Engaging Latino Students for Transfer and College Completion
Engaging Latino Students for Transfer and College Completion
A partnership between NSSE and the Center for Community College Student Engagement funded by the Kresge Foundation and the Greater Texas Foundation
As both community colleges and baccalaureate institutions across the US work to improve student success and college completion outcomes, while maintaining and improving the quality of students’ educational experiences, they face persistent and troubling gaps in educational attainment across diverse populations of students. Latinos are the largest and fastest-growing minority population in the US, yet they remain underrepresented and underserved in higher education. Engaging Latino Students for Transfer and College Completion, funded by The Kresge Foundation and Greater Texas Foundation, and conducted by NSSE in collaboration with the Center for Community College Student Engagement (CCCSE) at The University of Texas at Austin and in partnership with Excelencia in Education, focuses on strengthening the engagement and success of Latino students in major urban areas—particularly in California, Michigan, and Texas, states with large and growing urban Latino populations.
Twenty-four institutions from urban locations—that is, 12 pairs of community colleges and baccalaureate institutions—are participants. Among other commitments, selected institutional pairs will bring teams of five leaders from each institution to an intensive 2 1/2-day institute focused on strengthening the engagement, transfer, and college completion of their Latino students. Substantial data work and discussion prior to the institute prepares the teams for development of a collaborative action plan to be implemented on their campuses.
The Latino Student Engagement Institute will provide participating institutions the opportunity to form networks and develop action plans that focus on Latino engagement and success; accreditation projects on efforts to enhance Latino outcomes; improved staffing patterns and roles; and strategies for gathering evidence and monitoring the impact of institutional practices and initiatives.
Project contacts:
Jillian Kinzie, NSSE (jikinzie@indiana.edu)
Kay McClenney, CCCSE (kmcclenney@cccse.org)
The syntax below can be used to reproduce the disaggregated reports NSSE provided to assist in the completion of the Short Term Action Plan.
dataset close all.
*Insert the file path location of your institution's NSSE data sets. get file = 'C:\NSSE\NSSE12 Data (NSSEville).sav'.
add files /file=* /file='C:\NSSE\NSSE11 Data (NSSEville).sav'. execute.
*Selecting first-year and senior students that met NSSE criteria at time of sruvey completion. select if (inelig eq 1). select if any (smpl05, 1, 2, 3). select if any (classran, 1, 4). value labels classran 1 'First-year' 4 'Senior'. variable labels classran ' '.
*Recoding race-ethnicity. numeric race (F4.0). if (race05 eq 3) race eq 1. if (race05 eq 4) race eq 3. if (race05 eq 5 or race05 eq 6 or race05 eq 7) race eq 2. if (missing(race05) and ethnicit eq 1) race eq 1. if (missing(race05) and ethnicit eq 5) race eq 2. if (missing(race05) and ethnicit eq 4) race eq 3. if (race05 eq 10 and ethnicit eq 1) race eq 1. if (race05 eq 10 and ethnicit eq 5) race eq 2. if (race05 eq 10 and ethnicit eq 4) race eq 3. value labels race 1 'Black' 2 'Latino' 3 'White'. execute.
*Recoding gender. numeric sex2 (F4.0). if (sex eq 2) sex2 eq 0. if (sex eq 1) sex2 eq 1. if (missing(sex) and gender eq 2) sex2 eq 0. if (missing(sex) and gender eq 1) sex2 eq 1. value labels sex2 0 'Female' 1 'Male'. execute.
*Creating transfer status. numeric transfer (F4.0). if (enter eq 1) transfer eq 0. if (enter eq 2) transfer eq 1. value labels transfer 0 'Non-transfer' 1 'Transfer'. execute.
*Recoding time spent preparing for class item into hours per week. recode acadpr01 (1=0) (2=3) (3=8) (4=13) (5=18) (6=23) (7=28) (8=33) into acadprhrs. variable labels acadprhrs 'Hours per week spent preparing for class'. execute.
