Redesigning Courses with Empathy and Purpose
Navigating the shift toward generative technology requires acknowledging change in education is often experienced as a distinct loss. Rettinger noted that educators must sometimes grieve the removal of broad course content to prioritize essential learning objectives, such as ethical choice, empathy and contextual application. Instead of chasing innovation for innovation's sake, a grounded course redesign focuses heavily on the "must-have" human skills that cannot be easily outsourced to a machine.
"And we need to maybe let go some of the nice-to-haves in favor of making absolutely sure that the must-haves remain things," Rettinger said. "And that those are the human things. That's discernable choice. That's applying context from our experience. That's ethics. That's empathy."
Rethinking Integrity as a Conversation
Rather than relying on generic statements buried in a syllabus that are rarely discussed, faculty should ground academic integrity in fundamental values like trust, respect and responsibility. Rettinger stressed that instructors must build active conversations around what constitutes an unfair advantage versus simple learning mistakes. By framing rules as beneficial to the student rather than adversarial, educators can break down barriers and build a necessary culture of trust.
"What tools are appropriate, what behaviors are appropriate in a class, for an assignment, whatever, should be driven by what you're trying to help your students do," Rettinger said.
The Evolving Role of the Essay and Assessment
The traditional take-home essay is losing its reliability as an outcome-based assessment tool. As generative technology becomes integrated into academic life, evaluating a final product is less effective than evaluating the thinking process itself. Rettinger advocated for close observation, peer-to-peer review and oral assessments to verify student understanding and maintain a focus on the cognitive process.
"But now you're shifting from an outcome to a process assessment," he said.
Practical Takeaways for Faculty
- Compare manual and generated outputs: Ask students to manually write a document, perform the exact same task using a generative tool, and analyze the differences to identify where their own critical thinking remains essential.
- Focus on the revision process: Incorporate revision reflections where students explicitly explain their choices, detail how they incorporated feedback and verify their understanding.
- Make small, incremental updates: When revising a syllabus or assignment, implement just one small addition that thoughtfully incorporates technology during each course iteration, rather than attempting a radical, immediate overhaul of the entire course.
What's Next?
- Aug. 5 Event: Join the next community session covering "Navigating Academic Freedom and AI Guidance," which will address the tension between institutional policies and course syllabi.
- August Redesign Cohort: Participate in the month- long assignment redesign cohort starting the first week of August.
- September Redesign Cohort: Apply for the second upcoming assignment redesign cohort launching in September.
Related Google AI Educator Series Content
To build on the strategies discussed, explore the Google AI Educator Series to deepen your pedagogical partnership with these tools.
- Create process-based assessments: Directly aligning with Rettinger's advice to shift away from traditional, outcome-based essays, this Higher Ed Pedagogical Applications session helps faculty design assessments that capture student thinking and evaluate the cognitive process rather than just the final product.
- Create rubrics for assessments: In tandem with process-based tasks, this module guides educators in building robust rubrics to assess intermediate revisions and process choices, reinforcing the idea that writing is a skill to be observed and coached.
