15:00 – 22:00 CEST / 9:00 – 16:00 EDT
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15:00 – 22:30 CEST / 9:00 – 16:30 EDT
[website] [Zoom link]
16:00 – 20:30 CEST / 10:00 – 14:30 EDT
[website] [Zoom link]
16:00 – 22:00 CEST / 10:00 – 16:00 EDT
[website] [Zoom link]
17:00 – 20:00 CEST / 11:00 – 14:00 EDT
[website] [Zoom link]
17:30 – 22:30 CEST / 11:30 – 16:30 EDT
[website] [Zoom link]
A1.1 15:00 Automatically classifying student help requests: a multi-year analysis Zhikai Gao, Collin Lynch, Sarah Heckman and Tiffany Barnes
A1.2 15:20 Grouping Source Code by Solution Approaches — Improving Feedback in Programming Courses Frank Höppner
A2.1 15:00 Student-centric Model of Login Patterns: A Case Study with Learning Management Systems Varun Mandalapu, Lujie Chen, Zhiyuan Chen and Jiaqi Gong
A2.2 15:20 Embedding navigation patterns for student performance prediction Ekaterina Loginova and Dries Benoit
A3.1 15:00 Say What? Automatic Modeling of Collaborative Problem Solving Skills from Student Speech in the Wild Samuel Pugh, Shree Krishna Subburaj, Arjun Ramesh Rao, Angela Stewart, Jessica Andrews-Todd and Sidney D’Mello
A3.2 15:20 Linguistic and Gestural Coordination: Do Learners Converge in Collaborative Dialogue? Arabella Sinclair and Bertrand Schneider
B1.1 16:00 Estimating the Intelligent Tutor Effects on Specific Posttest Problems Adam Sales, Ethan Prihar, Neil Heffernan and John Pane
B1.2 16:20 Learning Expert Models for Educationally Relevant Tasks using Reinforcement Learning Christopher Maclellan and Adit Gupta
B1.3 16:35 Do Common Educational Datasets contain Static Information? A Statistical Study Théo Barollet, Florent Bouchez-Tichadou and Fabrice Rastello Best Short Paper Nominee
B2.1 16:00 Early Prediction of Conceptual Understanding in Interactive Simulations Jade Cock, Mirko Marras, Christian Giang and Tanja Käser Best Full Paper Nominee
B2.2 16:20 Quizzing Policy Using Reinforcement Learning for Inferring the Student Knowledge State Joy He-Yueya and Adish Singla
B2.3 16:35 Recommending Knowledge Concepts on MOOC Platforms with Meta-path-based Representation Learning Guangyuan Piao
B3.1 16:00 SimPairing - Exploring Dynamic Pairing Policies through Historical Data Simulation and User-centered Research Kexin Yang, Xuejian Wang, Vanessa Echeverria, Luettamae Lawrence, Kenneth Holstein, Nikol Rummel and Vincent Aleven
B3.2 16:20 Fair-Capacitated Clustering Tai Le Quy, Arjun Roy, Gunnar Friege and Eirini Ntoutsi
B3.3 16:35 A Novel Algorithm for Aggregating Crowdsourced Opinions Ethan Prihar and Neil Heffernan
C1.1 19:30 Knowing both when and where: Temporal-ASTNN for Early Prediction of Student Success in Novice Programming Tasks Ye Mao, Yang Shi, Samiha Marwan, Thomas Price, Tiffany Barnes and Min Chi
C1.2 19:50 Learning student program embeddings using abstract execution traces Guillaume Cleuziou and Frédéric Flouvat
C1.3 20:10 Using Student Trace Logs To Determine Meaningful Progress and Struggle During Programming Problem Solving Yihuan Dong, Samiha Marwan, Preya Shabrina, Tiffany Barnes and Thomas Price
C2.1 19:30 Acting Engaged: Leveraging Player Persona Archetypes for Semi-Supervised Classification of Engagement Benjamin Nye, Mark G. Core, Shikhar Jaiswal, Aviroop Ghosal and Daniel Auerbach
