Challenges and Strategies for Engaging with your IR office.
Dear STEP Community,
The Collecting Organizing & Making Use of Data Working Group has been working to address needs and concerns related to Collecting, Organizing & Making Use of Data. As a result of that effort, we are happy to share with you a summary of "Challenges and Strategies for Engaging with your Institutional Research Office"
Background: To identify and address top concerns of STEP Projects, the working group facilitators associated with STEP Central implemented a STEP Community Needs Assessment (April 2014). The Collecting, Organizing and Making use of Data Working Group (Dr. Rahman Tashakkori, Appalachian State University; Dr. Karen Olmstead, Salisbury University; and Dr. Jorja Kimball, Texas A&M University) then summarized responses applicable to their topic relating to the use of data. Then, to address top concerns as well as specific questions and issues people had, a team from the working group planned a Brown Bag Webinar (July 2014) discussion on "Challenges and Strategies for Engaging with your IR office". The results of that discussion are also listed below. Please feel free to add your own comments and suggestions to our list of Challenges and Strategies below!
Webinar Discussion Participants: Dr. Rahman Tashakkori, Appalachian State University Dr. Karen Olmstead, Salisbury University Dr. Jorja Kimball, Texas A&M University Dr. Ellen Berg, Evaluator, California State University - Sacramento Dr. Lynn Tashiro, Principal Investigator, California State University - Sacramento Karen Krapcho, Project Coordinator, University of Utah Adrienne Steele, Project Coordinator, Louisiana State University
Primary concerns expressed:
1) Understanding the format and sources of data. There are problems with IR re-coding the data so problematic to run-time series analysis.
2) Different people put data in differently. This results in a different output each time you run a query.
3) Problems with communications. Some IR feel they need to be paid for their work cleaning and prepping the data.
4) IR doesn't always understand the context of the data, whereas the external evaluator has a better sense.
5) It is a challenge to get all the data in the same place.
6) Political situation at University makes navigation team building difficult.
7) IR office have their own rules regarding coding data, that may not be capturing data that you need.
8) IR office must generate reports that adhere to their own requirements.
9) IR office does not always want to share the raw data. They want to produce the reports for you. You need raw data so they can look for trends.
10) Huge data set have lot of mistakes.
11) It is not always negative experiences! In many cases the IR office is really helpful. Reason for positive interaction is by not making a lot of demands.
12) IR offices collect a ton of data, but through their own rules. We have to figure out their language, and plug into the data that they are collecting to the extent that they can.
1) You don't know what you don't know! Engage IR in the proposal writing phase to establish positive relationships and workable data requirements.
2) Work around the IR by pulling the files and analyzing them separately.
3) Find other partners (admission/management) to put some pressure on the IR office. Having other people asking for the same data can help move the IR office.
4) Solve through structure of leadership of the project. Make someone at IR a co-PI on the project. VP of enrollment management as a Co-PI helps to get a response. “Agent J”
5) Run your own queries in retention using the student tracking system (people soft). You can look at the class rosters. This involves basic searching and sorting with excel.
6) Sit down with IR person and understand the meta data, and their language, and try to utilize their data structure as much as possible. It is important to understand their language
7) 3rd year visit helped to reinforce data needs for getting another NSF grant.
8) Go back to the same data source every time your run the analysis. To be consistent, go to the same data-source used in year prior.
9) Having a good relationship with IR is critical. Have a number of them on your advisory group, they should be on your team. Any proposal that has anything to do with data must involve the IR right away.
10) Engage IR staff in team building. Cultivate a good relationship, engage with teambuilding, and have very good communication with your contact at IR. Develop a champion in the IR office. Treat them like a professional. These are people who may not feel appreciated. Send them an appreciative email and cc their boss. Send thank you notes! And send a bag of chocolate.
11) Contact at the IR needs to be walked through everything you are interested in. Help them understand your parameters. Sit down and walk that person through your data needs will make it easier to get the data you need in the future.
12) If you can show the assessment office how your data can help them, they will be more cooperative.
13) Use “certified” data: statistical reports and totals on fact sheets – these are things you can already use.
14) Have students work with data. They can look up student data one at a time to fill out their own spreadsheets.
15) Be specific when you ask for data. Create a spreadsheet with the headings that they want. Ask them to fill out the spreadsheet.
16) Try not to make too many demands on them.
17) Develop and maintain your own database of your students
18) Buy part of a IR person time.
19) Have a smaller excel sheet to maintain our own budget internally for both scholarships and procurements.
20) Make the NSF on-line data submission requirements/questions earlier, so we know exactly what we needed to ask IR earlier on. Then the database would have been more effective. Have a person who understands what kind of data they need, and the data terms.
21) Try to identify just one person dedicated to collecting data for this project. Having a STEM person would be fantastic.
22) Have someone from IR on the internal advisory board.
23) Ensure thanks are sent to IR person that does help the project and copy their supervisor so they know of your satisfaction. Even a box of chocolate helps the next time you need something.