jeanette g. eggert concordia university – portland, oregon a comparison of online and...
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Jeanette G. Eggert
Concordia University – Portland, Oregon
A Comparison of Online and Classroom-based
Developmental Math Courses
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Developmental Math
Definition: Educational opportunities for students that lack the math skills needed for success in college-level math courses.
Citation
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Students in Developmental Math
Traditional and Non-traditional Previous bad experiences with math Gaps in their background Low self-efficacy High levels of math and test anxiety
Citation
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Math Labs at Concordia
Placement test Four half-semester courses Cover basic skills through
some intermediate algebra topics
Small class size
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Before 2005
Quizzes over each section Large portion of class time spent in
assessment supervision Mastery-based, but time-
sequencing problematic Quiz re-takes placed additional
demands on instructors
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Implementation of Computer-based quizzes
Immediate feedback for students
Increased instructional time
More time for individual help
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Online Math Labs Classroom notes Textbook
resources Quizzes Access to the
instructor Email Phone In-person
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This Study: Problem Statement
Use existing data to compare the effectiveness of online and classroom-based developmental math courses at a four-year liberal arts university.
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Theoretical Framework I
Media Debate Clark – 1983
Delivery truck analogy
Kozma – 1991 Instructional
attributes
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Theoretical Framework II
Instructional alternatives are needed for developmental students.
Citation
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Research Question #1
Is there a significant difference in successful course completion for online and classroom-based sections of the developmental math courses during the stated interval?
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Research Question #2
Is there a significant difference in student satisfaction at the conclusion of each course with regard to their participation in online and classroom-based sections of the developmental math courses during the stated interval?
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Research Question #3
Is there a significant difference in academic achievement in a subsequent college-level math course for those students who participated in online and classroom-based sections of the developmental math courses during the stated interval?
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Study Parameters
Ten semesters: Summer 2005 – Summer 2008, inclusive
Census of all students who completed developmental math courses
Parallel instructional methodologies
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Human Subjects Safeguarding
Existing data Coded to remove student and faculty
identifiers IRB approval
George Fox University Concordia University - Portland
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Data & Analysis: RQ #1Successful Course Completion
N = 718 Classroom n = 357 Online n = 361
Independent samples t - test Levene’s Test for Equality of
Variances
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Results: RQ #1Successful Course Completion Classroom-based
Mean = 0.80; Standard deviation = 0.398 Online
Mean = 0.83; Standard deviation = 0.373 No statistically significant difference
at an alpha level of 0.05 (t = – 1.039, n.s.)
Null hypothesis supported
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Data & Analysis: RQ #2Student Satisfaction N = 222
Classroom n = 100 Online n = 122
Two scales; reliability via Cronbach’s Alpha Satisfaction with course; 6 Likert-scale items Satisfaction with the instructor; 8 items
Independent samples t - test Levene’s Test for Equality of Variances
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Results: RQ #2 - First ScaleSatisfaction with Course Cronbach’s Alpha = 0.942 for the 6
items. Classroom-based
Mean = 25.34; Standard deviation = 6.189 Online
Mean = 26.55; Standard deviation = 4.398 No statistically significant difference at
an alpha level of 0.05 (t = – 1.698, n.s.) Null hypothesis supported
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Results: RQ #2 - Second ScaleSatisfaction with the Instructor Cronbach’s Alpha = 0.971 for the 8
items. Classroom-based
Mean = 37.29; Standard deviation = 6.091 Online
Mean = 37.89; Standard deviation = 4.613 No statistically significant difference at
an alpha level of 0.05 (t = – 0.828, n.s.) Null hypothesis supported
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Data & Analysis: RQ #3College-Level Math GPA
N = 118 Classroom n = 58 Online n = 60
Independent samples t - test Levene’s Test for Equality of
Variances
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Results: RQ #3College-Level Math GPA Classroom-based
Mean = 2.448; Standard deviation = 1.1275 Online
Mean = 2.978; Standard deviation = 0.9076 Statistically significant difference in the
means (t = – 2.818, p < 0.05) Both the null hypothesis and the
alternative hypothesis were rejected
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Summary of Results
No significant difference based on: Successful course completion Student satisfaction
Online instructional delivery was more effective for higher levels of academic achievement in a subsequent college-level math course.
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Implications Supports continuation of both
instructional delivery systems Revise online courses
Mastery-based Hyperlinked
Revise classroom-based courses Utilize web-based options Unique face-to-face opportunities
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Acknowledgments
• My students and colleagues at Concordia University – Portland
• My parents, Richard & Myra Gibeson• My husband, John Eggert• My dissertation committee at
George Fox University:• Dr. Scot Headley• Dr. Terry Huffman• Dr. Linda Samek
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Graphics
• Clip-Art from the Microsoft Collection
• WebCT view from Concordia University’s Online Math Lab course
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References Berenson, S. B., Carter, G., & Norwood, K. S.
(1992). The at-risk student in college developmental algebra. School Science and Mathematics, 92(2), 55-58.
Brown, D. G. (Ed.). (2000) Teaching with technology: Seventy-five professors from eight universities tell their stories. Bolton, MA: Anker Publishing Company.
Brown, D. G. (Ed.). (2003) Developing faculty to use technology: Programs and strategies to enhance teaching. Bolton, MA: Anker Publishing Company.
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References page 2 Clark, R.E. (1983). Reconsidering research on
learning from media. Review of Educational Research, 53(4), 445-459.
Dotzler, J. J. (2003). A note on the nature and history of post-secondary developmental education. Mathematics and Computer Education, 37(1), 121-125.
Duranczyk, I. M., & Higbee, J. L. (2006). Developmental mathematics in 4-year institutions: Denying access. Journal of Developmental Education, 30(1), 22-29.
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References page 3 Hodges, D. Z., & Kennedy, N. H. (2004).
Editor's choice: Post-testing in developmental education: A success story. Community College Review, 32(3), 35-42.
Kinney, D. P., & Robertson, D. F. (2003). Technology makes possible new models for delivering developmental mathematics instruction. Mathematics and Computer Education, 37(3), 315-328.
Kozma, R. B. (1991). Learning with Media. Review of Educational Research, 61(2), 179-211.
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References page 4 Mallenby, M. L., & Mallenby, D. W. (2004).
Teaching basic algebra courses at the college level. Primus: Problems, Resources, and Issues in Mathematics Undergraduate Studies, 14(2), 163-168.
Manto, J. C. (2006). A correlations study of ACCUPLACER math and algebra scores and math remediation on the retention and success of students in the clinical laboratory technology program at Milwaukee Area Technical College. Unpublished master’s thesis, University of Wisconsin – Stout, Menomonie, WI.
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References page 5 Reese, M. S. (2007). What’s so hard about
algebra? A grounded theory study of adult algebra learners. Unpublished doctoral dissertation, San Diego State University – University of San Diego, San Diego, CA.
Tanner, J., & Hale, K. (2007). The “new” language of algebra. Research & Teaching in Developmental Education, 23(2), 78-83.
Weinstein, G. L. (2004). Their side of the story: Remedial college algebra students. Mathematics and Computer Education, 38(2), 230-240.