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Jinnie Shin; Bowen Wang; Wallace N. Pinto Junior; Mark J. Gierl – Large-scale Assessments in Education, 2024
The benefits of incorporating process information in a large-scale assessment with the complex micro-level evidence from the examinees (i.e., process log data) are well documented in the research across large-scale assessments and learning analytics. This study introduces a deep-learning-based approach to predictive modeling of the examinee's…
Descriptors: Prediction, Models, Problem Solving, Performance
Jionghao Lin; Shaveen Singh; Lela Sha; Wei Tan; David Lang; Dragan Gasevic; Guanliang Chen – Grantee Submission, 2022
To construct dialogue-based Intelligent Tutoring Systems (ITS) with sufficient pedagogical expertise, a trendy research method is to mine large-scale data collected by existing dialogue-based ITS or generated between human tutors and students to discover effective tutoring strategies. However, most of the existing research has mainly focused on…
Descriptors: Intelligent Tutoring Systems, Teaching Methods, Dialogs (Language), Man Machine Systems
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Ouyang, Fan; Wu, Mian; Zheng, Luyi; Zhang, Liyin; Jiao, Pengcheng – International Journal of Educational Technology in Higher Education, 2023
As a cutting-edge field of artificial intelligence in education (AIEd) that depends on advanced computing technologies, AI performance prediction model is widely used to identify at-risk students that tend to fail, establish student-centered learning pathways, and optimize instructional design and development. A majority of the existing AI…
Descriptors: Technology Integration, Artificial Intelligence, Performance, Prediction