Recent Research Reports
This paper has links to the research papers included in the topics below that trace out the experience of LaGuardia students and the college’s limited success in supporting students along the path to graduation. The papers highlight the role of the college in transforming students from uncommitted learners to serious, successful graduates. The paper ends with a discussion of the need for further research.
In this report we examine the academic record of students who took more than two courses or nine equated credits, contrary to normal LaGuardia policy (most had permission, however). These students represent only 3% of all students taking Session 2 courses. We examined the GPA of students enrolled in the 2010-11 academic year. These students, who self-select for a high course or credit load in Session 2, appear to be doing well academically, while earning more credits and moving closer to graduation.
In this report we found that 20% of the students registered for LaGuardia classes in Spring 2012 had registered for at least one course that did not fulfill any of their degree requirements, according to the DegreeWorks data fields. In this report we show the proportion of students who are taking non-required courses within each academic major.
In this study we looked at a group of students who began together as a freshmen cohort and made steady progress, but some of whom then slowed down. Even though all students had earned at least 30 credits after three semesters, those who then earned fewer than 12 credits in their fourth semester (but more than zero), were 16% less likely to either be retained or graduate in the fifth semester. Slowing down may be a sign of approaching difficulty for some students.
This paper describes an interactive model that simulates retention data from LaGuardia Community College and the College of Staten Island. The model mathematically mimics the findings in Michalowski’s interview-based research on LaGuardia students: 1) Stressful life events happen to everyone at about the same rate; 2) A low level of preparation makes it harder to stay in college and graduate; 3) Students who experience an intervention are more likely to graduate; and 4) The more a student studies, the more likely it is that the student will graduate. The model may be used to help students and advisors understand the relationship between time spent studying, working and seeking help and probabilities of graduation.
This report presents the relationships between absence rates, GPA and next semester return rates. We show that rates of absence from classes negatively correlate with GPA for those college-level classes in which attendance was regularly taken. Rates of absence and GPA separately and together predict whether a student will return for the next semester. In fact, GPA and absence rate combined predict return rates quite well. Non-return is very well predicted by very high rates of absence and low GPA, but few students in any semester are in that category. When GPA is high and absence rates low, non-academic factors still come into play and predicting retention is compromised.
In this study we examine the last date of attendance of students in the Fall 2011 semester who failed to return for the Spring 2012 semester (and who did not graduate or transfer). The results show that the great majority of students decide to stop attending after the end of the semester. Loses during the semester are smaller, but not trivial, however.
In this study we demonstrate that students who eventually dropout are much more likely in any given semester to be taking one or more semesters off in their academic careers, compared to those who eventually graduate. Stopping out and attending part-time appear to be symptoms of pressures that will eventually prevent a student from graduating. A third symptom that may also be related to the amount of time available for school and studying is cumulative GPA. We also show how financial pressures appear to be a primary motivating force for students to stop out.
For this study we asked students why they had not registered for the coming semester, three weeks in advance of the first day of classes. We targeted students who were enrolled in the current semester. Approximately half who did not intend to register gave finances as the primary reason. About one-quarter had difficulties with LaGuardia, and another one-quarter had academic or life challenges beyond LaGuardia.
This report examines the one-semester return rate of enrolled degree students with GPAs greater than or equal to 3.00. We found that in every semester around 15% of this high GPA students did not return in the follow semester and never graduated.
At LaGuardia, most entering students are asked to take an initial questionnaire to identify areas in which they need extra help. The survey results can be used to shape and implement intervention efforts. In this paper we study the impact of help-seeking behavior on students' retention. After controlling for demographic variations and academic preparation, we found that students more willing to ask for assistance were more likely to be retained to the following semesters. Help-seeking was also positively associated with other longer-term retention predictors, such as grade point average and first semester credits earned.
In this video we compare students who are required to take differing numbers of developmental or pre-college-level (non-degree) courses. The more courses a student must take at the developmental level, the less likely the student is to graduate. We tested several theories as to why this might be. We found that developmental students do not drop out any faster than non-developmental students, nor do they have lower GPA's. They do, however, take longer to accumulate credits toward a degree, exposing them to the same problems that all our students face each semester on their way to graduation. The longer the path, the higher the exposure.
In this study we looked at New York State Department of Labor wage records of LaGuardia students. Among LaGuardia degree students beginning as freshmen, employment and constant dollar wages fell from 2004 to 2012, when the number of semester enrolled at LaGuardia was held constant. Nevertheless, students who began as freshmen became increasingly more likely to be employed, and they appeared to work more hours, the longer they attended LaGuardia. Students who were not working appeared more likely to graduate in any given semester.
In this paper we look at differences in drop-out rates (defined as not returning the following fall semester) among first-year students by first-year courses taken. We first looked for courses with high numbers of students who dropped out after taking each course and high numbers of students who dropped out after failing the course. We then looked for courses where the rate of dropping out was high after failing the course, indicating that course failure was somehow communicating to students that they should not be in college. We also looked at these rates normalized after deducting the rate for those who passed the course. We also re-ran the rates excluding failures where the student stopped attending and received a WU, failing grade. While freshman seminar and developmental course failure lead to large numbers of students dropping out, introductory courses in the humanities and social sciences had the highest net rates of drop out after failure. These courses may be particularly disheartening for students to fail.
