This quasi-experimental study focused on the initiatives undertaken by a community college's Academic Skills Enhancement Program (ASEP) commonly known as the Developmental Education Department to find an alternative delivery method to aid its students in learning developmental mathematics. Moreover, this study (1) conducted a comparative literature review on multimedia solutions used in developmental mathematics; (2) assessed the impact of the ICL software on actual and perceived student learning in developmental mathematics; (3) utilized Solomon's Four Group to assess for pretest sensitization; (4) identified variables for predicting student grades; (5) recommended methods for assessing data gathered in S4G; (6) expanded previous research of students perceived learning to developmental mathematics and identified two more factors to measure perceived learning; and (7) provided best practices for identifying and implementing technology for teaching and learning developmental mathematics. The study sample was students enrolled in a Community College in south Louisiana (CCsL) who tested into developmental mathematics according to the ACT Computer-Adaptive Placement and Support System (COMPASS). The study used four intact classes taught by two instructors. Students were oriented and advised on their preparedness for the instructional delivery method chosen through conference structured by the Conducive for Lifestyle Delivery Suggestion (CLDS) questionnaire. The computer-assisted courses have a maximum of 30 students per course while the FTF courses have a maximum of 20 students per course. A pilot study was conducted in 2005, N = 4,273 and n = 573 for Foundations of College Mathematics students; n = 742 Elementary Algebra students and n = 566 Intermediate Algebra students. An analysis of variance was conducted to compare mean scores of students receiving instruction from I CAN Learn[TM] and face-to-face instruction. The findings from the pilot provided several suggestions for implementation and improving the developmental mathematics program and this study. The study used four intact classes taught by two instructors. Since students select their delivery method and schedule; they were asked to complete a survey intended to assess their readiness for computer-assisted instruction. Solomon's Four-Group Design was used to rule out pretest sensitization. A 4 x 4 x 4 x 4 x 4 mixed design ANOVA was used to assess the difference in student mean scores. A significant difference was not found among the students' mean Student Self-Assessment (SSA)/Conducive for Lifestyle Delivery Suggestion (CLDS) scores (F (3, 45) = 2.105, p greater than 0.05. Then a series of assessments for pretest sensitization were conducted on student mean scores. Test A showed no significant difference was found (F (3, 45) = 1.079, p = 0.356. Test E or a one-way ANCOVA was calculated to examine the effect of treatment on the posttest, co-varying out the effect of pretest. The main effect of treatment was not significant (F (1, 23) = 1.419, p = 0.246). Therefore, Test H or independent samples t test was calculated. No significant difference in students' mean scores were found (t (24) = 1.623, p = 0.673. Finally, Test I or Stouffer's Z was calculated. The results from Stouffer's Z, p = -0.203, documented that no pretest sensitization was present. A 4 x 4 x 4 x 4 x 4 mixed design ANOVA was computed comparing students mean scores for perceived learning by groups. A significant difference was (F (3, 45) = 4.290, p = 0.01). A one-way ANOVA was computed comparing the students' mean scores for a final course grade which is actual learning. A statistically significant difference was found among the groups' mean scores for students' actual learning (F (1, 50) = 4.291, p = 0.043). The effect size was 0.73. S4G ruled out pre-test sensitization. Faculty provided qualitative input for this research by answering questions regarding their experiences teaching students in developmental mathematics courses. Although, the faculty members did recommend the ICL technology as a tool to impart knowledge they did not feel as if this technology would accommodate every students' learning needs. A multiple linear regression was calculated to predict students final course grades based on their mean scores for Student Self-Assessment, Pre/Post Test, Student Satisfaction, and Perceived Learning. A significant equation was found (F (6, 42) = 13.241, p less than 0.001, with an R[superscript 2] of 0.654. This study concluded with recommendations for future research and the meaning of the findings. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]