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Measuring the Outcome of At-Risk Stu...

Burns, Dana.

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Measuring the Outcome of At-Risk Students on Biology Standardized Tests When Using Different Instructional Strategies.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Measuring the Outcome of At-Risk Students on Biology Standardized Tests When Using Different Instructional Strategies./
Author:	Burns, Dana.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2017,
Description:	123 p.
Notes:	Source: Dissertation Abstracts International, Volume: 78-09(E), Section: A.
Contained By:	Dissertation Abstracts International78-09A(E).
Subject:	Educational tests & measurements. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10281791
ISBN:	9781369762686

Measuring the Outcome of At-Risk Students on Biology Standardized Tests When Using Different Instructional Strategies.
Burns, Dana.

Measuring the Outcome of At-Risk Students on Biology Standardized Tests When Using Different Instructional Strategies. - Ann Arbor : ProQuest Dissertations & Theses, 2017 - 123 p.

Source: Dissertation Abstracts International, Volume: 78-09(E), Section: A.

Thesis (Ed.D.)--Lindenwood University, 2017.

Over the last two decades, online education has become a popular concept in universities as well as K-12 education. This generation of students has grown up using technology and has shown interest in incorporating technology into their learning. The idea of using technology in the classroom to enhance student learning and create higher achievement has become necessary for administrators, teachers, and policymakers. Although online education is a popular topic, there has been minimal research on the effectiveness of online and blended learning strategies compared to the student learning in a traditional K-12 classroom setting.

ISBN: 9781369762686Subjects--Topical Terms:

3168483
Educational tests & measurements.

Measuring the Outcome of At-Risk Students on Biology Standardized Tests When Using Different Instructional Strategies.
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245 1 0 $a Measuring the Outcome of At-Risk Students on Biology Standardized Tests When Using Different Instructional Strategies.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2017
300 $a 123 p.
500 $a Source: Dissertation Abstracts International, Volume: 78-09(E), Section: A.
500 $a Adviser: Beth Kania-Gosche.
502 $a Thesis (Ed.D.)--Lindenwood University, 2017.
520 $a Over the last two decades, online education has become a popular concept in universities as well as K-12 education. This generation of students has grown up using technology and has shown interest in incorporating technology into their learning. The idea of using technology in the classroom to enhance student learning and create higher achievement has become necessary for administrators, teachers, and policymakers. Although online education is a popular topic, there has been minimal research on the effectiveness of online and blended learning strategies compared to the student learning in a traditional K-12 classroom setting.
520 $a The purpose of this study was to investigate differences in standardized test scores from the Biology End of Course exam when at-risk students completed the course using three different educational models: online format, blended learning, and traditional face-to-face learning. Data was collected from over 1,000 students over a five year time period. Correlation analyzed data from standardized tests scores of eighth grade students was used to define students as "at-risk" for failing high school courses.
520 $a The results indicated a high correlation between eighth grade standardized test scores and Biology End of Course exam scores. These students were deemed "at-risk" for failing high school courses. Standardized test scores were measured for the at-risk students when those students completed Biology in the different models of learning. Results indicated significant differences existed among the learning models. Students had the highest test scores when completing Biology in the traditional face-to-face model. Further evaluation of subgroup populations indicated statistical differences in learning models for African-American populations, female students, and for male students.
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