Challenges that students face because of prior academic preparation and time availability to study for and attend classes add greatly to the probability of dropping out, especially in the first two semesters. Even students not facing any of these challenges are dropping out in later semesters at a rate that approaches seven percent of the remaining cohort each semester. This study examines true drop outs, excluding early transfers and stop outs from those considered to be dropping out. First-time students with a higher GPA, going full-time and not needing any developmental courses were considered to be "doing well."
Most students at LaGuardia exhibit warning signs that they are under the sorts of stresses that can cause them to drop out. This essay details some of these warning signs and measures the retention rates associated with them singly and in combination. Improving retention may rest on how systematically the college is able to respond to these symptoms of stress. The warning signs studied include: skipping orientation, registering in the last few weeks before the start of the semester, avoiding freshman seminar, attending part-time, being absent from all classes, lower GPA, and not receiving financial aid after receiving it in the previous semester.
In this study the connection between late registration behavior and lower term GPA is demonstrated after controlling for demographic and time variables.
In this study the numbers of students continuing to register late is demonstrated.
In this paper we look at the probability that a student will not return if they have not yet registered by week during the registration period for Spring 2015. As registration continues, the concentration of non-returning students increases in the not-yet-registered pool. By the tenth week of registration, more than half the not-yet registered students will not return. These statistics have implications for “last ditch” retention efforts. Any outreach program targeted to not-yet-registered students has a high probability of finding a student intent on discontinuing his or her schooling.
In this analysis we examine whether return rate varied by when students took classes. Evening only students appeared to have a disadvantage until we controlled for part-time status. Even after controlling for part-time status, however, men who took only evening classes and were part-time had a lower return rate than day only part-time, male students. We postulate that this disadvantage may result from the lower help-seeking characteristic of men and the lesser availability of services in the evening.
Fifty-nine percent of the Fall 2015 degree students who did not graduate either Fall 2015 or Spring 2016 returned for classes in Fall 2016. In this paper we show the return rates for various categories of students. Lower return rates are seen for part-time, male, and new students. Students who owed money to the college at the end of Fall 2015 also had some of the lowest return rates.
In this study we show the large number of students who withdraw from all course at the beginning of the semester. In this study we attempt to show the timing of student decisions to leave college.
In this report we explore data generated by the SEMS (Student Enrollment Management System), the college’s office check-in system. Each check-in generates a “ticket.” The tickets analyzed were generated during the academic year 2015-16. The report answers questions like: How many students visited a particular office or lab? How long was the average visit? What was their return rate to the next semester? What was the most common reason for the visit? What “Reasons” are associated with the lowest return rates?
In this paper we examine a number of possible definitions of momentum. In terms of course load, the paper notes that the decline in load comes almost entirely from ceasing to take developmental courses after the initial semesters. The average student takes about three three-credit college level courses each semester with no decline in college-level load.
This paper gives data on course failure by level (31% of all below-100 level courses end in failure), credit load of the courses, department, credit load of the student, and student major. During Fall 2015 and Spring 2016, 16% of all course attempts ended in failure. The data on student credit load gives some weight to the argument that students should take heavier loads, although the causality is not clear. If students are making decisions about how to balance the demands of their lives and pass courses, then students taking heavier loads are making better decisions.
This paper demonstrates the connection between passing classes and one-semester return (or graduation). Only 29% of students who failed to pass any classes returned, while 90% of students who passed four classes returned the next semester. Return is less sensitive to the proportion of classes passed than it is to the number passed.
In this study we develop the results of 50 interviews of students who dropped out, stopped out or changed from full-time to part-time attendance. The study documents the kinds of pressures that caused students to lower their enrollment intensity. While all students described on-going pressures, in many cases a crisis event precipitated the need to decrease time at school. These events are called critical junctures. The study notes that many of these critical junctures are viewed by these students as problems created by LaGuardia.
In this paper we show that the primary reasons that students do not earn 15 degree credits each semester are 1) attending part-time, 2) taking developmental courses, and 3) failing degree courses. We show that stopping out and taking moot courses have a much smaller impact.
Only 22% of LaGuardia’s 2,227 graduates from 2010‐11 were counted in any CUNY Performance Management Report’s six‐year graduation rate measure, because of disqualifications of transfer students, spring semester start dates, time to graduation, and initial part-time status. The paper also examines the role of various predictors of the number of semesters necessary to graduate, including test results, average credit load, GPA, financial aid, the number of majors, and the number of failed courses.
In this report we examine the disposition of the 45% of students who began the Fall 2010 semester with at least 45 earned credits and did not graduate within two semesters. Slow rates of earning credits (part-time status) meant that many of these students are still attending. Nevertheless, 14% who began with at least 45 credits transferred to another college during the year, while 10% stopped attending.
The six-year graduation rate of new students (freshmen and transfer-in students) for Fall 2005 is 27.2%. Students who tested out of basic skill requirements graduated at a 36.6% rate, while those requiring basic skills coursework graduated at a 23.1% rate. We also discuss a failed attempt to find comparable national data.
