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Institutional Research and Analytics

Othot Information

OSU has partnered with the data analytics vendor, Othot, since Fall 2019 to help recruit our growing freshman classes. In May 2022, OSU expanded our partnership to support enrolled students on their paths to graduation.

Data privacy is one of our chief concerns and has been a frequent topic of conversation as we develop our reports and datasets. Wherever possible, unnecessary data has been eliminated from reports, sensitive data has been simplified or obscured, and personally identifiable information has been withheld. Data is transferred using a secure portal, and Othot has several data protection strategies in place.


Othot Dictionary

Below are a selection of terms that are unique to the Othot platform. Please review the IRA Data Dictionary for common terms at OSU. If there is an Othot term that is not included here that you would like to be added, please email dataliteracy@okstate.edu.

"Week" Factors

Among the Othot factors, some indicate a term and week designation. These selected weeks are generally significant within the academic calendar. Some factors, such as Account Balance, reflect a snapshot of data that updates weekly, up until the week indicated. Once that week has passed, the factor will become static, and a new factor with a later week will be updated. These factors may appear in a student's list of top importances/factors prior to the indicated week of the semester.

For example, in week 5 of the semester, you may see a factor that references week 6 ("Account Balance Week 6: Fall"). The value of this factor may change again in week 6, but will not change after that. A new factor with a future week will be updated from that point forward, up through the week indicated (such as "Account Balance Week 10: Fall").

Cumulative Factors

Cumulative factors count the number of relevant events or interactions up to the week or semester indicated. By analyzing historical data, the Othot models can identify a benchmark number that indicates a higher likelihood of student success. Measuring the cumulative value weekly allows us to compare it back to the indicated week or semester historically ("# Event Swipes (Cumulative) - Week 3: Fall"). In this way, we can identify students who have already achieved the benchmark identified by the factor versus students who are still working toward that goal.

Common Factors

  • # Event Swipes (Cumulative) - Week #
    The total number of sign-ins that the individual had for Events as of the indicated week of the term; events are most often recorded through CampusLink, Cowboy Central, or Slate

Othot Implementation

The implementation timeline for the Othot retention module is below. We are focusing our initial efforts on generating predictive models for first year students (freshmen and transfers). This is the most intensive stage as IRA builds the foundations for our recurring data sharing processes. Once we have a tested and trusted model for first-year students, we will continue to develop models for students through six years at OSU.

Implementation Timeline

December 20, 2021
Othot Contract Signed
May 1, 2022
OSU Hires Staff Member to Support Othot Project
May 16, 2022
Othot Retention Contract Begins
June - July 2022
Initial OSU Data Processes Built
First Training Data Files Submitted for First Year Students
August - December 2022
Othot Reviews Data Files
OSU Refines Processes
Othot Develops Retention Prediction Model for First Year Students
Fall 2022 Data Uploaded to Test Predictive Model
Spring 2023
OSU Staff Develop Strategy
Slate Integration Implemented
Summer 2023
Training Materials Developed
Ongoing Improvements to First Year Model
Fall 2023
Full Implementation for First Year Students
Training Offered to Faculty and Staff
Spring 2024
Training Offered to Faculty and Staff
Data Analysis Tools Developed
Summer 2024
Develop Separate Models for New Freshman and New Transfer Students
Update Files to be Compliant with New FAFSA Regulations
Submit Training Data Files for Continuing Students
Fall 2024-Spring 2025
Submit Training Data Files for Continuing Students and Develop Model
Training Offered to Faculty and Staff
Fall 2025
Implement Use of Continuing Students Model