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Key assessement project
Key assessement project
Key assessement project
Key assessement project
Key assessement project
Key assessement project
Key assessement project
Key assessement project
Key assessement project
Key assessement project
Key assessement project
Key assessement project
Key assessement project
Key assessement project
Key assessement project
Key assessement project
Key assessement project
Key assessement project
Key assessement project
Key assessement project
Key assessement project
Key assessement project
Key assessement project
Key assessement project
Key assessement project
Key assessement project
Key assessement project
Key assessement project
Key assessement project
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Key assessement project

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  1. Data Challenge • I have several data challenges in my area: • Retrieving data in a timely manner • Getting permission from different entities on campus to retrieve data • Ensuring the proper stakeholders are vetting so the process can be streamline • Once I receive the data then we need to analyze the data • This comes with it’s own set of challenges • Why our students are not succeeding in certain courses • Why the retention rate is not at the peak level compared to other ethnicities • What makes a successful GT student
  2. Assessment One of ways I can be certain my department is achieving the mission of department is to assess each program
  3. Assessment of Program • Summer bridge program • Assess the academic achievement of students that participates & compare to non-participants • Peer-mentoring program • Assess the level of participation and their academic achievement &compare them to non-participates • Academic Support • Assess the academic achievement of students that are tutored in our lab
  4. Peer-Mentoring Program Participants vs Non-Participants - Black Males 2.89 (59) Black Males 2.79 (61) Black Females 3.0 (44) Black Females 2.91 (27) Hispanic Males 3.19 (90) Hispanic Males 3.23 (108) Hispanic Females 3.06 (38) Hispanic Females 3.22 (38)
  5. Steps • I take an analysis of the GPAs from the fall semester: • And compared them to the GPAs of the following spring semester • Also, I took a look at the courses our students had academic challenges – and offered supplement assistance
  6. Impact on various programs – Peer Mentoring Peer-Mentoring • DATA is the vital component of our programs • School process • This is how we know our programs are successful • What we need to improve • What we need to revise • What we need to modify • Are we benchmarking and if so how do we compare Peer-Mentoring • Student Outcomes • With the proper assessment we are able to take a holistic approach • This will help us make better choices for our programming • Which will help with student retentions, performance, and overall student development
  7. Impact on Summer bridge program School Process • What we need to improve • What we need to revise • What we need to modify • Are we benchmarking and if so how do we compare • Recruit more or less students in particular majors Student Outcomes • With the proper assessment we are able to take a holistic approach • This will help us make better choices for our programming • Which will help with student retentions, performance, and overall student development
  8. Challenge vs Non-Challenge
  9. Impact on Academic Support program School Process • What we need to improve • What we need to revise • What we need to modify • Are we benchmarking and if so how do we compare • Recruit more or less students in particular majors Student Outcomes • With the proper assessment we are able to take a holistic approach • This will help us make better choices for our programming • Which will help with student retentions, performance, and overall student development
  10. Academic Support URM tutor visits 18% URM general study 34%URM pc/printer 13% URM student staff 16% URM independent study group# 1% URM other 18% Fall Overall URM Academic Support Visits (4015 total) 2.61 3 3.02 2.71 2.98 3.1 2.3 2.4 2.5 2.6 2.7 2.8 2.9 3 3.1 3.2 Black Hispanic Multi-Racial Fall URM GPA per overall participation non-participants participants
  11. Team Coach Program – Fall 2013 Team Coach – Offers support of Upperclassmen to 1st year students Participants Non-Participants
  12. Student Achievement • OMED: Educational Services is the unit charged by Georgia Tech with the retention, development, and performance of the complete student learner who is traditionally underrepresented: African American, Hispanic, Native American, and Multi-Racial.
  13. Student Achievement It is my responsibility, as Director to make sure that I am providing all the tools and resources necessary for the academic achievement of 1st year students If students are not achieving academically I need to re-assess my programs to find out why; where are we missing the mark, etc.
  14. Signature – Summer Bridge Program • Academic Performance from 2003 – 2012 • Comparing Non-Challenge students vs Challenge Students
  15. Data Trends I noticed our students did not always out-perform other minority students • This is problematic since we make the case that If you attend our programs “you should outperform” • The question becomes what happens during those years why did we over perform in most but not in ALL???
  16. Stakeholders- Data Steward Responsibilities Admission Office http://www.admission.gatech.edu/life- tech/class-profile Admitted Students Applied Students All pertain data relating to the applicant Registrar’s Office http://www.registrar.gatech.edu/ Midterm Grades Semester Grades Transcripts (student’s profile) Institute Research & Planning (IRP) http://www.irp.gatech.edu/ The overall population of the institute – The population based on gender, ethnicity, college, geographic location. Grades based on ethnicity – IRP is responsible for data resources to support the strategic planning and policy- making processes at Georgia Tech.