This report notes the declining proportion of students who come to LaGuardia with a GED. This report also notes that students with GEDs are less likely to graduate than students with a high school diploma, although that gap may be decreasing. The study indicates that inferior math preparation is the cause of the gap and that GED math preparation may be improving.
This video presents statistics on graduation rates for students in a cohort and then the rates for this cohort split into two groups : those who end their LaGuardia career with a 2.00 GPA or better and those who end with a GPA under 2.00. It ends with a look at how these graduation rates would have to change to move LaGuardia toward a goal of a 50% improvement (4 1/2 minutes).
This video presents statistics on graduation rates for students in a cohort and then the rates for this cohort split into two groups : those who end their LaGuardia career with a 2.00 GPA or better and those who end with a GPA under 2.00. It presents the numbers of students by semester of enrollment who must be helped to stay in college in order to meet this goal (2 1/2 minutes).
Using semester by semester reports from the National Clearinghouse on the Fall 2005 new student cohort, we determined whether members of the cohort were enrolled and whether they had graduated. Besides the 28% who graduated from LaGuardia, another 8% had graduated from other institutions without having graduated from LaGuardia first. Although eight years have gone by, 10% of that cohort is still enrolled without degrees. The potential graduation rate is therefore 46%, if all those still enrolled graduate.
In this study we show that, if all students who tried twice to pass their developmental courses and failed had passed instead and gone on to graduation, our graduation rate would increase by six percentage points. Far larger numbers of students drop out before trying twice to pass developmental requirements, while many also drop out after successfully completing their developmental requirements.
Enrollment and GPA data on 1,452 Spring 2014 graduates was used to measure time to graduation. Students who changed major outside of their original major Council (a group of similar majors, grouped together for advising purposes) required 1.5 more active semesters to graduate for each major change. Students with lower GPA's also tended to change majors more often. Students majoring in the Health Sciences tended to take longer to reach graduation, regardless of the number of major changes.
Students from the Fall 2009 ESL cohort who graduated from US high schools had a lower six-year graduation rate than students in that ESL cohort who came with a foreign diploma, especially those on a student visa. The placement of these students into ESL levels was similar.
In this study we examine the rates at which students who began in fall 2010 semester accumulated credits and quality points (credits times course grade) by their outcome six years later: graduate; early transfer; still attending; or drop out. The most important finding of the paper is the wide difference between those who graduate and the other groups, beginning with the first semester, in the accumulation of credits and the level of GPA. Those who graduate also appear to get developmental requirements out of the way quickly.
In this study we look at the graduation rate of students who began as first-time, full-time students, stayed for at least three semesters, and never changed major after the third semester. Although earlier research showed a longer time to graduation for those who change majors, the actual graduation rate among this group was higher for those who changed majors twice in three semesters and lowest for those who never changed. Changing majors may signal that a student is actively seeking a successful path to graduation.
In this paper we show that although the majority of LaGuardia graduates “start fast and run hard,” 30% of the 2015-16 LaGuardia graduates either began part-time, began with a first-semester GPA below 2.00 or took more than six years to graduate. If these students represent a successful transformation against the odds, then we begin with about half our new students needing a transformation and succeed with about one in five.
In this paper we show that the one-year increase in the LaGuardia three-year graduation rate of students who began as first-time, full-time was largely a result of the increase in ASAP and CUNYStart populations in the Fall 2012 cohort, compared to Fall 2011. The ASAP cohort has a much higher three-year graduation rate, while CUNYStart’s effect seems to be the removal of students from the cohort who would have left after one semester had they directly entered a degree-seeking cohort. (While CUNYStart’s effect appears slightly positive on those who matriculate, see “Using a Uniform Retention Assessment Methodology on Interventions and Other Identifiable Groups,” p. 2, the program has not been in existence long enough with enough students enrolled to show up in graduation rate statistics.)
In this set of tables, we present data on student characteristics by major, including: proportions by gender, proportions by race ethnicity, average proportion full-time, average credits attempted, average equated credits attempted, average age, average proportion foreign born, average proportion non-native English speakers, average cumulative GPA, average credits earned, average credits attempted, proportion of students with transfer credits, earned credits distribution, proportion passing each developmental test, proportion passing all developmental tests, and proportions of students changing in and out of each major.
In this paper we examine the number and timing of major changes by the new student cohort from Fall 2005 over their first six years at LaGuardia. Students in this cohort had on average 1.4 majors during the six years. Only 13% changed major after the start of the second semester. Liberal Arts majors did not dominate the “change out” statistics among student major changes.
This paper combines the results of two other papers detailing progress-toward-degree measures (also shown in this section of the IR&A website). A simple scoring mechanism was used in this paper to rank the success of various academic majors in moving students toward their degree. The measures include average rates of student graduation within a year, retention to the next year and earned credit accumulation.
This paper shows the success of various academic majors in graduating or retaining students during the academic year 2010-11. Students were grouped according to credits earned at the start of the year. The measure for students beginning with 45 or more credits was graduation within the year. Retention to Fall 2011 was added for students in brackets with beginning earned credit levels below 45.
This paper gives the average rate of credit accumulation over two semesters by major. To make comparisons among majors more relevant, students who began within certain credits-earned levels were examined separately. For the categories below 30 credits, credit accumulation measures included equated credits, allowing the inclusion in the comparison of students making progress against developmental requirements in the two lower brackets.
