What Is Process-Based Assessment in the Age of AI?

It is a grading approach that treats student thinking as the primary evidence of learning. You examine how a student arrived at an answer — not just the answer itself.

This aligns with Edudojo's core idea: grade the process, not the submission. The goal is not to ban AI but to make how students use it visible enough to assess fairly.

A polished essay, report, or code file can be generated or heavily edited by AI without reflecting real mastery. You may be grading machine fluency, not student understanding.

Artifact-only grading also pushes students to hide AI use. The better question is not "Did AI write this?" but "Did this student engage with the material and verify what AI produced?"

Useful signals vary by discipline, but most assignments benefit from the same categories. Look for evidence that thinking happened — not just formatting.

• Prompt quality and iteration — questions refined as understanding grows
• Revision depth — structural edits, not synonym swaps
• Verification — claims checked against sources or logic
• Student explanation — reasoning in their own words
• Socratic inquiry — responses to guided challenges, not answer dumps

Tools like the Socratic Engine capture this inside the assignment workflow instead of after submission.

Pick one assignment type — case studies, research memos, coding projects — and require a process portfolio alongside the final product. Publish a clear process-over-product policy so students know what counts.

This is not participation points for clicking around. Rubrics still reward quality of inquiry. And process evidence does not replace human judgment — the Engagement Score supports educators; it does not auto-grade understanding. Edudojo's Parishkar College pilot is MVP in testing; classroom deployment has not started yet.