Innovative teaching is essential to strong student learning outcomes. However, implementing substantial new educational approaches has the potential to affect how students evaluate a course. To encourage instructional innovation, faculty may request in advance to exclude a course's student evaluation data from their Review, Promotion, and Tenure (RPT) dossier.

Eligibility Criteria & Definition of Innovation

To qualify for a one-time evaluation exception, the proposed course modification must represent a substantial educational innovation. A qualifying innovation meets the following criteria:

  • Student-Centered Learning: Positions students as co-creators of knowledge or architects of their own learning pathways.
  • Continuous Improvement: Intentionally integrates assessment to foster continuous improvement in instruction and the student learning experience—including a commitment to using feedback to teach the course again within three years.

Eligible Innovations may also engage with:

  • Technology & Tools: Effectively leverages technologies and tools to advance student learning and success.
Application Process

Requests must be submitted and approved prior to the start of the course; retroactive exceptions are not permitted.

  1. Department Chair Agreement: Instructors should discuss the proposed innovation with their department chair or program director and secure their agreement to offer the course again within a three-year timeframe.
  2. OEIA Engagement: Afterwards, please fill out this form by the first day of class. Submissions must include:
  • A summary of the learning objectives and how learning gains will be assessed.
  • A brief description (less than one page) of the innovation, its goals, and any prior evidence of effectiveness.
Post-Course Requirements

Following completion of the course, the faculty member should include a description of the innovation and the resulting assessment data in their RPT dossier in place of the omitted student evaluations.

Key Rules & Constraints
  • Finality of Data Exclusion: Decisions to exclude evaluation data are final. Once processed, evaluation data for the course offering will remain permanently restricted, inaccessible to all reviewers, and excluded from departmental or institutional benchmarking.
  • Frequency Limits: Exceptions are approved on a one-time basis. In general, an instructor cannot request more than one exception in a three year period.

The Office of Educational Innovation & Assessment and the Working Group on AI in Education have collaborated to create guidance for crafting effective AI syllabus statements- linked here. 

Resources:

 Interactive HTML app- Download this file, then open it in any internet browser (note this will only work effectively on a computer, not on a phone).