C2.2 19:50 Early Prediction of Museum Visitor Engagement with Multimodal Adversarial Domain Adaptation Nathan Henderson, Wookhee Min, Andrew Emerson, Jonathan Rowe, Seung Lee, James Minogue and James Lester Best Full Paper Nominee
C2.3 20:10 Sharpest Tool in the Shed: Investigating SMART Models of Self-Regulation and their Impact on Learning Stephen Hutt, Jaclyn Ocumpaugh, Juliana Ma. Alexandra L. Andres, Nigel Bosch, Luc Paquette, Gautam Biswas and Ryan Baker
C3.1 19:30 Learning from Non-Assessed Resources: Deep Multi-Type Knowledge Tracing Chunpai Wang, Siqian Zhao and Shaghayegh Sahebi
C3.2 19:50 Student Performance Prediction Using Dynamic Neural Models Marina Delianidi, Konstantinos Diamantaras, George Chrysogonidis and Vasileios Nikiforidis
C3.3 20:10 Going Online: A simulated student approach for evaluating knowledge tracing in the context of mastery learning Qiao Zhang and Christopher MacLellan
| Poster Session 1 | Poster Session 2 | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| S | 192 | 274 | 271 | 211 | 155 | 109 | ||||||
| R | 96 | 90 | 19 | 126 | 276 | 176 | 95 | 78 | 134 | 79 | 208 | 80 |
| Q | 117 | 26 | 178 | 73 | 214 | 122 | 263 | 48 | 89 | 262 | 30 | 258 |
| P | 39 | 35 | 260 | 81 | 84 | 231 | 245 | 85 | 264 | 247 | 259 | 174 |
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | |
P1 Predictive Sequential Pattern Mining via Interpretable Convolutional Neural Networks Lan Jiang and Nigel Bosch
P2 The CommonLit Ease of Readability (CLEAR) Corpus Scott Crossley, Aron Heintz, Joon Choi, Jordan Batchelor, Mehrnoush Karimi and Agnes Malatinszky
P3 Using Data Quality to compare the Prediction Accuracy based on diverse annotated Tutor Scorings Sylvio Rüdian and Niels Pinkwart
P4 Measuring the Academic Impact of Course Sequencing using Student Grade Data Tess Gutenbrunner, Daniel Leeds, Spencer Ross, Michael Riad-Zaky and Gary Weiss
P5 Mining Course Groupings based on Academic Performance Daniel Leeds, Tianyi Zhang and Gary Weiss
P6 Predicting Executive Functions in a Learning Game: Accuracy and Reaction Time Jing Zhang, Teresa Ober, Yang Jiang, Jan Plass and Bruce Homer
Q1 Deep learning for sentence clustering in essay grading support Li-Hsin Chang, Iiro Rastas, Jenna Kanerva, Valtteri Skantsi, Sampo Pyysalo and Filip Ginter
Q2 Classroom Analytics for the Teacher, by the Teacher: Building Interpretable Descriptors for Student Posture Analysis in a Physical Classroom Lujie Chen and David Gerritsen
Q3 The Impact of Learning Analytics on Student Performance and Satisfaction in a Higher Education Course Dimitrios Tzimas and Stavros Demetriadis
Q4 Academic Integrity in Online Education during the COVID-19 Pandemic: a Social Media Mining Study Mohammad Parsa and Lukasz Golab
Q5 Is It Fair? Automated Open Response Grading John A. Erickson, Anthony F. Botelho, Zonglin Peng, Rui Huang, Meghana V. Kasal and Neil Heffernan
Q6 To Scale or Not to Scale: Comparing Popular Sentiment Analysis Dictionaries on Educational Twitter Data Conrad Borchers, Joshua Rosenberg, Ben Gibbons, Macy Alana Burchfield and Christian Fischer
R1 SimGrade: Using Code Similarity Measures for More Accurate Human Grading Sonja Johnson-Yu, Nicholas Bowman, Mehran Sahami and Chris Piech
R2 Feedback and Self-Regulated Learning in Science Reading Effat Farhana, Andrew Potter, Teomara Rutherford and Collin F. Lynch
R3 Text Representations of Math Tutorial Videos forClustering, Retrieval, and Learning Gain Prediction Pichayut Liamthong and Jacob Whitehill
