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Yiheng Wang; Liman Man Wai Li – British Journal of Educational Psychology, 2024
Background: Parents are often involved in their child's homework with the goal of improving their child's academic achievement. However, mixed findings were observed for the role of parental involvement in homework in shaping students' learning outcomes. Aims: The present study examined whether and how the effect of parental involvement in…
Descriptors: Data Analysis, Collectivism, Individualism, Parent Participation
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Prat, Alain; Code, Warren J. – International Journal of Mathematical Education in Science and Technology, 2021
The online homework system WeBWorK has been successfully used at several hundred colleges and universities. Despite its popularity, the WeBWorK system does not provide detailed metrics of student performance to instructors. In this article, we illustrate how an analysis of the log files of the WeBWorK system can provide information such as the…
Descriptors: Data Analysis, Homework, Student Behavior, Educational Technology
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Shi Pu; Yu Yan; Brandon Zhang – Journal of Educational Data Mining, 2024
We propose a novel model, Wide & Deep Item Response Theory (Wide & Deep IRT), to predict the correctness of students' responses to questions using historical clickstream data. This model combines the strengths of conventional Item Response Theory (IRT) models and Wide & Deep Learning for Recommender Systems. By leveraging clickstream…
Descriptors: Prediction, Success, Data Analysis, Learning Analytics
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Reinhart, Alex; Genovese, Christopher R. – Journal of Statistics and Data Science Education, 2021
Traditionally, statistical computing courses have taught the syntax of a particular programming language or specific statistical computation methods. Since Nolan and Temple Lang's seminal paper, we have seen a greater emphasis on data wrangling, reproducible research, and visualization. This shift better prepares students for careers working with…
Descriptors: Computer Software, Graduate Students, Computer Science Education, Statistics Education
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dos Santos, Roberta Alvarenga; Paulista, Cássio Rangel; da Hora, Henrique Rego Monteiro – Technology, Knowledge and Learning, 2023
The demand for in-depth studies on educational data presupposes the application of technologies that allow data analysis of vast quantities, and subsequently, drawing relevant information and knowledge. The research objective herein is to employ data mining techniques on PISA databases to identify potential patterns that may explain the…
Descriptors: Foreign Countries, Achievement Tests, International Assessment, Secondary School Students