Assessing Non-Traditional Assignments

Assessing creative or multimedia assignments—like videos, podcasts, infographics, or other non-traditional formats—requires a slightly different approach than evaluating essays or exams. With some thoughtful planning, you can provide fair, clear, and confidence-building feedback for students.

• Focus on Academic Goals: No matter the format, hold multimedia projects to the same intellectual standards as other coursework. Clear argumentation, organization, and evidence remain central.
• Clarify Expectations Early: Define the genre, conventions, and learning goals for the assignment in your prompt. Only grade production quality if students had clear instruction or access to training/resources. Otherwise, focus feedback on content, clarity of message, and design choices.
• Use Artist’s Statements: Consider asking students to submit a 1–2 page reflection describing their creative process, choices, intended message, how their work meets the assignment’s objectives, and/or how their creative project helped them engage with course material in new ways. This can clarify meaning and reduce the focus on technical perfection.
• Design With AI in Mind: To avoid an over-reliance on AI, consider asking students to connect non-traditional assignments to their personal experiences, offer scaffolded opportunities for students to work in class, and provide feedback on early drafts to ensure that the learning goals are being met.

Providing rubrics for assignments can help students understand their learning objectives, and can help other members of the teaching team to fairly assess students across sections. Suggested evaluation criteria might include:

• Alignment with Assignment: Did the student meet the guidelines and conventions of the genre (e.g., video essay, podcast, digital story)? If the conventions were not taught in the course, focus on how effectively the student used the medium to respond to the assignment.
• Purposeful Use of Medium: Are audio, images, and text integrated intentionally to convey ideas? Does the medium enhance—or distract from—the intended meaning?
• Content and Argument: Does the work present a clear thesis, organize ideas logically, and support claims with evidence? Is there a meaningful takeaway or new insight for the viewer/listener?
• Production Quality: Only evaluate technical skill if explicitly taught or supported with class resources.
• Citations: Are sources credited appropriately (e.g., in captions, credits, hyperlinks, use of AI)?

By centering your evaluation on learning objectives and transparent criteria, you’ll empower students to take creative risks and demonstrate deep learning in new ways.