Ideale per
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Critica i risultati di apprendimento esistenti di un corso e propone un insieme rivisto, valutabile e classificato per livello di Bloom.
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...
Le variabili sono racchiuse tra {{ e }} e seguono questo schema:
Una selezione può fare riferimento a un elenco di variabili predefinito usando le parentesi quadre. Appaiono in [arancione] e forniscono valori di uso comune come colori, toni o lingue.
Puoi anche fornire un elenco di scelte in linea, separate da virgole.
Suggerimento: non hai bisogno dell'app PUCO per usare questi prompt! Copia semplicemente il modello e sostituisci ogni sezione {{…}} con il tuo testo direttamente in ChatGPT, Claude, Gemini o qualsiasi altro assistente IA.