# Artificial Intelligence Competence of K-12 Students Shapes Their AI Risk Perception: A Co-occurrence Network Analysis

arXiv: https://arxiv.org/abs/2512.04115 · HTML: https://mlsanity.com/paper/2512.04115/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 68 references that are in the map.
- First posted on arXiv 1 Dec 2025.

## Builds on (most cited first, 4 of 4)

- [Beware of Metacognitive Laziness: Effects of Generative Artificial Intelligence on Learning Motivation, Processes, and Performance](https://mlsanity.com/paper/2412.09315/) (2024)
- [The Turing Trap: The Promise & Peril of Human-Like Artificial Intelligence](https://mlsanity.com/paper/2201.04200/) (2022)
- [Trust in Generative AI among students: An Exploratory Study](https://mlsanity.com/paper/2310.04631/) (2023)
- [Beyond Text-to-Text: An Overview of Multimodal and Generative Artificial Intelligence for Education Using Topic Modeling](https://mlsanity.com/paper/2409.16376/) (2024)

## Abstract (arXiv)

As artificial intelligence (AI) becomes increasingly integrated into education, understanding how students perceive its risks is essential for supporting responsible and effective adoption. This research aimed to examine the relationships between perceived AI competence and risks among Finnish K-12 upper secondary students (n = 163) by utilizing a co-occurrence analysis. Students reported their self-perceived AI competence and concerns related to AI across systemic, institutional, and personal domains. The findings showed that students with lower competence emphasized personal and learning-related risks, such as reduced creativity, lack of critical thinking, and misuse, whereas higher-competence students focused more on systemic and institutional risks, including bias, inaccuracy, and cheating. These differences suggest that students' self-reported AI competence is related to how they evaluate both the risks and opportunities associated with artificial intelligence in education (AIED). The results of this study highlight the need for educational institutions to incorporate AI literacy into their curricula, provide teacher guidance, and inform policy development to ensure personalized opportunities for utilization and equitable integration of AI into K-12 education.