*Recoding writing items into composite writing score. recode writemor (1=0) (2=62.5) (3=187.5 ) (4=387.5) (5=625) into wpg3. recode writemid (1=0) (2=30) (3=90) (4=186) (5=300) into wpg2. recode writesml (1=0) (2=6.25) (3=18.75) (4=38.75) (5=62.5) into wpg1. execute.
numeric writpgs (F4.1). compute writpgs = wpg3 + wpg2 + wpg1. variable labels writpgs 'Estimated number of pages written'. execute.
*Recoding service learning into done (at least some) and not done. recode commproj (1 = 0) (2 thru 4 = 1) (else eq sysmis) into srvlrn. value labels srvlrn 0 'not done' 1 'done'. execute.
*Recoding learning community into done and not done. recode lrncom04 (1 thru 3= 0) (4 = 1) (else eq sysmis) into lerncom2. value labels lerncom2 0 'not done' 1 'done'. execute.
*Recoding research with faculty into done and not done. recode resrch04 (1 thru 3= 0) (4 = 1) (else eq sysmis) into resear2. value labels resear2 0 'not done' 1 'done'. execute.
*Recoding internship into done and not done. recode intern04 (1 thru 3= 0) (4 = 1) (else eq sysmis) into intern2. value labels intern2 0 'not done' 1 'done'. execute.
*Recoding study abroad into done and not done. recode stdabr04 (1 thru 3= 0) (4 = 1) (else eq sysmis) into studyab2. value labels studyab2 0 'not done' 1 'done'. execute.
*Recoding culminating senior experience into done and not done. recode snrx04 (1 thru 3= 0) (4 = 1) (else eq sysmis) into seniorx2. value labels seniorx2 0 'not done' 1 'done'. execute.
*Dichotomizing exams to get percent that rated exams as "highly challenging". numeric dexams (F4.0). if (exams ge 6) dexams eq 1. if (exams le 5) dexams eq 0. value labels dexams 0 'Low challenge' 1 'High challenge'. execute.
*Dichotomizing envschol to get percent that said institution emphases studying and academic work "substantially". numeric denvschol (F4.0). if (envschol ge 3) denvschol eq 1. if (envschol le 2) denvschol eq 0. value labels denvschol 0 'Not Substantial' 1 'Substantial'. execute.
*Dichotomizing entirexp to get percent that rated their entire educational experience as "Good or Excellent". numeric dentirexp (F4.0). if (entirexp ge 3) dentirexp eq 1. if (entirexp le 2) dentirexp eq 0. value labels dentirexp 0 'Poor/Fair' 1 'Good/Excellent'. execute.
*Dichotomizing samecoll to get percent that said they would return to the same school if they could start over. numeric dsamecoll (F4.0). if (samecoll ge 3) dsamecoll eq 1. if (samecoll le 2) dsamecoll eq 0. value labels dsamecoll 0 'No' 1 'Yes'. execute.
*Full-time status from enrlment variable. numeric fulltime (F4.0). if (enrlment eq 2) fulltime eq 1. if (enrlment eq 1) fulltime eq 0. value labels fulltime 0 'Part-time' 1 'Full-time'. execute.
*Setting the following variables to scale level in order to produce a mean. variable level ACa ACL SFI EEE SCE acadprhrs writpgs (scale).
*If you would like to export your SPSS output into Excel, unstar the following lines of syntax (oms & omsend), and insert the file path of where you would like the file saved. *oms /select tables /IF SUBTYPES = ["Custom Table"] /destination format = xls outfile ='C:\Desktop\Engaging_Latinos_NSSEville_11-12.xls'.
*Insert the file path location of your institution's 2013 NSSE data set. get file = 'C:\NSSE\NSSE13 Data (NSSEville).sav'.
*Selecting first-year and senior students that met NSSE criteria at time of sruvey completion. select if (eligible eq 1). select if any (sample, 1, 2, 3). select if any (IRclass, 1, 4). value labels IRclass 1 'First-year' 4 'Senior'. variable labels IRclass ' '. execute.
