Profile of secondary program completers at Redbud Technology Center.

摘要

The purpose of this study was to manage and analyze quantitatively the archived data which would lead to the profile and description of secondary student completers at Redbud Technology Center (RTC). The research question asked: what are the characteristics of successful program completers for secondary students at RTC for the 2005-2006 school years? The basic design approach for this study were descriptive statistics which to establish a baseline for the collusion of and reference for future use of the data RTC has on file. Participants of this study were 103 secondary students at RTC who completed their program in the years 2005-2007; and had a complete set of data of program, gender, attendance, grade, economic status, race, complete scores of Prepare Learn ACT Now (PLAN) test, complete scores of KeyTrain, and complete scores of WorkKeys. Although RTC offers 24 programs to secondary students, participants in this study completed their education from 12 programs only. They were Air Conditioning/Refrigeration, Automotive Technology, Cosmetology, Collision Repair Technology, Culinary Arts, Drafting, Health Careers, Masonry, Manufacturing Technology, Pre-Engineering Technology, Residential/Commercial Construction, and Welding.;For data analysis, the researcher used archival data provided by RTC. The findings of profile student completers in each program and an overall average program were presented in chapter IV. The secondary student completers for the years 2005-2006 and 2006-2007 can be profiled as students who had (1) attendance ranging from 87.3 to 98.9 percent; (2) grade ranging from 2.6 to 4; (3) PLAN scores of composite total ranging from 13.2 to19.4; (4) Keytrain scores of mathematics ranging from 3.5 to 5.5, locating information ranging from 3.9 to 5.5, reading for information ranging from 3.8 to 5.6; and WorkKeys scores of mathematics ranging from 3.6 to 6, locating information ranging from 3.3 to 4.5, reading for information ranging from 3.6 to 5.6. The need to use and understand large data sets, such as the data presented in this study, is imperative for programs to improve and keep pace with a rapidly changing workplace.