Jeanette G. Eggert Concordia University – Portland, Oregon

1. Jeanette G. Eggert Concordia University – Portland, Oregon A Comparison of Online and Classroom-based Developmental Math Courses

2. Developmental Math Definition: Educational opportunities for students that lack the math skills needed for success in college-level math courses. Citation

3. 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

4. Math Labs at Concordia • Placement test • Four half-semester courses • Cover basic skills through some intermediate algebra topics • Small class size

5. 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

6. Implementation of Computer-based quizzes • Immediate feedback for students • Increased instructional time • More time for individual help

7. Online Math Labs • Classroom notes • Textbook resources • Quizzes • Access to the instructor • Email • Phone • In-person

8. 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.

9. Theoretical Framework I Media Debate • Clark – 1983 • Delivery truck analogy • Kozma – 1991 • Instructional attributes Citation

10. Theoretical Framework II Instructional alternatives are needed for developmental students. Citation

11. 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?

12. 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?

13. Research Question #3 Is there a significant difference in academic achievement in a subsequent college-level mathcourse for those students who participated in online and classroom-based sections of the developmental math courses during the stated interval?

14. Study Parameters • Ten semesters: Summer 2005 – Summer 2008, inclusive • Census of all students who completed developmental math courses • Parallel instructional methodologies

15. Human Subjects Safeguarding • Existing data • Coded to remove student and faculty identifiers • IRB approval • George Fox University • Concordia University - Portland

16. 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

17. 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

18. 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

19. 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

20. 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

21. 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

22. 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

23. 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.

24. 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

25. 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

26. Graphics • Clip-Art from the Microsoft Collection • WebCT view from Concordia University’s Online Math Lab course

27. Contact Information Jeanette Eggert jeggert@cu-portland.edu

28. 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.

29. 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.

30. 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.

31. 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.

32. 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.