In this report we show the average number of credits, including developmental and failed credits, a graduate attempts and earns by major, as well as the number of credits earned by the average graduate at other institutions. The graduates in some majors take larger numbers of developmental courses. The number of credits lost to failure also varies by major.
A goal of the Tortora Silcox Family Foundation grant of scholarship funding for students approaching graduation who face potential financial barriers is to raise graduation rates of students within 15 credits of graduation and to assist in building advising teams made up of faculty and advisors to these students. These tables show the history of cumulative graduation rates by council (the guiding group for a collection of teams for each major) for each cohort that enters the "within 15 credits of graduation" realm.
In this presentation we discuss how we developed a formula to predict the probability that any group of students will return or graduate in two semesters. We used three semester cohorts of students and stepwise logistic regression to develop the predictive model. We then used the model to demonstrate the effectiveness of interventions by area and by advising teams focused on particular majors. In many cases the work of the intervention had a positive effect and the Fall 2014 students returned to Fall 2015 at rates higher than predicted. We are also using the model to set targets for advising teams and other intervention projects with Fall 2015 degree students.
We matched a random sample of Fall 2009 students against 87 Federal Work Study (FWS) program students enrolled that semester. The return/graduation rate of the FWS students was 77%, while the return rate for the control group was 74%. The random sample was selected to have a proportionally similar distribution among ranges of GPA, F-1 visa status, basic skills requirement completion, 2009-10 credit load, earned credit level, and financial aid award.
We matched a random sample of Spring 2011 students against 631 College Discovery program students enrolled that spring semester. The one-semester return/graduation rate of the CD students was 79%, while the return rate for the control group was 74%. The random sample was selected to have a proportionally similar distribution among ranges of GPA, F-1 visa status, basic skills requirement completion, earned credit level, Spring 2011 credit load, and financial aid award.
We matched a random sample of Fall 2010 students against 214 students employed part-time (for at least two weeks during the 2010‐11 school year) on campus (but not employed in the Federal Work Study program) and enrolled that semester. The one-year return/graduation rate of the on-campus-employed students was 86%, while the return rate for the control group was 77%. The random sample was selected to have a proportionally similar distribution among ranges of GPA, F-1 visa status, basic skills requirement completion, 2010-11 credit load, earned credit level, and financial aid award.
The retention of the 945 students attending orientation from Spring 2011 to Fall 2012 was 81%, while those not attending orientation were only 70% retained. Note: it is impossible to determine from this study the impact of orientation itself. Students who elect to attend orientation are expected to be more likely to continue.
Return Rate of Students Attending Fall 2011 Orientation
This report compares the second semester return rates of freshmen and new transfers of those who attended New Student Orientation against those who did not for students beginning classes in fall 2011. The return rates for those attending orientation was 85%, while it was 76% for those who did not. While selection bias is evident in the numbers, further analysis demonstrates the positive effect of the orientation sessions themselves.
In this paper we present the results of five “Cell Matching” studies. The interventions included: working part-time on campus, Fall 2009 Federal Work Study, Fall 2010 Federal Work Study, participating in an accelerated basic skills (USIP) course, and the College Discovery program. Only the Fall 2010 FWS group showed no impact from the intervention. Cell Matching studies randomly pull control groups from the general population with distributions of retention-related comparisons similar to those in the intervention group.
In this study we matched a random sample of Fall 2010 students against 1,214 students who had ever attended and passed an accelerated basic skills (USIP) course and were also enrolled that semester. The one-year return/graduation rate of the USIP was 79%, while the return rate for the control group was 77%. The random sample was selected to have a proportionally similar distribution among ranges of GPA, F-1 visa status, basic skills requirement completion, 2010-11 credit load, earned credit level, and financial aid award.
Nearly 16% of the 6,654 new students in academic year 2007-08 were eventually placed one probation, some more than once. First-time students were twice as likely to be placed on probation than students who transferred in. Among all students placed on probation, 47% successfully got off probation. Nevertheless, only 9% of students placed on probation graduated through fall 2011 compared with 27% of those never on probation.
Allowing advanced students in good academic standing to take courses in addition to a COOP internship when they are close to graduating appears to be a sound policy. While the numbers of students graduating after the session is somewhat lower than expected, the number of courses passed, of those not dropped, is very high. Only 21 courses were failed out of a total of 412 that were completed, a pass rate of 95%.
In this study we attempted to compare the persistence of 14 students who received small scholarships for child care in Spring 2012 to a similar control group. All of the scholarship recipients either returned for the next semester or graduated. The control group returned or graduated at an 81% rate.
While the Solomon Scholarship recipients did not return for the next semester or graduate at rates significantly higher than a control group, the scholarship recipients did attempt and earn more credits in Spring 2012. The scholarship recipients attempted 13 and earned 11 credits, while the similar control group attempted 11 and earned 9.
This study looks at the impact of the Single Stop Office at LaGuardia. Single Stop assists students in applying for public benefits and provides legal and tax preparation help. This study examined whether students who were assisted in obtaining public benefits were more likely to remain in school, progress toward a degree or achieve a degree than similar students who had not worked with the office. The comparison group was selected to be similar to the treatment group along characteristics known to predict retention and graduation. The Single Stop students were more likely to return the next semester and attend full-time.
