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Smith, Karen G. – ProQuest LLC, 2019
Many adolescents struggle with reading comprehension, despite an emphasis on reading instruction over recent decades. Evidence suggests that informational text is particularly challenging for students. To implement assessments within a multi-tiered framework, schools must have psychometrically adequate tools. Using data of 473 students in Grades 6…
Descriptors: Reading Comprehension, Middle School Students, Grade 6, Grade 7
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Vella, Elizabeth J.; Turesky, Elizabeth F.; Hebert, Jenni – Quality Assurance in Education: An International Perspective, 2016
Purpose: The purpose of this paper is to use a heutagogical approach to determine whether students enrolled in blended courses achieve higher grades relative to those enrolled in completely online courses, in addition to identifying demographic predictors of academic success in college courses involving Web-based modes of instruction.…
Descriptors: Predictor Variables, Grade Point Average, Gender Differences, Blended Learning
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Knezek, Gerald; Christensen, Rhonda; Tyler-Wood, Tandra; Gibson, David – Journal of STEM Education: Innovations and Research, 2015
Data gathered from 325 middle school students in four U.S. states indicate that both male (p < 0.0005, RSQ = 0.33) and female (p < 0.0005, RSQ = 0.36) career aspirations for "being a scientist" are predictable based on knowledge of dispositions toward mathematics, science and engineering, plus self-reported creative tendencies. For…
Descriptors: Middle School Students, Gender Differences, STEM Education, Occupational Aspiration
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Gupta, Sat; Harris, David E.; Carrier, Nellie M; Caron, Paul – College Student Journal, 2006
Most undergraduate programs require completion of a mathematics course, but pass rates in these courses are often low. To determine predictors of student success in 100-level mathematics courses at the University of Southern Maine, we used a questionnaire to collect information on possible predictors of grade (student demographics, attitude,…
Descriptors: College Mathematics, Multivariate Analysis, Educational Experience, Student Attitudes