Proceedings of the International Conference on Educational Data Mining (EDM) (13th, Online, July 10-13, 2020)

International Educational Data Mining Society. e-mail: [email protected]; Web site: http://www.educationaldatamining.org

Y

861

Educational Improvement; Teaching Methods; Information Retrieval; Data Processing; Data Analysis; Equal Education; Student Diversity; Cooperative Learning; Online Courses; Demography; Transformative Learning; Blended Learning; Learning Strategies; Large Group Instruction; Artificial Intelligence; Educational Technology; Privacy; Learner Engagement; Student Motivation; Programming; Models; Game Based Learning; Competence; Problem Solving; Information Sources; Critical Theory; At Risk Students; Elementary Secondary Education; Spatial Ability; Visualization; Intervention; Student Characteristics; Automation; Remedial Reading; Handheld Devices; Video Technology; Item Response Theory; Reinforcement; Student Behavior; Prediction; Success; College Students; Data Collection; Masters Programs; Reaction Time; Reading Comprehension; College Admission; Essays; Peer Teaching; Performance; Teamwork; Student Projects; Inquiry; Electronic Publishing; Textbooks; Tests; Ethics; Legal Responsibility; Higher Education; Measurement Techniques; Reading Achievement; Grade 9; Video Games; Peer Evaluation; Secondary Schools; Computer Science Education; Physics; Feedback (Response); Semitic Languages; Technical Writing; Telecommunications; Personal Autonomy; Computer Software; Plagiarism; Curriculum; Collaborative Writing; Dropouts; Educational Assessment; Gender Differences; Difficulty Level; Social Media; Mental Health; Innovation; Student Role; Eye Movements; Foreign Countries; Bayesian Statistics; Scores; Distance Education; Student Attitudes; Scoring; Natural Language Processing; Middle School Students; Social Networks; Employment Qualifications; Intelligent Tutoring Systems; Anxiety; Second Languages; Cues; Visual Aids

Uruguay; Brazil

978-1-73367-361-7

The 13th iteration of the International Conference on Educational Data Mining (EDM 2020) was originally arranged to take place in Ifrane, Morocco. Due to the SARS-CoV-2 (coronavirus) epidemic, EDM 2020, as well as most other academic conferences in 2020, had to be changed to a purely online format. To facilitate efficient transmission of presentations all paper presenters pre-recorded their presentation as a video and then hosted it on YouTube with closed-captioning (CC). The official theme of this year's conference is Improving Learning Outcomes for All Learners. The theme comprises two parts: (1) Identifying actionable learning or teaching strategies that can be used to "improve" learning outcomes, not just predict them; (2) Using EDM to promote more "equitable" learning across diverse groups of learners, and to benefit underserved communities in particular. This year's conference features three invited talks: Alina von Davier, Chief Officer at ACTNext; Abelardo Pardo, Professor and Dean of Programs (Engineering), at UniSA STEM, University of South Australia; and Kobi Gal, Associate Professor at the Department of Software and Information Systems Engineering at Ben-Gurion University of the Negev, and Reader at the School of Informatics at the University of Edinburgh.

ERIC

2020

ED607784