This report examines the impact of LaGuardia Foundation Scholarships on the retention and graduation rates of students who had earned 45 or more credits before receiving the scholarships. These students were matched against a control group. The Fall 2011 and Fall 2012 scholarship recipients were combined. Next semester retention or graduation rates for students receiving scholarships were significantly higher than for the similar, comparison group of students.
In this study the strong, positive retention impact of choosing not to avoid the freshman seminar in the first semester is evaluated. While it is not possible to separate the impact of the seminar itself from student self-selection, the positive traits exemplified by self-selection match other studies of students who attend pre-enrollment orientation and request help appear to have the same effect. Using logistic regression and controlling for ethnicity and financial aid awards, we found that the probability of re-enrolling in the second semester was 50% greater for students who took freshman seminar.
Destination Graduation focused on 1,741 students during Fall 2011 who had earned 45 or more credits, had changed majors no more than once, were in degree programs, had at least a 2.00 GPA and had fulfilled all developmental requirements. 84% of these students either graduated in Fall 2011 or came back for Spring 2012 classes. Students with the same characteristics in Fall 2010 (before Destination Graduation focused on such students) graduated or returned at an 81% rate.
We compared students having earned 45 or more credits and who received LaGuardia Foundation supported scholarships to help them finish their degrees against a control group of students with similar academic progress and retention characteristics. The scholarship-receiving students were significantly more likely to be retained into the next academic year, earn more credits, get a higher GPA and return as full time than students in the control group.
Although the sample size was too small to give statistical significance, students given scholarships performed better than a control group of similar students on graduation rate, GPA and course load.
In this study we attempt to determine whether fulfilling the urban studies requirement early in a student’s academic career offers any advantage in terms of graduation, retention, GPA, credit load or credits earned success. No statistically significant results were obtained.
Colleges like LaGuardia utilize special programs, featuring intensive counseling to keep high risk students from dropping out. Concern about the costs and rates of success of these programs led to the analyses in this paper. Here we explore, using tables and graphs, the relationships among the proportion of the population selected for treatment, the cost of the intervening treatment, the efficacy of the treatment, and the accuracy of the selection criteria. These variables determine the overall cost of the intervention and the number of successes resulting from the treatment. In the cases examined, we found, while accuracy of selection represented by R-squared values was very helpful in improving the success rate of treatment when going from 0.1 to 0.2, the improvement from 0.2 to 0.3 was much less helpful. Greater impact on overall budget and the number of successes is driven by the proportion of the population selected for treatment.
This study compares the progress toward degree and graduation rates of students in learning communities/clusters and a control group. The control group was formed to control for credits earned before taking the cluster, full-time status, Day Student status, whether a Liberal Arts: Hum & SS major or not, and whether or not the student had passed the developmental math requirement. Control group students also had to take Eng 101 in the same semester. Motivation, however, was not controlled. All findings could be a result of a non-random assignment of students to clusters. In every measure of progress toward the degree, students in clusters did significantly better than similar students in the control group. They had higher GPA's, accumulated more credits and persisted at higher rates and longer. Unfortunately, they were no more likely to graduate. This result may indicate: 1) A statistically significant difference in progress measures may still be too small to force a change in outcomes, and/or 2) Changing outcomes may require a sustained effort on the part of the college, not just one-semester programs.
Students who visited the math lab in Fall semester 2014, Session I, had a significantly higher math or biology course grade than a control group of students who were in the same course section and had about the same pre-semester cumulative GPA and credits earned levels. Although this experiment does not totally eliminate the effect of superior help-seeking behavior, it does reduce the effect by controlling for pre-semester GPA and credits earned. Tutoring provided at the math lab raised the average course grade 37%.
In this study we found that students who used Academic Peer Tutors in the API program for Math 096 during the Fall 2014 semester passed the course at a higher rate than students who did not use API. We controlled for previous cumulative GPA levels and earned credit numbers. Students who benefitted most from the sessions had the lowest previous GPA and the lowest prior earned credits levels.
A goal of the Tortora Silcox Family Foundation grant of scholarship funding for students approaching graduation who face potential financial barriers is to raise graduation rates of students within 15 credits of graduation and to assist in building advising teams made up of faculty and advisors to these students. This report shows the progress by Advising Council of recent cohorts entering the "within 15 credits of graduation" realm toward increasing the graduation rate toward goals set within the grant.
A goal of the Tortora Silcox Family Foundation grant of scholarship funding for students approaching graduation who face potential financial barriers is to raise graduation rates of students within 15 credits of graduation. Using control groups made up of students with similar graduation-potential characteristics, this report shows the favorable impact on three cohorts of the Tortora Silcox scholarships on graduation and retention rates.
The chart in this report shows the retention to Spring 2015 (or Fall 2014 graduation) of Fall 2014's 16,259 degree students. These students generated 74,915 “hits” in SEMS of the 108,799 tickets generated from August 1, 2014 to March 1, 2015. The other hits were either from non-degree students, non-enrolled students, or students who gave invalid EmplIDs. A "hit" in SEMS indicates a visit to a department connected to the SEMS system including, advising, certain academic departments, financial aid, and other C-107 operations. The chart shows increasing retention with the number of office visits recorded in SEMS from 56% for students who do not show up at all in SEMS data to 89% for those with 20 or more visits.
