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Boyer, Kristy Elizabeth, Ed.; Yudelson, Michael, Ed. – International Educational Data Mining Society, 2018
The 11th International Conference on Educational Data Mining (EDM 2018) is held under the auspices of the International Educational Data Mining Society at the Templeton Landing in Buffalo, New York. This year's EDM conference was highly competitive, with 145 long and short paper submissions. Of these, 23 were accepted as full papers and 37…
Descriptors: Data Collection, Data Analysis, Computer Science Education, Program Proposals
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Park, Jihyun; Yu, Renzhe; Rodriguez, Fernando; Baker, Rachel; Smyth, Padhraic; Warschauer, Mark – International Educational Data Mining Society, 2018
Time management is crucial to success in online courses in which students can schedule their learning on a flexible basis. Procrastination is largely viewed as a failure of time management and has been linked to poorer outcomes for students. Past research has quantified the extent of students' procrastination by defining single measures directly…
Descriptors: Time Management, Online Courses, Electronic Learning, Probability
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Chen, Weiyu; Joe-Wong, Carlee; Brinton, Christopher G.; Zheng, Liang; Cao, Da – International Educational Data Mining Society, 2018
Adaptive online courses are designed to automatically customize material for different users, typically based on data captured during the course. Assessing the quality of these adaptive courses, however, can be difficult. Traditional assessment methods for (machine) learning algorithms, such as comparison against a ground truth, are often…
Descriptors: Online Courses, Comparative Analysis, Statistics, Correlation
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Crues, R. Wes; Bosch, Nigel; Anderson, Carolyn J.; Perry, Michelle; Bhat, Suma; Shaik, Najmuddin – International Educational Data Mining Society, 2018
The diversity in reasons that students have for enrolling in massive open online courses (MOOCs) is an often-overlooked aspect while modeling learners' behaviors in MOOCs. Using survey data from 11,202 students in five MOOCs spanning different academic disciplines, this study evaluates the reasons that students enrolled in MOOCs, using an…
Descriptors: Large Group Instruction, Online Courses, Enrollment, Student Attitudes
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Chopra, Shivangi; Gautreau, Hannah; Khan, Abeer; Mirsafian, Melicaalsadat; Golab, Lukasz – International Educational Data Mining Society, 2018
It is well known that post-secondary science and engineering programs attract fewer female students. In this paper, we analyze gender differences through text mining of over 30,000 applications to the engineering faculty of a large North American university. We use syntactic and semantic analysis methods to highlight differences in motivation,…
Descriptors: Gender Differences, Undergraduate Students, Engineering Education, STEM Education
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Cai, Zhiqiang; Graesser, Arthur C.; Windsor, Leah C.; Cheng, Qinyu; Shaffer, David W.; Hu, Xiangen – International Educational Data Mining Society, 2018
Latent Semantic Analysis (LSA) plays an important role in analyzing text data from education settings. LSA represents meaning of words and sets of words by vectors from a k-dimensional space generated from a selected corpus. While the impact of the value of k has been investigated by many researchers, the impact of the selection of documents and…
Descriptors: Semantics, Discourse Analysis, Computational Linguistics, Intelligent Tutoring Systems
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Akram, Bita; Min, Wookhee; Wiebe, Eric; Mott, Bradford; Boyer, Kristy Elizabeth; Lester, James – International Educational Data Mining Society, 2018
A key affordance of game-based learning environments is their potential to unobtrusively assess student learning without interfering with gameplay. In this paper, we introduce a temporal analytics framework for stealth assessment that analyzes students' problem-solving strategies. The strategy-based temporal analytic framework uses long short-term…
Descriptors: Educational Games, Problem Solving, Educational Environment, Short Term Memory
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Fancsali, Stephen E.; Yudelson, Michael V.; Berman, Susan R.; Ritter, Steven – International Educational Data Mining Society, 2018
Learners in various contemporary settings (e.g., K-12 classrooms, online courses, professional/vocational training) find themselves in situations in which they have access to multiple technology-based learning platforms and often one or more non-technological resources (e.g., human instructors or on-demand human tutors). Instructors, similarly,…
Descriptors: Intelligent Tutoring Systems, Tutors, Higher Education, Online Courses
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Mantecon, Jesus Gerardo Alvarado; Ghavidel, Hadi Abdi; Zouaq, Amal; Jovanovic, Jelena; McDonald, Jenny – International Educational Data Mining Society, 2018
The automatic evaluation of text-based assessment items, such as short answers or essays, is an open and important research challenge. In this paper, we compare several features for the classification of short open-ended responses to questions related to a large first-year health sciences course. These features include a) traditional n-gram…
Descriptors: Questioning Techniques, Comparative Analysis, Models, Semantics
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Chen, Weiyu; Lan, Andrew S.; Cao, Da; Brinton, Christopher; Chiang, Mung – International Educational Data Mining Society, 2018
Knowledge of prerequisite dependencies is crucial to several aspects of learning, from the organization of learning content to the selection of personalized remediation or enrichment for each learner. As the amount of content is scaled up, however, it becomes increasingly difficult to manually specify all of the prerequisites among the different…
Descriptors: Behavioral Science Research, Measures (Individuals), Online Courses, Prerequisites
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Cook, Connor; Olney, Andrew M.; Kelly, Sean; D'Mello, Sidney K. – International Educational Data Mining Society, 2018
Automatic assessment of the quality of classroom discourse can have a transformative effect on research and practice on improving teaching effectiveness. We improve on a previous automated method to measure teacher authentic questions -- open-ended questions without pre-scripted responses that predict student achievement growth -- using classroom…
Descriptors: Vocabulary, Academic Discourse, Teacher Effectiveness, Partnerships in Education
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Tran, Khoi-Nguyen; Lau, Jey Han; Contractor, Danish; Gupta, Utkarsh; Sengupta, Bikram; Butler, Christopher J.; Mohania, Mukesh – International Educational Data Mining Society, 2018
Instructional Systems Design is the practice of creating of instructional experiences that make the acquisition of knowledge and skill more efficient, effective, and appealing [18]. Specifically in designing courses, an hour of training material can require between 30 to 500 hours of effort in sourcing and organizing reference data for use in just…
Descriptors: Behavioral Objectives, Instructional Design, Reference Materials, Prediction
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Botelho, Anthony F.; Baker, Ryan S.; Ocumpaugh, Jaclyn; Heffernan, Neil T. – International Educational Data Mining Society, 2018
Student affect has been found to correlate with short- and long-term learning outcomes, including college attendance as well as interest and involvement in Science, Technology, Engineering, and Mathematics (STEM) careers. However, there still remain significant questions about the processes by which affect shifts and develops during the learning…
Descriptors: Psychological Patterns, Time, Computer Assisted Instruction, Affective Behavior
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Sahebi, Shaghayegh; Brusilovsky, Peter – International Educational Data Mining Society, 2018
Performance prediction has emerged as one of the most popular approaches to leverage large volume of online learning data. In the majority of current works, performance prediction is based on students' past activities in graded learning resources (such as problems and quizzes), while their activities in non-graded resources (such as reading…
Descriptors: Performance, Prediction, Measurement Techniques, Learning Activities
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Xu, Yiqiao; Lynch, Collin F.; Barnes, Tiffany – International Educational Data Mining Society, 2018
Massive Open Online Courses (MOOCs) are designed on the assumption that good students will help poor students thus offloading the individual support tasks from the instructor to the class. However prior research has shown that this is not always true. Students in MOOCs tend to form distinct sub-communities and their grades are closely correlated…
Descriptors: Friendship, Online Courses, Peer Relationship, Social Networks
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