Resources: Evaluating Learning


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Designing Spacecraft with AI in the Loop

As part of the Fall 2026 CET Faculty Showcase, Jim Chase from the Viterbi School of Engineering’s Department of Astronautical Engineering shared how ASTE 331 integrates AI to prepare students for its use in spacecraft engineering. Three examples highlighted a communications assignment requiring students to identify AI errors, a simulated spacecraft fault for students to diagnose, and a grading process in which AI advocates for the student’s work before a human grader makes the final decision.

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Brief Peer Review Tool: Syllabus

This document offers a peer review framework with criteria and rubrics that instructors can use to evaluate a colleague’s course syllabus and provide feedback on clarity, alignment, transparency, and student support.

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Student Use of AI in Assignments: A Decision Protocol for Instructors

This six-step decision protocol helps instructors determine when and how students should use AI in assignments by anchoring those decisions in learning objectives and core thinking skills. It guides instructors to map assignment workflows, evaluate where AI supports or undermines learning, and produce clear, student-facing guidance on appropriate AI use. It includes a note-capture template and a worked example of the protocol.

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Assignments

This resource supports instructors in designing purposeful, transparent assignments that promote student learning and are manageable to assess. It includes research-informed strategies, templates, and examples adaptable across course contexts.

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Active Learning

This resource provides strategies on active learning for a variety of teaching settings, including tips for implementation, sample activity descriptions, options for planning active learning, and relevant research.

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