This report details the information from the Student Engagement Management System (SEMS) for Fall 2014. The data can be used to show ticket counts by areas, by reason and by person closing the ticket. (Each entry by a student into a service area is logged as a "ticket.") The average time of the visit by ticket characteristic is also shown. Various breakdowns are matched against return rates by students served. This report is intended to show the potential of the SEMS system for analyzing the effectiveness of services.
This report gives the results of 50 interviews with LaGuardia students on the subject of academic advising. Two-thirds of the students discussed advising sessions with Advising Office staff and one-third discussed sessions with faculty members. The interviews show the challenges that students face that must be overcome before a schedule of classes for the coming semester can be completed. The interviews show the skill of faculty and staff at helping students overcome these challenges and the occasions when the challenges cannot be overcome. Of critical importance seems to be the ability of the faculty or staff member in instilling a sense of confidence in the student that they can succeed and that they can trust the faculty or staff member’s advice.
This report summarizes the results of 16 interviews of faculty members and academic advisors on the subject of advising. The report details the activities in an advising session, the challenges and the trans-office dependencies of good advising. The words of the faculty and advisors are used to illustrate the various activities, challenges and linkages.
We compared students who received foundation scholarships in two semesters, Fall 2013 and Fall 2014, against students matching on four characteristics who applied for but were denied scholarships. In general, students receiving scholarships attempted and earned slightly more credits, but had the same GPA in the semester in which the scholarships were given. Scholarship students were also slightly more likely to graduate. None of these differences was statistically significant. When compared against all non-scholarship recipients, scholarship recipient outcomes are significantly stronger, but we can no longer tell whether these differences are due to the scholarship or the self-selection of applicants.
IR&A analyzed two semesters of Anatomy Lab data to show usage times and intensities and participation rates by course, previous cumulative GPA and credits earned. A control group of students from the same sections with the same previous cumulative GPA and credits earned ranges had lower average course grade points and a significantly lower pass rate than lab-visiting students.
IR&A analyzed one semester of Math Lab data to show usage times and intensities and participation rates by course, previous cumulative GPA and credits earned. A control group of students from the same sections with the same previous cumulative GPA and credits earned ranges had about the same average course grade point but had a significantly lower pass rate than lab-visiting students. Some of the lack of significance of the GPA may be due to the reduced numbers in that comparison because of the pass/fail nature of many of the MAT 096 sections.
Students in sections supported by API tutors in four Spring Semesters, 2011-2014, had a significantly higher pass rate and higher average grade in Math 096 than students in a matching control group. Students in the API sections did not return the next semester at a higher rate than students in the control group. Looking only at students who passed the course, the API sections did not have a significantly higher average grade. The primary impact of the API tutors appears to be in helping students pass Math 096 who would normally fail the course.
In this report, using a matched control group, we show that students joining an athletic team at LaGuardia during the academic years 2013-14 and 2014-15 were more likely to return the semester following their initial semester on the team than a similar group of students.
Students visiting API tutors three of more times passed Math 096 during Fall 2014 and Spring 2015 at a significantly higher rate (61.1% vs. 48.2%) than students matched on eight characteristics, including having taken Math 095 previously, number of times Math 096 was taken, previous cumulative GPA, and previous number of credits earned.
In this report we compared only Business & Technology and Liberal Arts majors on their rate of return to the next fall semester. To make the comparison, we used matched sampling to hold constant gender, Pell grant eligibility, student visa status, remedial needs, full-time status in the spring semester, age (older than 23 or not), and admissions status (first-time or transfer). We found that FYS students were more likely to return in the fall than FSM students. Full-time FYS students were more likely to stay full-time than FSM students, while part-time FYS students were more likely to come back as full-time than FSM students.
In this study we show the differences between students who enrolled in a College Now course in high school and then came to LaGuardia and students who came to LaGuardia as freshmen without college course experience. College Now cohorts, compared to the non-college now group, tend to have a higher proportion of women, be more likely to have passed developmental testing and, as expected, to begin as freshmen with college credits. As a result, they tend to accumulate more college credits and have higher cumulative GPAs in their earlier semesters. Fewer of them transfer before getting a degree and more graduate within the short timeframe of the study.
In this externally supported program RTS students have been provided coaches, occasional cash assistance and MetroCards after they had succeeded in two new First Year Seminars. 84% of the RTS students returned for Spring semester 2016, while 75% of a matching control group returned. The RTS also had significantly better credit load and GPA outcomes than the control group.
This report matched 238 Veterans’ Services clients enrolled in Fall 2015 against a control group on seven characteristics, including gender, cumulative GPA and credits earned. There was no difference on return/graduation rate, semester GPA, or pass rate between the veterans’ group and the matched control group.
We evaluated student performances in MAT 095 by session to determine the safety of pairing courses for students regardless of the session. If students performed much worse in Session II than in Session I, then pairing courses with Math 095 in Session II might not be advisable. A total of 804 first time course takers from Fall 2012 through Fall 2015 were included in the study. While differences in course completion rates were significant, differences in course passing rates were not.
