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De Los Santos Rodríguez, Sabrina; Martínez-Gudapakkam, Audrey; Storeygard, Judy – Mathematics Teacher: Learning and Teaching PK-12, 2021
The authors' experiences with Latinx families confirm research that shows parents are willing and have the desire to help their children with their mathematics schoolwork (Colegrove and Krause 2016). However, structural barriers make it challenging for Spanish-speaking parents to support their children's mathematics learning. For example,…
Descriptors: Hispanic Americans, Parent Attitudes, Parent Role, Hispanic American Students
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Kelly, Kim; Heffernan, Neil; Heffernan, Cristina; Goldman, Susan; Pellegrino, James; Soffer-Goldstein, Deena – North American Chapter of the International Group for the Psychology of Mathematics Education, 2014
Much debate surrounds the effectiveness of the common educational practice of homework (Cooper et al., 2006). A randomized-controlled trial has shown that using a web-based homework system that provides immediate feedback to students, while they are doing their mathematics homework, and detailed item reports to teachers significantly improves…
Descriptors: Homework, Mathematics Instruction, Educational Technology, Technology Uses in Education
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Kensington-Miller, Barbara; Novak, Julia; Evans, Tanya – International Journal of Mathematical Education in Science and Technology, 2016
This paper describes a case study of two pure mathematicians who flipped their lecture to teach matrix determinants in two large mathematics service courses (one at Stage I and the other at Stage II). The purpose of the study was to transform the passive lecture into an active learning opportunity and to introduce valuable mathematical skills,…
Descriptors: Blended Learning, Mathematics, Professional Personnel, Lecture Method
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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