Best For
- Starting from a structured, reusable prompt instead of a blank chat.
- Adapting the prompt to your own inputs while keeping the original intent intact.
- Workflows related to Education & Academic, Educators.
Critiques existing course learning outcomes and proposes a revised, assessable set tagged by Bloom level.
ROLE: You are an educational developer specialising in the education level and field of the course below.
CONTEXT:
Course: {{Course Details: e.g. Mobile App Development with SwiftUI – 3 ECTS – 14 sessions of 90 minutes}}
Level: {{Level:[education_levels]}}
Existing outcomes (if any): {{Existing Outcomes: Paste existing outcomes or type none}}
Professional context graduates work in: {{Professional Context: e.g. App developers in Swiss agencies and SMEs}}
TASK:
1. Critique each existing outcome: is the verb observable? Is the Bloom level appropriate for the level? Is it assessable within the course? Is it actually 2 outcomes?
2. Propose a revised set of 4–7 outcomes in the form "By the end, students will be able to [verb] [content] [condition/standard]". Tag each with Bloom level and knowledge type (factual, conceptual, procedural, metacognitive).
3. Flag any outcome that AI tools could easily satisfy on the student's behalf in an unsupervised task, and suggest how its assessment should differ.
CONSTRAINTS: Avoid "understand", "know", "be familiar with". Don't exceed 7 outcomes.
OUTPUT: table (original | issue | revised outcome | Bloom level | assessment idea).
e.g. Mobile App Development with SwiftUI – 3 ECTS – 14 sessions of 90 minutes
[education_levels]
Paste existing outcomes or type none
e.g. App developers in Swiss agencies and SMEs
ROLE: You are an educational developer specialising in the education level and field of the course below. CONTEXT: Course: e.g. Mobile App Development with SwiftUI – 3 ECTS – 14 sessions of 90 minutes Level: [education_levels] Existing outcomes (if any): Paste existing outcomes or type none Professional context graduates work in: e.g. App developers in Swiss agencies and SMEs TASK: 1. Critique each existing outcome: is the verb observable? Is the Bloom level appropriate for the level? Is it assessable within the course? Is it actually 2 outcomes? 2. Propose a revised set of 4–7 outcomes in the form "By the end, students will be able to [verb] [content] [condition/standard]". Tag each with Bloom level and knowledge type (factual, conceptual, procedural, metacognitive). 3. Flag any outcome that AI tools could easily satisfy on the student's behalf in an unsupervised task, and suggest how...
Variables are wrapped in {{ and }} and follow this pattern:
A selection can reference a predefined variable list using square brackets. These appear in [orange] and provide commonly used values like colors, tones, or languages.
You can also provide an inline list of choices separated by commas.
Tip: You don't need the PUCO app to use these prompts! Simply copy the template and replace each {{…}} section with your own text directly in ChatGPT, Claude, Gemini, or any other AI assistant.