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Hi Jeffrey,

We measure persistence Fall-to-Fall. For lower division courses, we report strictly students who were enrolled and who are continuing, and the count is labeled "persisted." For upper division courses, we report students were enrolled and either are continuing or who graduated, and the count is labeled "persisted or graduated." We have a significant number of transfer students, so unless asked, I do not worry about whether the students are in the FTFT cohort for a given academic year.

For the 2016-17 academic year, our university had 10,344 students, enrolled undergraduate or graduate programs.

*         1283 non-duplicated students (12.4% of enrollment) participated in Peer Tutoring.

*         2007 non-duplicated students (19.4% of enrollment) participated in Writing Tutoring.

*         1977 non-duplicated students (19.1% of enrollment) participated in SLA.

*         3907 non-duplicated students (37.8% of enrollment) participated on one or more of the services listed above.

Martin

From: Open Forum for Learning Assistance Professionals [mailto:[log in to unmask]] On Behalf Of White, Jeffrey
Sent: Friday, March 23, 2018 9:56 AM
To: [log in to unmask]
Subject: Re: Collected Data

Hi Martin,
Thanks for your contribution to Kaddour's post? How do you measure persistence? I'm also curious how many unique users you serve?
All the best,
Jeffrey



On Mar 23, 2018 6:49 AM, "Golson, Martin" <[log in to unmask]<mailto:[log in to unmask]>> wrote:

Hello Kaddour,



I may be a little slow answering your inquiry. Our center does not use SAS to perform the statistical analysis. However, we do collect an lot of data for analysis.



First, we collect descriptive data. For each service offered (Peer Tutoring, Writing Center, Community Tutoring,  Structured Learning Assistance (SLA), and Full Spectrum Learning):

*         Number of non-duplicated students supported

*         Total number of sessions (for SLA, this is number of courses/sections supported)

*         Average number of sessions provided to each student supported

*         Supported population demographics (gender and race)

*         Academic programs supported (name of program and percentage of services provided that went to that program)



Then, we collect data on course impact:

*         For courses with n large enough for analysis:

o   Grades, sessions attended, ACT Sub-scores, and most recent term enrolled for all students enrolled in the course

o   This data is used to determine:

*  Difference in grade between those using the service and those who didn't, disaggregated by the ACT Sub-score which best correlates to course performance.

*  Difference in grade by number of sessions attended

*  Difference in persistence between those who used the service and those who didn't

o   For each of the items listed above, we use either a T-test or Chi Square (whichever is appropriate for the data) to determine significance. Our data indicates that while participation in tutoring does not always result in a significant difference in grade earned, it consistently produces significant improvement in persistence ( significant at the 0.001 level).

*         For select courses (either new to the SLA program or of interest to the administration or a department)

o   We pull the following data upon request:

*  Class

*  High School grade

*  ACT Sub-scores

*  Section

*  Start time of lecture

*  Instructor

*  Grade

*  Overall GPA

*  Most recent term enrolled

o   Using this data, we determine

*  Impact of SLA on student performance, disaggregated by ACT Sub-score and HS GPA

*  Impact of start time on student performance

*  Impact of SLA on student persistence

*  We also have the ability to determine impact of instructor on student outcomes (performance and persistence), but this is only done at the request of a responsible party (Provost, Associate Provost, Dean, or Chair)

*  All of the data is checked for significance



Finally, we collect information which helps us complete the picture of what our services provide to students and the learning community

*         Results from student surveys

*         Number of student employees who earned certification, disaggregated by certification level

*         Staff members who have earned certification (Learning Center Leadership Certification through NCLCA), presented, or published during the previous academic year, as well as staff engagement in professional organizations (board members, reviewers, etc.)

*         Two or three stories of the impact our services have made on students' lives (employees and clients), as told by the students (these short narratives can be quite touching).



This has been a lengthy post, but I hope it is helpful.





Martin Golson

Director, Academic Support

Certified Learning Center Professional - Level 4

Austin Peay State University



(931) 221-6553



"Luck is what happens when preparation meets opportunity." - Seneca













From: Open Forum for Learning Assistance Professionals [mailto:[log in to unmask]] On Behalf Of Boukaabar, Kaddour
Sent: Wednesday, March 21, 2018 3:16 PM
To: [log in to unmask]<mailto:[log in to unmask]>
Subject: Collected Data



Hello All,

I wonder if any center uses SAS for statistical analysis of the collected data that relates tot he center's use.  Also, perhaps more importantly, what data is collected and how?  The data is for purpose of center assessment and end of semester/year report to the dean. Thank you.

Kaddour



Kaddour Boukaaabr,Ph.D.

Math Lab Director

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Hello Kaddour,

I may be a little slow answering your inquiry. Our center does not use SAS to perform the statistical analysis. However, we do collect an lot of data for analysis.

