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Pei, Bo; Xing, Wanli – Journal of Educational Computing Research, 2022
This paper introduces a novel approach to identify at-risk students with a focus on output interpretability through analyzing learning activities at a finer granularity on a weekly basis. Specifically, this approach converts the predicted output from the former weeks into meaningful probabilities to infer the predictions in the current week for…
Descriptors: At Risk Students, Learning Analytics, Information Retrieval, Models
Livieris, Ioannis E.; Drakopoulou, Konstantina; Tampakas, Vassilis T.; Mikropoulos, Tassos A.; Pintelas, Panagiotis – Journal of Educational Computing Research, 2019
Educational data mining constitutes a recent research field which gained popularity over the last decade because of its ability to monitor students' academic performance and predict future progression. Numerous machine learning techniques and especially supervised learning algorithms have been applied to develop accurate models to predict…
Descriptors: Secondary School Students, Academic Achievement, Teaching Methods, Student Behavior
Kim, Sunha – Journal of Educational Computing Research, 2018
This study compared the direct, indirect, and total effects of information, communication, and technology (ICT) variables on math achievement for second-generation immigrant, first-generation immigrant, and nonimmigrant students. A path model was used to analyze U.S. nationally representative data from the Program for International Student…
Descriptors: Immigrants, Migrant Children, Migrant Education, Predictor Variables
Gökçearslan, Sahin; Karademir, Tugra; Korucu, Agah Tugrul – Journal of Educational Computing Research, 2017
Technological Pedagogical Content Knowledge, one of the frameworks proposed in order to popularize the use of technology in a classroom environment, has been customized and has taken the form of Web Pedagogical Content Knowledge. The Relational Screening Model was used in this study. It aims to determine whether a profile of preservice teachers…
Descriptors: Foreign Countries, Preservice Teachers, Knowledge Level, Pedagogical Content Knowledge
Holland, Denise D.; Piper, Randy T. – Journal of Educational Computing Research, 2016
The technology integration education model is a 12 construct model that includes 8 primary constructs and 4 moderator constructs. By testing the relationships among two primary constructs (motivation and technological, pedagogical, and content knowledge competencies) and four moderator constructs (goals, feedback, task value, and self-regulation),…
Descriptors: Technology Integration, Preservice Teachers, Models, Objectives
Kang, Minseok; Shin, Won sug – Journal of Educational Computing Research, 2015
This study proposes an extended technology acceptance model to predict acceptance of synchronous e-learning by examining relationships among variables associated with factors influencing the technology acceptance of synchronous e-learning. Learners at an online university participated through an online survey; there were 251 respondents in all.…
Descriptors: Foreign Countries, Graduate Students, Student Attitudes, Adoption (Ideas)
Shapley, Kelly; Sheehan, Daniel; Maloney, Catherine; Caranikas-Walker, Fanny – Journal of Educational Computing Research, 2010
In the study of the Technology Immersion model, high-need middle schools were "immersed" in technology by providing laptops for each teacher and student, instructional and learning resources, professional development, and technical and pedagogical support. This article reports third-year findings for the teacher component of the…
Descriptors: Class Activities, Middle Schools, Technology Integration, Educational Technology