---
title: Prompt Engineering
type: concept
frequency: 9
papers_count: 9
related_concepts:
  - AI Literacy
  - Responsible AI Use
  - Algorithmic Bias
  - Algorithmic Bias in Large Language Models
  - Explainable Artificial Intelligence (XAI)
tags:
  - concept
---
# Prompt Engineering

## Definition

Die Fähigkeit, strukturierte und kontextreiche Eingaben (Prompts) für KI-Systeme zu formulieren, um optimale Outputs zu erzielen. Umfasst Techniken wie iterative Verfeinerung und Strukturierung nach Persona, Task, Context und Format.

## Co-occurrence

| Konzept | Gemeinsame Papers |
|---------|------------------|
| [[AI Literacy]] | 6 |
| [[Responsible AI Use]] | 2 |
| [[Algorithmic Bias]] | 2 |
| [[Algorithmic Bias in Large Language Models]] | 1 |
| [[Explainable Artificial Intelligence (XAI)]] | 1 |
| [[AI Competency Framework]] | 1 |
| [[AI Ethics Principles]] | 1 |
| [[Machine Learning Literacy]] | 1 |

## Papers

- [[Beyond transparency and explainability- On the need for adequate and contextualized user guidelines (Barman_2024_Beyond_transparency_and_expl)]]
- [[What are artificial intelligence literacy and competency- A comprehensive framework to support them]]
- [[AI literacy and competency- definitions, frameworks, development and future research directions]]
- [[Prompten nach Plan- Das PCRR-Framework als pädagogisches Werkzeug für den Einsatz von Künstlicher Intelligenz]]
- [[Prompten nach Plan- Das PCRR-Framework als pädagogisches Werkzeug für den Einsatz von Künstlicher In (Freinhofer_2025_Prompten_nach_Plan_Das_P)]]
- [[Responsible prompting recommendation- Fostering responsible AI practices in prompting-time]]
- [[Large language models are zero-shot reasoners]]
- [[Artificial Intelligence Competence Needs for Youth Workers]]
- [[Introducing Generative Artificial Intelligence into the MSW Curriculum- A Proposal for the 2029 Educational Policy and Accreditation Standards]]

## Assessment-Divergenz

Von 3 bewerteten Papers: 0 Divergenzen (0%)