R4 The Cold Start Problem and Interpretation of Knowledge Tracing Models’ Predictive Performance Jiayi Zhang, Rohini Das, Ryan S. Baker and Richard Scruggs
R5 Are Violations of Student Privacy “Quick and Easy”? Investigating the Privacy of Students’ Images and Names in the Context of K-12 Educational Institution’s Posts on Facebook Macy Burchfield, Joshua Rosenberg, Conrad Borchers, Tayla Thomas, Benjamin Gibbons and Christian Fischer
R6 Fine-Grained Versus Coarse-Grained Data for Estimating Time-on-Task in Learning Programming Juho Leinonen, Francisco Enrique Vicente Castro and Arto Hellas
S2 Predicting Young Students' Self-Regulated Learning Deficits Through Their Activity and Self-Evaluation Traces Thomas Sergent, Morgane Daniel, François Bouchet and Thibault Carron
S3 Catalog: An educational content tagging system Saad Khan, Joshua Rosaler, Jesse Hamer and Tiago Almeida
S4 Generate: A NLG system for educational content creation Saad Khan, Jesse Hamer and Tiago Almeida
S5 Execution Trace Based Feature Engineering To Enable Formative Feedback on Visual, Interactive Programs Wengran Wang, Gordon Fraser, Tiffany Barnes, Chris Martens and Thomas Price
S6 Detecting Careless Responding to Assessment Items in a Virtual Learning Environment Using Person-fit Indices and Random Forest Sanaz Nazari, Walter Leite and Anne Huggins-Manley
D1.1 14:30 Can Feature Predictive Power Generalize? Benchmarking Early Predictors of Student Success across Flipped and Online Courses Mirko Marras, Julien Tuan Tu Vignoud and Tanja Käser
D1.2 14:50 Knowledge Transfer by Discriminative Pre-training for Academic Performance Prediction Byungsoo Kim, Hangyeol Yu, Dongmin Shin and Youngduck Choi Best Short Paper Nominee
D1.3 15:05 Combining Cognitive and Machine Learning Models to Mine CPR Training Histories for Personalized Predictions Florian Sense, Michael Krusmark, Joshua Fiechter, Michael G. Collins, Lauren Sanderson, Joshua Onia and Tiffany Jastrzembski Best Short Paper Nominee
D2.1 14:30 Which Hammer should I Use? A Systematic Evaluation of Approaches for Classifying Educational Forum Posts Lele Sha, Mladen Rakovic, Alexander Whitelock-Wainwright, David Carroll, Victoria M. Yew, Dragan Gasevic and Guanliang Chen
D2.2 14:50 Automated Claim Identification Using NLP Features in Student Argumentative Essays Qian Wan, Scott Crossley, Michelle Banawan, Renu Balyan, Danielle McNamara and Laura Allen
D2.3 15:05 Integrating Deep Learning into An Automated Feedback Generation System for Automated Essay Scoring Chang Lu and Maria Cutumisu
D3.1 14:30 Behavioral Testing of Deep Knowledge Tracing Models Minsam Kim, Yugeun Shim, Seewoo Lee, Hyunbin Loh and Juneyoung Park
D3.2 14:50 Predicting Student Performance Using Teacher Observation Reports Menna Fateen and Tsunenori Mine
D3.3 15:05 LANA: Towards Personalized Deep Knowledge Tracing Through Distinguishable Interactive Sequences Yuhao Zhou, Xihua Li, Yunbo Cao, Xuemin Zhao, Qing Ye and Jiancheng Lv
E1.1 15:30 Deep-IRT with independent student and item networks Emiko Tsutsumi, Ryo Kinoshita and Maomi Ueno
E1.2 15:45 Context-aware knowledge tracing integrated with the exercise representation and association in mathematics Tao Huang, Mengyi Liang, Huali Yang, Zhi Li, Tao Yu and Shengze Hu
E1.3 16:00 Effects of Algorithmic Transparency in Bayesian Knowledge Tracing on Trust and Perceived Accuracy Kimberly Williamson and Rene Kizilcec