  17. Stakeholders- When should data be shared & used Admission Office •Once the data is collected and vetted •Data is used in the summer, fall and spring Registrar’s Office Once the professors input grades – 2x per semester Data is used in the summer, fall and spring Institute Research & Planning (IRP) Data is collected by the data steward Data is used during the fall & spring semester – also when an overall view is needed of the population
  18. How is the Data shared & used Admission Office Data is only shared when permission is granted and there are several layers of permission – via reports This helps determine who was admitted in our target population, State or Country, student profile Registrar’s Office Data is only shared when permission is granted and there are several layers of permission – via reports This helps us keep track of academic performance Institute Research & Planning (IRP) Data is only shared when permission is granted and there are several layers of permission- Our Research manager uses SASS to pull in data This report helps to isolate our target population
  19. Integration & Comprehension Admission Office This report helps to understand the type of student, where they came from, and their profile SAT scores can determine the academic performance of a student (often) Registrar’s Office Combining with this report – will Institute Research & Planning (IRP)
  20. Outcome of Data • Our department strategically looked at the classes that our target population weren’t doing well in and provided extra support • We would send targeted emails to our students and make available tutors that could assist with our efforts • We noticed that some classes were taught by TA’s so we hired the TA’s to lead “Concept Classes” these are special sessions to enforce the material covered in those classes
  21. Innovative Practices during Challenge Challenge Calculus I Or Challenge Calculus II Students that took either Calculus received an A their freshmen Calculus
  22. Innovative Practices – Team Coach Transfer Students & Dual Degree students Pair them with ONLY transfer students or dual degree students Students were able to connect better with mentors that totally understood the challenges of being a transfer/dual degree studen
  23. CHALLENGE – DATA IN ORDER TO IDENTIFY, PURPOSE AND DESCRIBE OUR DATA; THESE ARE TOOLS WE USE TEAM COACH – DATA IN ORDER TO IDENTIFY, PURPOSE AND DESCRIBE OUR DATA; THESE ARE TOOLS WE USE ACADEMIC SUPPORT– DATA IN ORDER TO IDENTIFY, PURPOSE AND DESCRIBE OUR DATA; THESE ARE TOOLS WE USE DATA COLLECTION: WE COLLECT DATA FROM VARIOUS SOURCES DURING VARIOUS TIMES OF THE SEMESTER DATA COLLECTION: WE COLLECT DATA FROM VARIOUS SOURCES DURING VARIOUS TIMES OF THE SEMESTER DATA COLLECTION: WE COLLECT DATA FROM VARIOUS SOURCES DURING VARIOUS TIMES OF THE SEMESTER DATA ANALYSIS: WE EXPORT THE DATA USING SASS, MICROSOFT ACCESS AND EXCEL DATA ANALYSIS: WE EXPORT THE DATA USING SASS, MICROSOFT ACCESS AND EXCEL DATA ANALYSIS: WE EXPORT THE DATA USING SASS, MICROSOFT ACCESS AND EXCEL DATA REPORTS: CHALLENGE REPORTS ARE SUBMITTED VIA EXCEL WHICH PAINTS THE COMPARISON PICTURE DATA REPORTS: TEAM COACH REPORTS ARE COMPILED IN EXCEL, WORD DOCMENT, AND ACCESS DATA REPORTS: ACADEMIC SUPPORT REPORTS CONSIST OF GRAPHS AND VIEWED IN EXCEL
  24. Deficits & Merits in our Data collection Deficits • Enrollment file • File is extremely large • Most information does not speak to our target population • Grade file • Grades aren’t posted at the same time; we need to re- run the file until all grades are posted Merits • Enrollment File • We are able to view students that were admitted vs non- admitted students • Often asking the ? Why they weren’t admitted • Grade File • We can view grades from all students to compare with our target • We can view which classes students have challenges
  25. In order to solve the actual Data issues that are outlined we use the following tools to assist with the disaggregation of data I. Excel makes manipulating of the exported data easier II. Assess makes looking at large amounts of data easier III. SASS allowing us to import all files from different sources
  26. In order to solve the issues of obtaining various permissions to our data I. I task the Research and Review manager to go and get the data needed for our programs
  27. The stakeholders in my department are the programmers These are staffers that run the various programs. They are charged with ensuring that they have the data available to make sound decisions regarding their programs If they do not receive their data in a timely fashion then they can not run their reports, and I will not be able to gauge the critical areas It is imperative that each programmers understands the importance of their data, benchmark their programs, meet frequently with the Research and Review manager to ensure they are receiving accurate information It is also imperative that they look for certain trends in their data- in each data group there are certain trends
  28. Over-Arching Goal • In spite of the data, in spite of the time and effort it takes to produce the data, export and import the data into various databases • The goal is to produce Global Leaders, Critical Thinkers, and successful students that can speak to the importance of being engaged with OMED • Our target population is capable of achieving such successes but often it is things out of our control that keep them from succeeding. 1. First-Generation Students 2. Connectivity to the GT culture 3. Marginalization 4. Racism & Sexism
  29. Engaged OMED Students OMED Programs & Initiatives Challenge Summer Bridge Program Team Coach/Peer Mentor/utilized tutorial services Tower Award Recipient Summer Intern w/partnering Company 2nd year CHBE OMED Programs & Initiatives OMED Programs & Initiatives OMED Programs & Initiatives Challenge Summer Bridge Program Georgia Tech Fall 2008 – Aerospace major Team Coach & Challenge Counselor GTBAO- Unsung Hero Award 2008-2013 Tower Award Recipient Graduate School Challenge Summer Bridge Program – utilized tutorial services President Scholar-GT Fall 2012 Tower Award Recipient 2nd year IE Challenge Summer Bridge Program Tech Promise Scholar 2011 Tower Award Recipient Peer Mentor & Tutor @ OMED MSRI-UP program @ Berekeley 3rd year MATH

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