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Qi Zhou; Wannapon Suraworachet; Mutlu Cukurova – Education and Information Technologies, 2024
Collaboration is argued to be an important skill, not only in schools and higher education contexts but also in the workspace and other aspects of life. However, simply asking students to work together as a group on a task does not guarantee success in collaboration. Effective collaborative learning requires meaningful interactions among…
Descriptors: Learning Analytics, Cooperative Learning, Nonverbal Communication, Speech Communication
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Mitra, Reshmi; Schwieger, Dana; Lowe, Robert – Information Systems Education Journal, 2023
Many universities have, or are facing, the task of providing high quality essential customer services with fewer financial and human resources. The growing diversity of students, their needs and proficiencies, along with the increasing variety of university program offerings, make providing customized, ondemand, automated solutions crucial to…
Descriptors: Universities, Academic Advising, Artificial Intelligence, Faculty Workload
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Young, Nicholas T.; Caballero, Marcos D. – Journal of Educational Data Mining, 2021
We encounter variables with little variation often in educational data mining (EDM) due to the demographics of higher education and the questions we ask. Yet, little work has examined how to analyze such data. Therefore, we conducted a simulation study using logistic regression, penalized regression, and random forest. We systematically varied the…
Descriptors: Prediction, Models, Learning Analytics, Mathematics
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Xi Lin; Ken Luterbach; Kristen H. Gregory; Sarah E. Sconyers – Online Learning, 2024
This study explored the impact of integrating ChatGPT into asynchronous online discussions. The analysis encompassed students' log data from Canvas and their perspectives on using ChatGPT. Results revealed a significant enhancement in overall discussion participation when ChatGPT is encouraged, emphasizing its potential as a catalyst for…
Descriptors: Artificial Intelligence, Computer Software, Teaching Methods, Computer Mediated Communication
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Yang, Albert C. M.; Chen, Irene Y. L.; Flanagan, Brendan; Ogata, Hiroaki – Educational Technology & Society, 2021
Precision education is a new challenge in leveraging artificial intelligence, machine learning, and learning analytics to enhance teaching quality and learning performance. To facilitate precision education, text marking skills can be used to determine students' learning process. Text marking is an essential learning skill in reading. In this…
Descriptors: Grading, Computer Assisted Testing, Automation, Artificial Intelligence
Steven Moore; John Stamper; Norman Bier; Mary Jean Blink – Grantee Submission, 2020
In this paper we show how we can utilize human-guided machine learning techniques coupled with a learning science practitioner interface (DataShop) to identify potential improvements to existing educational technology. Specifically, we provide an interface for the classification of underlying Knowledge Components (KCs) to better model student…
Descriptors: Learning Analytics, Educational Improvement, Classification, Learning Processes