In this paper we discuss the development of a methodology for comparing the actual two-semester return rate of a group of students against an initial prediction of return. The prediction is built from historical data using stepwise logistic regression. The group of students can be those involved in a retention project. The paper shows the factors used in the prediction and the results for projects such as ASAP and College Discovery in getting students enrolled in their programs in fall 2014 to return to fall 2015 (or graduate before that semester).
In this paper we look at programs and offices that help students stay in college. Students assigned to the teams according to major and who visited advisors or faculty had group probabilities of return from fall 2014 to fall 2015 based on the methodology discussed in “Developing a Single Tool for Assessing Student Retention Interventions.” Results show the strong impact of the ASAP and College Discovery programs on improving the return rate of students in their programs.
In this paper we look at advising teams, advisors and faculty that help students stay in college. Students assigned to the teams according to major and who visited advisors or faculty had group probabilities of return from fall 2014 to fall 2015 based on the methodology discussed in “Developing a Single Tool for Assessing Student Retention Interventions.” Advising teams were rated as transformative, well above expectations, better than expected, meets expectations, disappointments, and under duress, depending on their ability to return students to the latter semester above predicted rates for their groups. The same methodology was used to note the success of faculty and the advising office in improving the expected return of students.
In this research we show a significant improvement in pass rate for first-level math courses and an improvement return rate for students who visit API (Academic Peer Instruction) tutors, especially those who visited more than twice. The study matched API tutor visiting non-visiting students with similar levels of credit accumulation, cumulative GPA and developmental math experience.
In this study we look at the degree of response to interventions by probability of success. We examined two interventions: ASAP (Accelerated Studies in Associate Programs) and CD (College Discovery). We predicted that the both programs would improve retention most among students with moderate probabilities of success, while students with the greatest and least challenges would show lesser improvements. In fact, while neither program was able to offer large improvements to those with an already high probability of retention, only one cohort of CD students showed only good improvement for the medium-risk students. ASAP provided excellent improvement to the higher risk students and good improvement to moderate risk students, moving both nearly to the return level of the low-risk students. CD students from Fall 2015 showed very little improvement across the board.
RTS students had significantly better rates of college credits earned and percentage of equated credits earned than a control group. The credits-earned difference is equivalent to one in four RTS students earning one extra three-credit class in the spring 2016 semester compared with similar students. RTS students also registered for more credits in the fall 2016 semester. No difference in impact was seen between peer counselors and faculty coaches.
An analysis that matched Fall 2016 scholarship recipients against a control group on nine characteristics showed no significant impact of scholarships on semester academic performance or return rates. Those recipients who returned for the Spring 2017 semester, however, and who were full-time in Fall 2016 were more likely to return as full-time in the spring than a matched control group.
This paper compares the actual two-semester return (or graduation) rate of Road to Success students against a predicted probability for the group (and sub-groups). The prediction is based on a formula that includes cumulative GPA, gender and credits earned at the start of the two-semester period. Only students who began with high expected probabilities of return appear to have benefited from the program. While lower expected probability of return students who visited RTS advisors, as recorded in the SEMS system, also appeared to beat return expectations, the numbers were not large enough to make the results for the higher risk tiers favorable for these program tiers overall.
Each week Institutional Research and Assessment creates a list of students who have signed up for college-level courses that are not required by their major according to Degree Works. In one semester the advising office examined the list and attempted to contact students who appeared to have signed up for a “moot” course. In the analysis of these contacts, the majority of students contacted did not feel that they had signed up for the course in error. Nevertheless, 38% of the students did take action by either dropping the course, changing major officially, or pursuing course substitution permission.
In this paper we show that the impact on graduation rates of short-term and/or merely statistically significant interventions is small. The example used in the paper is the impact of preventing full-time students from dropping to part-time, assuming that those who remain full-time instead of changing to part-time after a successful intervention would graduate at the higher rate of current full-time students.
We looked at CUNY Office of Institutional Research & Assessment records of students who had transferred from LaGuardia to other CUNY colleges (both four‐year and two‐year) beginning Fall 2007. LaGuardia students who transferred before earning their degree lost on average 5.8 of 46.5 credits, while those with degrees lost 6.6 of 68.3 credits. The data does not provide information on whether the transferred credits had been applied toward degree requirements, however.
Using National Clearinghouse data, the transfer destination colleges of 20 years of Barnard Intercollegiate Program (ICP) participants were studied. Three hundred LaGuardia students were listed as former participants. Two hundred graduated from LaGuardia and, of these, 67.5% transferred to four-year colleges. In all, 185 of the 300 transferred to another college.
This paper contains a series of graphs showing the number and proportion of students who transfer from LaGuardia before receiving their degree. It looks at the Fall 2006 cohort and the semester-by-semester numbers.
This graph shows the 26% higher baccalaureate graduation rate of students from the Fall 2005 new student cohort who transferred to four-year institutions AFTER earning a LaGuardia degree than those who transferred early. Students were followed using Clearinghouse data for eight years after their Fall 2005 entry to LaGuardia.
The colleges to which LaGuardia Fall 2012 through Fall 2014 graduates transferred are available in this report. Majors and options are grouped to make the report easier to read. These groupings are shown in the final section of the report. The report shows transfer college destination by college then by major.