First, we collect descriptive data. For each service offered (Peer Tutoring, Writing Center, Community Tutoring,  Structured Learning Assistance (SLA), and Full Spectrum Learning):

*         Number of non-duplicated students supported

*         Total number of sessions (for SLA, this is number of courses/sections supported)

*         Average number of sessions provided to each student supported

*         Supported population demographics (gender and race)

*         Academic programs supported (name of program and percentage of services provided that went to that program)

Then, we collect data on course impact:

*         For courses with n large enough for analysis:

o   Grades, sessions attended, ACT Sub-scores, and most recent term enrolled for all students enrolled in the course

o   This data is used to determine:

*  Difference in grade between those using the service and those who didn't, disaggregated by the ACT Sub-score which best correlates to course performance.

*  Difference in grade by number of sessions attended

*  Difference in persistence between those who used the service and those who didn't

o   For each of the items listed above, we use either a T-test or Chi Square (whichever is appropriate for the data) to determine significance. Our data indicates that while participation in tutoring does not always result in a significant difference in grade earned, it consistently produces significant improvement in persistence ( significant at the 0.001 level).

*         For select courses (either new to the SLA program or of interest to the administration or a department)

o   We pull the following data upon request:

*  Class

*  High School grade

*  ACT Sub-scores

*  Section

*  Start time of lecture

*  Instructor

*  Grade

*  Overall GPA

*  Most recent term enrolled

o   Using this data, we determine

*  Impact of SLA on student performance, disaggregated by ACT Sub-score and HS GPA

*  Impact of start time on student performance

*  Impact of SLA on student persistence

*  We also have the ability to determine impact of instructor on student outcomes (performance and persistence), but this is only done at the request of a responsible party (Provost, Associate Provost, Dean, or Chair)

*  All of the data is checked for significance

Finally, we collect information which helps us complete the picture of what our services provide to students and the learning community

*         Results from student surveys

*         Number of student employees who earned certification, disaggregated by certification level

*         Staff members who have earned certification (Learning Center Leadership Certification through NCLCA), presented, or published during the previous academic year, as well as staff engagement in professional organizations (board members, reviewers, etc.)

*         Two or three stories of the impact our services have made on students' lives (employees and clients), as told by the students (these short narratives can be quite touching).

This has been a lengthy post, but I hope it is helpful.


Martin Golson
Director, Academic Support
Certified Learning Center Professional - Level 4
Austin Peay State University

(931) 221-6553

"Luck is what happens when preparation meets opportunity." - Seneca






From: Open Forum for Learning Assistance Professionals [mailto:[log in to unmask]] On Behalf Of Boukaabar, Kaddour
Sent: Wednesday, March 21, 2018 3:16 PM
To: [log in to unmask]<mailto:[log in to unmask]>
Subject: Collected Data


Hello All,

I wonder if any center uses SAS for statistical analysis of the collected data that relates tot he center's use.  Also, perhaps more importantly, what data is collected and how?  The data is for purpose of center assessment and end of semester/year report to the dean. Thank you.

Kaddour



Kaddour Boukaaabr,Ph.D.

Math Lab Director
~~~~~~~~~~~~~~~ To access the LRNASST-L archives or User Guide, or to change your subscription options (including subscribe/unsubscribe), point your web browser to http://www.lists.ufl.edu/archives/lrnasst-l.html<https://na01.safelinks.protection.outlook.com/?url=https%3A%2F%2Furldefense.proofpoint.com%2Fv2%2Furl%3Fu%3Dhttps-3A__na01.safelinks.protection.outlook.com_-3Furl-3Dhttp-253A-252F-252Fwww.lists.ufl.edu-252Farchives-252Flrnasst-2Dl.html-26data-3D02-257C01-257Cwhite-2540up.edu-257C4a46b89340614e0311bd08d590c4e730-257Cea8f3949231c40b6a33f56873af96f87-257C0-257C0-257C636574097745324303-26sdata-3DjWNcOab92VHunRKHvfLBHk-252B-252FLB9vr4W-252BFHGd6WkYn-252Fg-253D-26reserved-3D0%26d%3DDwMF-g%26c%3DpZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM%26r%3DyBiE514ByeBuT9iMcmLL81H9l3w_eWJJCNWWYb5qET4%26m%3D2XA5aY5-uSICU8Fk3b2chy8axmLKiwyj3P5kyzolJpM%26s%3DlpwbEEgb1_hd7r4nxYhrP2e223uPoKsYHe0ItOhOy8I%26e%3D&data=02%7C01%7Cgolsonm%40APSU.EDU%7Cc3756194c1b64116f59c08d590ce47a5%7Ca45657c5d99648ce803c4267cb5ab373%7C0%7C0%7C636574138020959429&sdata=LG9ozyaRdRzDASxf9Na%2FQhF1e8M8RHSnDsRVSyWSPy0%3D&reserved=0> To contact the LRNASST-L owner, email [log in to unmask]<mailto:[log in to unmask]>
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