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Chih-Yueh Chou; Wei-Han Chen – Educational Technology & Society, 2025
Studies have shown that students have different help-seeking behavior patterns and tendencies and furthermore, that students with certain help-seeking behavior patterns and tendencies may have poor performance (i.e., at-risk students). This study applied an educational data mining approach, including clustering and classification, to analyze…
Descriptors: Student Behavior, Help Seeking, Problem Solving, Information Retrieval
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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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Gitinabard, Niki; Gao, Zhikai; Heckman, Sarah; Barnes, Tiffany; Lynch, Collin F. – Journal of Educational Data Mining, 2023
Few studies have analyzed students' teamwork (pairwork) habits in programming projects due to the challenges and high cost of analyzing complex, long-term collaborative processes. In this work, we analyze student teamwork data collected from the GitHub platform with the goal of identifying specific pair teamwork styles. This analysis builds on an…
Descriptors: Cooperative Learning, Computer Science Education, Programming, Student Projects
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Maniktala, Mehak; Cody, Christa; Isvik, Amy; Lytle, Nicholas; Chi, Min; Barnes, Tiffany – Journal of Educational Data Mining, 2020
Determining "when" and "whether" to provide personalized support is a well-known challenge called the assistance dilemma. A core problem in solving the assistance dilemma is the need to discover when students are unproductive so that the tutor can intervene. Such a task is particularly challenging for open-ended domains, even…
Descriptors: Intelligent Tutoring Systems, Problem Solving, Helping Relationship, Prediction
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Inwood, Shoshanah; Becot, Florence; Bjornestad, Andrea; Henning-Smith, Carrie; Alberth, Andrew – Journal of Extension, 2019
A number of current events are exacerbating farm stress. Extension and farm organizations have mobilized responses to an emerging mental health crisis among farmers. To evaluate these responses, we conducted an online scan of resources to present a baseline typology of current mental health programs and response efforts in the 12-state Extension…
Descriptors: Mental Health, Agricultural Occupations, Extension Education, Mental Health Programs
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Borsari, Brian; Yalch, Matthew M.; Pedrelli, Paola; Radomski, Sharon; Bachrach, Rachel L.; Read, Jennifer P. – Journal of American College Health, 2018
Objective: This study examined how profiles of alcohol use and symptoms of common mental health disorders (depression and posttraumatic stress disorder [PTSD]) influenced the perceived need for and actual seeking of different types of treatment (for alcohol versus psychological distress) in college student drinkers. Participants: Undergraduate…
Descriptors: Trauma, Drinking, Symptoms (Individual Disorders), Undergraduate Students
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Lynch, Collin F., Ed.; Merceron, Agathe, Ed.; Desmarais, Michel, Ed.; Nkambou, Roger, Ed. – International Educational Data Mining Society, 2019
The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…
Descriptors: Data Collection, Data Analysis, Information Retrieval, Content Analysis