E1.4 16:15 pyBKT: An Accessible Library of Bayesian Knowledge Tracing Models Anirudhan Badrinath, Frederic Wang and Zach Pardos
E2.1 15:30 Assessing attendance by peer information Pan Deng, Jianjun Zhou, Jing Lyu and Zitong Zhao
E2.2 15:45 Gaining Insights on Student Course Selection in Higher Education with Community Detection Erla Guðrún Sturludóttir, Eydís Arnardóttir, Gísli Hjálmtýsson and María Óskarsdóttir
E2.3 16:00 Exploring the Importance of Factors Contributing to Dropouts in Higher Education Over Time Hasan Tanvir and Irene-Angelica Chounta
E2.4 16:15 Sentiment Analysis of Student Surveys - A Case Study on Assessing the Impact of the COVID-19 Pandemic on Higher Education Teaching Haydée Guillot Jiménez, Anna Carolina Finamore, Marco Antonio Casanova and Gonçalo Simões
E3.1 15:30 Extending Adaptive Spacing Heuristics to MultiSkill Items Benoît Choffin, Fabrice Popineau and Yolaine Bourda
E3.2 15:45 Affect, Support and Personal Factors: Multimodal Causal Models of One-on-one Coaching Lujie Karen Chen, Joseph Ramsey and Artur Dubrawski
E3.3 16:00 Mapping Python Programs to Vectors using Recursive Neural Encodings Benjamin Paaßen, Jessica McBroom, Bryn Jeffries Grok, Irena Koprinska and Kalina Yacef
F1.1 18:30 Topic Transitions in MOOCs: An Analysis Study Fareedah Alsaad, Thomas Reichel, Yuchen Zeng and Abdussalam Alawini
F1.2 18:50 The effects of a personalized recommendation system on students’ high-stakes achievement scores: A field experiment Nilanjana Chakraborty, Samrat Roy, Walter Leite and George Michailidis
F1.3 19:05 Finding the optimal topic sequence for online courses using SERPs as a Proxy Sylvio Rüdian and Niels Pinkwart
F2.1 18:30 Just a Few Expert Constraints Can Help: Humanizing Data-Driven Subgoal Detection for Novice Programming Samiha Marwan, Yang Shi, Ian Menezes, Min Chi, Tiffany Barnes and Thomas Price Best Full Paper Nominee
F2.2 18:50 Modeling Creativity in Visual Programming: From Theory to Practice Anastasia Kovalkov, Benjamin Paassen, Avi Segal, Kobi Gal and Niels Pinkwart
F2.3 19:05 More With Less: Exploring How to Use Deep Learning Effectively through Semi-supervised Learning for Automatic Bug Detection in Student Code Yang Shi, Ye Mao, Tiffany Barnes, Min Chi and Thomas Price
F3.1 18:30 Generative Grading: Near Human-level Accuracy for Automated Feedback on Richly Structured Problems Ali Malik, Mike Wu, Vrinda Vasavada, Jinpeng Song, Madison Coots, John Mitchell, Noah Goodman and Chris Piech
F3.2 18:50 Automatic short answer grading with SBERT on out-of-sample questions Aubrey Condor, Max Litster and Zachary Pardos
F3.3 19:05 ALL-IN-ONE: Multi-Task Learning BERT models for Evaluating Peer Assessments Qinjin Jia, Jialin Cui, Yunkai Xiao, Chengyuan Liu, Parvez Rashid and Edward Gehringer
G1.1 19:30 Investigating the Validity of Methods Used to Adjust for Multiple Comparisons in Educational Data Mining Jeffrey Matayoshi and Shamya Karumbaiah
G1.2 19:50 Experimental Evaluation of Similarity Measures for Educational Items Jaroslav Čechák and Radek Pelánek
H1.1 19:30 Online Estimation of Student Ability and Item Difficulty with Glicko-2 Rating System on Stratified Data Jaesuk Park
G2.1 19:50 Methods for Language Learning Assessment at Scale: Duolingo Case Study Lucy Portnoff, Erin Gustafson, Joseph Rollinson and Klinton Bicknell
