ArticleScientific reports2025
A framework for AI ethics literacy: development, validation, and its role in fostering students' self-rated learning competence.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Psychological readiness for AI in health professions education: the role of innovativeness and cognitive flexibility among Turkish students.BMC medical education · 2026Article
- Development and psychometric validation of the ethical AI Dilemma Anxiety Scale among university students.Frontiers in psychology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
This study investigates the relationship between AI ethics literacy and students' self-rated learning competence using AI by developing a comprehensive framework of AI ethics literacy comprising knowledge, attitude, and competence dimensions. Data were collected from 482 college students through an online questionnaire and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Key findings reveal that: (1) AI ethics knowledge is primarily characterized by four ethical principles: fairness and inclusivity, privacy protection, human-centricity, and responsibility and accountability; (2) AI ethics knowledge positively influences both AI ethics attitude and competence; and (3) AI ethics attitude and competence significantly enhance students' self-rated learning competence using AI. This research contributes a novel theoretical framework for understanding AI ethics literacy while providing practical insights for cultivating students' self-rated learning competence using AI.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.