Learning to Program Alongside AI: Critical Thinking, AI Ethics, and Gendered Patterns of German Secondary School Students

TL;DR

This study explores how German secondary students critically engage with AI tools in programming, revealing ethical awareness but inconsistent understanding, with gender differences influencing AI use and perceptions.

Contribution

It provides novel insights into secondary students' critical AI literacy, ethics perceptions, and gendered patterns in AI-assisted programming within a German educational context.

Findings

Students show strong ethical reasoning about AI but often use AI-generated code without full understanding.

Majority attribute AI responsibility to politics and corporations, reflecting cultural context.

Boys use AI more frequently and experimentally; girls are more skeptical and collaborative.

Abstract

The first generation of students is learning to program alongside GenAI (Generative Artificial Intelligence) tools, raising questions about how young learners critically engage with them and perceive ethical responsibilities. While prior research has focused on university students or developers, little is known about secondary school novices, who represent the next cohort of software engineers. To address this gap, we conducted an exploratory study with 84 German secondary school students aged 16-19 attending software development workshops. We examined their critical thinking practices in AI-assisted programming, perceptions of AI ethics and responsibility, and gender-related differences in their views. Our results reveal an AI paradox: students demonstrate strong ethical reasoning and awareness about AI, yet many report integrating AI-generated code without a thorough understanding of it. The majority of our cohort attributed significant responsibility for AI practices to politics and corporations, potentially reflecting Germany's cultural context, with its strict regulations and data privacy discourse. Boys reported more frequent and experimental use of AI-assisted programming, whereas girls expressed greater scepticism and emphasised peer collaboration over GenAI assistance. Our findings highlight the importance of culturally responsive software engineering education that strengthens critical AI literacy in AI-assisted programming by linking ethics to concrete code artefacts and preparing young learners for this AI-driven software landscape.