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Walkington, Candace; Bernacki, Matthew L. – Journal of Experimental Education, 2018
Instruction can be made relevant to students when it draws upon and utilizes their interests, experiences, and "funds of knowledge" in productive ways to support classroom learning. This approach has been referred to as "context personalization." In this paper, we discuss the cognitive basis of personalization interventions,…
Descriptors: Individualized Instruction, Instructional Design, Relevance (Education), Cognitive Processes
Zhao, Manqian; Lapuk, Karen – Mathematics Teacher, 2019
According to the National Center for Education Statistics (2016), the number of public school students in the United States who were English learners (ELs) was estimated at 4.5 million. However, in 2005, the national standardized testing scores (Fry 2007) show that about 51 percent of eighth-grade EL students were behind other students in reading…
Descriptors: Mathematics Education, Mathematics Instruction, English Language Learners, Mathematics Teachers
Lifen, He; Junying, Yong – English Language Teaching, 2016
Perception is the reconstruction and interaction between the new information and prior knowledge in mind or in the process of internalization about the new information. It has three teaching procedures: First, teachers elicit the learners to acquire text meaning. Second, teachers create situation in practical teaching. Third, learners comprehend…
Descriptors: Foreign Countries, Middle Schools, English (Second Language), Second Language Instruction
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection

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