Understanding teens' self-beliefs when learning to construct and deconstruct AI/ML systems: Developing a survey instrument

2026-04-24

AI Summary

This study addresses the lack of effective instruments for assessing computational empowerment and self-beliefs among adolescents engaged in constructing and deconstructing AI/ML systems. It develops and validates a six-factor self-belief measurement model tailored to youth, encompassing creative expression, problem-solving self-belief, auditing self-efficacy, interest in auditing, beliefs about design justice, and perceived value of learning AI/ML. Confirmatory factor analysis of survey data from 124 adolescents supports the validity of the proposed six-factor structure and reveals significant positive associations between design justice beliefs and problem-solving self-belief, auditing self-efficacy, and creative expression. By integrating dimensions of construction, deconstruction, and design justice, this work offers a novel instrument for evaluating adolescent AI literacy.

Technology Category

• Cognitive Modeling & Cognitive Systems: Computational Creativity
• Humans and AI: Learning Human Values and Preferences
• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness

Application Category

• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• User Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking

Abstract

Despite growing calls to foster AI literacy, there are few available survey instruments designed for children and youth that study computational empowerment alongside construction and deconstruction activities. In such activities, learners' beliefs about their abilities and attributes can impact their engagement. In this paper, we introduce and validate a survey instrument with constructs related to construction (creative expression and problem-solving self-beliefs) and deconstruction (auditing self-efficacy and fascination with auditing), along with more general self-beliefs related to design justice and the value of learning about AI/ML. We administered the instrument to 124 teenagers and assessed the six-factor structure of the instrument using confirmatory factor analysis. In addition to confirming the structure, we found that design justice beliefs strongly correlated with problem-solving, auditing self-efficacy, and creative expression.

Problem

• AI literacy
• self-beliefs
• construction and deconstruction
• survey instrument
• computational empowerment

Innovation

• survey instrument
• AI literacy
• computational empowerment
• construction and deconstruction
• self-beliefs