The Effects of a Computerized-Algebra Program on Mathematics Achievement of College and University Freshmen Enrolled in a Developmental Mathematics Course

References

• “ALEKS” (2001). T.H.E. Journal 28(9). Retrieved October 26, 2002, from http://www.thejournal.com/.
   Google Scholar
• Acelajado, M. J. (2001). The impact of using technology on students' achievement, attitude, and anxiety in mathematics. Retrieved August 12, 2005, from De La Salle University, Manila Philippines Web site: http://www.mathematics.ecnu.edu.cn/earcome3/sym3/Earcome3_Maxima%20J_sym3.doc.
   Google Scholar
• Alkhateeb, H. M. (2004). Internal consistency reliability and construct validity of an Arabic translation of the shortened form of the Fennema-Sherman Mathematics Attitude Scale. Psychological Reports, 94, 565–571.
   PubMedGoogle Scholar
• American Educational Research Association. (2006). Standards for reporting on empirical social science research in AERA publications. Educational Researcher, 35(6), 33–40.
   Google Scholar
• Boylan, H. (2002). What works: Research-Based best practices in developmental education. Boone, NC: National Center for Developmental Education.
   Google Scholar
• Boylan, H., Bonham, B., & Bliss, L. (1994). Who are the developmental students? Research in Developmental Education, 11(2), 1–4.
   Google Scholar
• Boylan, H., & Saxon, P. (2004). Outcomes of remediation: Prepared for the League for Innovation in the Community College. Retrieved May 11, 2005, from Appalachian State University, Boone, NC Web site: http://www.ncde.appstate.edu/reserve_reading/Outcomes_of_Remediation.htm.
   Google Scholar
• Capraro, M. M., Capraro, R. M., & Henson, R. K. (2001). Measurement error of scores on the Mathematics Anxiety Rating Scale across studies. Educational and Psychological Measurement, 61, 373–386.
   Web of Science ®Google Scholar
• Casazza, M. E. (1999). Who are we and where did we come from? Journal of Developmental Education, 23(1), 1–7.
   Google Scholar
• Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum.
   Google Scholar
• Crocker, L., & Algina, J. (1986). Introduction to classical & modern test theory. Belmont, CA: Waldworth Group/Thomson Learning.
   Google Scholar
• Cross, K. P. (1971). Beyond the open door. San Francisco: Jossey-Bass.
   Google Scholar
• Cross, K. P. (1976). Accent on learning. San Francisco: Jossey-Bass.
   Google Scholar
• Dwindell, P. L., & Higbee, J. L. (1991). Affective variables related to mathematics achievement among high-risk college freshmen. Psychological Reports, (69), 399–403.
   Google Scholar
• Fennema, E., & Sherman, J. A. (1976). Fennema-Sherman mathematics attitudes scales: Instruments designed to measure attitudes towards the learning of mathematics by females and males. Journal for Research in Mathematics Education, 7, 324–326.
   Google Scholar
• Goolsby, C. B., Dwindell, P. L., Higbee, J. L., & Bretscher, A. S. (1988). Factors affecting mathematics achievement in high risk college students. Research & Teaching in Developmental Education, 4(2), 18–27.
   Google Scholar
• Henson, R. K. (2001). Understanding internal consistency reliability estimates: A conceptual primer on coefficient alpha. Measurement & Evaluation in Counseling & Development, 34, 177–189.
   Web of Science ®Google Scholar
• Jones, E. D., Wilson, R., & Bhojwani, S. (1997). Mathematics instruction for secondary students with learning disabilities. Journal of Learning Disabilities, 30, 151–163.
   PubMed Web of Science ®Google Scholar
• Keup, J. R. (1998). Using technology in remedial education. Retrieved October 26, 2002, from http://www.gse.ucla.edu/ERIC/eric.html. (ERIC Document Reproduction Service No. ED421180).
   Google Scholar
• Kinney, D. P. (2001). An application of developmental theory in a developmental mathematics program. Journal of Developmental Education, 25(2), 10–18.
   Google Scholar
• Kinney, D. P. (2002a) Implementation models for interactive multimedia software in developmental mathematics. In M. R. Hay & N. L. Ludman (Eds.), 2001 Selected conference papers (pp. 35–40). Dowagiac, MI: National Association for Developmental Education.
   Google Scholar
• Kinney, D. P. (2002b). Students with disabilities in mathematics: Barriers and recommendations. The AMATYC Review, 23(1), 13–23.
   Google Scholar
• Kinney, D. P., & Kinney, L. S. (2002). Instructors' perspectives of instruction in computer-mediated and lecture developmental mathematics classes. In J. L. Higbee, I. M. Duranczyk, & D. B. Lundell (Eds.), Developmental education: Policy and practice (pp. 127–138). Warrensburg, MO: National Association for Developmental Education.
   Google Scholar
• Kinney, D. P., & Robertson, D. F. (2003). Technology makes possible new models for delivering developmental mathematics instruction. Mathematics and Computer Education, 37, 315–328.
   Google Scholar
• Kinney, D. P., Stottlemyer, J., Hatfield, J., & Robertson, D. F. (2004). A comparison of the characteristics of computer-mediated and lecture students in developmental mathematics. Research & Teaching in Developmental Education, (21), 14–28.
