grimaldi, Richard G. Baraniuk:
qDKT: Question-centric Deep Knowledge Tracing. - Patara Trirat, Sakonporn Noree, Mun Yong Yi:
IntelliMOOC: Intelligent Online Learning Framework for MOOC Platforms. - Hannah Valdiviejas, Nigel Bosch:
Using Association Rule Mining to Uncover Rarely Occurring Relationships in Two University Online STEM Courses: A Comparative Analysis. - Qian Wan, Scott A. Crossley, Laura K. Allen, Danielle S. McNamara:
Claim Detection and Relationship with Writing Quality. - Zichao Wang, Yi Gu, Andrew S. Lan, Richard G. Baraniuk:
VarFA: A Variational Factor Analysis Framework For Efficient Bayesian Learning Analytics. - Audrey Tedja Widjaja, Lei Wang, Nghia Trong Truong, Aldy Gunawan, Ee-Peng Lim:
Next-Term Grade Prediction: A Machine Learning Approach. - Yunkai Xiao, Gabriel Zingle, Qinjin Jia, Harsh R. Shah, Yi Zhang, Tianyi Li, Mohsin Karovaliya, Weixiang Zhao, Yang Song, Jie Ji, Ashwin Balasubramaniam, Harshit Patel, Priyankha Bhalasubbramanian, Vikram Patel, Edward F. Gehringer:
Detecting Problem Statements in Peer Assessments. - Tao Xie, Chaohua Gong, Geping Liu:
An Empirical Analysis of Skewed Temporal Data for Distribution-based Course Similarity. - Kang Xue:
Semi-supervised Learning Method for Adjusting Biased Item Difficulty Estimates Caused by Nonignorable Missingness under 2PL-IRT Model. - Yingbin Zhang, Luc Paquette:
An effect-size-based temporal interestingness metric for sequential pattern mining.
DC papers
- Dalila Bebbouchi:
Mutual spontaneous aid between students in distance learning and the role of the feeling of social belonging to a training group. - Afrizal Doewes, Mykola Pechenizkiy:
Structural Explanation of Automated Essay Scoring. - John A. Erickson:
Natural Language Processing for Open Ended Questions in Mathematics within Intelligent Tutoring Systems. - Effat Farhana:
Self-Regulated Learning and Science Reading of Middle-School Students. - Aleksandr Gromov:
Developing Curriculum Analytics and Student Social Networking for Graduate Employability Model. - Daneih Ismail:
Overcoming Foreign Language Anxiety in an Emotionally Intelligent Tutoring System. - Kakyeong Kim, Il-Hyun Jo:
The Effect of Visual Cues on Cognitive Load Depending on Self-Regulation in Video-Based Learning. - Ajay Kulkarni, Michael Eagle:
Towards Understanding the Impact of Real-Time AI-Powered Educational Dashboards (RAED) on Providing Guidance to Instructors. - In-Hye Lee:
Estimation for cognitive load in Video-based learning through Physiological Data and Subjective Measurement by Video Annotation. - Aditi Mallavarapu, Leilah Lyons:
Exploration Maps, Beyond Top Scores: Designing Formative Feedback for Open-Ended Problems. - Mehak Maniktala, Tiffany Barnes, Min Chi:
Extending the Hint Factory: Towards Modelling Productivity for Open-ended Problem-solving. - Jessica McBroom, Kalina Yacef, Irena Koprinska:
Scalability in Online Computer Programming Education: Automated Techniques for Feedback, Evaluation and Equity. - Lavendini Sivaneasharajah, Katrina Falkner, Thushari Atapattu:
Investigating Students' Learning in Online Learning Environment. - Oana Maria Teodorescu:
Building Test Recommender Systems for e-Learning Systems. - Elad Yacobson:
Crowd-sourcing and Automatic Generation of Semantic Information in Blended-Learning Environments.
Industry Papers
- Deepak Agarwal, Ryan Baker, Anupama Muraleedharan:
Dynamic knowledge tracing through data driven recency weights. - Soma S. Dhavala, Chirag Bhatia, Joy Bose, Keyur Faldu, Aditi Avasthi:
Auto generation of diagnostic assessments and their quality evaluation. - Kevin Dieter, Jamie Studwell, Kirk Vanacore:
Differential Responses to Personalized Learning Recommendations Revealed by Event-Related Analysis. - Youngnam Lee, Byungsoo Kim, Dongmin Shin, JungHoon Kim, Jineon Baek, Jinhwan Lee, Youngduck Choi:
Prescribing Deep Attentive Score Prediction Attracts Improved Student Engagement. - Shengni Wang, Yuxin Zhao, Wei Ma, Zhenjun Ma, Ryan Baker:
The Results of Zone of Proximal Development on Learning Outcome.
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