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Hsiao, I-Han, Ed.; Sahebi, Shaghayegh, Ed.; Bouchet, Francois, Ed.; Vie, Jill-Jenn, Ed. – International Educational Data Mining Society, 2021
For this 14th iteration of the International Conference on Educational Data Mining (EDM 2021), the conference was held completely online. EDM is organized under the auspices of the International Educational Data Mining Society and was meant to happen in Paris, France. The official theme of this year's conference was Shifting Landscape of…
Descriptors: Blended Learning, Distance Education, Learning Analytics, Educational Technology
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Wan, Qian; Crossley, Scott; Banawan, Michelle; Balyan, Renu; Tian, Yu; McNamara, Danielle; Allen, Laura – International Educational Data Mining Society, 2021
The current study explores the ability to predict argumentative claims in structurally-annotated student essays to gain insights into the role of argumentation structure in the quality of persuasive writing. Our annotation scheme specified six types of argumentative components based on the well-established Toulmin's model of argumentation. We…
Descriptors: Essays, Persuasive Discourse, Automation, Identification
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Deng, Pan; Zhou, Jianjun; Lyu, Jing; Zhao, Zitong – International Educational Data Mining Society, 2021
Attendance rate is an important indicator of students' study motivation, behavior and Psychological status; however, the heterogeneous nature of student attendance rates due to the course registration difference or the online/offline difference in a blended learning environment makes it challenging to compare attendance rates. In this paper, we…
Descriptors: Attendance Patterns, Peer Influence, Online Courses, Blended Learning
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Condor, Aubrey; Litster, Max; Pardos, Zachary – International Educational Data Mining Society, 2021
We explore how different components of an Automatic Short Answer Grading (ASAG) model affect the model's ability to generalize to questions outside of those used for training. For supervised automatic grading models, human ratings are primarily used as ground truth labels. Producing such ratings can be resource heavy, as subject matter experts…
Descriptors: Automation, Grading, Test Items, Generalization
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Gao, Zhikai; Lynch, Collin; Heckman, Sarah; Barnes, Tiffany – International Educational Data Mining Society, 2021
As Computer Science has increased in popularity so too have class sizes and demands on faculty to provide support. It is therefore more important than ever for us to identify new ways to triage student questions, identify common problems, target students who need the most help, and better manage instructors' time. By analyzing interaction data…
Descriptors: Automation, Classification, Help Seeking, Computer Science Education
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Andersen, Øistein E.; Yuan, Zheng; Watson, Rebecca; Cheung, Kevin Yet Fong – International Educational Data Mining Society, 2021
Automated essay scoring (AES), where natural language processing is applied to score written text, can underpin educational resources in blended and distance learning. AES performance has typically been reported in terms of correlation coefficients or agreement statistics calculated between a system and an expert human examiner. We describe the…
Descriptors: Evaluation Methods, Scoring, Essays, Computer Assisted Testing
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Nye, Benjamin D.; Core, Mark G.; Jaiswa, Shikhar; Ghosal, Aviroop; Auerbach, Daniel – International Educational Data Mining Society, 2021
Engaged and disengaged behaviors have been studied across a variety of educational contexts. However, tools to analyze engagement typically require custom-coding and calibration for a system. This limits engagement detection to systems where experts are available to study patterns and build detectors. This work studies a new approach to classify…
Descriptors: Learner Engagement, Profiles, Artificial Intelligence, Student Behavior
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Jia, Qinjin; Cui, Jialin; Xiao, Yunkai; Liu, Chengyuan; Rashid, Parvez; Gehringer, Edward – International Educational Data Mining Society, 2021
Peer assessment has been widely applied across diverse academic fields over the last few decades, and has demonstrated its effectiveness. However, the advantages of peer assessment can only be achieved with high-quality peer reviews. Previous studies have found that high-quality review comments usually comprise several features (e.g., contain…
Descriptors: Peer Evaluation, Models, Artificial Intelligence, Evaluation Methods
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Prihar, Ethan; Heffernan, Neil – International Educational Data Mining Society, 2021
Similar content has tremendous utility in classroom and online learning environments. For example, similar content can be used to combat cheating, track students' learning over time, and model students' latent knowledge. These different use cases for similar content all rely on different notions of similarity, which make it difficult to determine…
Descriptors: Computer Software, Middle School Teachers, Mathematics Teachers, College Students
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Sense, Florian; Krusmark, Michael; Fiechter, Joshua; Collins, Michael G.; Sanderson, Lauren; Onia, Joshua; Jastrzembski, Tiffany – International Educational Data Mining Society, 2021
Cardiopulmonary resuscitation (CPR) is a foundational lifesaving skill for which medical personnel are expected to be proficient. Frequent refresher training is needed to prevent the involved skills from decaying. Regular low-dose, high-frequency training for staff at fixed intervals has proven successful at maintaining CPR competence but does not…
Descriptors: First Aid, Training, Artificial Intelligence, Prediction
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Marras, Mirko; Vignoud, Julien Tuân Tu; Käser, Tanja – International Educational Data Mining Society, 2021
Early predictors of student success are becoming a key tool in flipped and online courses to ensure that no student is left behind along course activities. However, with an increased interest in this area, it has become hard to keep track of what the state of the art in early success prediction is. Moreover, prior work on early success prediction…
Descriptors: Benchmarking, Predictor Variables, Academic Achievement, Flipped Classroom
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PaaBen, Benjamin; Bertsch, Andreas; Langer-Fischer, Katharina; Rüdian, Sylvio; Wang, Xia; Sinha, Rupali; Kuzilek, Jakub; Britsch, Stefan; Pinkwart, Niels – International Educational Data Mining Society, 2021
Many modern anatomy curricula teach histology using virtual microscopes, where students inspect tissue slices in a computer program (e.g. a web browser). However, the educational data mining (EDM) potential of these virtual microscopes remains under-utilized. In this paper, we use EDM techniques to investigate three research questions on a virtual…
Descriptors: Anatomy, Science Instruction, Computer Simulation, Computer Software
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Kim, Minsam; Shim, Yugeun; Lee, Seewoo; Loh, Hyunbin; Park, Juneyoung – International Educational Data Mining Society, 2021
Knowledge Tracing (KT) is a task to model students' knowledge based on their coursework interactions within an Intelligent Tutoring System (ITS). Recently, Deep Neural Networks (DNN) showed superb performance over classical methods on multiple dataset benchmarks. While most Deep Learning based Knowledge Tracing (DLKT) models are optimized for…
Descriptors: Models, Artificial Intelligence, Knowledge Level, Evaluation Methods
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Chung, Cheng-Yu; Hsiao, I-Han – International Educational Data Mining Society, 2021
The distributed practice effect suggests that students retain learning content better when they pace their practice over time. The key factors are practice dosage (intensity) and timing (when to practice and how in between). Inspired by the thriving development of image recognition, this study adopts one of the successful techniques,…
Descriptors: Models, Drills (Practice), Pacing, Computer Uses in Education
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Malik, Ali; Wu, Mike; Vasavada, Vrinda; Song, Jinpeng; Coots, Madison; Mitchell, John; Goodman, Noah; Piech, Chris – International Educational Data Mining Society, 2021
Access to high-quality education at scale is limited by the difficulty of providing student feedback on open-ended assignments in structured domains like programming, graphics, and short response questions. This problem has proven to be exceptionally difficult: for humans, it requires large amounts of manual work, and for computers, until…
Descriptors: Grading, Accuracy, Computer Assisted Testing, Automation
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