   Google Scholar
• Kulik, C. L., & Kulik, J. (1986). Effectiveness of computer-based education in colleges. AEDS Journal, 19, 81–108.
   Google Scholar
• Lundell, D. B., Higbee, J. L., Chung, C., Ghere, D., & Kinney, D. P. (2001). Setting the pace: Theoretical perspectives for developmental education. In M. R. Hay & N. L. Ludman (Eds.), 2001 Selected conference papers (pp. 45–49). Dowagiac, MI: National Association for Developmental Education.
   Google Scholar
• Ma, X. (1999). A meta-analysis of the relationship between anxiety toward mathematics and achievement in mathematics. Journal for Research in Mathematics Education, 30, 520–540.
   Web of Science ®Google Scholar
• Maxwell, W. E. (1979). Improving student learning skills. San Francisco: Jossey Bass.
   Google Scholar
• McDade, R. (2000). No one to waste: A report to public decision-makers and community college leaders. Washington, DC: Community College Press.
   Google Scholar
• National Center for Education Statistics (NCES). (1996). Remedial education in higher education institutions in the fall of 1995. Washington, DC: U.S. Department of Education, Office of Educational Research and Improvement.
   Google Scholar
• National Center for Education Statistics (NCES). (2000). Remedial education at degree-granting postsecondary institutions in fall 2000. Retrieved June 15, 2006, from http://nces.ed.gov/pubs2004/2004010.pdf.
   Google Scholar
• National Center for Education Statistics (NCES). (2003). The condition of education 2003(NCES 2003–067). Washington, DC: U.S. Department of Education.
   Google Scholar
• National Commission on Excellence in Education (NCEE). (1998). A nation still at risk. Retrieved June 15, 2006, from the Thomas B. Fordham Foundation Web site: http://www.fordham.org/library/manifes.html.
   Google Scholar
• National Council of Teachers of Mathematics (NCTM). (1989). Curriculum and evaluation standards for school mathematics. Reston, VA: Author.
   Google Scholar
• National Council of Teachers of Mathematics (NCTM). (2000). Principles and standards for school mathematics. Reston, VA: Author.
   Google Scholar
• Pallant, J. (2001). SPSS survival manual. Buckingham, PA: Open University Press.
   Google Scholar
• Paravate, V., Anjaneyulu, K. S. R., & Rajan, P. (1998). Math magic: An adaptive remediation system for mathematics. The Journal of Computers in Mathematics and Science Teaching, 17, 265–284.
   Google Scholar
• Robert, M. F. (2002). Problem solving and at-risk students: Making “mathematics for all” a classroom reality. Teaching Children Mathematics, 8, 290–295.
   Google Scholar
• Roueche, J., & Roueche, S. (1993). Between a rock and a hard place. The at-risk student in the open door college. Washington, DC: The Community College Press.
   Google Scholar
• Saxon, P., & Boylan, H. (1999). Characteristics of community college remedial students. [Research]. Appalachian State University, The League for Innovation in the Community College.
   Google Scholar
• Schwartz, A. (2000). Axing mathematics anxiety. The Education Digest, 65, 62–64.
   Google Scholar
• Scott, V. (2001). Mathematical mediocrity: The legacy of mathematics education. Principal Leadership [High School Ed.], 2(2), 7–9.
   Google Scholar
• Steele, D. F., & Arth, A. A. (1998). Lowering anxiety in the mathematics curriculum. The Education Digest, 63, 18–23.
   Google Scholar
• Strawser, S., & Miller, S. P. (2001). Mathematics failure and learning disabilities in the postsecondary student population. Topics in Language Disorders, 21(2), 68–84.
   Web of Science ®Google Scholar
• Suinn, R. M., & Winston, E. H. (2003). The Mathematics Anxiety Rating Scale brief version: Psychometric data. Psychological Reports, 92, 167–173.
   PubMed Web of Science ®Google Scholar
• Tapia, M., & Marsh, G. E. (2004). An instrument to measure mathematics attitudes. Academic Exchange Quarterly, 8(2), 16–18.
   Google Scholar
• Texas Education Coordinating Board. (2005). Developmental education data profile. Retrieved May 1, 2008, from http://www.thecb.state.tx.us/.
   Google Scholar
• OS/SuccessInitiatives/DevEd/DEData/.
   Google Scholar
• Thomas, P., & Higbee, J. (1999). Affective and cognitive factors related to mathematics achievement. Journal of Developmental Education, 23(1), 8–16.
   Google Scholar
• Thomas, P. V., & Higbee, J. L. (2000). The relationship between involvement and success in developmental algebra. Journal of College Reading and Learning, 30, 222–232.
   Google Scholar
• Thompson, B. (2003). Score reliability: Contemporary thinking on reliability issues. Thousand Oaks, CA: Sage.
   Google Scholar
• Webb, J., & Hlavaty, J. (1962). National Achievement Test: First Year Algebra Test. Huntsville, AL: Psychometric Affiliates.
   Google Scholar
• Wilkinson, L., & Task Force on Statistical Inference. (1999). Statistical methods in psychology journals: Guidelines and explanations. American Psychologist, 54, 594–604.
   Web of Science ®Google Scholar