DC1 19:30 A Longitudinal Approach to Detect Patterns and Predict Help-Seeking Behaviour in Adaptive Educational Systems Raquel Horta-Bartomeu, Olga C. Santos
DC2 19:50 Mixed Data Sampling in Learning Analytics Julian Langenhagen
DC3 20:10 Towards fair, explainable and actionable clustering for learning analytics Tai Le Quy, Eirini Ntoutsi
DC4 20:30 Towards a Conception and Integration of an Educational Social Network into an Institutional Learning Platform Romaric Bassole, Frédéric T. Ouedraogo, Laurence Capus
| Poster Session 2 | |||||||
|---|---|---|---|---|---|---|---|
| S | 109 | 84 | 39 | 122 | 178 | 26 | |
| R | 95 | 78 | 79 | 134 | 208 | 80 | 55 |
| Q | 263 | 48 | 89 | 262 | 30 | 258 | 126 |
| P | 245 | 85 | 264 | 247 | 259 | 174 | 117 |
| 7 | 8 | 9 | 10 | 11 | 12 | 13 | |
P7 Leveraging Survey and Motion Sensors Data to Promote Gender Inclusion in Makerspaces Edwin Chng, Stephanie Yang, Gahyun Sung, Tyler Yoo and Bertrand Schneider
P8 Identifying Hubs in Undergraduate Course Networks Based on Scaled Co-Enrollments Gary Weiss, Nam Nguyen, Karla Dominguez and Daniel Leeds
P9 A New Readability Assessment Tool Rebecca Watson and Ekaterina Kochmar
P10 Early Detection of At-risk Students based on Knowledge Distillation RNN Models Ryusuke Murata, Tsubasa Minematsu and Atsushi Shimada
P11 Demonstrating REACT: a Real-time Educational AI-powered Classroom Tool Ajay Kulkarni and Olga Gkountouna
P12 Tracing Knowledge for Tracing Dropouts: Multi-Task Training for Study Session Dropout Prediction Seewoo Lee, Kyu Seok Kim, Jamin Shin and Juneyoung Park
P13 Deep learning for sentence clustering in essay grading support Li-Hsin Chang, Iiro Rastas, Jenna Kanerva, Valtteri Skantsi, Sampo Pyysalo and Filip Ginter
Q7 Sex-Related Behavioral Differences in Online Math Classes: An Epistemic Network Analysis Yufei Gu and Kun Xu
Q8 Restructuring Curricular Patterns Using Bayesian Networks Ahmad Slim, Gregory Heileman, Chaouki Abdallah, Ameer Slim and Najem Sirhan
Q9 Linguistic Features of Discourse within an Algebra Online Discussion Board Michelle Banawan, Renu Balyan, Jinnie Shin, Walter Leite and Danielle McNamara
Q10 Towards Difficulty Controllable Selection of Next-Sentence Prediction Questions Jingrong Feng and Jack Mostow
Q11 Towards Explainable Student Group Collaboration Assessment Models Using Temporal Representations of Individual Student Role and Behavioral Cues Anirudh Som, Sujeong Kim, Bladimir Lopez-Prado, Svati Dhamija, Nonye Alozie and Amir Tamrakar
Q12 Mining sequential patterns with high usage variation Yingbin Zhang and Luc Paquette
Q13 The Cold Start Problem and Interpretation of Knowledge Tracing Models’ Predictive Performance Jiayi Zhang, Rohini Das, Ryan S. Baker and Richard Scruggs
R7 Analysis of Factors Influencing User Contribution and Predicting Involvement of Users on Stack Overflow Maliha Mahbub, Najia Manjur, Mahjabin Alam and Julita Vassileva
R8 Analyzing Ranking Strategies to Characterize Competition for Co-Operative Work Placements Shivangi Chopra and Lukasz Golab
R9 AQuAA: Analytics for Quality Assurance in Assessment Manqian Liao, Yigal Attali and Alina A. von Davier
R10 Analysis of stopping criteria for Bayesian Adaptive Mastery Assessment Androniki Sapountzi, Sandjai Bhulai, I. Cornelisz and Chris Van Klaveren
R11 Automatic Domain Model Creation and Improvement Philip I. Pavlik Jr., Luke Eglington and Liang Zhang
