DMCA
STUDENT ENGAGEMENT AND ACADEMIC ACHIEVEMENT IN TECHNOLOGY ENHANCED AND TRADITIONAL CLASSROOM ENVIRONMENTS (2014)
BibTeX
@MISC{Johnson-smith14studentengagement,
author = {Tomeko Rene Johnson-smith and Tomeko Johnson-smith},
title = {STUDENT ENGAGEMENT AND ACADEMIC ACHIEVEMENT IN TECHNOLOGY ENHANCED AND TRADITIONAL CLASSROOM ENVIRONMENTS},
year = {2014}
}
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Abstract
The purpose of this study was to determine the extent to which student engagement and academic achievement were associated with exposure to different modes of instruction; specifically technology enhanced environments vs. traditional FACE-TO-FACE environments. A cross-sectional survey was conducted in October 2013 at a local community college in Charlotte, NC. The Class Level Survey of Student Engagement (CLASSE) was administered to collect valid and reliable variables relating to student engagement from a convenience sample consisting of 80 volunteers enrolled in the Medical Science and Science divisions. Other variables were collected using the Demographic Questionnaire, and the Instructional Environment Questionnaire. The community college also provided secondary archival data consisting of the frequency distributions of grades achieved by 4102 students in October 2013. The cross-sectional survey revealed that students may be more engaged by technology than by traditional FACE-TO-FACE instruction; however, educational practices such as preparing for classes, taking notes, outside reading, and doing homework, with low levels of absence were relatively more important predictors of student engagement than the use of technology. Analysis
Keyphrases
student engagement cross-sectional survey medical science educational practice local community college science division community college class level survey academic achievement traditional face-to-face environment traditional face-to-face instruction convenience sample demographic questionnaire instructional environment questionnaire environment v secondary archival data reliable variable low level frequency distribution different mode important predictor