*Recoding race-ethnicity. numeric race (F4.0). if (re_latino eq 1) race eq 2. if (re_latino eq 0 and re_all eq 3) race eq 1. if (re_latino eq 0 and re_all eq 6) race eq 3. if (missing(re_all) and IRrace eq 3) race eq 1. if (missing(re_all) and IRrace eq 4) race eq 2. if (missing(re_all) and IRrace eq 6) race eq 3. if (re_all eq 9 and IRrace eq 3) race eq 1. if (re_all eq 9 and IRrace eq 4) race eq 2. if (re_all eq 9 and IRrace eq 6) race eq 3. value labels race 1 'Black' 2 'Latino' 3 'White'. execute.
*Recoding gender. numeric sex (F4.0). if (gender eq 0) sex eq 0. if (gender eq 1) sex eq 1. if (missing(gender)) sex eq IRgender. value labels sex 0 'Female' 1 'Male'. execute.
*Creating transfer status. numeric transfer (F4.0). if (begincol eq 0) transfer eq 0. if (begincol eq 1) transfer eq 1. value labels transfer 0 'Non-transfer' 1 'Transfer'. execute.
*Recoding service learning into done (at least some) and not done. recode servcourse (1 = 0) (2 thru 4 = 1) (else eq sysmis) into servcourseR. value labels servcourseR 0 'not done' 1 'done'. execute.
*Recoding learning community into done and not done. recode learncom (1 thru 3= 0) (4 = 1) (else eq sysmis) into learncomR. value labels learncomR 0 'not done' 1 'done'. execute.
*Recoding research with faculty into done and not done. recode research (1 thru 3= 0) (4 = 1) (else eq sysmis) into researchR. value labels researchR 0 'not done' 1 'done'. execute.
*Recoding internship into done and not done. recode intern (1 thru 3= 0) (4 = 1) (else eq sysmis) into internR. value labels internR 0 'not done' 1 'done'. execute.
*Recoding study abroad into done and not done. recode abroad (1 thru 3= 0) (4 = 1) (else eq sysmis) into abroadR. value labels abroadR 0 'not done' 1 'done'. execute.
*Recoding culminating senior experience into done and not done. recode capstone (1 thru 3= 0) (4 = 1) (else eq sysmis) into capstoneR. value labels capstoneR 0 'not done' 1 'done'. execute.
*Dichotomizing exams to get percent that rated exams as "highly challenging". numeric dchallenge (F4.0). if (challenge ge 6) dchallenge eq 1. if (challenge le 5) dchallenge eq 0. value labels dchallenge 0 'Low challenge' 1 'High challenge'. execute.
*Dichotomizing envschol to get percent that said institution emphases studying and academic work "substantially". numeric dempstudy (F4.0). if (empstudy ge 3) dempstudy eq 1. if (empstudy le 2) dempstudy eq 0. value labels dempstudy 0 'Not Substantial' 1 'Substantial'. execute.
*Dichotomizing entirexp to get percent that rated their entire educational experience as "Good or Excellent". numeric devalexp (F4.0). if (evalexp ge 3) devalexp eq 1. if (evalexp le 2) devalexp eq 0. value labels devalexp 0 'Poor/Fair' 1 'Good/Excellent'. execute.
*Dichotomizing samecoll to get percent that said they would return to the same school if they could start over. numeric dsameinst (F4.0). if (sameinst ge 3) dsameinst eq 1. if (sameinst le 2) dsameinst eq 0. value labels dsameinst 0 'No' 1 'Yes'. execute.
*Setting the following variables to scale level in order to produce a mean. VARIABLE LEVEL HO RI QR LS CL DD SF ET QI SE coursenum tmprephrs wrpages (scale).
*If you would like to export your SPSS output into Excel, unstar the following lines of syntax (oms & omsend), and insert the file path of where you would like the file saved. *oms /select tables /IF SUBTYPES = ["Custom Table"] /destination format = xls outfile ='C:\Desktop\Engaging_Latinos_NSSEville_2013.xls'.
*Ctables commands to produce report output. CTABLES /TABLE (HO + RI + QR + LS + CL + DD + SF + ET + QI + SE + tmprephrs + wrpages + coursenum) [MEAN F4.1 VALIDN] BY IRclass > (race + sex + transfer).