R12 LMS Log Data Analysis from Fully-Online Flipped Classrooms: An Exploratory Case Study via Regularization Jin Eun Yoo and Minjeong Rho
R13 Towards automated content analysis of feedback: A multi-language study Ikenna Osakwe, Alexander Whitelock-Wainwright, Guanliang Chen, Rafael Ferreira Mello, Anderson Pinheiro Cavalcanti and Dragan Gašević
S7 Recommendation System for Engineering Programs Candidates Bruno Mota da Silva and Claudia Antunes
S8 Mining Course Groupings based on Academic Performance Daniel Leeds, Tianyi Zhang and Gary Weiss
S9 Predictive Sequential Pattern Mining via Interpretable Convolutional Neural Networks Lan Jiang and Nigel Bosch
S10 To Scale or Not to Scale: Comparing Popular Sentiment Analysis Dictionaries on Educational Twitter Data Conrad Borchers, Joshua Rosenberg, Ben Gibbons, Macy Alana Burchfield and Christian Fischer
S11 The Impact of Learning Analytics on Student Performance and Satisfaction in a Higher Education Course Dimitrios Tzimas and Stavros Demetriadis
S12 Classroom Analytics for the Teacher, by the Teacher: Building Interpretable Descriptors for Student Posture Analysis in a Physical Classroom Lujie Chen and David Gerritsen
H1.2 19:30 Benefits of alternative evaluation methods for Automated Essay Scoring Øistein E. Andersen, Rebecca Watson, Zheng Yuan and Kevin Yet Fong Cheung
H1.3 19:45 UPreG: An Unsupervised approach for building the Concept Prerequisite Graph Varun Sabnis, Kumar Abhinav, Venkatesh Subramania, Alpana Dubey and Padmaraj Bhat
H2.1 19:30 Toward Improving Student Model Estimates through Assistance Scores in Principle and in Practice Napol Rachatasumrit and Kenneth Koedinger
H2.2 19:45 Analyzing Student Success and Mistakes in Virtual Microscope Structure Search Tasks Benjamin Paaßen, Andreas Bertsch, Katharina Langer-Fischer, Sylvio Rüdian, Xia Wang, Rupali Sinha, Jakub Kuzilek, Stefan Britsch and Niels Pinkwart
H2.3 20:00 Studying Retrieval Practice in an Intelligent Tutoring System Jeffrey Matayoshi, Hasan Uzun, Eric Cosyn Best Paper Award at L@S 2020
H3.1 19:30 Using Keystroke Analytics to Understand Cognitive Processes during Writing Mo Zhang, Hongwen Guo and Xiang Liu Best Short Paper Nominee
H3.2 19:45 Speeding up without Loss of Accuracy: Item Position Effects on Examinees’ Performance in University Exams Leonardo Vida, Maria Bolsinova and Matthieu J. S. Brinkhuis
H3.3 20:00 What you apply is not what you learn! Examining students’ strategies in German capitalization tasks Nathalie Rzepka, Hans-Georg Müller and Katharina Simbeck
I1.1 20:30 Improving Automated Scoring of Student Open Responses in Mathematics Sami Baral, Anthony F Botelho, John A Erickson, Priyanka Benachamardi and Neil T Heffernan Best Full Paper Nominee
I1.2 20:50 Automatic Assessment of the Design Quality of Python Programs with Personalized Feedback Walker Orr and Nathaniel Russell
I1.3 21:05 On the Limitations of Human-Computer Agreement in Automated Essay Scoring Afrizal Doewes and Mykola Pechenizkiy
I2.1 20:30 Math Operation Embeddings for Open-ended Solution Analysis and Feedback Mengxue Zhang, Zichao Wang, Richard Baraniuk and Andrew Lan
I2.2 20:50 Math Question Solving and MCQ Distractor Generation with attentional GRU Networks Neisarg Dave, Riley Owen Bakes, Bart Pursel and C. Lee Giles
I2.3 21:05 Targeting Design-Loop Adaptivity Stephen Fancsali, Hao Li, Michael Sandbothe and Steven Ritter
