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Xu, Jianzhong; Corno, Lyn – Metacognition and Learning, 2022
Informed by two theoretical models of homework effects, we extended a model of homework on mathematics achievement in a large sample of Chinese eighth graders. Our model incorporated six clusters of homework variables -- student background factors, homework characteristics, teacher variables, parent variables, student motivation, and homework…
Descriptors: Models, Homework, Hierarchical Linear Modeling, Foreign Countries
Flunger, Barbara; Trautwein, Ulrich; Nagengast, Benjamin; Lüdtke, Oliver; Niggli, Alois; Schnyder, Inge – Journal of Experimental Education, 2021
The present study illustrates the utility of applying multilevel mixture models in educational research, using data on the homework behavior of 1,812 Swiss eighth-grade students in French as a second language. A previous person-centered study identified 5 homework learning types characterized by different patterns of high or low homework time and…
Descriptors: Foreign Countries, Middle School Students, Grade 8, Multivariate Analysis
Fung, Karen; ElAtia, Samira – TESL Canada Journal, 2015
Using Hierarchical Linear Modelling (HLM), this study aimed to identify factors such as ESL/ELL/EAL status that would predict students' reading performance in an English language arts exam taken across Canada. Using data from the 2007 administration of the Pan-Canadian Assessment Program (PCAP) along with the accompanying surveys for students and…
Descriptors: Foreign Countries, Hierarchical Linear Modeling, Predictor Variables, English (Second Language)
Zhu, Yan; Leung, Frederick Koon Shing – International Journal of Science and Mathematics Education, 2012
Though it is generally believed that doing homework promotes better learning, no consensus has been achieved concerning its importance and relevance to students' achievement. The historical up-and-down status of public attitudes toward homework indicates that understanding about the role of homework in students' learning is far from comprehensive…
Descriptors: Homework, Mathematics Achievement, Academic Achievement, Educational Practices
Xu, Jianzhong – Educational Psychology, 2012
The present study examined empirical models of variables posited to predict students' homework environment management at the secondary school level. The participants were 866 8th graders from 61 classes and 745 11th graders from 46 classes. Most of the variance in homework environment management occurred at the student level, with classmates'…
Descriptors: Feedback (Response), Homework, Grade 8, Grade 11
Matsuoka, Ryoji – Educational Studies in Japan: International Yearbook, 2014
Japanese compulsory education had been praised because of its equality around the early 80s. However, since the third wave-educational reform that began in the 1980s and still persists, it has been pointed out that there are disparities between schools in terms of students' socioeconomic background and academic performance. Although there have…
Descriptors: Foreign Countries, Compulsory Education, Educational Change, Socioeconomic Background
Xu, Jianzhong – Teachers College Record, 2011
Background/Context: For many children, doing homework becomes an emotionally charged event and one of the most disappointing aspects of school life. It is surprising to note, however, that homework emotion management is noticeably absent from much contemporary homework literature. Purpose: The primary propose of the present study was to propose…
Descriptors: Feedback (Response), Homework, Emotional Response, Student Motivation
Baker, Ryan S. J. D.; Goldstein, Adam B.; Heffernan, Neil T. – International Journal of Artificial Intelligence in Education, 2011
Intelligent tutors have become increasingly accurate at detecting whether a student knows a skill, or knowledge component (KC), at a given time. However, current student models do not tell us exactly at which point a KC is learned. In this paper, we present a machine-learned model that assesses the probability that a student learned a KC at a…
Descriptors: Intelligent Tutoring Systems, Mastery Learning, Probability, Knowledge Level
Xu, Jianzhong – American Educational Research Journal, 2008
This aim of this study was to test empirical models of variables posited to predict homework interest at the secondary school level. Student- and class-level predictors of homework interest were analyzed in a survey of 1,046 8th graders from 63 classes and of 849 11th graders from 48 classes. Most of the variance in homework interest occurred at…
Descriptors: Feedback (Response), Homework, Grade 8, Grade 11
Trautwein, Ulrich; Ludtke, Oliver; Schnyder, Inge; Niggli, Alois – Journal of Educational Psychology, 2006
According to the domain-specific, multilevel homework model proposed in the present study, students' homework effort is influenced by expectancy and value beliefs, homework characteristics, parental homework behavior, and conscientiousness. The authors used structural equation modeling and hierarchical linear modeling analyses to test the model in…
Descriptors: Homework, Models, Expectation, Structural Equation Models
Chang, Mido; Singh, Kusum; Mo, Yun – Educational Research and Evaluation, 2007
The study explored the relationship of self-concept and locus of control to science engagement and science achievement. Furthermore, the relationship of self variables with science engagement and science achievement was studied across ethnicity, gender, and socioeconomic status (SES). The data were accessed from the 3 waves of the National…
Descriptors: Locus of Control, Science Achievement, Item Response Theory, Science Education
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