In this report we present a summary of a new online table now available on our website. We examined the rate of graduation from a CUNY BA/BS program of LaGuardia transfers within six years of starting at LaGuardia. The summary report shows that early transfers (before graduation) of LaGCC students have slightly more credits disallowed for use in their BA/BS major, but finish in slightly less time. The results are shown both individually and combined for students who begin at LaGuardia and those who transfer in. Also shown separately and combined are the results for students who received a LaGuardia degree and those who transferred early.
This paper examines how well LaGuardia associate’s graduates do after transfer compared to the college’s early transfer students. While getting a degree at LaGuardia continues to give an advantage, the advantage is uneven across the CUNY campuses to which our students transfer and across the majors from which our students come. City and Hunter do not appear to be good places to go after you get your degree at LaGuardia. BA/BS graduation rates within six years are higher for those who have transferred from LaGuardia early at these colleges. In most other cases, students can improve their chances for graduation by completing their degree at LaGuardia.
This report presents a portion of an assessment of an office at LaGuardia. The Grants Development Office surveyed clients on the effectiveness of the service they provided during both the grant development and grant management phases of their work. This report gives the results of the survey along with additional suggestions and kudos provided by responding clients.
This paper tests whether the University, CUNY community colleges and LaGuardia improved their performance over time as measured by the PMP (Performance Management Program). If producing and publicizing these measures was a reasonable way of managing a university, then we would expect to see broad improvement. The paper shows that 40% of the measures at all three levels from LaGuardia up to the university demonstrated improvement. Given the heavy emphasis on year-to-year improvement, 40% seems reasonable. Nevertheless, there is so much uniformity among the trends that LaGuardia did not appear to "improve" any more than the average community college.
This presentation attempts to use the CUNY PMP (Performance Management Process) indicators to chart the relationship between a general decrease in the proportion of student course hours taught by full-time faculty and other indicators of quality. No relationships were noted. Enrollment increase was clearly a driving factor. Turning the PMP indicators into indexes allowed aggregation of similar indicators to smooth trends.
In this study we gathered quarterly wage data on the cohort of new students who entered LaGuardia in Fall 2005. The New York State Unemployment data does not include wages earned out of state or under the table. We found that the highest average wages belonged to students the year after graduating with a baccalaureate. These students more than tripled their pre-college earnings in the year after graduation. The second highest average wages belonged to students in the year after earning an associate’s without going on to receive a baccalaureate. The year after graduation these students made more than five times what they made in the year before initial matriculation. The students with the highest average wages in the year before Fall 2005 were the students who did not graduate. Those with the lowest pre-college earnings went on to get baccalaureates. Students who are still attending without a degree have made more, on average, while attending college than the other groups. Among groups of majors, STEM baccalaureate graduates had the highest average wages.
In this report we tested whether restrictions to enrollment in online courses should remain by examining course failure rates of matched courses during Fall 13 and Spring 14. Online courses are restricted to students who are not in their first semester, have a GPA at or above a 2.00, who have completed all developmental requirements and not taking other online courses. Because many students enrolled in these courses in violation of the restrictions, there was sufficient data for hybrid courses but not for fully online courses to draw conclusions. Students taking more than one hybrid course did not perform worse than students taking more than one. Students who violated the other restrictions, however, performed significantly worse in hybrid courses than non-hybrid courses.
Eight sections of Math 096 taught by full-time faculty provided 469 student records. Of these 200 students used the ALEKS platform and the remainder used EDUCO. No signficant difference in GPA performance was found between the two groups of students using the different platforms. A similar test was made with 1,637 students taught be both full-time and part-time faculty. Again, no significant difference in student GPA performance was found.
In this study we examine the structure of pre- and co-requisite rules as maintained in tables that prevent students from registering incorrectly. Based on a preliminary look, we find that the tables may need updating and revision, and that high rates of exceptions are needed for what appear to be ordinary registration situations. Many hours appear to be spent by students, faculty and staff manually making exceptions to the rules.
This report uses students’ own words to describe encounters at LaGuardia within the structure of the Credit Student Success Framework. Each encounter is analyzed in terms of the information available as perceived by the student, policies that frame the encounter, decisions, behaviors and emotions of the student, and implications for future behavior (feedback). The CSS framework divides the encounters into several arenas: the academic path, support communities, measuring progress, college feasibility, career services, and learning support.
This report places relevant quotations from students into the structure of the Credit Student Success Framework. Students discuss accelerators and barriers to momentum along their academic path, the importance of connecting to the college, the challenges of financing their education, and the ways they have used technology to navigate and gain academic assistance at the college.
In this report we tabulate the proportion of classes and student credit hours taught by adjunct faculty. The tabulations are by semester and session, level and department (also by level).
In this paper we demonstrate a methodology for finding the cost for each type of college “output”: graduate, early transfer, and drop-out. The methodology uses average total Educational and General cost per credit for each year in a student’s academic career and applies that cost to each credit attempted in all the years before the student leaves (“becomes an output”). Each graduate produced during academic year 2010-11 cost $35,519 on average over their entire academic career, while 2010-11 drop-outs cost on average $19,107. A comparative analysis of national figures is also included.
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