I3.1 20:30 Student Strategy Prediction using a Neuro-Symbolic Approach Anup Shakya, Vasile Rus and Deepak Venugopal
I3.2 20:50 Student Practice Sessions Modeled as ICAP Activity Silos Adam Gaweda and Collin Lynch
I3.3 21:05 From Detail to Context: Modeling Distributed Practice Intensity and Timing by Multiresolution Signal Analysis Cheng-Yu Chung and I-Han Hsiao
The annual conference of the Educational Data Mining society is intended to foster community and exchange of ideas among those working in the field of educational data mining.
Everyone involved in the conference -- from organizers to presenters to attendees to sponsors -- is expected to adhere to the code of conduct throughout the conference, both in their formal and informal participation in the conference and in all channels of interaction and communication, including social media. The EDM 2021 code of conduct described here is inspired by and adapted from similar codes of conduct from recent international conferences on machine learning and artificial intelligence (ICLR, ICML).
Everyone has a right to participate in the conference free from harassment and intimidation, and in an environment that recognizes the inherent worth of all people and their potential to contribute valuable ideas to the scientific discussion. Everyone has the right to a safe and discimination-free conference regardless of race, ethnicity, national origin, gender identity, gender expression, socioeconomic status, sexual orientation, disability status, religion or lack of religion, physical appearance, technology choices, or other identities or beliefs. What may be intended as “joking” can be offensive and demeaning. Bullying, intimidation, personal attacks, harassment, sustained disruption of talks or other events, and behavior that interferes with another participant's full participation will not be tolerated. This includes but is not limited to sexual harassment, unwelcome repeated contacts, harassing photography or recording, unwelcome sexual attention, display of belittling or gratuitous images in public spaces, public vulgar exchanges, and diminutive characterizations, which are all unwelcome in this community. Revealing private information in a public setting without permission, such as posting a participant’s personal information, is not permitted.
If you see someone engaging in any of these behaviors, please ask them to stop. If you experience or observe any behavior you’re concerned about or that you believe may constitute harassment or discrimination, please report it to program co-chairs Sharon Hsiao (sharon.Hsiao@asu.edu) and Shaghayegh (Sherry) Sahebi (ssahebi@albany.edu) via email with subject line “EDM’21 - concerning observation”. During the conference, we will follow up within 24 hours, and outside the days of the conference, we will respond within two business days.
Consequences for violating this code of conduct will be decided by the program and general chairs and may include a formal or informal warning, expulsion from the virtual conference with no refund, barring from participation in future conferences or the EDM organization, reporting the incident to the offender’s local institution or funding agencies, or other actions. A response of "just joking" will not be accepted; behavior can be harassing without an intent to offend. If action is taken, an appeals process will be made available.